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Italian Young Innovative Companies and their
Financial Needs: the Role of Law 221/2012
Scuola di Ingegneria Industriale e dell’Informazione
Corso di Laurea Magistrale in Ingegneria Gestionale - Finanza
Anno Accademico 2015-2016
Relatore: Prof. Grilli Luca
Correlatore: Prof. Giudici Giancarlo
Tesi di laura di:
Girelli Edoardo
814335
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“Amat Victoria Curam”
(Latin proverb)
Dedicato alla mia famiglia,
che non ha mai smesso di inseguire al mio fianco le mie più grandi ambizioni.
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◊ Index
List of figures and Tables....…………………………………………………….……3
Abstract ……………………………………………………………………….……..6
1. Introduzione (Italian language)…………………………………………..………...7
1. Introduction………………………………………………………………….…...17
2. The Young Innovative Companies……………………………………………….25
2.1 The importance of Small and Medium Enterprises…………………….……..25
2.2 Key success factors of YICs…………………………………...………….…..29
2.3 YICs and economic growth: a matter of knowledge…..……………………...31
2.4 How YICs can profit from innovation………………………………………...32
3. Efficiency problems of capital markets…………………………………………...36
3.1 Origins and consequences of capital market imperfections…………………..36
3.2 Differences between European and American markets……………………….43
4. Venture Capital and YICs………………………………………………….……..46
4.1 The venture capital market……………………………….…………………...46
4.2 The role of venture capital………………………………….…………………50
4.3 The effects of venture capital………………………………….……………...52
4.4 Government Venture Capital…………………………………….…………...59
5. Public intervention………………………………………………………..………63
5.1 The role of the public sector…………………………………………….…….63
5.2 Governments’ menu of instruments……………………………………….….69
5.3 The rationale of government investment……………………………………...75
5.4 The effectiveness of public policies, do they really work?...............................79
5.5 Limitations and obstacles to public intervention…………………….………..82
5.6 The Matthew effect…………………………………………………….……..84
5.7 The “Jamaica and Singapore” case: an example of two different
growth models…………………………………………………….………….86
5.8 Vertical subsidies VS horizontal ones. The guidelines for policies design…...88
5.9 A review of public policies in European countries……………….…………...95
5.10 The American case………………………………………………….……….98
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5.11 The Italian case………………………………………………………….…..99
5.12 The German case……………………………………….…………………..102
5.13 The European Investment Fund………………………….………………...104
6. The Law 221/2012. A specific support to “innovative start-ups”…….…………106
6.1 The program “Decreto Crescita 2.0”………………………………….……..106
6.2 Definitions and guidelines of the Law………………………………….……108
6.3 Instruments of the policy………………………………………………….…110
6.4 Additional measures for fostering innovation…….…………………………113
6.5 Access to the Guarantee Fund for Small and Medium Enterprises…………..114
6.6 Company Register-Innovative start-ups: descriptive statistics of
the main results (up to 3rd quarter 2015)……………………………………115
7. Research Hypotheses……………………………………………………….…...126
7.1 A focus on the Italian VC market…………………………………………....126
7.2 The research hypotheses…………………………………….………………129
8. Data………………………………………………………………….………….132
8.1 Samples construction……………………………………………….……….132
8.2 Descriptive statistics of the samples…………………………………….…...135
8.2.1 The large sample………………………………………………………...135
8.2.2 The small sample......................................................................................140
9. The econometric model…………………………………………………….…...154
9.1 The econometric framework…………………………………………….…..154
9.2 The econometric models…………………………………………………….158
9.3 Variables of the model……………………………………………….……...160
9.4 Results of the estimates………………………………………………….…..165
9.4.1 Model 1A……………………………………………………………….165
9.4.2 Model 1B……………………………………………………….……….167
9.4.3 Model 2A……………………………………………………...….…….169
9.4.4 Model 2B…………………………………………………………….….172
9.5 Second transitions implications……………………………………….…….173
10. Conclusions………………………..…………………………….…………….176
Bibliography and Sitography…………………………………………….………...184
Ringraziamenti..…………………………………………………………….……..190
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◊ List of figures and tables
- Figure 1: Population pyramid for largest US/European companies
- Figure 2: Average growth of successful firms of the selected countries
- Figure 3: Total VC investment by country
- Figure 4: Total C investment in the European Union and Euro area
- Figure 5: Total VC investment in % by GDP (2013)
- Figure 6: Total VC investment in % of GDP (2007-2013)
- Figure 7: VC funds raised in the U.S. in the period (2012-2015)
- Figure 8: Conceptual model on the relationship between founders’
human capital, VC and growth
- Figure 9: Domains of an entrepreneurship ecosystem
- Figure 10: Direct vs indirect subsidies in different countries
- Figure 11: Policy mind map for financing innovation
- Figure 12: The heuristic firm growth model for European NTBFs
- Figure 13: Overview of the SMEG MAP process flow
- Figure 14: Monthly and aggregated subscriptions to the innovative startup
register
- Figure 15: Distribution of start-ups by capital size
- Figure 16: Distribution of start-ups by legal status
- Figure 17: Age of registered start-ups
- Figure 18: Distribution of start-ups by economic sector
- Figure 19: Distribution of start-ups by production value
- Figure 20: Distribution of start-ups by the number of employees
- Figure 21: Time evolution of the need of capital for a start-up and its
possible investors
- Figure 22: Evolution of the number of financed companies by early stage
investments in Europe
- Figure 23: Distribution of start-ups by number of years with available
financial documents (large sample)
- Figure 24: Distribution of start-ups by age (large sample)
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- Figure 25: Distribution of start-ups by total assets value (large sample)
- Figure 26: Distribution of start-ups by revenue (large sample)
- Figure 27: Distribution of start-ups by number of employees (large
sample)
- Figure 28: Start-ups backed by VC and/or GF VS not backed-start-ups
(large sample)
- Figure 29: Distribution of start-ups by number of years with available
financial documents (small sample)
- Figure 30: Distribution of start-ups by age (small sample)
- Figure 31: Distribution of start-ups by total assets value (small sample)
- Figure 32: Distribution of start-ups by revenue (small sample)
- Figure 33: Distribution of start-ups by number of employees (small
sample)
- Figure 34: Start-ups backed by VC and/or GF VS not backed-start-ups
(small sample)
- Figure 35: Distribution of start-ups by sector (small sample)
- Figure 36: Presence of southern start-ups (small sample)
- Figure 37: Distribution of start-ups by number of shareholders
- Figure 38: Average age of shareholders in the single start-up
- Figure 39: Number of shareholders in the start-up
- Figure 40: Distribution by working years, by type and amount (SUM)
- Figure 41: Distribution by working years, by time and amount (AVG)
- Figure 42: Education degrees
- Figure 43: Total amount of education degrees
- Figure 44: Distribution of start-ups by amount of education in technologic
and economic fields
- Figure 45: Distribution of start-ups by education
- Figure 46: State-transition diagram for the bivariate survival model
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- Table 1: Effects of IVCs VS Effects of CVCs
- Table 2: National government direct financial support policy to NTBFs
- Table 3: National government direct financing policies for only NTBFs
- Table 4: Taxonomy of national direct support schemes covering
Italian NTBFs
- Table 5: Policy instruments to support the entrepreneur ecosystem
- Table 6: Overview of the main objectives of the policy (Law 221/2012)
- Table 7: Number and dimension of start-ups and limited companies
- Table 8: Regional distribution of start-ups
- Table 9: Provincial density – ranking of the first 10 provinces
- Table 10: Distribution by economic sector
- Table 11: Personnel employed in start-ups
- Table 12: Shareholders’ presence in start-ups
- Table 13: Presence and predominance of female, young, and foreign
persons
- Table 14: Main profitability indicators
- Table 15: Descriptive data on loans granted by the GFSMEs to
innovative start-ups
- Table 16: Regional distribution of loans granted by the GFSMEs
- Table 17: Distribution of loans by financing bank type
- Table 18: VC an GF distribution in the sample and relative evolution
- Table 19: Structure of the applied econometric models
- Table 20: Definition of explanatory variables
- Table 21: Determinants of start-up access to Venture Capital and
Guarantee Fund – Models 1A and 1B
- Table 22: Determinants of start-up access to Venture Capital and
Guarantee Fund – Models 2A and 2B
- Table 23: Summary of the effects found in Model 1A
- Table 24: Summary of the effects found in Model 1B
- Table 25: Summary of the effects found in Model 2A
- Table 26: Summary of the effects found in Model 2B
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◊ Abstract
Several studies have highlighted that young innovative companies (YICs) are often
financially constrained in a way that hampers their growth and threatens their
survival. Therefore, these kind of firms are likely to need external financing
coming from private or public investors. The provision of venture capital (VC)
may allow firms to overcome these obstacles. However, the support by a VC may
be limited, especially in bank-based countries such as Italy.
The public sector may try to intervene and relax the constraints suffered by YICs
through the implementation of a various set of instruments. In this regard, Italy has
developed a wide policy program (i.e. Law 221/2012) that offers a menu of
facilitations directed to a specific category of firms identified as “innovative start-
ups”. Firms that fall within this category benefit from faster procedures,
facilitations, tailor made regulations, individual support and direct access to the
Guarantee Fund for Small and Medium Enterprises, which covers most part of the
credit issued by a bank.
This study investigates the determinants of YICs access to the public guarantee
fund and venture capital. The analysis gives a better understanding of the
investment selection criteria adopted by VCs and it draws some considerations on
the effectiveness of the Law in relaxing financial constraints. Moreover, the study
tries to identify the existing relationship between private and public investors: it
aims to assess the existence of a complementary/substitution effect exerted on each
other, and the presence of a certification effect. In order to do so, the research study
considers a sample of 2526 Italian innovative start-ups and resorts to the estimation
of a dynamic bivariate survival model to highlight simultaneously the determinants
of firms’ access to both these modes of financing.
The results of the estimates confirm the relevance of founders’ competencies as
important drivers of VC investment decisions, while the public sector is found to
limit the evaluation to firms’ financial properties. In the end, the findings suggest
the absence of both substitution and complementary effects between private and
public funds.
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1. INTRODUZIONE
Nella letteratura imprenditoriale, da quella più datata sino alla più recente, le
Piccole e Medie Imprese (PMI) sono considerate un elemento fondamentale per la
crescita e la stabilità dell’economia. Secondo recenti analisi infatti (Asdrubali &
Signore, 2015), le PMI rappresentano il 99,8% delle società europee e
contribuiscono per il 60% al PIL complessivo e per il 70% alla forza lavoro totale.
Le cosiddette start-up innovative (“Young Innovative Companies” in inglese
YICs), che appartengono alla categoria delle PMI, hanno un’importanza ancora
maggiore in quanto costituiscono il mezzo principale attraverso cui l’innovazione
evolve. Esse alimentano il progresso con la costante introduzione di innovazioni
nel mercato in termini di nuovi prodotti (Timmons & Spinelli, 2003), nuovi
processi e miglioramenti organizzativi. In questo modo esse stimolano e mettono
in discussione i paradigmi tecnologici esistenti, gli “standard” della società,
scoperchiano nuovi segmenti di mercato e favoriscono il flusso di conoscenza in
svariati settori. L’evidenza empirica dimostra che le start-up innovative sono più
efficaci delle società di grandi dimensioni quando si tratta di innovazione
(Schumpeter, 1942). Questo è dovuto principalmente alla loro struttura snella e
molto focalizzata proprio su prodotti ad alto valore tecnologico, che si trasformano
in innovazioni ad elevato valore sociale. In un’analisi di Storey e Tether (1998) si
evidenzia come questa tipologia di imprese abbia tipicamente un tasso di
sopravvivenza superiore alla media, una crescita del corpo dipendenti più rapida e
soci fondatori più istruiti. Nonostante questa serie di caratteristiche positive però,
è altrettanto comprovato quanto le start-up innovative soffrano di un male comune:
la forte difficoltà a trovare finanziamenti. A causa di mancanza di risorse
finanziarie infatti, moltissime di loro non riescono a consolidare la propria attività
anche nel caso la loro idea di business si possa rivelare valida. Shane (2009), in
riferimento al mercato statunitense, afferma che la tipica start-up cessa l’attività
entro cinque anni dall’avvio.
Le start-up attirano l’attenzione di molti attori dell’economia moderna, primo fra
tutti il settore pubblico. Il governo è attivo da sempre sul fronte “public policy” per
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implementare i corretti interventi pubblici finalizzati ad alleviare quei vincoli che
minacciano la crescita di queste imprese ad alto potenziale, in modo che possano
perseguire i propri obiettivi e adempire al proprio ruolo di catalizzatore
dell’economia nazionale.
Gli ostacoli che si incontrano nel mondo dell’innovazione hanno come
conseguenza principale e diretta un sotto-investimento da parte delle imprese
private rispetto a livello sociale ottimale (Jewkes, 1958; Mansfeld, 1977). I policy
maker di conseguenza devono intervenire per colmare questo gap causato
principalmente da due cose: la presenza di spillover (Teece, 1986), che minaccia
la sopravvivenza delle giovani imprese mancanti di meccanismi legali di
protezione efficienti (appropriabilità e sistemi di brevetti), e le imperfezioni del
mercato dei capitali. In relazione a quest’ultimo fattore in particolare, si nota che
la possibilità che le start-up hanno di ricevere finanziamenti in forma di equity o
debito è molto limitata dalla presenza di conflitti principale-agente e di profonde
asimmetrie informative (Peneder, 2008), le quali danno luogo a problemi di
selezione avversa e azzardo morale (Carpenter e Petersen, 2002a). Esse inoltre
sono spesso più svantaggiate rispetto ad altre società poiché, date le loro
caratteristiche, tipicamente mancano di cash flow stabili, di un track-record
consistente e soprattutto mancano di asset validi come collaterale. Ad aggravare la
situazione si aggiunge la natura innovativa del loro business, che si basa molto su
attività di ricerca e sviluppo. Questa tipologia di attività è considerata molto incerta
in termini di prospettive di rendimento, quindi risulta essere anche più costosa da
finanziare rispetto ad un investimento ordinario (Hall, 2002; Jensen e Meckling,
1976).
L’industria del venture capital (VC) costituisce una seconda principale modalità di
supporto per le start-up innovative (Hall, 2002). In particolare, essa è riconosciuta
generalmente come la soluzione migliore ai problemi di finanziamento
dell’innovazione. Ciò che rende questi investitori privati particolarmente efficaci
e migliori è la loro capacità di gestire le asimmetrie informative (Lerner, 2002;
Tian, 2011; Wang e Zhou, 2004). Infatti, essi si distinguono per la loro abilità nel
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saper valutare e individuare i “limoni”1 presenti nel mercato (Gompers e Lerner,
2001).
Il venture capital è considerato l’investitore per eccellenza per finanziare le giovani
imprese innovative e il suo sistema di finanziamento con equity si dimostra essere
dominante. Nonostante le premesse generali positive però, il panorama italiano
non si presenta come un ambiente accogliente per questi investitori privati: un
mercato del lavoro poco flessibile, la mancanza di fondi pensione privati e una
Borsa valori (Milano Stock Exchange) relativamente ridotta comportano un
mercato del VC molto debole (AIFI, 2014). Una mancanza di questo attore
nell’economia comporta una forte perdita di opportunità che non si limita ad essere
di tipo finanziario. Il venture capital è noto, oltre che per le sue capacità di
finanziamento, anche per la funzione di coaching (Baum e Silverman, 2004;
Colombo, Grilli, Bertoni, 2011) che svolge nei confronti delle società che supporta
(treatment effect) e per il segnale di qualità (Colombo et al., 2006) che può
comunicare al mercato (quality signal, certification effect), una sorta di stampo
d’approvazione per la società finanziata.
Di pari passo con il VC, va il secondo fattore chiave per la sopravvivenza delle
giovani imprese innovative: il capitale umano. La letteratura che affronta lo studio
del capital umano all’interno di una società è molto vasta, in particolare si è cercato
di capire come e con quale entità il capitale umano influenzi la crescita
dell’impresa. Svariati studi confermano tale rilevanza (Colombo e Grilli, 2005;
Colombo e Grilli 2010; Grant, 1996). L’istruzione in campo economico-
manageriale e gli anni di esperienza lavorativa sono empiricamente dimostrati
essere i fattori guida per una crescita sostenuta. Molto frequentemente infatti, la
commercializzazione di un’innovazione si rivela vincente quando è presente una
combinazione di conoscenze tecniche specifiche e altre capacità o asset:
marketing, manufacturing, supporto post-vendita e capacità manageriale sono tutti
asset specializzati complementari tradizionalmente necessari. Un venture capital
1 Vedi Akerlof (1970): il meccanismo del “mercato dei limoni”.
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può effettivamente aiutare l’impresa anche da questo punto di vista, in quanto può
giocare un ruolo attivo nella gestione della stessa fornendo competenze e risorse.
Il venture capital, assieme alla moltitudine di vantaggi e abilità, porta con sé anche
una serie di difficoltà che limitano il suo operato e la sua efficacia. In primo luogo,
è possibile che la strategia e gli obiettivi dell’imprenditore e quelli del VC
differiscano; spesso questi ultimi puntano ad un’uscita dall’investimento
profittevole come può essere un’IPO oppure una “trade-sale”. Secondariamente,
siccome le asimmetrie informative sono di natura bilaterale, anche l’imprenditore
stesso può esitare nel divulgare informazioni chiave riguardo la propria idea di
business ad un investitore esterno che potrebbe in seguito approfittarne e
realizzarla per conto proprio. Terzo, i costi per lo screening e le procedure di
supporto sono molto elevati, di conseguenza i VC potrebbero esserne condizionati
e non investire in imprese in uno stadio eccessivamente prematuro.
Questo porta quindi alla necessità di un’ulteriore “mano” che deve provenire dal
settore pubblico. Tutt’ora, nonostante la moltitudine di studi e analisi sviluppate
nel corso degli anni, la questione del se e del come i governi siano in grado di
influenzare positivamente l’attività imprenditoriale è lontana dall’essere risolta.
Ad esempio, quando si tratta di fondi di venture capital di natura pubblica (GVC),
studi dimostrano che tali fondi, nati per seguire le orme di quelli privati, non sono
efficaci allo stesso modo per una serie di ragioni. Il migliore risultato si raggiunge
unendo fondi di venture capital pubblici e privati, solo in questo modo i primi
hanno impatti positivi significativi (Lukkonen et al., 2013; Schaefer e Schilder,
2006; Grilli e Murtinu, 2014).
La letteratura che tratta di public policy concorda su diversi punti chiave che i
policy-maker dovrebbero seguire (Lerner, 2002). Primo, il settore pubblico deve
investire nella costruzione e consolidamento dei propri rapporti con l’industria dei
venture capital, in modo da avvicinarsi e comprenderne al meglio le caratteristiche
guida. Secondo, è importante che vengano supportate quelle tecnologie e settori
poco considerati tradizionalmente dai venture capital; bisogna coprire quella parte
in cui i VC tendono a non agire. Terzo, è necessario migliorare il grado di
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flessibilità di cui i VC sono bisognosi, dato il loro processo d’investimento che
spesso deve cambiare direzione per gestire l’elevato grado di incertezza che
caratterizza il business innovativo. Quarto, i policy maker dovrebbero costruire
uno schema e processo di valutazione per migliorare le proprie capacità di
scouting. In altre parole, riconoscendo la priorità del venture capital come
investitore principale richiesto dal mercato imprenditoriale delle start-up, il
governo dovrebbe agire a supporto di questo legame, in questo modo anch’esso
può diminuire gli ostacoli vissuti dalle giovani imprese. Oltretutto, il settore
pubblico è anche l’unico ad avere la capacità di agire in particolari ambiti
attraverso la regolamentazione.
Generalmente, il menu di strumenti di intervento utilizzati da esso si compone di
finanziamenti in forma diretta indirizzati alle PMI e start-up ad alto valore
tecnologico, l’implementazione di riforme per incentivare il mercato dei capitali,
programmi di equity financing e schemi di garanzia.
Per quanto detto sino ad ora, le start-up innovative necessitano principalmente di
tre cose: risorse finanziarie, conoscenza (knowledge capital) e asset
complementari; il settore pubblico può agire su tutti e tre gli aspetti.
Secondo Lerner (2010) e Teece (1986), i policy maker devono tenere in
considerazione una serie di punti che vanno oltre il solo supporto finanziario. Per
prima cosa, l’attività imprenditoriale può svilupparsi agevolmente solo quando gli
imprenditori possono contare su validi partner, quindi bisogna indirizzare a
supporto delle imprese non solo capitali ma anche altri componenti dell’arena
produttiva in cui esse operano. Secondo, è importante non sovra-ingegnerizzare il
programma di policy, costruendo eccessive regole e condizioni; bisogna al
contrario ricordarsi che è il mercato ad indicare la direzione. Terzo, è fondamentale
promuovere la base di ricerca e le strutture accademiche scientifiche locali, in
quando la culla della conoscenza risiede spesso in parchi scientifici o incubatori.
Quinto, il governo deve accettare l’orizzonte temporale di lungo periodo che
caratterizza le iniziative di public venture. Infine, esso dovrebbe alimentare la base
di istruzione di tutti gli attori del sistema (imprenditore, investitori pubblici e
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privati) per “oliarne” gli ingranaggi. Gli investitori venture capital anche
internazionali devono recepire il potenziale del mercato locale con le sue
opportunità, gli imprenditori devono allinearsi con le aspettative di investitori
privati “top-tier”, mentre il settore pubblico risulterebbe molto avvantaggiato da
una migliore comprensione delle sfide imprenditoriali e lo sviluppo del venture
capital, in maniera tale da non rendere vani i costosi errori fatti in passato e, al
contrario, tendere al miglioramento continuo.
Questo studio parte da tutti questi presupposti riguardanti gli investimenti privati
e pubblici, offre una spiegazione dettagliata dei fattori di successo chiave per
ognuno dei due e, allo stesso tempo, analizza i limiti e gli ostacoli di cui questi due
attori soffrono. E’ inoltre disponibile una guida sul policy-design che racchiude i
risultati, i suggerimenti e le considerazioni dei principali studi svolti sin ora a
riguardo. Inoltre, viene proposto il confronto fra la situazione europea (con un
focus specifico su alcuni Stati europei rilevanti) e quella americana per quanto
riguarda sia il mercato dei venture capital che il background storico delle public
policy.
L’Italia storicamente ha sempre mostrato un mercato dei venture capital carente,
inoltre, anche dal punto di vista della regolamentazione, non si era mai focalizzata
specificatamente sulla categoria delle giovani imprese innovative (YICs). Questo
vale fino al 2012, anno in cui le cose hanno preso una piega “innovativa”.
Regolamentazione chiara, flessibilità del mercato del lavoro, procedure
burocratiche veloci e snelle, un sistema legale che incoraggi l’imprenditoria e non
etichetti il fallimento come “disastro”, l’opportunità di raccogliere capitale
azionario: tutti questi elementi contribuiscono alla creazione di un ambiente
dinamico e fertile per la creazione di business, capace di guadagnarsi stima su scala
globale. Questi sono i principi su cui il governo italiano ha fondato lo sviluppo di
un programma di policy originale e senza precedenti: il Decreto Legge 221/2012,
anche riconosciuto come il “Decreto Crescita 2.0”, che è entrato in vigore il 17
Dicembre 2012.
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La legge è stata creata per incoraggiare la nascita e lo sviluppo di giovani imprese
innovative, che vengono individuate attraverso una nuova espressione coniata
dalla Legge stessa, le “start-up innovative”. Questa espressione definisce un
determinato tipo di imprese che devono soddisfare determinati requisiti. In
particolare, una start-up innovativa è quella società nuova e ad alto valore
tecnologico che presenta specifiche caratteristiche di età, locazione, oggetto di
business e altre peculiarità elencate in dettaglio successivamente.
Il quadro regolativo (art. 25-32) è disegnato specificatamente per questo tipo di
imprese senza far distinzione alcuna riguardo settore o età dell’imprenditore. Esso
opera attraverso una moltitudine di strumenti che agiscono su tutto il ciclo di vita
della società. Nel dettaglio la Legge offre alle start-up esoneri da diritti camerali e
imposte di bollo, deroghe alla disciplina societaria, facilitazioni nel ripianamento
delle perdite, disciplina del lavoro tagliata su misura, remunerazione flessibile
delle persone, remunerazione con strumenti avanzati, credito d’imposta, incentivi
fiscali, equity crowdfunding, sostegno individuale nel processo di
internazionalizzazione e accesso diretto al Fondo di Garanzia per le Piccole e
Medie Imprese. Quest’ultimo è un fondo pubblico che facilita l’accesso al credito
attraverso la concessione di garanzie sui prestiti bancari.
Lo scopo di concedere alle start-up l’accesso diretto al fondo pubblico di garanzia
è diminuire le difficoltà che queste incontrano quando sono alla ricerca di
finanziamenti sotto forma di debito. Spesso le nuove imprese mancano di asset
validi come collaterale, un elemento fondamentale per la concessione di un debito
da parte di una banca.
Partendo da queste premesse, questo studio si propone come primo obiettivo di
analizzare gli effetti che la Legge effettivamente esercita sulle start-up innovative
analizzando la relazione esistente tra la policy e il venture capital. In particolare,
lo studio stima la possibilità che il ricevimento di fondi grazie al fondo di garanzia
funga come “segnale” nei confronti dei venture capital, valutando anche la
presenza di un possibile effetto di sostituzione (substitution effect) nel mercato. In
altre parole, viene analizzata l’eventualità che il ricevimento di supporto pubblico
influenzi il ricevimento di un successivo supporto privato e, vice versa, se essere
14
supportati da un VC aumenti o diminuisca le probabilità di ricevere supporto dal
fondo pubblico.
Il secondo obiettivo di questa analisi è studiare le determinanti di accesso a
entrambi i tipi di supporto, in particolare, valutare la significatività del capitale
umano in termini di educazione ed esperienza lavorativa quando si tratta di
ottenere finanziamenti esterni.
L’analisi di ricerca fa uso di due campioni. Il primo racchiude tutte le start-up
innovative presenti sulla lista del Registro Imprese in data 8 dicembre 2014 e che
possedevano dati finanziari (stato patrimoniale e conto economico) disponibili al
2 novembre 2015; questo porta ad un campione composto da 2526 imprese. Il
secondo campione è un sottoinsieme del primo in quanto considera le sole imprese
facente parte ai settori manifatturiero e servizi, ma con una base di informazioni
molto ampliata. Questo secondo data-set composto a mano include una grande
quantità di informazioni riguardanti i fondatori/azionisti di ogni impresa: per ogni
persona fisica presente nell’azionariato di ogni impresa di questo campione, sono
state registrate informazioni personali in termini di educazione ed esperienza
professionale.
Il modello econometrico applicato in quest’analisi segue le orme di Mosconi e Seri
(2006). Nel dettaglio, viene implementato un modello survival dinamico bivariato
(dynamic bivariate survival model), che permette di stimare le proprietà
dell’accesso a venture capital e fondo di garanzia come un processo binario a
tempo discreto bivariato (bivariate discrete-time binary process), quindi permette
di stimare le determinanti di accesso ad ognuno dei due metodi di finanziamento
e, inoltre, l’influenza reciproca che provoca uno sull’altro.
Nel suo complesso, lo studio si compone di quattro modelli suddivisi in due
categorie: una prima categoria fa uso del sample più grande, mentre la seconda usa
il sample ridotto. Di conseguenza il primo eseguirà la valutazione imposta dagli
obiettivi di ricerca facendo uso principalmente di variabili finanziarie, di locazione
e di tempo (variabili che considerano l’anno in cui l’impresa opera). L’ultimo
invece aggiunge all’analisi anche delle variabili che descrivono le caratteristiche
15
del capitale umano interno all’azienda. Inoltre, entrambe le categorie di modelli si
sviluppano in due versioni ciascuna: ogni categoria possiede una prima versione
del modello che considera nello studio una categoria di venture capital che include
sia i venture capital tradizionali (independent VC) che i captive VC (i.e. corporate
venture capital, bank venture capital, government venture capital), mentre
successivamente il modello viene ripresentato considerando come VC solamente
la categoria di independent venture capital.
I risultati della prima categoria di modelli suggeriscono che il supporto da parte di
VC si rivolge principalmente a quelle imprese che non sono in grado di generare
sufficienti profitti, ma che presentano una buona struttura finanziaria e
dimensionale, con uno staff e un management piuttosto solido. Al contrario, il
settore pubblico sembra essere più propenso al finanziamento di quelle imprese
molto giovani con una base finanziaria discreta, per la maggior parte rappresentata
dal loro valore degli asset.
Per quanto riguarda la categoria di modelli che considera le variabili di capitale
umano, le stime dichiarano una netta differenza tra le imprese finanziate dai due
investitori: quelli privati (VC) tipicamente supportano le società che hanno un
team fondatore e un management solidi, che sembrano avere le capacità di
affrontare le difficoltà di gestione tipiche del primo periodo di una nuova società;
le variabili finanziarie passano in secondo piano rispetto alle caratteristiche del
management. D’altro canto, l’investitore pubblico sembra dare poca se non alcuna
importanza alle caratteristiche del capitale umano e supporta sempre le imprese
molto giovani guardando a caratteristiche più di carattere finanziario.
Infine, tutti e quattro i modelli dichiarano che investitori privati e settore pubblico
non si sovrappongono nel finanziamento delle start-up. Quando un’impresa riceve
un finanziamento da uno dei due, sembra perdere il vincolo dettato dalle difficoltà
finanziarie e non necessitare così di ulteriori misure di supporto. Questo suggerisce
che settore pubblico e privato non siano né sostituti né complementari, ma che, al
contrario, ci sia più una situazione di segmentazione fintantoché i due investitori
finanziano due tipologie di imprese differenti.
16
In tutti e quattro i modelli non è presente un effetto significativo esercitato
dall’accesso al fondo di garanzia sulla probabilità di ricevere un successivo
supporto da parte di venture capital. Quest’evidenza porta alla conclusione che non
sia presente alcun effetto di certificazione significativo associato al ricevimento di
fondi pubblici nei confronti degli investitori privati.
17
1. INTRODUCTION
As it has long been recognized in the economic literature, small and medium
enterprises (SMEs) are considered a fundamental factor for economies’ stability
and growth. According to recent analysis (Asdrubali & Signore, 2015), they
represent the 99,8% of European companies, contributing to almost 60% of GDP
and 70% of the total workforce. Young innovative companies (YICs), which
belong to this category of firms, are found to be strikingly important because they
carry the burden of developing solid and sustainable progress through the
introduction of innovations into the market (Timmons & Spinelli, 2003) in terms
of new products, processes and organizational enhancements. They stimulate and
test existing technological paradigms, play a disciplining role towards established
leaders, open up new market segments and favor the flow of knowledge among
several industries. YICs, more than their larger peers (Schumpeter, 1942), perform
better when it comes to innovate thanks to their structure and features that allow
them to develop important innovations with significant commercial applications
and social value. Indeed, Storey and Tether (1998) find that these firms exhibit a
higher than average survival rate, a faster employment growth and founders with
a better education. However, due to their young age and business nature, these
firms share a common and cumbersome constraint: the lack of access to financing
resources. Evidence from the U.S. (Shane, 2009) shows that the typical start-up is
dead in five years.
YICs draw the attention of many actors in modern economies, first among
everyone the public sector. Since very long time, governments try to design several
types of intervention in order to alleviate those constraints that hamper the growth
of high-potential young innovative companies to let them fulfill their main role:
spawn the scene for new products and markets being the crucial catalyst for
national economies.
Policy makers need to step in, as long as private firms are found to invest less than
social optimum in most of economies. Two main reasons are universally
acknowledged to explain the gap between private firms’ investments and its social
18
optimum level: spillovers (Teece, 1986), which jeopardize the survival of YICs
that suffer from inefficient mechanisms of protection (limited appropriability of
new knowledge), and capital market imperfections.
In regard of this latter in particular, their chance of obtaining equity or debt
financing is restricted by the presence of principal-agent conflicts and information
asymmetries (Peneder, 2008), which give rise to adverse selection and moral
hazard problems (Carpnter and Petersen, 2002a)
Young companies are often financially constrained more than others because they
usually lack of stable cash flows, track records and, most importantly, lack of
collateral. Moreover, their innovative nature is based on R&D activity, which is
more expensive than other ordinary investments to be financed (Hall, 2002; Jensen
and Meckling, 1976).
The venture capital industry constitutes a second major supporter for YICs. In
particular, it is known among various descriptions as the free market solution to
the problems of financing innovation. The strength of this private investors is their
ability to face information asymmetries in a better way (Lerner, 2002; Tian, 2011;
Wang and Zhou, 2004). Indeed, they are more capable to select and identify
“lemons”2 and to address information problems (Gompers and Lerner, 2011).
The venture capital is actually seen as the most effective solution for financing
YICs and also the dominant form of equity financing. Nevertheless, the Italian
landscape does not offer a proper environment suitable for venture capitalists
(AIFI): the labor market is not flexible, private pension funds hardly exists and the
Milan Stock Exchange is quite small compared to other international realities. This
entails a rather poor presence of this kind of investors, which, besides its financial
capacity, exert a relevant coaching function (Baum and Silverman, 2004;
Colombo, Grilli, Bertoni, 2011) towards backed-companies (treatment effect) and
it also communicates a quality signal (Colombo et al., 2006) to outsiders
(certification effect).
2 See Akerlof (1970): the “market for lemons” mechanism.
19
Another crucial factor considered essential for firms’ survival goes hand in hand
with the VC: the human capital. There exists a wide literature concerning the role
of human capital in the firm’s life, more precisely, how and to what extent it affects
growth. Evidence from several studies (Colombo and Grilli, 2005; Colombo and
Grilli, 2010; Grant, 1996) confirm that one of the two key drivers of success of a
YIC is the human capital, together with access to venture capital.
Indeed, economic/management education and years of working experience are
found to be significant leaders for a superior growth. More often than not, the
commercialization of an innovation is successful when there is a conjunction
between the specific know-how and other capabilities or assets: marketing,
manufacturing, after-sale support and general business management are
specialized complementary assets usually needed. A venture capital can actually
help the firm from this point of view as well, as long as they play an active role in
the management providing competences and resources.
Despite all these considerations, the venture capital may not be the solution to
alleviate YICs’ financial constraints completely. As a matter of fact, there are
relevant obstacles even in the private. First, it is possible that the strategy and
objective of the entrepreneur diverge from the investor ones; VCs often aim at a
profitable exit strategy such as IPOs or a trade sale. Second, as the information
asymmetries are bilateral, the entrepreneur itself may hesitate to divulge key
information to a private external investor that could poach the innovative business
idea. Third, screening and procedural fixed costs are considerably high, so that VC
investors may be restrained from targeting very early-stage financing.
Although the venture capital industry seems to play the most relevant and effective
role when it comes to back YICs up, very often it is not enough. Moreover, the
Italian bank-based system offers a very weak VC market.
There is a strong need for another “hand”, which has to come from the public
sector. However, a broad search of literature shows that the fundamental and
general question of how, and if, governments are able to influence positively
entrepreneurial activity is far from being resolved. When it is the case of
20
government venture capital funds, for instance, the evidence suggests that these
public funds, born to follow in private funds’ footsteps, are not significantly
effective for several reasons. A better positive result is achieved through the
combination of GVC funds and venture capital activity, as long as their synergies
as well exploited (Lukkonen et al., 2013; Schaefer and Schilder, 2006; Grilli and
Murtinu, 2014).
The literature covering the role of public intervention and policy design is sizeable
and the whole line agrees upon most conclusions. There are some general
recommendations applicable to public programs (Lerner, 2002). First, public
officials need to invest in building relationships with the venture capital industry
and get a better understating of it. Second, regulators should consider those
technologies that are not currently popular among venture investors, since these
latter are used to be very sector-focused; they must support the VC industry where
it lacks. Third, federal officials must appreciate the need for flexibility, which is
central to the VC investment process that often presents changes such as shifts in
product market, strategy and management team, all due to the great uncertainty
characterizing the business. Fourth, they should build a better examination
framework to strengthen their scouting capabilities.
The VC is the most effective supporter, and the public sector should act at his side
in order to dissolve those obstacles that hinder it. In this way, also public actions
exert a relevant positive effect. Governments are the only one that have certain
instruments of intervention; therefore, they are deeply needed for operating on
specific regulation levels, which make the business environment more thriving for
both entrepreneurs and private investors.
In particular, in order to ease the access to financial resources, policies usually
make their selection from the following fan of instruments: direct funding of firms
targeted to SMEs and high-tech startups, fiscal incentives for investors oriented to
classes of assets, stimulation of capital markets through regulatory reforms, equity
programmes and guarantee schemes.
21
As a matter of fact, young innovative companies need three main elements to
achieve growth and success (Grilli 2014): financial resources, knowledge capital
and complementary assets; the public sector can influence the three of them.
According to Lerner (2010) and Teece (1986), policy makers should take into
consideration interventions that go beyond financial matters. First of all,
entrepreneurial activity does not exist in a vacuum, on the contrary, entrepreneurs
are very dependent on their partners. Therefore, it is essential to address not just
the need of capital but also other components of a productive arena in which
entrepreneurs can operate. Second, it is important not to over-engineer the policy
program, remembering also that it is the market to provide direction. Third, since
the cradle of knowledge and innovation is also found to be science parks and
incubators, promoting the local academic scientific and research base is essential.
Fourth, embrace the conformity of global standard. Fifth, accept the long lead time
typical of public venture initiatives. Finally, governments should build education
for each of the three actors involved (entrepreneur, private and public actors) in
order to oil the whole mechanism. Foreign venture investors need to understand
the potential of the local market and its opportunities, entrepreneurs must
understand the expectations of top-tier private investors, while the public sector
would deeply benefit from an understanding of the challenges of entrepreneurship
and venture capital development, so that expensive errors made in the past could
be avoided allowing for a process of continuous improvement.
This study will go through all the aspects concerning public and private
investments, offering a detailed explanation of the key success factors of each one
and, at the same time, analyzing limits and obstacles these two actors face. A policy
design guideline is also available, which gathers all the findings, suggestions and
considerations of the main studies concluded so far on this matter. Furthermore,
the study presents a comparison between the European situation (with a specific
focus on some relevant European countries) and the American one for what
concerns both the venture capital market and the policies historical background.
22
Historically, Italy shows a weak venture capital market and a policy track record
that has not focused on this specific category of companies (i.e. YICs) yet.
Nevertheless, in 2012 the situation has changed. Clear rules of fiscal fulfilment,
labor market flexibility, quick and fluid bureaucratic procedures, a legal system
encouraging entrepreneurship and not tagging failures as disasters or “point of no
return”, the opportunity to raise equity capital: each one of these elements
contribute to the creation of a dynamic and prosperous environment, capable of
gaining a good reputation to its country on a global scale. These are the leading
principles on which the Italian government has founded the development of an
innovative policy program: the Decree Law 221/2012, also known as “Decreto
Crescita 2.0”, which entered into force on December 17th 2012.
The Law3 has been created to foster the birth and the development of young
innovative companies, which are recognized with the new expression “innovative
start-ups”, as the regulation has established a precise meaning to this definition. In
particular, the innovative start-up is a new innovative company with a high level
of technology (i.e. high-tech innovative firm), which presents specific peculiarities
in terms of age, location, object of business and further features fully listed in later
on in this study.
The regulatory framework (art. 25-32) is designed specifically for these kind of
firms without any distinction of sectorial nature or relation to the entrepreneur’s
age. It operates with new instruments and supporting measures that work on the
whole life cycle of the company. In detail, the Law offers to innovative start-ups a
much faster process of foundation, reliefs from royalties and duty stamp,
exceptions to ordinary regulation, facilitations in paying losses back, tailor made
employment regulation, flexible remuneration for employees, tax credit when
hiring qualified personnel, fiscal subsidies for investors, equity crowdfunding,
individual support, a fail-fast program that encourages entrepreneurs and the direct
access to the Guarantee Fund for SMEs.
3 From now on, the expression “the Law” will refer to the Law 221/2012.
23
The aim of giving YICs the access to the guarantee fund is to lessen the difficulties
that these firms suffer from when they seek for debt financing. Banks ask for an
even more burdensome amount of collateral when companies are in the start-up
phase, and the guarantee fund aims to alleviate this distortion.
Starting from these premises, this study investigates on the effects that the Law
actually exerts on innovative start-ups and, at the same time, it analyzes the
relationship between the policy and venture capitalists. In particular, as a first aim
the study investigates whether the receipt of funds thanks to the guarantee fund
exerts some kind of signaling effect toward VC investors, evaluating the possible
presence of substitution effects in the markets. In other words, in investigates
whether the receipt of public support influences private investors and, vice-versa,
if being backed by a VC increases the chances of being financed by a bank through
the guarantee fund model.
The second aim of the study is also to understand the role played by human capital
characteristics in terms of education and work experience when it comes to win a
financier over, either a private or a public one.
The research analysis makes use of two samples. The first one gathers all the
innovative start-ups that were on the Company Register list up to December 8th
2014 and that had all the financial data available up to November 2nd 2015; this
translates in a sample of 2526 firms. The second sample is a subset of the first one,
but with an augmented info base for each company. This hand-collected dataset
includes a remarkable and large amount in information with regard to the founders
of each firm: for each founder of the firms included in this second sample, personal
data about education and work experience have been searched and registered.
The econometric model applied in this analysis follows in the footsteps of Mosconi
and Seri (2006). In detail, the study employs a dynamic bivariate survival model,
which allows to model access to both VC and Guarantee Fund support as a
bivariate discrete-time binary process.
The whole study includes four models divided in two categories: one category uses
the large sample, while the other one uses the small one. Therefore, the former
24
investigates the research objectives using mainly financial firm-specific, time-
specific and location-specific info. The latter adds to the group of variables also
the data describing the human capital characteristics. Moreover, both of them
employ two versions of the model in order to differentiate between a general
category of venture capital, which involves both independent venture capital and
captive venture capital, and the sole category of independent venture capital.
The findings of the first category of econometric analysis suggest that VCs support
firms that are not able to make a good profit yet, but show a rather good financial
and dimension structure, with a more solid staff and manager base. The public
support instead, is found to be more inclined toward very young firms that show
at least a basic good financial base, mostly represented by the total assets owned
by them.
For what concerns the category with human capital data, it is found a clear
difference between the firms that are financed by the two investors: the private one
subsidizes those firms with a solid founding team and management, which can
actually look capable to face the challenges of making the start-up overcoming the
early difficult period. Human capital characteristics therefore are found to play a
relevant role. On the other hand, the public investor seems to give no relevance to
the characteristics of the human capital and it supports firms with other
characteristics more of financial kind.
In the end, all the four models find that private and public investors do not overlap
in their subsidizing processes, because once a firm has received a financing support
from one of them, its financial constraints fall away and it does no need any further
aid. This suggests that private and public funds are neither substitutes nor
complementary, on the contrary, there seems to be a segmentation effect between
them, as long as they are found to support different kind of firms.
In any of the four models, there is a significant effect exerted by policy measures
on the YICs’ likelihood of accessing VC financing, leading to the exclusion of the
existence of any important certification effect associated with the reception of
public subsidies.
25
2. THE YOUNG INNOVATIVE COMPANIES
In order to better understand the purposes of this research study, this chapter gives
a quick and detailed overview of the analysis’ object, the YICs. In particular, it
gathers the information that have been recognized so far by the existing
entrepreneurial literature and clarifies the main growth drivers and limitations.
2.1. The importance of Small and Medium Enterprises
Small Business Enterprises (SMEs) can be seen as the roots, the future of a nation’s
economy. They are broadly recognized to be crucial for economies’ growth and
for nations’ development and welfare. Accordingly to recent analysis (Asdrubali
& Signore 2015), they represent the 99,8% of European companies, composing
almost 60% of GDP (total value added) and near 70% of the total workforce. As a
matter of fact, SMEs constitute the connective tissue of the productive fabric.
Moreover, SMEs category includes a particular class of enterprises found to be
strikingly important because they are supposed to lead the future wealth and
competitiveness of a nation’s economy: they are known as Young Innovative
Companies (YICs). Indeed, creation of employment and wealth in modern
“knowledge based” economies is led by these type of firms (Storey & Tether,
1998). They carry the burden of developing solid and sustainable progress through
the introduction of radical innovations into markets (Timmons & Spinelli, 2003)
in terms of new products, processes and organizational enhancements. NTBFs
stimulate and test existing technological paradigms, they play a disciplining role
towards established industry leaders, open up new market segments and favor the
flow of knowledge among different industries.
The focus of this research is on these companies, also known as innovative start-
ups or young innovative companies, which have greater potential among others to
develop important innovations with significant commercial applications and social
value. They differ from usual companies for three typical characteristics: age,
26
because they are in the early stage or even at the seed-phase of their life, dimension,
since they are typically small, and nature of their business, which mirrors their
intense engagement in innovation activities.4
Another related term often used in the literature is “gazzelles”, which alludes to
fast growing companies, not necessarily small or innovative though.
There is a considerable and growing literature dealing with the high potential
nature of NTBFs. Storey and Thether (1998) find that these firms manifest a higher
than average survival rate, a faster employment growth even though the job
creation tends to remain modest, and that their founders have a better education.
However, they underline that NTBFs have a common and cumbersome constraint
to growth: lack of access to financing resources.
What makes YICs receive such attention is not their large number or their
employment offer, but the interest is rather rooted in the expectations on their
direct and indirect effects on innovation, especially when they happen to shape
radically new markets or to bear disruptive challenging standards.
Since long time, one of the most common theme of research has been (Schumpeter
1942) to determine whether they perform better than large firms when innovating.
Economies of scale and scope surely matter and favor large firms, however, a
greater dimension typically brings loss of managerial control and bureaucratization
of innovation activity. Consequently, returns to scale decrease.
Despite everything, much of the multivariate empirical analysis on the relationship
between firm size and innovation has not found significant results (even
controlling with the incorporation of a wide set of firm and industry characteristics)
of a clear positive or negative effect of size on innovative performance. Market
concentration, technological opportunities and technology life cycle are all
elements that interfere with the pure effect that size could exert in this regard. In
fact, some findings show that small firms perform better in new and less
4 To clarify the terms seen so far, it is proper to state that the broader definition of SMEs in high-tech sectors does not include the concept of newness of the company and the deepness of its technological activities. The use of the term NTBFs does.
27
concentrated industries (Utterback 1986) and are more likely to introduce product
innovations in niche markets, especially in comparison to process innovations.
On the other hand, incumbents also affect the innovative behavior of new firms:
the large and solid companies are inclined not to innovate in order to preserve
existing profits from cannibalization, but, at the same time, they could be willing
to innovate for preempting new entries. The decision stands on different factors,
some are endogenous and more manageable and some others are external: some
examples are the likelihood of entry in a market, the possibility of licensing, the
strength of intellectual property, the market efficiency in front of new ideas, the
collaboration with a venture capital and the control of complementary assets.
Furthermore, size has an influence not only on the entity but also on the type of
innovation as well: small new enterprises have the most focused and flexible
structure, which make them able to face better radical innovations, while large
firms usually tend to be more inclined to incremental innovations.
Hence, it is reasonable to say that small enterprises spawn the scene for new
products and markets, the very products on which other companies then probably
build further improvements accelerating the development of the underlying
potential. This process is of much importance to the whole economy as it is to
institutions because, once it starts, the innovation is typically emphasized,
examined, enhanced, accelerated by other actors and therefore it is likely to
contribute to increase the general level of innovation the society can benefit from.
Innovation has a very positive effect towards new firms too, in fact, it is often the
key to overcome new entry barriers. Many studies show a positive impact of
innovation on post-entry performance of new firms, leading to an increase of the
survival rate (Acs and Audretsch 1990).
YICs in this way provide a crucial catalyst to national economies, attracting the
attention of scholars and even more of policy makers who have increasingly
analyzed their performances in order to analyze the driving factors.
Generally, these kind of firms exhibit a rapid growth thanks to their innovative
nature that opens the door to an accelerated business development, when the
28
business idea matches the market needs; usually when it does match latent
customer needs, fast growth is the immediate consequence. That is why growth
rate is often taken as a sort of indicator of market acceptance toward their product
and services, namely an indicator of business success.
Growth is not easy and especially not regular though, since most of NTBFs remain
small after several years since establishment.
Evidence from the US (Shane 2009) shows that the typical start-up is a company
capitalized with about $25.000 of the founder’s savings that operates in retail or
personal services, it is probably home-based and aims to generate a revenue of
$100.000 in the first five years. These typical firms are not the ones that transform
depressed economic regions, create jobs and boost progress, despite what common
thought and the “economic growth myth” would say. George W. Bush in a speech
to the Small Business Week Conference in 2006 said: “small businesses are vital
for our workers…That is why it makes sense to have the small business at the
cornerstone of a pro-growth economic policy…The Small Business
Administration is working hard to make it easier for people to start-up
companies…We have doubled the number of small business loans out of SBA”.
As well, Gordon Brown in 1998 said that a great effort would have been made in
order to dismantle every barrier to productivity, prosperity and employment
creation through policies promoting entrepreneurship and industries partnerships.
Unfortunately, neither the rate of formation of new start-ups and nor the intensity
of the entrepreneurship force foster economic development. As a matter of fact,
the typical U.S. start-up is dead in five years and the average firm that survives,
grows and contributes to the economy welfare has some distinctive characteristics,
whereof the main one is a certain human capital base. This latter seems to play a
crucial role and to be necessary, even if not sufficient, for success, as it will be
discussed later. This situation is valid not only for the U.S. economy, but also for
the thirty-four countries in the Global Entrepreneurship Monitor Dataset.
A first thing that policy makers should consider in view of this is that encouraging
more people to become entrepreneurs is bad public policy (Shane 2009).
According to Shane, there is ample evidence that when governments intervene to
29
encourage the creation of new businesses, they stimulate more people to start new
companies disproportionately in competitive industries with lower barriers to entry
and high rates of failure. In fact, studies (Caree et al. 2002) demonstrate how the
opportunity cost of running a personal business, namely being entrepreneur,
increases when countries get wealthier and so do real wages: increasing
opportunities get people to work for others instead of running their own company5.
Failure rates go up when entrepreneurship is emphasized indiscriminately, because
doing so means providing incentive for people to start the typical failing business,
since the typical entrepreneur is a bad businessman (Johnson 2004). Unemployed
people are more inclined to start business than employed ones because they have
less to lose by becoming entrepreneurs, and they perform worse in leading
companies compared to the ones who quit a job to start a personal business.
Policies should not be designed to increase the total number of new businesses,
otherwise the result is a disproportionate attraction of the worst entrepreneurs.
2.2. Key success factors of YICs
The existing literature brings insights into the questions of why some NTBFs grow
faster, have higher profits, create more employment and introduce more new
products. Chamanski (2001a) calls this research field the “organizational-level
success of NTBFs”, valuated by profitability, number of employees and number
of product launches.
Innovations are the competitive primary success factor according to Chamanski,
followed by technology and business strategy. Technological strategy requires the
development of competences and resources for technological advances, while
business strategy needs the conjunction of internal competences, favorable
environmental conditions, and a proper market entry-timing. When both factors
are contemplated, then the success is most probable.
5 Looking at the correlations between rates of new firm formation and economic growth over the medium-to-long term, it is found that firm formation declines as economic growth increases (Global Entrepreneurship Monitor, The World Development Report).
30
Here is a brief list of other, more specific, key success factors for NTBFs gathered
from different studies (Beaver, 2001; Chamanski, 2001; Forrest, 1990; Westhead
et al. 2000): management commitment/motivation, external R&D, management
team size, management functional and educational heterogeneity and tenure,
strategic alliances, science park location and intelligence system. Above all, it is
common opinion though, that knowledge management is fundamental for success,
since it is the vehicle of the realization of technological advances and innovation.
Those studies date back to several years ago and even though they bring the most
relevant recommendations, it is important to acknowledge the development of the
economic environment that shaped several conditions through the past years. For
this purpose, internationalization and globalization must be considered when
understanding the factors that are key to YICs, because they are phenomena of
increasing importance. Benefiting from each other, they have quickly become two
leading factors to take into account when considering a company’s growth.
The study of Kiederich and Kraus (2015) is the first to deal with this specific topic.
They recognize several types of internationalizing firms: born global, early-stage
technology-based, global start-up, high-tech start-up, internationalizing high-tech
small and medium sized firms, international new venture, new venture firms and
small knowledge intense firm.
A NTBF have to satisfy some requirements for succeeding in the
internationalization process: for instance finding suitable foreign target market,
have a good knowledge of international markets and operations, attract foreign
partners and collaborators, be aware of global environment transformations, face
increasing funding needs, multilingual and cultural sensitive negotiation, offer
solid management capabilities and embrace joint R&D activities. Moreover, it
seems that the chances to succeed internationally rise when NTBFs actively toil
for satisfying these requirements even before starting internationalization.
Internationalization is found to have a very positive effect on the growth of those
companies that can deal with those prerequisites, it reinvigorates their
performances. Several global leaders of these days like Google, SAP or Amazon,
were born as start-ups with a substantial innovative and technology nature.
31
Internationalization, nowadays, could be considered mandatory, at least in terms
of expansion, if the management strictly pursues the company’s value and growth
in the long term. On the other hand, there might be also a negative impact from the
point of view of the entrepreneur: it may happen that rapid growth and
internationalization increases the risk of a take-over.
2.3. YICs and economic growth: a matter of knowledge
Non-large companies are essential for the broad economy, because of their
numerousness, their employment potential and their driving role of the economic
tissue. When these firms are young, they are much more inclined to innovation,
with a preference for radical innovation. When companies are strongly innovative,
they may contribute significantly to economic growth. Therefore economy, as well
as society, benefits at most from non-large, young innovative firms.
The great contribution that societies get from YICs is the knowledge coming from
innovation or, in other words, from research and development activities (R&D).
This activity has always topped the objectives list of policy makers and the
“Lisbona Strategy” (2000) is a bright example of that: “To become the most
dynamic and competitive knowledge-based economy in the world”.
In line with this, there is Europe 2020, a ten-year program that aims to carry on a
strategy on European scale that supports a smart, sustainable and inclusive growth.
The program was born in Lisbon in 2010. Research and innovation are the key
points of this program that states the headline objective of increasing spending on
R&D to 3% of GDP by 2020. By now, the spending is equal to 2,6% in the US and
3,4% in Japan; in Europe it is below 2%. “It is not only the absolute amount spent
on R&D that count – Europe needs to focus on the impact and composition of
research spending and to improve the conditions for R&D private sector in the EU.
Our smaller share of high-tech firms explains half of our gap with the U.S.”
(European Commission, 2010: p. 10).
The quote clears out that the second priority of the European program is to increase
the share of high-tech firms, which are characterized by high level of innovation.
32
Griliches (1992) studies the relationship between R&D activity and growth. His
analysis focuses on spillovers: indeed, R&D spillovers represents, potentially, a
major source of endogenous growth in various “New Growth Theory” models and
are generally found to be both prevalent and important for growth. First, new
growth economics emphasizes that technical change is the result of conscious
economic investments and explicit decisions by many different economic units
(Griliches 1957, 1958 and 1964). Secondly, economic growth is unlikely to
proceed at a constant, undiminished rate into the future unless there are significant
externalities, spillover, or other sources of social increasing returns (Griliches
1992).
There are two notions of R&D spillovers: R&D intensive inputs purchased from
other industries at less than their full “quality” price is the first one, but it is not the
“real” one. True spillovers instead are ideas borrowed by research teams of one
industry from the research results of another one. Their presence has been widely
identified by several studies that adopt different approaches (Mansfield et al. 1977,
Griliches-Lichtenberg 1984, Bernstein-Nadiri 1991). The evidence confirm that
R&D spillovers have a large magnitude in terms of social rates of returns.
Furthermore, these social rates of return are found to be significantly above private
ones, which underlines the importance of such spillovers.
2.4. How YICs can profit from innovation
Independently from the spillover’s mechanism, however, the consequences do not
change: firms invests below the social optimum in R&D. Few studies have
examined how the substantial gap between private and social rate of return varies
with firm characteristics: Jewkes (1958) and Mansfeld (1977) state that spillover
problems are particularly severe among small firms, because they may be not
effectively able to defend their intellectual property positions or to extract most of
the rents in the product market.
It is possible to explain this last phenomenon relying on a study of Teece (1986).
He explains that innovating firms often fail to obtain significant economic profits
33
from an innovation, while customers, imitators and other industry participant
benefit from it. Indeed, developing new products that meet customer needs will
not ensure fabulous success, because often competitors or imitators profit more
form an innovation than the firm that first commercialized it.
Three measures must be put in place when trying to profit from an innovation. The
first one is an appropriability regime in terms of environmental factors that capture
the profits generated by an innovation, excluding firm and market structure. Two
are the most important elements of such a regime: the nature of technology and the
efficacy of legal mechanisms of protection6. The former, indeed, provide little
protection, especially in case of process innovation, because the legal requirements
for upholding their validity or for providing their infringement are high. Only
chemical formulas can be protected after their launch.
The second measure is the dominant design paradigm: in the early stages of
industry development, product design is smooth, flexible, and firms compete for
the best design; after a considerable phase of trial and error in the marketplace, one
design emerges as the most promising and becomes the “standard”. Competition
then shifts to price, where economies of scale and economies of learning get more
important and innovation is sought in processes. The “standard” takes the lead
unless or until the paradigm is overturned. The presence of a dominant design
watershed counts significantly in the distribution of profits between innovator and
followers. When imitation is quite easy and the innovator has already introduced
the basic design of the product, an imitator may cut in and introduce modifications
still relying on the fundamental design.
Finally, the third factor: complementary assets. More often than not,
commercialization of an innovation is successful if there is a conjunction between
the specific know-how and other capabilities or assets. Marketing, manufacturing,
after-sale support and general business management are specialized
complementary assets usually needed.
6 Legal instruments: patents, copyrights, trade secrets; Nature of technology: product, process, tacit, codified.
34
From these three blocks, some issues may arise especially in the case of YICs:
first, tight appropriability is the exception rather than the rule, so intellectual
property protection for young companies seeking innovation is low. Secondly, if
the products do not fit the market, the design process must restart from the
beginning. Thus the probability of entering the market with a dominant design is
problematic and it grows as the relative cost of prototyping decreases. Thirdly, as
the dominant design starts to be detected by the market, volumes of production
increase and firms start gearing up for mass production by acquiring specialized
equipment. Access to complementary assets become very critical, also because
they involve irreversibilities and risks, and the competition is led by prices. The
problem can be faced through contracting or integrating, both not easy solutions
for a young company since it seldom has enough contractual power to induce
suppliers to make costly commitments (contracting issue) and very often does not
have the financial power to integrate (worst case when the investment required is
major and the time required to position is long). Integration generally is worth the
cost when complementary assets are specialized, there is a weak appropriability
regime, the specialized assets are critical, the cash position is good and competitors
are better positioned. Otherwise, in need of complementary assets, the solution for
access is usually contracting. However, the weaker the legal protection, the greater
the incentive to integrate into the relevant co-specialized assets.
Moreover, even following the optimal strategy does not grant success. What an
innovator can do in order to play up returns to R&D is to calibrate its R&D
investment portfolio, maximizing the probability of getting technological
discoveries that are either easy to protect or that need commercialization co-
specialized assets already possessed by the firm.
Innovating firms without the necessary manufacturing and related capacities may
die, even though they are the best at innovating.
To conclude, private firms are found to invest less than the social optimum in most
of economies. Since very long time, this issue is being analyzed by scholars and
policy makers and, accordingly to the mainstream opinion, policy intervention
35
needs to step in. Two main reasons are universally acknowledged to explain this
gap between actual private firms’ investment and the social optimum: spillovers
represent one of them, while capital market imperfections represent the second
one. The next chapter will extensively discuss this last matter, explaining how and
why private investments are tampered.
36
3. EFFICIENCY PROBLEMS OF CAPITAL MARKETS
3.1. Origins and consequences of capital market imperfections
As discussed in chapter 2, investments of private firms are very frequently under
the social optimum value. The main source of this underinvestment is commonly
attributed to financial problems in general, with a strong focus on capital market
imperfections.
The very first studies that opened the doors to the discussion of this matter go back
to famous works and theorems widely recognized from the literature worldwide.
After them, there followed a collection of analyses on what actually makes external
financing expensive and what constrains firms’ investments.
To begin with, the theorem of Modigliani and Miller (1958, 1961) declaims: a firm
that chooses optimal level of investment should be indifferent to its own capital
structure and should face the same price for investment and R&D investment on
the margin (capital structure irrelevance position). The last dollar spent on each
type of investment should yield the same expected rate of return, after adjustment
for non-diversifiable risk. In simple words, they hypothesized that in perfect
markets, it does not matter what capital structure a company uses to finance its
operations. They theorized that the market value of a firm is determined by its
earning power and by the risk of its underlying assets, and that its value is
independent of the way it chooses to finance its investments or distribute
dividends. This theorem formed the basis of capital structure modern thinking.
However, its demonstration implies no light hypotheses: absence of taxes, of
bankruptcy costs, of agency costs, asymmetric information and efficient markets.
In this special environment, the value of a firm is unaffected by how that firm is
financed (the capital structure irrelevance principle).
In order to conclude the opposite suggestion of Modigliani and Miller’s theorem,
it is necessary to start with rejecting one hypothesis after another. Understanding
why and how the theorem can fail highlights some critical points that explain real
market imperfections: uncertainty and incomplete markets together make
37
inevitable an approach to R&D investment decisions that follows often the
minimization of costs. Furthermore, cost of capital varies by source of funds for
both non-tax reasons and tax-reasons; the cost of capital may also differ across
types of investments (tangible and intangible) for both tax and other reasons.
With respect to R&D investments, economic theory advances many reasons why
there might be a gap between the external and internal cost of capital; these can be
divided into three main groups: moral hazard, asymmetric information, which are
discussed later on, and tax considerations that drive a wedge between external
finance and finance by retained earnings. This latter is mainly explained by the
firm’s capital structure, its R&D activity organization, taxes and source of funds.7
Under the same hypotheses of Modigliani and Miller, Jorgenson (1963) developed
a theory of firms’ inter-temporal optimal investments. In his model, availability of
internal capital such as current cash flows plays no role, internal and external
capital are perfect substitutes and their cost is set by market equilibrium (Bertoni,
Colombo and Croce, 2010, analyze the sensitivity to cash flow for NTBFs).
Akerlof (1970) introduced the concept of uncertainty relatively to quality, through
his “Market for Lemons” mechanism. He discusses the information asymmetries
that occur when the seller knows more about a product than the buyer. A lemon is
an American slang term for a car that is found to be defective only after it has been
bought. Akerlof’s paper uses the market for used cars as an example of the problem
of quality uncertainty. It concludes that owners of good cars will not place their
cars on the used car market because this latter would not evaluate them properly.
Myers and Majluf (1984) and Greenwald et al. (1984) demonstrate this “lemons”
problem can be associated to equity offerings of firms. These types of models have
shown to be very powerful in the context of corporate finance since they can
explain why firms rely on one type of financing rather than another and why firms
may have preferences over different ways of paying out profits to shareholders. In
particular, Myers and Majluf (1984) develop an adverse selection model of equity
issuance, in which firms (which are trying to maximize profits for existing
7 For a wider explanation of these three causes of cost of capital differences, see Hall (2002).
38
shareholders) issue equity only if they are desperate. This statement comes from
the information asymmetries problem, which induces investors to prefer some
types of securities, such as debt, over others like equity. As the “lemon market”
creates mispricing problems, when investors are worse informed about investment
opportunities of a firm than its management, and this latter acts in the interests of
shareholders, then the management issues new shares only when the company’s
stock is overvalued. In fact, several studies have provided evidence that stock
prices decline upon the announcement of equity issues, basically because of the
negative signal communicated to the market.
Stiglitz and Weiss (1981) contributed to widen this issue to the debt point of view:
external capital in form of debt is rationed provoking the non-financing of some
profitable investments. Indeed, these information problems applies for debt
markets as well. The theorem shows that if banks find difficulties in discriminating
among companies, raising interest rates can get adverse selection effects. That
happens because high interest rates discourage everyone but the highest-risk
borrowers, in this way the quality of the loan pool declines significantly. The
immediate consequence is credit rationing, since banks may restrict the amount of
lending rather than increasing interest rates in order to address this adverse
selection problem.8
Thus, these problems are vivid in both equity and debt markets and both are due
to information asymmetries between investors and entrepreneurs. Economists
argue that specialized intermediaries can address this problem by intensively
scrutinizing firms before providing capital and monitoring them afterwards, in this
way capital constraints are reduced.
Jensen and Meckling (1976) also demonstrate that agency problems between
managers and investors may prejudice the willingness of both equity and debt
holders to provide capital: raising equity from external investors gives the manager
an incentive to spend thoughtlessly because he bears only part of the costs. While,
8 Jaffee and Russell (1976) report similar conclusions about this topic, focusing of credit rationing deriving
from uncertainty and market imperfections.
39
on the debt side, the manager may increase risk more than he would have done in
absence of debt financing.
Consequently, all these considerations create distortions in the financing market,
which make firms follow a “pecking order” when financing investments
(Myers&Majluf, 1984), a sort of preference list they have when they seek funds.
Choice number one is to rely on internal capital (equity), which has the lowest
opportunity cost. When this last one is used up, it is the turn of external capital at
the lowest cost, which is usually debt for low-leveraged companies.
Peneder (2008) reviews the major finance-related causes of private under-
investment in innovation. It has been introduced that the decision to invest in
innovation depends on two critical factors, namely the incentive to allocate
resources for innovation and the capacity to raise the necessary financial means.
Therefore, two are the inadequacies in the pure market-based allocation of
resources that may cause suboptimal private expenditures on innovation: limited
appropriability of new knowledge and capital market imperfections. This section
focuses on the latter one.
The European Commission (2004) made an innovation survey in order to quantify
these problems asking firms to define the factors that most hamper innovation:
high innovation costs (21%), excessive perceived risk (15%) and lack of
appropriate source of financing (15%) resulted to be the main hampering factors.
In particular, the categories of firms that are found to suffer most from these last
three factors are the following: small enterprises, enterprises operating in the
manufacturing sector and enterprises with high innovation activity.
The principal function of capital markets is to address financial resources to the
most profitable scopes. Investments are driven by expectations about future returns
that, since they are common predictions, are characterized by uncertainty.
Incomplete information dominates the investment environment and the so-called
information asymmetries between entrepreneurs and investors provoke market
inefficiency.
40
Asymmetric information refers to the fact that the inventor has better information
and understanding about the chance of an innovation to succeed compared to the
potential investor. In the extreme version of the “lemons” model, the market for
R&D projects disappears if the information problem persists.
The consequence of the presence of asymmetric information is twofold: adverse
selection and moral hazard. The former represents the difficulty of identifying
correctly the quality of a project, which links to the theorem of Stiglitz and Weiss
just quoted. Entrepreneurs have better information not credibly communicable and
investors cannot differentiate properly, thus, credit is denied instead of interest
rates to be increased.
The latter scenario is known as the incentive problem, which occurs with the
separation between ownership and management, a tradition in most of modern
industrial companies. This separation induces a typical principal-agent problem
when the principal and the agent are oriented to different goals, which may entail
investment strategies not maximizing the share-value.
Entrepreneurs/managers are inclined to adapt their behavior (Jensen and Meckling,
1976; Hall, 2002) generally in two ways: first, spending on activities benefiting
themselves and second, being reluctant to invest in uncertain R&D (this holds
more for managers than for entrepreneurs). Thus, the cost of monitoring becomes
mandatory for the investor who needs to know clearly how the business is being
managed, and even if the amount of free cash flow to the managers were reduced
in order to soften the first problem, the company would have to use external funds
at a higher cost to finance R&D.
Concerning the second type of principal-agent conflict, managers are more risk-
adverse than shareholders and, when the risk involves bankruptcy, they wish to
avoid variance-increasing projects as long as the opportunity cost is lower than
their current earnings. A possible solution would be increasing long-term
incentives rather than reducing free cash flow. In this regard, some have argued
that institutions such as mutual and pension funds often control larger block of
shares than individuals, making monitoring more effective and rewarding.
41
Eng and Shackell (2001) find that firms that adopt long-term performance-plans
for their managers do not increase their R&D spending but, on the contrary, R&D
activity is greater when ownership is in institutional hands. Also Majumdar and
Nagarajan (1997) find that large institutional investor ownership leads to lighter or
even no cuts in R&D. Lastly, according to Francis and Smith (1995), diffusely held
firms are less innovative. These results suggest that monitoring is an effective way
to lessen agency costs enabling good innovation.
All these hurdles seen so far are even more emphasized for SMEs, whose risk
assessment and other transaction costs can be very high. Additionally, other
difficulties may arise for them due to their young age, due to their lack of a stable
cash flow, of a lack of track record and most importantly due to their lack of
collateral. Banks and other debt holders prefer to use physical assets to secure loans
and are reluctant to lend money when the underlying investment involves a
relevant amount of R&D. In support of this clear reluctance, Alderson and Betker
(1996) find liquidation costs to be positively related to R&D across firms,
concluding that the sunk costs of R&D are higher than those of ordinary
investments.
A solid literature analyze also the cash flow relationship to the financing matters.
In particular, the sensitivity of firms’ investments to cash flow connected to
growth, R&D investments and total assets. Bertoni, Colombo and Croce (2010)
show that the investment rate of NTBFs has a strong and positive correlation with
their current cash flow. Colombo et al. (2012) find that investment cash flow
sensitivity of NTBFs decreases with both size and age, moreover, it vanishes as
soon as the firm obtains venture capital from independent investors. Also Guariglia
(2008) with a panel of UK firms demonstrates that this sensitivity is monotonically
decreasing with firm size.
In addition, Himmelberg and Petersen (1994) find economically large and
statistical significant relationship between R&D investments and cash flow;
Carpenter with Petersen (2002b) document that the growth of firms’ total asset
strictly depends on the amount of the available cash flow.
42
Again, everything is even more aggravated when the investment has an innovative
nature (Peneder, 2008). Indeed, in the case of complex projects there is a higher
need of knowledge, the information asymmetries grow as does the uncertainty, the
entrepreneur become more hesitant so adverse selection gets worse as well as
moral hazard and, as a further weakness, YICs usually have few tangible assets
worth for collateral. These companies achieve higher innovative performances
especially when innovations are radical (Schneider and Veugelers, 2010) and, in
view of previous considerations, it is very likely that radical projects further
exacerbate asymmetric information problems and market failures.
A large literature supports the wide differences in these terms between small and
large firms, since these hampering specific factors inhibit YICs to innovate and
they can have an important negative public impact. Schneider and Veugelers also
demonstrate that financial constraints are the most important barriers to innovation
for YICs, both external and internal.
It is worth to notice that R&D projects have relevant differences from ordinary
investments (Hall, 2002). First, half of the spending goes to salaries and wages of
the human resources involved in the project, whose efforts end to be mainly an
intangible asset, namely the firm’s knowledge base. Thus, the possibility that those
resources disappear if such workers leave must be taken into consideration too.
The second feature of R&D investments is the degree of uncertainty related to its
output, which is particularly high in the first stages of the projects.
Nevertheless, the reduction of information asymmetries through complete
disclosure cannot work, because imitation of new ideas has to be avoided as much
as possible in order to stimulate inventions. Firms try to reveal the least possible,
understanding that they could be facing a solid loss otherwise but causing in this
way an unavoidable reduction of the quality signal they communicate of a project
(Bhattacharya, 1983).
In general, the presence of either asymmetry information or principal-agent
conflict implies that new debt or equity finance will be relatively more expensive
for R&D than for ordinary investment, and lack of collateral further reduces the
possibility of debt finance.
43
NTBFs are the firms that suffer most from these capital market imperfections
(Carpenter and Petersen, 2002a) and those that are also small are even more
financially constrained than their larger peers9. Indeed, large firms are well known
(more publicly visible), possess more tangible assets10 and usually suffer less from
hidden information complications.
3.2. Differences between European and American markets
There is some evidence that these financial barriers are larger in Europe than in the
United States. There is a gap between the European Union and the United States
which is most commonly explained by a lack of young and dynamic high-growth
businesses in the EU. In Europe, new firms’ entrance, the exit of inefficient firms
and, most relevant, the growth of successful surviving ones are hindered (Aghion
et al., 2008).
Additional studies (Veugelers 2009) prove how in the U.S. and other non-
European countries, young companies compose a much larger proportion of
leading innovators than in Europe. Moreover, the fewer young European leading
innovators are still less R&D intensive than their U.S. peers.
U.S has been since long time a step ahead of EU in some terms. For instance, U.S.
is the one who has given Europe the impetus for the development of Science Parks
(Storey and Tether, 1998), which are property based initiatives encouraging the
formation and development of knowledge-based businesses. They play as a
management support for transferring technology and business skills between the
businesses on the Park and the local university or research centre.
Philippon and Véron (2008) give a deeper insight on the matter. They affirm that
Europe is widely recognized to be suffering from economic inertia and lack of
dynamism, opposite to America that is constantly self-reinventing the corporate
9 Berger and Udell (1998) examine the economics of finance small business in private equity and debt markets, analyzing the firms with a financial growth paradigm in which different capital structures are optimal at different points in the cycle. 10 Harhoff and Koerting (1998) show that propensity of banks to ask for collateral decreases with firm’s size, using a sample of German companies with maximum 500 employees.
44
finance industry. Indeed, old established companies characterize Europe’s
corporate landscape.
Figure 1 shows the number or largest US versus European firms categorized by
age. Europe’s giants born in the second half of the twentieth century are only 12
against 51 in the United States. This suggests that young companies suffer more in
order to emerge in Europe.
Competition is considered as one of the factors that makes the difference, since
American firms are found to be more challenged both externally by new entrants
and internally by their own shareholders who often tend to divest non-core
activities or to split up.
45
On the contrary, European companies are likely to stay on top for long time. Once
overcome the survival step, they tend to grow more slowly.
Figure 2 displays that, among the survived firms, growth is quicker in the first
years in the U.S. (data analyzed by the OECD).
(The bars represent the average firm size relative to size at creation).
Source: Eric Bartelsman, John Haltiwanger and Stefano Scarpetta, "Microeconomic Evidence of Creative Destruction in Industrial and Developing Countries", IZA Discussion paper No 1374, 2004.
46
4. VENTURE CAPITAL AND YICs
4.1. The venture capital market
The venture capital represents another relevant factor that differs between the
European and the American economies. Hall (2002) reports some evidence dated
1996 according to which the total venture capital (VC from now on) disbursements
at that time were almost equal in EU and USA. There was a sharp difference
though: the allocation of those disbursement in seed and start-ups valued 27,1% in
USA versus only 6,5% in Europe.
The VC industry is known among various descriptions as a free market solution to
the problems of financing innovation, made of a specialized pool of mostly private
funds managed and invested in companies by experts of the relative industry. The
underlying idea is that a better-informed management is actually more capable to
select and evaluate ‘lemons’ properly. At the same time, moral hazard is also
reduced thanks to a higher level of monitoring compared to the one traditionally
used in arm’s length investments.
VCs are specialized in funding young high-technology firms and, by doing so, they
lessen their financial constraints. They tend to be the solution in the middle of the
two imperfect systems, which are arm’s length market-based financial systems
such as the American environment, and bank-centered capital market systems like
continental Europe and Japan. The VC combines the strengths of those two
systems with its ability to provide at the same time incentives for
entrepreneurs/managers, typical of stock markets, and monitoring, typical of bank-
centered systems.
VCs have limits as well though, according to Hall (2002) they often have a deep
focus on few markets at a time, which precludes the consideration of other different
opportunities. Second, the minimal investment size they are used to set is too large
in some sectors; some promising ideas might be not even considered.
47
Historically, the first modern venture capital firm was formed in 1946 under the
name of American Research and Development (ARD). It made high-risk
investments driven by a small group of venture capitalists in emerging companies
and lasted 26 years generating large profits (for instance, it made $355million out
of an initial investment of $70.000). ARD was as a publicly traded close-end fund,
marketed mostly to individuals, and the few funds following venture organizations
were close-end funds as well.
In 1958 was founded the first venture capital limited partnership, while most
organizations at that time were used to raise money through close-end funds or
small investment companies. Afterwards, the activity in the venture industry grew
strongly in late 1970s and early 1980s.
Few years later, many of the most successful high-tech companies that are very
famous in recent time have been backed by venture capitalists, especially in the
1980s and 1990s (Apple Computer, Cisco Systems, Genentech, Netscape,
Starbucks).
Some statistics about the main VC markets are shown by Figures from 3 to 7 , in
particular there is a focus on Europe in the first part (figures 3 to 6) and after on
the United States (figure 7).11
11 Source of statistics from Figure 3 to 6: European Commission – Enterprise and Industry
48
Source: EVCA, Europe and country year book (2013)
The global VC investment amount at the end of 2013 valued around 37 billion
Euros.
Source: EVCA, Europe and country year book (2013)
49
Venture capital investments in European companies rose to the highest figure since
the third quarter of 2001, according to data by Dow Jones Venture Source.
European companies raised 2,6 billion Euro in the first quarter of 2015, with an
increase of 41% in the amount raised from 4Q 2014. Half of it has been allocated
to consumer services through 103 deals and the most favored destination for equity
financing during this period was Germany, which raised 921 million Euros,
followed by United Kingdom with 886 million Euros (The Wall Street Journal,
April 2015).
50
4.2. The role of venture capitalists
VC organizations employ a variety of mechanisms in order to address the
information problems that constrain young small firms, particularly high-tech
ones. First, scrutinizing the business plan: companies in early stage usually have
available few information to communicate to an investor, often in the seed stage
the only thing reliable is a business plan. Knowledgeable individuals can
outperform average investors in the screening process, helping the selection of the
most promising ventures for growth12. Doing so, most give great importance to the
experience and the flexibility of the management team and the size of the potential
market (Lerner, 2002).
Second, they include specific conditions in the deal: in exchange for capital, VCs
ask for preferred stocks with restrictive covenants and representation on the board
of directors.
Third, a close monitoring does lessen information asymmetries. The potential
presence in the BoD, contacting firms frequently and arranging monthly update
meetings make the entrepreneur feel followed, controlled. Plus, an informed VC
is also a better supporter.
Fourth, the disbursement of the funds may follow stages. In this way, venture-
backed firms are forced to generate returns in order to get the additional tranche of
financing and VCs have a guarantee that the money is not squandered on
unprofitable projects.
Stage financing has been studied more deeply in specific studies (Wang and Zhou,
2004; Tian, 2011) because it plays a relevant role in relaxing agency problems.
Gompers (1995) proves VC stage-financing is commonly used in industries with
higher level of asset intangibility, higher market-to-book ratio, greater activity of
R&D, which therefore express more agency complications. As seen before, these
complications force VCs to monitor closely the firm running then into high costs.
Stage financing is found to be a valid substitute of intensive monitoring and, while
it is certainly a source of costs as well, VCs balance the costs of monitoring with
12 According to Fenn et al. (1995), of those firms that submit business plans to VC organizations, historically only 1% has been funded.
51
the ones of stage financing13. Anyway, staging allows at the same time to gather
information when financing high-risk companies with pervasive moral hazard
problems, whereby VC can learn about the entrepreneurial firm over time. More
concretely, this mechanism reduces the amount of the single VCs’ investment in
the firm giving the option to quit at any time with fewer losses.
With the flexibility of stage financing, many projects that may otherwise be
abandoned under upfront financing, become profitable. Wang and Zhou (2004)
show that the efficiency of staged financing constitutes the first best choice for
highly promising firms. However, it is not always dominant over upfront financing
in terms of social welfare when the projects do not seem promising.
Hellmann (1994) argues that VCs resort to stage financing in order to avoid risk,
and, even though it may trigger entrepreneur’s short term behavior, when it is made
by equity it induces an incentive to monitoring, which relaxes this issue.
Tian (2011) adds more details to the matter: he finds some relation with the
distance between the VC and the location of the backed-firm. In particular, when
the VC is located farther away from an entrepreneurial firm, it tends to finance the
firm using a larger number of financing rounds, shorter durations between
successive rounds and smaller amount in each round. Nevertheless, the propensity
to staging is independent from distance.
Finally, Tian demonstrates that staging positively affects some factors: the
entrepreneurial firm’s propensity to go public, the operating performance in the
initial IPO year and the post-IPO survival rate. This holds only for firms located
far away from the VC investor, otherwise the number of financing rounds is
negatively related to IPOs.
13 Sahlman (1990) discusses several aspects of venture capital, in which agency problems are emphasized, and he observes that stage financing is the most potent control mechanism a venture capitalist can employ to deal with the agency problems.
52
4.3. The effects of venture capital
Venture capital is seen as the most effective solution for financing the constrained
young innovative companies and it is considered the dominant form for equity
financing. In particular, the best environment where it is developed and it can
prosper is found to be a stock market that makes an IPO efficient, that has a flexible
labor market, that has a large private pension sector and offers a low capital gains
taxation.
Clearly, Italy does not fit these characteristics well: historically, Italy does not
present a flexible labor market, private pension funds hardly exist and the Milan
Stock Exchange is quite small, which means IPOs are not common and trade sales
are by far the principal exit suitable to VCs. On the contrary, the U.S., UK and
Israel exhibit great chances of being just the right house for a developed VC
market.
Many studies have analyzed the effects of VC investments on firm growth
comparing growth of sales, growth of employees and growth of total assets
between backed and non-backed companies; most of them share the common
conclusion that there is a positive association between VC financing and growth.
When VCs back YICs indeed, the effects are multiple and positive. First, as
explained before, their superior scouting capabilities can actually identify the best
projects with hidden value (Gompers & Lerner, 2001). Second, they keep the
management under pressure because they are not silent partner like other investors
such as banks or government might be. Third, they indirectly add value to the firm
providing their network of business contacts that eases the strategy from several
points of view, which range from getting a better supplier to improving
internationalization through competitive partners that would be out of reach
otherwise.14
14 Ozmel, Robinson, Stuart (2013) study the trade-off that biotech start-ups face in the private equity market when they choose between raising firm-level capital from venture capitalists or project-level capital from strategic alliance partners. They examine whether there is a substitution or complementarity effect between strategic alliances and venture capital. They find that increased alliance activity makes future alliance more likely, nu future VC activity less likely. On the contrary, VC activity makes both future alliance and future activity more likely.
53
The third one is what generally is called “coaching” function: VCs are
knowledgeable individuals who join the business of the firm and add their abilities
and management expertise that strongly enhance the competitiveness and the
probability of success.
Finally, being backed by a VC usually communicate a signal to outsiders that the
firm is valuable and thus it makes easier to team up with other companies that
possess complementary resources and capabilities (Colombo et al., 2006). This
signal is also known as quality effect or certification effect. Therefore,
endorsement by a VC investor makes it easier for portfolio firms to obtain access
to other external financial resources, to tangible and intangible assets.
It is universally acknowledged that the support of VC is positive and helps NTBFs
out. Nevertheless, some studies analyze what is this positive effect due to, whether
it comes more from the sorting/selection effects (pick-winners) or from the
genuine treatment effect.
Colombo, Grilli and Bertoni (2011) on this purpose isolate the treatment effect
from the selection one using a sample of 538 Italian NTBFs observed over a 10-
year period (1993-2003). They find that VC investments have a large positive
statistically significant treatment effect in the growth of employment and sales,
over and beyond the effect attributable to selection. More specifically, employment
is boosted at most after the first financing round, afterwards it is progressively
decreasing but remaining still over the one of non-VC-backed firms (sales follow
a similar pattern). Trend and magnitude of the treatment effect found by Colombo,
Grilli and Bertoni are very similar to the ones reported by Puri and Zarutskie
(2008) who led an equivalent analysis on US privately held firms, but, at the same
time, other studies support there is a positive selection effects in the U.S.. It is
appropriate to conclude saying that VC investors in Italy generate a larger
additionality.
Moreover, Colombo, Grilli and Bertoni find the selective effect to have no positive
value, concluding that in Italy VC investors do not pick winners. In other words,
they do not invest in firms that would grow either with or without VCs. Anyway,
54
this does not mean that the VC treatment is random: on the contrary VC results to
have precise selection criteria solidly grounded on the human capital of the firm.
Precisely, beyond being attracted by very young and relatively large firms, VCs
prefer the ones established by teams of individuals with university education in
management and economics and prior managerial experience.
There exists a wide literature concerning the role of human capital in the firm life,
more precisely, how and to what extent it affects growth. Human capital is
generally seen as one of the two key drivers of the success of NTBFs, together
with access to VC.
Colombo and Grilli (2010) jointly analyze the effects of founders’ human capital
and access to venture capital financing on the growth of 439 Italian NTBFs. In
order to approach this study, a competence-based view is conceived to define the
effects of both educational skills and working experience. They find that economic
and managerial education has a positive and significant effect, just like the
technical work experience. As a corollary, what significantly and positively leads
to a superior growth are an economic/management education and years of working
experience in the technical sector of the start-up.
It is acknowledged by other studies that the main source of the sustainable
competitive advantage is made by the capabilities inside the firm (Grant, 1996);
these capabilities are strictly related to the knowledge and skills of the founders
(Colombo and Grilli, 2005). When an innovative idea occurs, the firm needs to be
established and the business must start, but the knowledge of the founder is most
likely not enough for successfully exploit the new opportunity. Indeed, a team of
other individuals with strong and different skills is important, so that a team well
integrated with complementary context-specific knowledge forms the root of the
success. Those who possess greater educational achieving, greater work
experience and managerial skills are likely to have better entrepreneurial
judgement and more focused knowledge.
55
This constitutes a positive direct effect on firm’s growth. However, it is not the
only one: indeed, there exists a second effect provoked by a certain structure and
essence of founders’ human capital, which is still positive but indirect.
A great human capital, which looks promising and reliable under certain evaluation
methods, is more likely to attract VC investments, as long as VC investors are able
to recognize this potential15. The study also showed surprising results about the
effect of some competences of the human capital: technical experience developed
in sectors close to the relative start-up seems to row upstream and discourage VCs.
They are attracted instead by the management experience of the funding team that
does not seem to play any direct role in favoring growth.
Once demonstrated that VC is a key driver and that the same applies to human
capital of founders as well, it is interesting to understand whether the VC’s human
capital might play a relevant role from the viewpoint of a better management of
the start-up in its crucial early stage. This would be an additional positive effect.
The question wants to find which, between the “coach” function and the “scout”
function played by the VC, performs better, if one of them does.
The scout function links back to the selection effect and it is intended as the major
capability of picking high-growth prospect firms. The coach function instead is
referred to the possibility that VC may provide portfolio firms with actual
additional competences, beyond the other resources and factors seen before. A real
improvement in the ability of the general management of the firm, strengthened by
additional, prepared and experienced human capital coming from the VC team.
This bears the new concept of a financial supporter that does not only play the role
of the financer and the one who monitors, but has also an active role in the
management, to a greater or lesser extent, providing competences and resources.
In this view, the VC brings real consultancy services in fields such as strategy,
planning, marketing, finance, accounting, and human resource management,
which are all fields where high-tech firms typically lack of. They are also found,
15 This argument applies to the management experience of the funding team and to founders’ university-level economic and managerial education (Colombo and Grilli, 2010)
56
for instance, to favor the recruitment of external managers (Hellmann and Puri,
2002), the adoption of stock option plans, the enhancement of human resource
policies. VCs make a NTBF professional.
Following this lead, it has been demonstrated (Colombo and Grilli, 2010) that once
a firm gets a VC, founders’ human capital become a weaker determinant of growth.
The characteristics of founders’ human capital found earlier to have a significant
positive impact on growth, happen to have a smaller effect after obtaining a VC,
since its advent changes the configuration of firm’s distinctive capabilities.
As a corollary, the several studies analyzing the role of VC related to NTBFs
growth deduce that VC investors are mostly interested in firms to which they can
add most value post-investment through their coach function (Baum and
Silverman, 2004)16.
Figure 8 shows a clear conceptual model on the relationship between founders’
human capital, venture capital and NTBF growth, summarizing these last concepts.
Despite all these considerations, VC may not be the solution to alleviate NTBFs’
financial constraints in the real world, or at least completely.
16 As demonstrated also by the analysis on the 439 Italian NTBFs, which suggests that the main role played
by Italian VC investors is not “scouting”.
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Some conflicts may arise from the agency relation between the entrepreneur and
the VC investor. First, the strategy and the objective of the entrepreneur and the
investor may diverge; the latter may want to follow their exit strategy such as an
IPO, rather than a trade sale, which could not match the expectations of the
entrepreneur who prefers not to go public.
Secondly, as the entrepreneur hesitates to divulge key information in order not to
communicate externally sensible knowledge, he might be uncertain about the
reliability of a VC as well. Indeed, the VC could poach the innovative business
idea and exploit this itself.
Third, screening and procedural fixed costs are considerably high, so that VC
investors may be restrained from targeting very early-stage financing, considering
therefore only high-tech firms in a more mature stage. Finally, as already
introduced in the previous chapter, when the country has a bank-based financial
system the supply of venture capitalists is usually thin.
The VC, as a major player, can be further understood making a distinction on the
VC investor type. Several characteristics make a VC different from another one,
including investment target, screening evaluation methods, governance
mechanisms, objectives, skills and competences.
Investments by different types of VC investors are unlikely to produce the same
effects on the investee firms’ conduct and performance (Colombo, Bertoni and
Grilli, 2013). The most widespread distinction is between independent venture
capital (IVC) and corporate venture capital (CVC).
The former is how VC is generally intended, namely a management company with
a pool of capital provided by institutional and individual investors. Each pool is a
legally separated limited partnership with a management company as a general
partner and the investors serving as limited partners; limited partners do not
participate to the active management of the investments (Sahlman 1990).
CVCs are investment vehicles or business units of non-financial companies
provided of capital by the parent company that can influence the investment
decisions of the management.
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IVC and CVC differ along several dimensions: objectives, investment horizon,
competences, and complementary assets for portfolio firms. What changes the
most is that CVC mainly provides access to the parent company’s distinctive
competences and specialized assets such as laboratories, specialized technical
human capital, sales force, etc. All assets that IVC cannot provide, at least directly.
Most probably corporate VC also have personal strategic objectives that go beyond
the financial purpose and therefore they can use the investment as enhancements
of personal competences or technologies. This may lead to a mediocre interest in
the performance of the investee per se.
IVC and CVC present these essential differences that lead also to a different impact
of the treatment effect. Gompers (1996) supports the “grandstand hypothesis”
according to which IVC investors, especially young, are inclined to “grandstand”,
which is intended as to take actions that signal their capabilities, so that their assets
under management are likely to rise. Therefore, the treatment effect of an IVC is
expected to be greater in the short term, in terms of sales growth, than the CVC’s
one.
A study in line with this matter17 shows results congruent with the expectations:
both IVC and CVC investments have a positive and considerable treatment effect
in the long run on both sales and employment growth, the two measures taken as
indicators of growth. With regard to the short term, the IVC effect on sales growth
arises immediately after the first round of financing, while its CVC peer acts more
gradually. Moreover, the treatment effects on employment growth of both IVC and
CVC result similar and smaller than the IVC effect on sales.
The “grandstanding” theory is proved. CVC investors feel less pressure for
“grandstanding” firstly because they rarely use a limited partnership structure, and
more importantly because the management is much closer to the parent company
17 Colombo, Bertoni and Grilli (2013) is one of the few studies that takes into consideration the heterogeneity among VC investors. Chemmanur et al. (2010) make a similar study on CVC and IVC-backed IPO firms, finding that sales growth, after the IPO, is instead greater for CVC firms (the difference decreases over time). Anyway, this does not contradicts the previous work, since the sample is made of sole firms that reached an IPO, which is the most successful exit mechanism for VC investors.
59
and the need of signaling decreases. On the other hand, IVCs focus on boosting
sales that are universally considered as an indicator of business success18, which
becomes even more relevant when a firm lacks of a track-record or other
noteworthy information.
The employment rate in both cases is less supported by the effect of VCs because,
in presence of high uncertainty, investments in specialized assets and human
capital are usually limited, in order to avoid possible sunk costs. NTBFs find it
easier contracting externally instead of hiring and training new personnel.
Below, table 1 makes a simple summary of the effects by IVC and CVC, in the
short and in the long term, on sales and employment growth (arrows indicate the
positive treatment effect, multiple arrows indicate a more immediate effect).
Table 1. Effects of IVCs VS Effects of CVCs
Short term Long Tem Short Term Long Term
IVC ↑↑↑↑ ↑ ↑↑ ↑
CVC ↑↑ ↑ ↑↑ ↑
Sales Growth Employees Growth
Additional research (Maula et al., 2005) provides evidence that CVC and IVC
investors add value to their portfolio companies in a complementary way: the latter
helps more in mitigating financial constraints, while the former excels in building
commercial credibility and providing technological support.
4.4. Government venture capital
A further distinction among the types of venture capital funds discriminates
between its public or private nature. So far, the term VC concerned the private
18 Bayar (2006) finds that firms with higher sales growth are more likely to choose an IPO over an acquisition. The probability of going public with an IPO, for an NTBF, depends on the evaluation of outside investors regarding the validity of the business model and this valuation is positively influenced by rapid sales growth.
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sphere. Government venture capital (GVC) is another player in the promotion of
early stage companies, conceived for overcoming funding gaps.
However, VCs differ substantially from each other according to four main focal
characteristics that may cause very different effects in terms of ability to perform
value-adding activities. First, the human capital they provide the firm with, which
can be more or less useful depending on their ability to supply high quality and
value-adding services to portfolio firms. Second, the objective of the investment,
which governs the amount of time and effort they devote to the portfolio firms.
Third, the investment horizon: the longer it is, the greater the incentive to “coach”.
Fourth, the type of firm they target, in terms of age and level of uncertainty.
Finally, their ownership and governance structure.
The focus now is on the last characteristic as a first approach to public
interventions in the matter of young companies, which will be deeply analyzed in
the next chapter.
Lukkonen et al. (2013) examine this specific issue: the comparison between GVC
and IVC19. First of all, the general literature agrees upon the fact that government
funds are less engaged in coaching and value-adding activities, which should
translates in worse performances. On this purpose, Schaefer and Schilder (2006)
note that GVC has limited potential for concretely supporting firms because of the
high number of firms per manager.
The empirical evidence shows that, even though GVC is found to add less value
to firms than what IVC does, there is significant difference only across different
dimensions of value added indicators and not in the same specific one20.
GVC-supported firms seem to benefit most from the financial function of the
relative investor. Therefore, IVC does not add larger value to the firm it backs,
however, results suggest that the areas of value-adding activities offered by GVC
funds differ from those provided by IVC funds. Generally, the latter investor gives
more support in terms of professionalization, operating actively on the
19 Similar findings are reported by Grilli and Murtinu (2014). 20 For instance, the value added by IVC in recruiting international board members is significant but the other factors supporting internationalisation, such as recruiting managers, are not.
61
composition of the management team, and exit orientation. Moreover, they provide
a major certification effect than government funds.
On the other hand, GVC-backed firms face fewer complications from the adverse
effects point of view. In particular, problems arising from different opinion about
the business strategy between the firm’s management and the investor are lighter
and the interaction is easier.
More recently, Grilli and Murtinu (2014) analyzed the impact on growth
performance21 of young high-tech companies located in seven European countries,
concluding that private venture funds are actually more effective than GVCs. More
precisely, the only positive impact exerted by government funds comes from the
syndication with other private VC operators, even though this result is statistically
significant just when the syndicate targets very young companies.
The reasons why GVC performs worse than IVC can be summarized in three main
points. The first is connected to the ownership structure and the fact that GVCs are
created by some regulatory and political process. In this way, the fund manager
and the institutional investor do not get the chance to agree upon the terms
regulating the investments of the funds, as it happens instead for private funds,
because regulators are entitled to do it. Consequently, many of the covenants that
typically mitigate agency problems, such as restrictions on the size of the
investment, use of debt, public disclosure of fund matters, etc., are not provided.
GVC covenants are much less efficient than IVC ones (Cumming and MacIntosh,
2007). Secondly, also the terms defining the compensation and the coverage of
fund managers are less structured and less efficient, they do not vary across
managers and fund originating employee retention problems.
Third, GVCs cannot make independent decisions. They face pressure to invest in
predetermined activities such as marginal quality and geographically remote
21 In terms of sales and employees growth.
62
projects. Moreover, they also feel political pressure to not fire or replace the
founding entrepreneurs in order not to incur political problems.22
Finally, the objectives of GVCs may be very different from the regular ones:
indeed, they often have to pursue social goals instead of financial returns, such as
employment maximization.
Cumming, Grilli and Murtinu (2014) empirically find that IVCs increase the
likelihood of a positive exit and at the same time, they find the impact of GVC to
be negligible. However, the study shows how the syndication between the private
and the public funds can meet outcomes that exceed the single contribution of
IVC23.
Diseconomies of scale due to larger funds are one of the disadvantages that may
occur though. Additionally, when the efforts of the two partner investors are
substitutable and the resulting value-added is mitigated, conflicts between them
can arise for determining who is responsible for assisting the investee (free-riding
issue).
Syndication, however, bears several global benefits: first, firms enjoy GVC
financing without suffering from its less efficient structure, taking advantage of
IVC limited partnership. Second, on the same line, firms enjoy the benefits
associated with the IVC compensations terms. Third, there is no political pressure
as the decision-making is independent for the private partner. Fourth, the network
provided by the venture capital actors is even more expanded thanks to the further
government-related contacts, which can accelerate regulatory approvals if
necessary.
As a corollary, because political connections are valuable and because IVCs can
mitigate the cost on inefficient GVC structures, combining IVC to GVC in a
partnership is likely to make the firms perform better than it would do with the sole
independent (or other private) venture capital.
22 Cumming (2008) find IVCs to replace founding entrepreneurs as the CEO on a regular basis, they possess the contractual right to do so. 23 The impact of mixed IVC-GVC syndicates is positive and statistically significant at 1%, and the marginal effect shows a 117% greater likelihood of a positive exit.
63
5. PUBLIC INTERVENTION
5.1. The role of the public sector
The presence of financial aids by the private venture sector is essential for the
survival of innovative start-ups and, most probably, it plays the major role in
alleviating their financial constraints. Nonetheless, there still might be room for
public intervention in order to support young high-tech firms and address the
capital market imperfections that this type of firms is likely to suffer from.
GVC funds, introduced in the previous chapter, represent only a minor part of the
set of instruments in the hands of the public sector. Many are the ways through
which government can play a role in an entrepreneurship ecosystem.
As introduced in the second section, the special effect of the entrepreneurship
policy on the development of an economy, and especially its positive impact on
economic growth has been highlighted by numerous scholars (Audretsch et al.
2002; Gilbert et al. 2004). However, a broad search of literature shows that the
fundamental and general question of how, and if, governments are able to influence
positively entrepreneurial activity is far from being resolved. In the analysis on
GVC funds, for instance, the results led to the conclusion that they are not directly
significantly effective for several reasons and that a better influence on the matter
can be achieved combining GVC with the leading private side of venture capital
activity.
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Isenberg (2011), in his analysis of the entrepreneurship ecosystem, builds a scheme
of six domains (see Figure 9) in which the policy plays one of the six key roles and
he says that every entrepreneurship ecosystem is unique. In particular, he specifies
generic root causes of this ecosystem have limited practical value due to multi-
dimensional cause-effect relations that are impossible to track down to one or two
key roots. According to him, the entrepreneurship ecosystem becomes relatively
self-sustaining as soon as all six domains are strong enough.
Mazzuccato (2011) describes the important role of the state in the innovation
ecosystem as follows: many young companies benefit from early stage financing
and state-sponsored technologies, which often form the basis for their new
products and services. Through a high level of investment in R&D of new
technologies, the state has the opportunity to actively shape the markets of the
future. This can be done through public investment, banks and other instruments
of different nature that will be listed later.
Therefore, two are the compelling lines that government must follow in the short
term. First, financial public support, which is essential to boost and fund new
businesses, especially in the earlier stages of a new venture; this holds especially
in markets where the venture capital funding is less mature, even though doing this
excessively may lead to distortions and unwanted negative effects. Second, dealing
with the obstacles provoked by R&D spillovers that hamper the liberty to innovate
developing new ideas.
A boundless literature in regulatory economics and industrial organization has
considered the structure of regulatory bodies, how regulators can monitor and
shape industry behavior taking into consideration the nature of the specific
entrepreneurship ecosystem. Lerner (2002) summarizes some general
recommendations applicable to public venture capital programs. First, public
officials need to invest in building relationships with the venture capital industry
and get a better understanding of it, because of its proved effectiveness and of the
magnitude of its success. Second, VC investments tend to be very focused into a
few areas of technology that are perceived to have great potential and an increase
in venture fundraising is likely to lead to more intense price competition for
65
transactions within existing set of technologies, rather than greater diversity in the
types of companies funded. Regulators should then consider those technologies
that are not currently popular among venture investors, and provide follow-on
capital to firms already funded by VC during periods when venture inflows are
falling. A corollary to this second point is that government should support the VC
industry where it lacks.
Third, federal officials must appreciate the need for flexibility, which is central to
the VC investment process that often presents heavy changes such as shifts in
product market, strategy and management team, which are due to the great
uncertainty characterizing the supported businesses; these changes are not
troubling indicators but a natural part of the evolution.
Fourth, government officials should examine the track-record of the firms
receiving public venture awards: certain company characteristics seem to be
strictly correlated with a company’s ability to achieve its research and
commercialization goals. A better understanding of these leading factors, such as
the experience of the management team, a clear market strategy and a desire to
seek private financing, together with new relative evaluating methods could make
government officials more able to distinguish between high-performing and
underachieving firms.
The fan of instruments through which policy makers can act is wide. A first set is
composed of public subsidies designed to raise incentive for private investment in
innovation. The form that these incentives can assume is twofold: fiscal incentives
and direct funding of targeted expenditures. The former allow companies to reduce
their tax payments and are known as indirect instruments.
Among fiscal incentives there are several tools: the most common is the possibility
for firms to deduct expenditures on R&D from the taxable income, the same logic
is used in some countries with current expenditures on training and marketing
activities. Additionally, it is possible to implement rules for an accelerated
depreciation of R&D equipment (some countries include in the classification
“equipment” also buildings used for research). A second way is tax allowances
offering firms to deduce an additional percentage of expenditures on innovation
66
from their tax base. Third, there are tax credits that allow to detract a certain
percentage of the targeted expenditures directly from their tax liabilities. The
fourth method takes into consideration the fact that fiscal subsidies cannot be
exploited by high-tech start-ups that do not generate profits. In this case, an
innovation premium is paid to companies that have not earned a positive taxable
income. Moreover, it is possible to apply the carry-over of a claim on certain
benefits to a period where the firm is liable to pay taxes on its returns.
The final instrument is the alternative tax base, where R&D rebate can be detracted
from the employer’s part of the wage tax and social security contribution of R&D-
related personnel.
The impact of tax incentives varies from country to country, depending on the
design of its fiscal scheme.
For what concerns direct funding instruments, they have a broad gamma of
financing methods as well. While fiscal incentives are defined as “automatic”,
since they generally give the chance to be exploited by each firm satisfying the
requisites, direct funding is defined as “selective” subsidies, because they give
governments more scope to make deliberate choices about which projects they
want to support. This latter method gives the opportunity to discriminate better
between projects and the potential pay-off is higher leverage through the more
narrow targeting of public resources, for instance, towards projects with
particularly high spillovers. Anyhow, direct public subsidies may also target other
social objectives such as the support of small-medium enterprises, start-ups,
regional cohesion and other public objectives of major priority for the society; for
instance, the support of depressed areas of the country.
Traditional tools are grants or public loans at low rates of interest. Loans can offer
additional facilitating characteristics such as conditional reimbursement, in other
words repayable only in case of successful innovation. Contrary to fiscal
incentives, direct subsidies can be issued by any local, national, supranational or
non-governmental authority. Thanks to this flexibility, as soon as the awareness of
the importance of innovation to the process of economic development has
67
increased, the number of agencies and initiatives targeting innovation policies has
grown in the recent years.
Guellec and Van Pottelsberghe de la Potterie (2003) investigate the aggregate net
effect of fiscal incentives and direct public finding in a panel of 17 OECD
countries, finding a positive impact of both on R&D24.
The optimal solution is a combination of both forms of public subsidies and their
optimal allocation depends on the particular context, aim and priorities of national
innovation policies. Peneder (2008) reports a graph that summarises the aggregate
trends for direct vs indirect financial incentives showing that individual countries
choose very different combinations of the two forms of policy instruments. The
graph is represented in Figure 10. On the vertical axis, there is the share of business
expenditures on R&D funded by the government, which stands for the measure of
the use of direct subsidies in innovation policy, while on the horizontal axis the
OECD’s B-index25 represents the relative generosity of fiscal incentives (Warda,
2001). The graph displays the position of each country in terms in direct and
indirect support in the year 1991 and 2002; a line connects these two points in
order to show how the specific combination evolved.
24 The relative impact depends on the size of the supporting scheme. Guellec and Van Pottelsberghe de la Potterie (2003) find that direct and indirect instruments of government support are substitutes in the sense that increasing the generosity of one instrument reduces the impact of the other one. 25 The B-index is defined as the income before tax needed to break even on one dollar of R&D outlay. BERD: Business Expenditures on Research and Development.
68
Peneder (2008) underlines a general trend of decreasing shares of governemental-
financed business expenditures on R&D. USA (30% in 1981 – 10% in 2003) and
France show the most pronounced downward shifts, while most other countries
experienced a similar development. For what concerns EU-15, in 1981 the
respective shares valued 19%, while in 2003 the value was equal to 8%.
At the same time, the tax treatment of R&D became more generous and the relative
importance of direct and indirect tools has thus shifted towards the fiscal
incentives. Two possible reasons could be the following: a growing concern about
the administrative costs of direct funding and/or the fact that fiscal incentives do
not raise total government spending as a ration of GDP, which is a performance
indicator against which governments are often benchmarked.
69
5.2. Governments’ menù of instruments
As mentioned above, public policies address obstacles to innovation caused by
R&D spillovers as well as capital merket imperfections. In order to ease
specifically the access to financial resources, policies usually make their selection
from the following menu of instruments: direct funding of firms targeted to SMEs
and high-tech start-ups, fiscal incentives for investors in targeted classes of assets
and stimulation of capital markets through regulatory reforms, equity programmes
and guarantee schemes.
The main objective in this case is to enhance the chances of getting financing in
different forms for those promising firms, young and innovative, that are
financially constrained and cannot develop their business ideas. Direct funding
here is a limited support, it usually consists in a targeted grant or preferential loan
at low interest rates for start-ups. As a pure subsidy, it is clearly limited in terms
of volume and degree of selectivity and, most probably, it cannot back the
expansion of fast growing high-tech start-ups that pursue true radical innovations.
What policy must aim for is the mobilisation of private resources. Offering fiscal
incentives to financial investors on the condition that, in turn, they provide equity
to specified ventures is a valid instrument from this point of view. However, this
is not even close to be enough, government needs aidditonal tools to bridge
persistent gaps in the financing of high-risk ventures. A first way could be to
stimulate risk capital market through regulatory reforms, alleviating the
restrictions on investors. Second, government may stimulate the market by
substituting private investors with its own equity programme: it would provide
equity either directly to venture entrepreneurs, or indirectly in the form of fund-of-
funds investor.
Finally, the public sector can offer guarantees. As they faster address the
underlying risk of investments as a principal source of the financing gap, their
potential leverage on private investment is significant. Loan guarantees are
common in several countries, while equity guarantees are a more recent
development and address either individual investment or the portfolios of equity
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funds. Through equity guarantees, it is possible to encourage relatively
inexperienced investors to invest in riskier segment of the market.
Guarantees, however, have two main shortcomings: the danger of increasing moral
hazard by raising the risk profile and the problem of taking on the risk of
investments that would have been undertaken anyway.
Figure 11 illustrates a first policy mind map, useful to reorganize the ideas
explained so far.
Aghion et al. (2009) analyze the policy role in a larger dynamic system perspective,
giving importance to side factors that public institutions must consider when
implementing supporting actions. In particular, the creation of complementary
policy interventions is important in order to take note of the need for coordination
across well-defended boundaries of specialization within the economic policy
community. In other words, it is not sufficient to implement actions through the
instruments seen previously, because they might get different or not efficient
effects without giving attention to the context in which STIG policies26 operate.
According to Aghion and Howitt (2005) indeed, R&D subsidy strategies are rather
ineffective when scarse attention is paid to the context set by policies for educating
and training, and this is only the first area to consider. A higher level of education
should speed the process of building research capacity.
26 The increasing awareness of the close and multiple connections of technological change and innovation with advances in science, on the one hand, and the set of socio-economic institutions operating in a given context, on the other, encourages the conceptualization of “science, technology, innovation and growth systems” (STIG) as appropriate subjects for policy-oriented research (Aghion et al., 2009)
71
72
It is correct that R&D policies stimulate the demand for scientist and engineers in
the private sector through tax incentives and grants, nevertheless, they depend on
the supply response from the educational system. Even a well-designed and
generous program of R&D subsidies will fail to induce more innovation and faster
growth if the educational system does not provide sufficient supply of scientists
and engineers. According to Romer (2000), endogenous growth theory shows that,
in order to accelerate growth, increasing R&D expenditures is not enough. It is
rather necessary to increase the total quantity of inputs related to the R&D process.
A second area to look at is competition. Easy entry into mature new industries is
positive in terms of stimulation of incumbents’ creativity. Multiple studies
highlighted the positive effect that vivid product market competition has on
productivity growth and patenting. The same applies for entry threats, which hold
incumbent firms alert and inclined to innovation. Competition then must be kept
alive.
Third, macroeconomics plays a relevant role as well: R&D investments are very
sensitive to economic fluctuations. Innovating requires uncertain and long term
investments, which carry sunk costs and therefore firms tend to cut them when
they go through a period of retained earnings or face an unexpected need to create
reserves against major liabilities. For this reason, policies able to maintain private
innovative activities during recession periods are convenient.
Finally, the labor market: innovation requires labor market flexibility in order to
minimize the cost of dismissing employees. Especially in the environment in
which young and innovative companies perform, the cost of dismissing employees
must be minimized and instead the ease with which economically obsolete
practises can be dismissed must be increased.
As a corollary, policy complementarities matter greatly, and R&D subsidies have
been proven to be comparatively ineffective when other basic innovation system
ingredients are missing.
Up to this point, it has been argued that the major beneficial effect obtainable for
lessening the financial constraints faced by innovative start-ups because of market
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imperfections is attributable to the private venture capital sector. The public sector
can have a positive influence as well, even if it can be less effective under certain
points of view. However, the instruments in its hands are multiple and able to touch
areas not reacheable otherwise.
Studying the simultaneous effects of private and public actors on the growth of
young innovative companies is crucial for understanding the complementary
effects that their different operating tools can have. On this purpose, Grilli (2014)
develops a model that shapes the growth of European NTBFs, framing the different
drivers and the actors involved. The growth model is displayed in Figure 12.
The scheme is organized identifying three main building blocks considered to be
the roots of growth: knowledge capital, financial resources and complementary
assets. The part concerning the relations of the firm with VC and other private
actors will be seen briefly because the argument has already been analyzed in depth
in the previous chapters.
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Founders’ human capital is widely found to be a key asset for new firms in general,
even more fundamental in knowledge-intensive sectors where sector-specific
competencies are decisive. It offers the firm not only a welath effect but also a
capability one. The former comes from the greater level of personal financial
resources found on average in people with high level of human capital. The latter
affects the skills and the competencies of the founding team.
VC is a second important actor that contributes significantly to the knowledge
capital, in addition to the financial resources level. It provides guidance,
monitoring and coaching to investee companies, general competences that
frequently high-tech firms lack of. The figure names this effect “build winner” to
identify the VC’s function27, also known as coaching function. Founders’ human
capital has also an effect on VC because the latter takes into high consideration the
competencies of the founding team when selecting the investee.
Since NTBFs are unlikely to possess all of the necessary tangible and intangible
assets, they establish links with other organizations such as other firms,
universities or other-related public research institutions (in the scheme named
PROs). Among these organization there are science parks and incubators, which
are found to be an additional source of knowledge capital.
Moreover, a very important effect generated by the collaboration with PROs and
VCs is the sponsorship and endorsement function that they exert. Indeed, VC’s
brokerage and endorsement function may increase a NTBF’s capacity to stipulate
commercial alliances with other firms (Colombo, Grilli and Piva, 2006).
The public sector enters the system in two time frames, a short and a long one. As
mentioned above, in the long-term public policy is crucial in creating an
institutional background that encourages innovation and healthy entrepreneurship,
while in the short-term it aims to challenge market imperfections and R&D
spillovers through specific instruments. In particular, two effects are highlighted,
one direct and one indirect. The former comes from the provision of direct
27 The build winner definition is taken from Baum and Silverman 2004.
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subsidies for NTBFs, the typical supporting instrument. Even though on average
the empirical literature confirms the positive effects of direct policy measures,
some specific analyses with a more strict focus on Eruoepan NTBFs suggest that
this positive effect is not taken for granted and, on the contrary, it may be effective
only under certain conditions and subsidy’s characteristics. Looking at the Italian
context, the impact of subsidies changes according to the type of the granted
support (Colombo, Giannelli and Grilli, 2013). More specifically, automatic
subsidies seem to have no impact, that is the case of fiscal incentives or other forms
of subsidy accessible by all firms that satisfy certain requirements. On the other
hand, when the subsidy is selective (e.g. grants) the effect on the growth of NTBFs
is found to be greater and significant.
This suggests that selective subsidies create the indirect effect know as
“certification effect” (Halo effect for Grilli 2014, Lerner 1999), according to which
the “selected” firm gets a sort of stamp of approval, which influence positively the
other actors involved in the NTBFs growth environment (VCs, other firms offering
complementary assets, others).28
5.3. The rationale of government investment
In line with this opinion is the last of the three pillars29 declared by Lerner (2010),
on which the rationale for government investment rests. According to the third
pillar, governments can effectively promote entrepreneurship and venture capital,
and in a broader viewsight there are some indications about how to shape the policy
28 According to Schneider and Veugelers (2010), young innovative firms benefit more from public support interventions than mature ones, and furthermore, they do even more when the policy is selective. 29 The first pillar affirms that, contrary to what most of the economists thought in the 19th century, the crucial driver of growth is changes in the way inputs are used and it is not a matter of adding more inputs in order to get more output. In other words. Innovation is the key for growth and many governments has recognized this fact. Second, entrepreneurship and venture capital own the reputation of being the roots of innovation, as highlighted by academic research. Moreover, hundreds of studies find a negative relationship between size and innovation; one in particular estimates that a single dollar of venture capital generates as much innovation as three dollars of traditional corporate research and development, thanks to the tools developed by VC that are particularly well suited to the challenging task of undertaking high-risk but promising new ideas. (Lerner, 2010)
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intervention considering factors that often, erroneously, are moved to the
background.
First, entrepreneurial activity does not exist in a vacuum: entrepreneurs are very
dependent on their partners. Managers, marketing experts, lawyers and engineers
as well as customers willing to take a chance on a young firm are necessary
elements, often more necessary than availability of capital. Taking a broad view
and addressing not just the need of capital but also other components of a
productive arena in which entrepreneurs can operate is essential. There are barriers
beyond the basic financing problem.
Second, let the market provide direction. Policymakers should use the market for
guidance, identifying independent venture funds in order not to compete with them
and avoiding to finance firms that cannot be able to raise private capital. To
succeed with the highest probability, programs may need to work closely with the
organization to refine strategies, recruit additional partners and identify potential
investors.
Third, do not overengineer the policy program. It is easy and common to fall into
the temptation of adding restrictions on multiple and often excessive dimensions
that hamper the flexbility of entrepreneurs and venture investors. Some examples
are limitations on the location where the firm can operate, the type of securities
VCs can use, later acquisition or secondary sales of stock, etc.
Fourth, promote the local academic scientific and reasearch base. In may regions
of the world there is a mismatch between the low level of entrepreneurial activity
and VC financing, on the one hand, and the strength of the scientific and research
base, on the other. The presence of technology transfer offices is very important
for the education of nascent academic entrepreneurs and their introduction to
venture investors.
Fifth, embrace the conformity to global standards. The Israeli government serves
as a model in this sense: in 1992 it established a US $100 million fund wholly
owned by the public sector, called Yozma Venture Capital Ltd. At the time
entrepreneurs were suspicious of venture investors, whose presence in the nation
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was very reduced. What made Yozma successful was its aim and capability to
bring foreign venture capitalists’ investment expertise and network of contacts.
Global institutional investors and venture funds may be discouraged if customary
partnership and, for instance, preferred stocks cannot be employed in a certain
nation. Therefore, policymakers should allow transactions that conform to the
models widely and internationally accepted as the best practise. Companies can
surely benefit from relationships with funds based elsewhere but investing locally,
which, in turn, communicate an attractive signal towards more overseas capital.
Global connections then are useful to broaden the firm’s boundaries towards
intarnational markets and it is widely recognized that, in order to be successful, a
multinational presence is a must.
Sixth, acknowledge the long lead time typical of public venture initiatives.
Impatience and creation of rules that force program participants to focus on short-
term return have been a very common failure of public entrepreneurship and
venture capital initiatives. Indeed, very often promising programs have been
abandoned too early on the basis of partial indicators not performing as expected.
Seventh, find the appropriate size for venture initiatives. Too small programs are
likely to do little to improve the environment for pioneering entrepreneurs and
venture funds, as well as too large ones might cause an imbalance between
plentiful capital and limited opportunities, turning up with backing groups not
capable to encourage properly entrepreneurship and probably crowding out local
investors (see the Canadian case30).
Finally, build education for all the three actors involved in order to oil the whole
mechanism. Foreign venture investors need to understand the potential of the local
market and its opportunities, otherwise their engagement can hardly be robust.
Entrepreneurs must understand the expectations of top-tier private investors, of
potential strategic partners and investment bankers to get the same shared view of
the path to follow. At the same time, the public sector would deeply benefit from
30 The Canadian Labor Fund Program backed incompetent groups that contributed little to spur entrepreneurship and crowded out some of the most knowledgeable local investors (Lerner, 2009; Lerner, 2010).
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an understanding of the challenges of entrepreneurship and venture capital
development, so that expensive errors made in the past could be avoided allowing
for a process of continuous improvement.
Besides paving the way to venture initiatives, there are additional methods that
government may consider. Teece (1986) gives some recommendations in his study
that focuses on the spillover matter. After some general considerations, most of
which have been discussed in the previous chapters, Teece argues that a
fundamental role of the state consists in creating an appropriate legal structure
suitable for young innovative companies. Indeed, legal enhancements can be made
not only on the investment structure of venture funds, but also on protection
methods especially in terms of intellectual property. However, it must be
recognized that there are inherent limits to the legal protection of IP, and that
business and national strategy are threefore likely to be the critical factors in
determining how the gains from innovation are shared worldwide. If a nation has
great innovations skills then, in the absence of iron clad protection for IP, it must
maintain well-developed complemetary assets if it is to capture the spillover
benefits from innovations. According to Teece (1986), the ownership of
complementary assets, particularly when specialized and/or cospecialiazed, helps
to establish who wins and who loses from innovation. Imitators indeed can
outperform innovators if they are better positioned with respect to the critical
complementary assets. As a consequence, public policies aimed at promoting
innovation must focus not only on R&D, but also on complementary assets, as well
as on the underlying infrastructure. It would be important to clear barriers
impeding the development of complementary assets which tend to be specialized
or cospecialized to innovation. As a corollary, Teece’s approach establishes that it
is the structure of the firms, more than the structure of markets, which determines
the distribution of the profits amongst innovators and imitators, in particular the
scope of their boudaries coupled with national policies with respect to the
development of complementary assets.
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5.4. The effectiveness of public policies, do they really work?
The extant literature that handles the efficacy and the efficiency of public policies
is really vast. In particular, direct measures are under the microscope.
First of all, it is worth introducing a model called “of noisy selection” as a general
background31. According to this model, newborn firms do not know ex-ante their
cost function and so their relative efficiency, but they rather discover it through a
process of learning that occurs in the early stages of their lifecycle. Afterwards,
those entrepreneurs with an efficient firm survive and grow, otherwise they exit
the market.32 Several studies that have handled this matter (Geroski, 1995;
Audretsch, 1995) share some general results. First, high entry rates are generally
associated with high exit rates, which means turbolence. Second, in most industrial
sectors many start-ups exit the market during the first years after inception (infant
mortality). Third, those small newborn firms which survive exhibit higher growth
rates than their larger peers.
Santarelli and Vivarelli (2002) study one of the most frequently used instruments
of industrial policy in the Eurozone: public subsidies in support of new firm
foundation. Their sample is made of 129 newborn firms that did not benefit from
national schemes aimed at supoprting entry of start-up companies. The dataset
used comes from the Italian National Institute for Social Security and identifies
new firms in electrical and electronic engineering starting-up in January 1987. Of
those 129, 83 still survived in 1993. This study reports results consistent with
others (Audretsch and Mahmood 1995, Audretsch et al. 1999) and notes a
dramatically high incidence of early failure, more pronounced in the very first
years of firms’ lifecycle. Moreover, the hazard rate (number of exited firms on
number of survived firms in the previous year) peaks in the second year of activity
and then the trend decreases.
What these results demostrate is that fewer efficient entrepreneurs find their cost
functions to be higher than expected and then exit the market. The role of subsidies
31 Boyan Jovanovic first introduced the model of noisy selection in 1982. 32 Santarelli and Vivarelli (2002) call this theory the “try and see” interpretation.
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in supporting new firms is to allow the cost functions to move downwards and
therefore strongly interfere with the market selection of less efficient
entrepreneurs. In presence of subsidies, entry rates increase and so do survival rates
in the first years following inception.
Two well-known distortions may arise in this case under the “try and see”
interpretation assumption (the noisy selection model): on the one hand, a higher
entry rate may translate into a higher number of early failure as soon as the effect
of the subsidy ceases. On the other hand, the process of market selection is biased
and delayed, allowing less efficient entrepreneurs to remain in the market until the
the subsidy is over.
In the first case, the subsidy happens to be useless, because efficient entrepreneurs
do not need it and the less efficient ones exit the market just like they would have
done without the subsidy, only later33. In the latter case instead, the subsidy
becomes harmful, since less efficient entrepreneurs are given an artificial seedbed,
while market competition would have induced them to leave the market. The first
scenario describes a situation where the industrial policy supporting entry is
affected by a deadweight component, while the second one transaltes in a
substitution effect.
In light of these considerations, there are two possible alternatives: either subsidies
belong to a post-entry policy and not to an “entry”one, or incentives to entry are
released on the basis of efficiency measures different from the start-up size34.
As a final consideration on this matter, it is worth to add that an entry subsidy may
also bias the adjustment process that takes place in the very fist years after entry:
in that period, efficient firms which entered the market at a suboptimal scale
survive through accelerated growth, while, in the following years, newborn firms
33 Audretsch (1995) extended a similar survey to 11.314 firms in all industries in US manufacturing, finding that survival rates in the first six years after start-up are rather homogeneous across industries. This supports make possible the generalization of the study led by Santarelli and Vivarelli (2002) which is focused on a confined Italian manufacturing sector. 34 The recommendation of not to take firm size as an indicator of efficiency is consistent with the study of Santarelli and Vivarelli (2002) and Audretsch et al. (1999). Their analyses find no significance evidence that likelihood of survival tends to be higher for firms whose start-up size is larger (this result holds for the Italian case in particular). Therefore, it cannot be considered as a proper proxy of post-entry efficiency and likelihood of survival.
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assume a Gibrat-like behaviour35 . The presence of subsidy may reduce the
difference of performances between those efficient firms that, lacking the subsidy,
would have decided to grow and the less efficient ones that would have decided to
exit.
Another work concerning the actual effects of public intervention analyses the
effect of public subsidies on firms’ investments in a sample of italian unlisted non-
venure capital backed owner-managed NTBFs (Colombo, Croce and Guerini,
2013). In particular, it measures the treatment effect of public subsidies on the
investment rate and investment-cash flow sensitivity of NTBFs. A substancial
investment-cash flow sensitivity is considered as the indication that a firm is
financially constrained. Whether the removal of the financial contraints is transient
or persistent is also assessed.
Theoretically, public subsidies are expected to have both direct and indirect
implications. The former consists in an immediate increase of investments, since
financially constrained firms find profitable projects that would not be so without
the subsidy; while in the case of not constrained firms, a substitution effect may
occur as long as the public subsidy replaces internal funds or debt.
The latter has a twofold nature: first, firms may use the subsidy in order to acquire
tangible assets valuable then also as collateral; second, there can be a certification
effect out of a selective subsidy program.
The empirical findings indicate that small NTBFs are actually able to remove the
financial constraints when receiving public subsidies: their investment rate
increases and investments are no longer positively related to internal cash flows,
so they can finance the projects previously postponed. In addition, as expected,
this result does not hold significantly for large NTBFs, whose investment rate is
not that much affected. In particular, the study suggests that the impact of the first
public subsidy is definitely more important than subsequent ones.
35 It has been proven by Santarelli and Vivarelli (2002) that Gibrat’s Law does not hold for new entrants. Gibrat's law (sometimes called Gibrat's rule of proportionate growth or the law of proportionate effect) is a rule defined by Robert Gibrat in 1931 stating that the size of a firm and its relative rate of growth are independent.
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For what concerns the persistency or the transience of the beneficial effect, it has
been discovered that the influence on the investment cash flow is persistent,
contrary to the one on the investment rate which is not36. From a general point of
view, public aids may have an enduring positive effect on the investment activity
because small companies get the chance to grow unconstrained becoming large
enough to be no longer bound. Secondly, the possible signal effect broadens the
fan of financing sources.
Czarnitzki (2006) follows a similar study on West and East Germany companies,
showing that the receipt of public subsidies leads to a 60% increase in the
probability of a firm located in East Germany investing in R&D (the figure for
West Germany is +24%).
All these findings contribute to support the idea that public subsidies can help
small NTBFs in persistently removing the financial constraints binding their
investment activity.
5.5. Limitations and obstacles to public intervention
Public intervention manifests also a considerable range of inefficiences though: an
extensive literature, which analyzes the effectiveness of public instruments, very
often underlines also the main limitations, obstacles and problems that public
policies are liekly to encounter.
To begin with the non-technical reasons why public efforts may not solve the
financing problems of small firms, Lerner (2002) mentions the distortions that may
result from government subsidies because of particular interest groups or
politicians seeking direct subsidies in a manner that benefits themselves.
Distortions may arise in different ways. As a first instance, firms may seek transfer
payments that directly increase their profits and politicians may agree to such
36 For small subsidised NTBFs, the null hypothesis of no persistent positive dependence of investments on cash flow shocks after receipt of a public subsidy cannot be rejected at conventional confidence levels. Regarding the investment cash flow sensitivity of large NTBFs, receiving a public subsidy has no effect even in the long run. On the other hand, the effect of public subsidies on the investment rate of both small and large NTBFs is not persistent over time (Colombo et al. 2013).
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transfers when companies are politically connected. Another possibility is that
officials may seek to select firms based on their likely success, and fund them
without really consider whether the government funds are needed or not. In this
way they can claim credit for the firms’ success even if the marginal contribution
of the public funds was very low. The danger of this circumstances to show up gets
higher in programmes where a central group makes highly visible awards.37
More in general, there is a fundamental reason to be cautious when assessing the
efficacy of government intervention: government can simply get the allocation
wrong, supporting bad entrepreneurs and/or in a counterproductive manner. Lerner
(2010) notices that, looking at the factors that affect the quality of governmental
efforts in general, more competent programs live in wealthier nations with more
heterogeneous populations, and an English legal tradition.
Critical contraints usually affect any kind of economic policy, in different ways
and intensity. In addition to the exposure to manipulations by vested interests
mentioned above, another typical issue to take into consideration are the
administrative costs of running policies, which characterize limitations more often
than not. However, a deeper concern in policy design is the question of ‘leverage’
versus ‘displacement’ effects. In fact, positive leverage is achieved if private
investments rise by more than the amount of the subsidy, but when the opposite
happens, in other words if “crowding-out” occurs, the subsidies displace part of
the private investments that firms would have financed themselves. The foregone
opportunity to direct public resources in a better usage, with positive leverage,
constitutes the social cost of policy failure.
Furthermore, there is another relevant effect policy maker need to consider when
planning a policy scheme: the signal the public support might exert. Colombo,
Grilli and Verga (2007) evaluate the certification/signal effect supposed to flow
37 Some examples of this issue are the following: the US Small Business Administration, in the 1960s, funded hundreds of funds whose managers were incompetent because of the haste to roll out the Small Investment Company program. Norway wasted much of its oil wealth in the 1970s backing up failing ventures and funding ill-conceived new businesses begun by relatives of parliamentarians and bureaucrats.
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out of a selective subsidy. In particular, they study whether the receipt of a public
aid, a policy measure, exerts any effect on the NTBFs’ likelihood of accessing VC
financing. They don’t find any significant effect in this sense, and so exclude the
existance of any imporant certificationn effect associated with the receipt of public
subsidies for what concers the italian situation.38
Grilli and Murtinu (2014) follow a similar study, they examine how selective
subsidies work on young high-tech firms in terms of quality signal towards their
potential R&D alliance partners. On this detail, they find public grants in support
of NTBFs to exert the “stamp of approval” effect in the access of these firms to
R&D alliances. Moreover, this certification effect applies to both corporate and
academic partners, even though it is stronger on academics.
All these considerations lead to the conclusion that not only the governmental duty
of supporting innovation and the social environment is delicate to manage through
a variety of instruments, but also that theoretical consequences originating from
specific public interventions are definitely not to be taken for granted. It is
important to remark that policy interventions are evaluated primarily on their
ability to produce additional positive effects, positive contributions not reachable
otherwise. As a consquence, not only the screening/picking capabilities must not
lead the resources towards “bad” companies, but also they should not support the
best ones as well, because these latter would probably perform well either way
(cherry-picking). The next section deals with this issue analyzing one of the most
famous effects policy makers should not forget, the matthew effect.
5.6. The Matthew Effect
In addition to the collection of effects arising from public policies, there is one
strictly related to R&D public subsidies in the form of selective programs that can
turn into an additional government failure. This effect is called “Matthew effect”39
38 The study is developed on a sample of 550 Italian NTBFs that operate in both manufacturing and services sectors (Colombo et al., 2007). 39 In sociology, the Matthew Effect is a social phenomenon often linked to the idea that 'the rich get richer and the poor get poorer.' In essence, this refers to a common concept that those who already have status are
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and it has been studied by Antonelli and Crespi (2013). In more detail, their
analysis consists in exploring the causes and the effects in the discretionary
allocation of public subsidies to R&D activities performed by private firms, and it
elaborates a clear distinction between virtuous Matthew effects and vicious
Matthew effects. The former indentifies the persistence of the provision of
subsidies to firms that have been actually able to use previous subsidies to
effectively increase their research activity, while the latter includes the cases of
persistence in the assignment of public subsidies based solely on reputation, even
to firms that have reduced their commitment to R&D after receiving previous
subsidies. In this sense, vicious cases are considered another potential source of
government failure in the provision of R&D grants. Indeed, this negative effect is
supposed to take place in the selective allocation of public resources based upon
beauty contests, when the members of the selection committees could be too much
influeced by the scientific and technological reputation of the candidates, rather
than by the sheer quality of the projects. The underlying idea is that the reputation
of the candidates would become a proxy for the quality of the projects, in
particular, this very reputation would be strongly influenced by previous awards
and in this case by the inclusion in precedent assignments tournaments. The study
of Antonelli and Crespi conducts an empirical analysis based on the exam of
transition probabilities between states: both the descriptive and econometric results
show that past grants increase the chances to access further funding and therefore
that the access to public subsidies for R&D activities is actually characterized by
significant persistence.
The empirical findings related to the Italian evidence provide some support to the
hypothesis that positive persistence is at work, namely there is a virtuous Matthew
effect in the Italian experience that agrees with the adoption of a “picking the
winner strategy” by public authorities.
often placed in situations where they gain more, and those that do not have status typically struggle to achieve more. This phrase has been attributed to sociologist Robert K. Merton and based it off a biblical verse in the Gospel of Matthew.
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However, in general, selective subsidies risk to provide benefiting firms with an
artificial competitive edge, therefore they have the potential to keep inefficient
recipients alive and inducing a crowding out of non-subsidized firms. Furthermore,
the persistence in the assignment of these public aids could create, in a long-term
perspective, problems of lock-in and stickiness to existent technological paths, at
both micro and system levels. In order to minimize the occurrence of a vicious
Matthew effect the evaluation process must take into account this issue, monitoring
the use of objective criteria based on past performance.
5.7. The “Jamaica and Singapore” case: a great example of two
different growth paths
A great example of comparison between two singular cases is brought by Lerner
(2010). This case contrasts Jamaica and Singapore and it is a great example to
understand the importance of public programmes.
Both the island countries are quite tiny with under 5 million residents each and,
what is most important for this evaluation, they were of equal wealth in the 1960s,
when Singapore had its independece and Jamaica its own establishment as a
nation.
The Gross Domestic Product (GDP) at that time was $2.850 per Jamaican person
and Singapore’s $2.650 was only slightly lower. Both nations had a centrally
located port, a tradition of British colonial rule, and governments with a strong
capitalist orientation. Moreover, Jamaica had a generous amount of natural
resources and a solid tourist industry.
The situation of the two states four decades later was unbelievably different:
Singapore had reached a GDP per capita of $31.400, while Jamaica reported a
dramatically lower value with a GDP equal to $4.800.40
The reason of such a dissimilar evolution is attributed to many factors: Singapore,
immediately after independence, invested in several essential fields as
40 Figures computed using the World Bank’s World Development Indicators database (Lerner, 2010).
87
infrastructures, education, the maintainance of an open and corruption-free
economy and established sovereign wealth funds that made a wide variety of
investments.
On the opposite, Jamaica in those years lived a period of political instability with
shifts from a market economy to a socialist orientation, moreover, a heavy public
debt and violence made an implementation of long-run economic policy very
difficult.
Coming back to Singapore, a great share of its notable growth came from its
policies towards entrepreneurship. Public funds for venture investors seeking to
locate in the city-state, subsidies for firms in targeted technologies, encouragement
of potential entrepreneurs and mentoring for inexperienced ventures, subsidies for
leading biotechnology researchers to move their laboratories to the city and awards
for failed entrepreneurs. All these elements contributed largely to develop an
entrepreneurial sector. At its first steps, the growth of Singapore can be attributed
to macroeconomic policies, political stability and other factors, but in the medium
and long term the entrepreneurship initiatives certainly have been a crucial
ingredient in the process of stimulating growth.
On the same line, barriers to entrepreneurship are seen as a relevant reason for the
inability of Jamaican growth. In the World Bank’s 2008 analysis “International
Finance Corporation” (2010a), are listed some of the barriers holding back
entrepreneurship development. First, Jamaica ranked 170th out of 178 in the burden
of complying with tax regulations and the valuation included not only the cost of
taxes themselves, but also the administrative burdens associated with complying
with the tax code. Several studies agree on the shared opinion that one of the most
important source of financing for the typical entrepreneur is the cash flow
generated by the business itself in order to be reinvested and, since most of the
income goes to meet tax obligations, business owners find hard to have the
resources to invest in the enterprises.41
41 In the same classification of the International Finance Corporation, Singapore ranked 2nd worldwide, with a burden of 23%.
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A second barrier is the cost of registering property, in front of which Jamaica’s
situation ranked 108th out of 178 with a cost equal to 13,5% of the value of the
property. Generally, higher costs of registering property lead to fewer people
registering their holdings, which translates to less secure propery rights. In the
specific case of entrepreneurs and new companies, this matter is even heavier
because without a firm legal title to property, it is unlikely to borrow against this
holding from a bank. Therefore entrepreneurs have again fewer resources to tap
into.
5.8. Vertical subsidies VS horizontal ones. The guidelines for
policies deisgn
While understanding the importance of public support measures is quite immediate
for the variety of reasons seen so far, realizing how to design them is not.
Whether the subsidy is selective or automatic, the relative impact differs
considerably. Another relevant major distinction in the structure of a public
measure is its focus, whom it is addressed to. This distinction is stated through the
expression “vertical” or “horizontal” subsidy, meaning that horizontal ones are not
specifically designed for a target type of companies, for example NTBFs, contrary
to the vertical ones.
Colombo and Grilli (2006) study this very issue, taking into consideration the
Italian case. Differently from some other European countries that adopt national
government support policies targeted to NTBFs, Italy had not implemented any
specific support measure designed for this type of firms, yet. They investigates
whether horizontal general-purpose direct support mechanisms at national level
permit an efficient allocation of public funds.
Generally, policies can differ according to four main characteristics: the main
objective, the evaluation method, the main instrument and the main target group.
The first one is categorized in three fields: investments in R&D, general purpose
investments and depressed areas. The second one distinguish between automatic
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and selective measures42. Main instruments can identify two types of support,
fiscal benefits or incentives, and fiscal contributions. In the end, the main target
group classifies whether the national scheme is devoted to support all firms or new
entrepreneurship and small-medium enterprises.
The study (Colombo and Grilli, 2006) was meant to find possible inefficiences
associated with particular types of schemes or to prove that they concern the whole
set of public support measures. Their findings state that inefficiences are actually
associated with all types of horizontal direct schemes and may not be imputed to
specific policy measures: the results highlight the high risk that these policies bring
end up in a substitution effect in young high-tech sectors.
In conclusion, NTBFs benefit more from specific and customised policy schemes,
in other words from vertical subsidies. Therefore, it should be considered at first
a focus on vertical technology policies targeted to young high-tech firms. Priority
must be given to public interventions targeting firms potentially successful and
characterized by high-growth prospects. Secondary, a policy measure needs to
support those high-growth prospect firms that suffer from market imperfections.
It is also true that following this route, government faces relevant costs in terms of
adverse selection and moral hazard problems. That is why indirect support
schemes delegating these problems to specialized institutions are probably more
effective, such as technology incubators and the venture capital industry. It is
worth to notice that Italy in particular is weak in both of these last two elements,
because it is slower than other countries in high-tech activities and it also has a
bank-based system. Therefore, interventions that are meant to reduce the
managerial and administrative costs of venture capitalists become vital in order to
make firms more attractive and strenghten their chances to be financed.
Martin and Scott (2000) examine this vertical interventions deeply, asserting that
the force leading to private underinvestment in innovation differ from sector to
sector across the economy, and policy design should take these differences into
42 As a reminder, “automatic” means the financial assistance is given to all applicants that fulfil all of the requirements specified in the law; “selective” refers to the financial support that goes to selected applicants after a competition between candidates. In this latter case a committee formed by experts judges the projects of the candidates.
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account managing properly the variety of contributions of public resources that
can take many forms. According to their point of view, not only public support
should not take the form of horizontal measure, but neither of vertical direct grants.
That is because government usually has a weak record of identifying ultimately
successful lines of technological development in advance. Moreover, they would
exclude also the forms of government debt or direct equity financing. On the other
hand, government should rather focus on setting up market infrastructure and on
creating an environment conducive to entrepreneurship, encouraging product-
market competition with an anti-trust regime for instance.43
However, this approach in practise cannot work, because technologically intensive
firms are actually constrained and investments are limited. As a consequence, the
prevalence of innovation market failure and underinvestment in technology
expresses the need to establish a long-term institutional framwork for the support
of basic research and commercialization. To address the diversities among sectors
in the economy and promote innovative start-ups, a simple distinction between
high-tech and low-tech may not be enough though, because it easily excludes
important sectors such as agriculture, whose technological advance is low-tech,
can bring huge potential pay-off.
The main categories to focus on are: the development of innovative inputs with
public support for venture capital markets, the development of complex systems
promoting R&D cooperation also with subsidies early in the life of cooperation
activity, the application of innovative inputs facilitating technology transfer and
the support of high science-content technology. Institutional support acts as
bridging institutions in the last two points.
Policy in fact, should also be open to the possibility of direct subsidies, but only in
the early period and, according also to Colombo, Giannelli and Grilli (2012), this
holds also for general direct financing: they study the impact of public subsidies
on emplyment growth of NTBFs, finding selective schemes to have a larger impact
only if the firms receives it in the early period.
43 See Nelson (1982): an antitrust regime that faces the erection of artificial barriers to entry will promote innovation by new firms.
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Storey and Tether (1998) focus on the theme of culture, education and incubators,
as anticipated in the third chapter. They propose five policies areas to converge the
efforts in, and three out of five concern education: indeed, apart from the two
general advises of giving a direct government financing to NTBFs and give them
advisory services, the focal point lies on science parks, PhDs and universities
collaborations. Science parks have grown in many countries as a partnership
between regional and national governments, universities and regional and local
private sector interest groups. It is well known that the United States have always
had an edge over other countries, and it served as a catalyst for Europe to drive in
this direction indeed. Even so, the European situation improved in the last two
decades: currently France and United Kingdom are the leaders with about 60
science parks each and also with a great advantage (the third in the list is Finland
with 24 science parks), while Italy, even though it has improved notably in the last
twenty years, counts 6 science parks (www.unesco.org).
Moving to the individual level, the proportion of founders of NTBFs that have a
science or technology based PhD has increased strikingly in recent years.
According to Storey and Tether, only individuals who have studied at the highest
academic level have sufficient understanding of the technologies that the leading
edge firms are seeking to develop. However, not only individuals with science-
based PhDs will be the owners of NTBFs: also teams that combine managerial and
technical skills can turn out successful. Nevertheless, as the technology becomes
more sophisticated, NTBFs at the leading edge are less likely to come into
existence without someone the in the senior management team having highly
sophisticated technical knowledge. It must be underlined that not all, or even a
sizeable proportion, of these individuals with science-based PhDs seek to become
owners of an NTBFs. On the contrary, the vast majority of them express their wish
to continue with their science, rather than seeking to directly commercialise their
expertise. Moreover, and this holds particularly for Italy, the educated to the
highest level (PhD) often recognise that better employment opportunities are found
abroad.
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Going on with the guidelines for composing a correct policy, Grilli (2014) stresses
a particular area of intervention already mentioned but often less considered by
policy makers: the cultural approach of entreprenerus towards failure. The
underlying idea is that, from a welfare perspective, to have a great number of
successful NTBFs, it would be essential not only to just encourage more people to
become entrepreneurs (the negative consequences of encouraging too much have
been already explained quoting Shane 2009) but rather to push those with the best
chances to succeed creating their own high-tech businesses. It is important because
the opportunity cost for those high-level educated individuals to invest their human
capital in high-tech entrepreneurship, instead of pursuing alternative options, is
comparatively high in Europe. Indeed, in the Euroepan context the administrative
and cultural burdens associated with failure are relevant, therefore the multitude
of business failures, typical of the high-tech entrepreneurship, influences deeply
the willing of valid individuals to undertake this kind of career.
In this respect, policy makers should intervene at cultural levels as well as at
regulatory ones in order to lessen the cultural burdens of failure. The same concept
has been introduced talking about Singpore and its habit of giving an award to the
best failed entrepreneur. Moreover, some countries of Europe have adopted, in the
recent past, new law reforms with regard to bankrupcy. Italy itself belongs to this
group with its lesgislative decree of September 2007. However, more often than
not the priority resides in increasing the options for rescuing financially distressed
companies, rather than enhance the conditions for the failed entrepreneur to start a
rapid second beginning.
Vanacker et al. (2014) provide evidence on the relationship between national legal
systems and the financing of private NTBFs. Moreover, they analyze the
implication of the strenght of shareholder protection on equity financing. First of
all, they study how cross-country differences in shareholder protection against
self-dealing and personal bankrupcy laws affect the financing of NTBFs. Second,
they study how VC investors, acting as expert monitors and initators of good
governance practises in firms, moderate those relationships. The sample embraces
companies from six European countries and the findings show that better
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shareholder protection rights increase the probability of rising external equity
financing and allows firms with larger amounts of it. Furthermore, less forgiving
personal bankrupcy laws decrease the probability of raising debt financing and
limit the amount of financial resources raised. The conclusions of Vanacker et al.
points to increase the supply of VC financing as a general cure for external
financing constraints, and the beneficial effect is even stronger in countries with
strong investor protection rights and entrepreneur-friendly personal bankrupcy
laws.
Looking at the European context, during the first decade of the 21st century, only
28 reforms measures enabling a rapid second start have been introduced, overall.
Anyhow, 88 policy interventions oriented to reduce administrative burdens on the
creation of start-ups have been produced44.
What needs to be enhanced is how business failure is perceived from a cultural
sphere. In other words, Europe must shape and develop a mentality that sees
failures as normal “events” in an evolution process, and not equal to the “end of
the world”. At present, Europe lacks of a policy-making that considers both
legislative and cultural layers, and it should point to the creation of a risk loving
attitude.
The proper tuning of a public intervention is clearly all but simple and, indeed,
there is evidence that the right way to proceed with public policies is to implement
more than one intervention at the same time.
Mohnen and Roller (2005) study exactly this specific issue, they develop a
framework for testing discrete complementarities in innovation policy using
European data on obstacles to innovation. These latter obstacles are mainly four:
lack of appropriate sources of finance, lack of skilled personnel, lack of
opportunities for cooperation with other firms and technological institutions, and
legislation, norms regulation, standards and taxation.
44 Source MICREF database, June 2014.
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They test the decision to innovate or not (i.e. probability to innovate) and if so, by
how much (i.e. intensity of innovation). Overall, the results of the former test
suggest that there is a considerable substitutability across most obstacles.
On the contrary, testing intensity of innovation they find a significant
complementarity over several obstacles: in particular, lack of finance is
complementary with all other obstacles meaning that insufficient finance resources
lower the intensity of innovation by more whenever there is lack of valid internal
human capital, or lack of opportunity to cooperate with other firms or when
regulatory hindrances exist. It is found a relationship of substitutability between
lack of internal human capital and lack of cooperation with other firms, as well as
between this latter one and regulations.
The divergence between the two analysis highlights that the existance of
complementarity depends on the phase of innovation, whether to innovate or not
and if so with what intensity, as well as on the particular obstacle pair.
Under these circumstances, the design of an optimal policy can result particularly
difficult as long as there are these dissimilarities between the two phases of
innovation: while complementarity is rejected for promoting the propensity to
become an innovator, lack of access to finance is complementary to all other
obstacles regarding the intensity of innovation. To clarify, when two obstacles are
substitutes, the presence of one relieves the pressure from the other one, therefore,
by removing it the other is aggravated. The implication is that to operate efficiently
both obstacles need to be removed jointly. On the other hand, two complement
obstacles strenghten each other and the removal of one entails an attenuation of
the other one.
As a corollary, when it comes to turn non-innovators into innovators, it is surely
reasonable to remove a bunch of obstacles at the same time. Policy makers then
should intervene with a package of policies, for example increasing the amount of
skilled personnel and reducing the regulatory burden. Easier is the case when the
objective is to boost the intensity of innovation, because one or other policies can
be effective, such as easing access ti finance or making more skilled labor
available.
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5.9. A review of public policies in European countries
Historically, European countries have faced the government intervention issue in
different ways, with different commitment and/or direction. It has been explained
previously how the United States have always been one step ahead of Europe from
the point of view of high-tech innovation and the development of a fertile
environment for start-ups, especially the technology based ones.
Looking at the last decades of the 20th century, the differences were more evident.
In some of EU countries, such as Belgium, Germany45 and Spain, most forms of
industrial assistance were provided at a local or regional level as well as by national
governments. In other countries such as France or UK, even though there was a
delivery of assistance, the policy was mainly delivered only through national
government schemes.
The discrepancy between European countries emerges from the descriptive
analysis of the national government support policies, as it emerged from the data
on the presence of science parks. Table 2 displays the direct national financial
support policy situation in the ‘90s in the European region, in particular, it shows
the policy intervention focusing on small and medium enterprises in areas where
high-tech start-ups were important. Data go back to the last part of the last century
in order to have an overview of the policies that shaped the ground on which
economy stands nowadays. A further comparison with more recent interventions
has not been included in this broad group because of difficuties to reach latest data.
Anyhow, single recent interventions of specific areas (e.g. Europe, Germany, Italy)
are discussed later on.
45 The Laender in Germany provided financial support to NTBFs which, in monetary terms, exceeded the value of national government schemes.
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Table 2. National government direct financial support policy to NTBFs.
Support focusing on SMEs but where NTBFs were important
No. of Schemes Grant Interest relief Other46
Austria 2 1 1
Belgium 0
Denmark 0
Finland 3 1 1 1
France 1 1
Germany 3 1 1 1
Greece 2 1 1
Ireland 1 1 1
Italy 2 1 1 1
Netherlands 2 1 1
Portugal 1 1
Spain 2 1 1
Sweden 0
United Kingdom 0
From the table, it seems that Sweden and United Kingdom did not introduce any
policy to back young innovative firms up; on the contrary, Sweden, UK and
Germany were the only three coutries which produced policies targeted explicitly
and exclusively upon NTBFs: indeed, Germany and Sweden made one scheme
each (Sweden in form of interest relief), while United Kingdom produced two
schemes (one grant and one interest relief in this direction). The preferred strategy
is clearly to have schemes which focus strongly, but not exclusively, upon NTBFs.
Table 3 covers the schemes in those three European countries that have focused
exclusively upon NTBFs.47
46 The category “other” includes other minor forms of assistance such as tax relief and provision of guarantees. 47 To have an illustration of national government direct funding policies covering NTBFs among SMEs, see Storey and Tether (1998), page 1050.
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Table 3. National government direct financing policies for only NTBFs.
Country Scheme name Function Instrument
Germany BTU: Equity
capital for small
technology
firms
To incentivize
investors to
provide additional
support for the
birth and
devlopment of
NTBFs
Promotion of equity capital
investments (guarantees,
co-investments)
Sweden Seed financing
of product
development in
NTBFs
Easy access to
finance for NTBFs
Subsidized interest rates
and access to funding
UK 1. Small firm
merit award
scheme
2. Support for
products under
research
To overcome
problem in early-
stage financing of
NTBFs
To provide support
for innovative
projects at an early
stage
Winners of the competition
receive the cover of 75% of
project costs for the first
year. A possible additional
award of 30% flat rate
support up to maximum of
£250.000
Source: Storey and Tether (1998)
Worth to notice is the German scheme that includes two types of schemes, one
provides guarantees and one is a co-investor model.
Overall, all these specific interventions had positive results and were considered
successful. Even though there is no evidence of the elimination of the financial
gaps, they clearly played a valuable role, suggesting that NTBFs suffer from
financial constraints not shared with all enterprises or even all SMEs.
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Consequently, these specific young high-tech innovative firms need their own
special schemes of intervention.
More recently, in 2004, France strengthened its effort in supporting high-tech new
firms with the scheme called "Jeune entreprise innovante" (JEI)48, which basically
consists in deductions related to research expenditures for young innovative
companies born between 2004 and 2016 and with less than eight years of age.
The Europe 2020 strategy of the European Commission has formulated the target
to invest to 3% of the annual gross domestic product in all member states into
research and development activities. Recent analyses of Eurostat (2012) shed some
light on the situation: the gross domestic expenditure on R&D in 2010 amounted
in the EU-27 states to 245,7 billion Euro, which represents an increase of 3,8%
compared to the previous year and of 43,5% compared to 2000.
5.10. The American case
Very remarkable is the case of the United States, whose famous SBIR program
dates back to 1982. Indeed, the Small Business Innovation Research (or SBIR) was
established with the passing of the “Small Business Innovation Development” Act
in the same year, in order to award federal research grants to small businesses. The
SBIR program has four original objectives: to stimulate technological innovation,
to use small businesses to meet Federal research and development needs, to foster
and encourage participation by minorities and disadvantaged people in
technological innovation and to increase private sector commercialization
innovations derived from Federal R&D.
The program is composed of three phases with award monetary contracts and/or
grants in the following manner: in phase one, the start-up phase, it makes awards
of "up to $150,000 for approximately 6 months support for exploration of the
technical merit or feasibility of an idea or technology."
48 The title translated corresponds to “Young innovative company”.
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In phase two, it awards grants of "up to $1 million, for as many as 2 years," in
order to facilitate expansion of phase one results. R&D work is performed and the
developer evaluates the potential of commercialization. Up to 2014 phase two
grants were awarded exclusively to phase one award winners, but in 2014 the DOD
(Department of Defence), NIH (National Institutes of Health) and Education are
allowed to make "direct to phase two" awards.
Finally, phase three is intended to be the time when innovation moves from the
laboratory into the marketplace. No additional SBIR set-aside funds may be
awarded for this phase, "The small business must find funding in the private sector
or other non-SBIR federal agency funding."
In 2010, the SBIR program across 11 federal agencies provided over $2 Billion in
grants and contracts to small U.S. businesses for research in innovation leading to
commercialization. The company owns the intellectual property and all
commercialization rights. Companies such as Symantec, Qualcomm, Da Vinci
Surgical System and iRobot received largely important early-stage funding from
this program.
The approach pursued by the United States is certainly stronger and actually more
effective. A study of the Kauffman Foundation (Kauffman 2012) showed that
between 2000 and 2010, almost all new jobs in the USA have been created by fast-
growing tech start-ups.
5.11. The Italian case
Italy belonged to the part of Europe which did not targeted NTBFs with specific
policy measures and it also lacked any systematic indirect support to them.
The topic is deeply studied by Colombo and Grilli (2006) and Colombo, Guerini
and Croce (2013), who gathered a very detailed collection of informations about
the historical policy schemes from the ‘90s to the first decade of the 21st century.
In those years, the only partial policy oriented towards NTBFs dates back to 1999
with the Law 297/1999, whose aim was to encourage the creation of academic
start-ups.
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A complete picture of the policies that came one after another in the period from
year 1965 until 2001 is shown by Table 4, which reports a taxonomy of the Italian
national direct support schemes using a classification of four criteria (Colombo
and Grilli, 2006): objective of the policy, evaluation method, instrument of
application of the policy and targeted group. Looking at the “table”, it is possible
to make some considerations: Italian policy makers strongly prefer measures of
interventions in form of general-purpose investments, far from the idea of focusing
on NTBFs; there is not a predominant evaluation method, since automatic and
selective schemes are equally pursued (16 and 12 respectively); there is a
preference for granting public direct subsidies as financial contributions rather than
fiscal benefits or incentives (20 vs 14); finally, not only legislators did not address
specific interventions towards NTBFs, but also those schemes devoted to stimulate
the creation of entrepreneurship and SMEs (11) are much fewer than the ones
directed to support all firms in general (17).
In the following years, the support to firms located in the depressed areas of the
South of Italy has traditionally been the priority objective, because those areas
suffer from and economic and social gap compared to the other regions. In
particular, almost half of the total amount of subsidies to private firms in the years
2000-2003 had depressed areas as the target.49 One fifth of those subsidies had as
objective the support to R&D and innovation, while almost 10% of it went to
investments in tangible and intangible assets. The remaining share of the total
amount of subsidies were addressed to other purposes such as internationalization
of firms’ activities.
49 Historically, the most important schemes directed to depressed areas are the Law 64/1986 and 488/1992,
which provided grants and other forms of support to the firms in the South of Italy.
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5.12. The German case
Germany is a great example for Europe of how to embrace the innovation
philosphy. It is the largest economy in Europe and the fourth largest economy
worldwide. Differently from USA, the tendency in the population to get self-
employed is not only still marginal, but also despite governmental efforts, the
number of people interested in starting their own business has declined since 2004
in 23 of the 27 member States of the European Union to 37% of the population. In
this regard, 78% of the German population shares this idea (EU Commission
2012). However, today the employment situation in Germany is very positive and,
due to a shortage of people with academic qualifications, the career opportunities
for academics are good.
The regulatory environment is getting more welcoming under several points of
view. First, research and technology transfer is supported by various legislations
such as the “Pact for Research and Innovation” or the German “Employed
Inventor’s Act”50, including university laws: the “University Freedom Law” grants
universities more freedom setting up their strategies for research and in terms of
spin-off creation and support. Second, the ease of registering a new business is
quite efficient compared to other European countries, since it takes 12 days to
found a proprietorship and 24 for founding a Limited Liability Company; even
though in the U.S. it takes only 5 days. The majority of Europeans have rated the
founding process to be too complex and bureaucratic. Third, there has been funded
a support for start-ups and innovation projects, otherwise the German total
corporate tax of 49,4% would be a hard enemy for new companies. For instance,
to promote the venture capital motivation, in 2013 a grant was introduced giving
business angels investing in innnovative companies a 20% subsidy in their
investment to lower the risk. However, the entrepreneurship awareness as risk-
taking propensity is not the strongest and also VCs often think like bankers
avoiding risks. Many countries in Europe attach a serious social stigma to
bankrupcy and those who fail are considered losers by their peers.
50 The German Employment Inventor’s Act revoked, in 2002, the long-standing privilege for employees of
universities, which allowed university researchers to take possession of patent rights to their inventions.
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Finally, access to finance. Federal research funding in Germany is constantly rising
and close to reach the 3% goal of the European 2020 Strategy, it has increased
from 7.8 billion Euro in 2005 to 10,9 billion Euro in 2011. The recent flagship
initiative is the High-Tech-Grunderfonds, a public-private venture capital
investment firm based in Bonn that, as an early stage seed investor, focuses on
high potential high-tech start-ups. It was launched in 2005 with a total amount of
272 million Euro and, in a period of 6 years, it has launched successfully 250
companies.
Table 5 reports a summary of the policy initiatives to support the entrepreneur
ecosystem.
Table 5. Summary of the policy initiatives to support the entrepreneur ecosystem
(GSVA: German Silicon Valley Accelerator; BVK: federal association of German equity investment
organization; UG: entrepreneurial company with limited liability). Source: Fuerliniger et al. (2015).
Policy Analysis
Framework
Science-based Innovation Process
Research &
Innovation
Early Stage Tech
Development
Product & Business
Development
Pol
icy
Mea
ns a
nd In
stru
men
ts
Regulatory
Environment
-German Employment
Innovator’s Act
-Pact of Research and
Innovation
University
Freedom Law
-UG
-Second Chance
-Bankrupcy
resilience
Entrepreneurship
education & awareness
-University excellence
initiative
-More chairs of
entrepreneurship
Access to Finance Aim of 3% Public
R&D financing
Hightech
Grunderfond
-New VC Law
-BVK
-KfW
Tech Exchange,
Innovation &
Networking
-EXIST
-Fraunhofer
Society
-State-level agencies
-GSVA
-German House of
research and
innovation
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In conclusion, German government understands the importance of
entrepreneurship and acts on many levels to build a sustainable ecosystem, which
is very likely to become the birthplace of new technology-based, fast-growing, and
global companies.
5.13. The European Investment Fund
One of the latest intervention made by the European Commission is the Multi-
Annual Programme (MAP) for enterprises and entrepreneurship “EU Guarantees
on Credit to SMEs” with the European Investment Fund (EIF). On this regard,
Asdrubali and Signore (2015) analyse the economic impact of this program of
guarantee facility in central, eastern and south eastern countries (CESEE) of
Europe in the period 2005-2012.
The loan window of the MAP guarantee facility for SMEs was managed by the
EIF and provided guarantees on loans to borrowers by covering a share of the
default risk of the loan (see Figure 13). Concretely, the EIF, under the mandate of
the European Commission, extended credit guarantees to financial intermediaries
such as public and mutual guarantee institutions, microfinance institutions and
banks (commercial or publicly-owned or controlled banks). On the whole, 14.000
SMEs belonging to the CESEE region were supplied with around 16.000 loans
from 2003 to 2010.
The use of Public Credit Guarantee Schemes (PCGSs) derives from the shared
awareness that the financial constraints of which SMEs suffer from are
exacerbated by the lack of adequate collateral. It is a common direct policy tool
across OECD and non-OECD economies that alleviates SMEs’ financial distress:
the estimates of OECD (2015) on 14 EU members report an amount of 200 billion
Euro provided to SMEs in the period from 2007 to 2013, which potentially
generated an amount of financing ten times larger. The decision to focus on
CESEE countries lies in the situation these countries have been in during the
financial crisis, which have brought constrained supply of credit, low profitability
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and rising levels of non-performing loans that have limited banks’ risk-taking
capacity.
The study of Asdrubali and Signore (2015) evaluates the effect of having received
a MAP-guaranteed SME loan on the firm performance measured as employment,
production, profitability and factor productivity. Their findings indicate that, on
average, the beneficiearies of the public aid have experienced a significant increase
in the employment base in the order of 14% to 18% compared to their non-
beneficiaries peers. Slightly less significant is the rise in turnover up to 19% within
the firs five years since receipt of the loan. Noteworthy is that companies that
benefited most from the size effect of this policy measure belong to the category
of small and medium enterprises and are typically young.
In conclusion, the general result is that the EU SME Guarantee Facility has been
successful in bringing significant positive effects on beneficiary firms in CESEE
countries, both in terms of employment and turnover, representing size and sales
respectively.
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6. THE LAW 221/2012. A SPECIFIC SUPPORT TO
INNOVATIVE START-UPS
6.1. The program “Decreto Crescita 2.0”
In modern economies, there is one necessary requisite to let the society and the
economy thrive: innovation. In fact, an innovative environment promoting
scientific research and entrepreneurship is critical to a country’s competitiveness.
Clear rules of fiscal fulfilment, labour market flexibility, quick and fluid
bureaucratic procedures, a legal system encouraging entrepreneurship and not
tagging failures as disasters or “point of no return”, the opportunity to raise equity
capital: each one of these elements contribute to the creation of a dynamic and
prosperous environment, capable of gaining a good reputation to its country on a
global scale in order to attract both financial and human capitals.
Innovation comes largely from new fims, which are often small and face problems
in the first phases of their life. In this regard, the public sector has the chance to
play a key role: it can shape the system through levers not manageable otherwise,
in order to create a stimulating environment for start-ups.
The advantages in this sense are multiple: economic and employment growth,
especially for young people, knowldege spill-over all over the entrepreneurship
sector, better social equilibrium and mobility, more robust bound between
universities and companies, and a push to a greater attitude towards entrepreneurial
risk. Moreover, depending on how the intervention is structured, it may delvelop
a new high-tech production combined with high skills, which is the case of Italy.
Several European countries, beware of the importance of the matter, are working
in this direction giving birth to numerous programmes of intervention. Italy has
started to move concretely as well.
As it has been showed in chapter 5, the Italian country had not applied any specific
policy scheme focused on young innovative companies, until 2012 when it
introduced the Decree Law 179/2012, known also as “Ulteriori misure urgenti per
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la crescita del Paese” or also “Decreto Crescita 2.0”. This D.Law has been created
specifically to foster the birth and the development of innovative young firms, later
defined and afterwards recognized as “innovative start-ups”, since the regulation
establishes a precise meaning to this definition. It was introduced on October 18th
of 2012, then coordinated with the conversion in Law 221/2012 on December 17th
and officially published on December 18th, number 224.
A great contribution to this work comes from the suggestions made by “Restart,
Italia!”, a complete report composed by a task force of 12 experts established by
the Ministry of Economic Development. The Law has introduced in the Italian
judicial system the so-called “innovative start-up”, which is defined as new
innovative company with a high level of technology (i.e. high tech innovative
company), and has assembled a regulatory framework (art. 25-32) specifically
designed for these kind of companies without any distinction of sectorial nature or
relation to the entrepreneur’s age. It operates through new instruments and
supporting measures that work on the whole life cycle of the company, from its
launch to its growth, development and maturity stages; overall, this policy
represents a relevant, original, up to date and complete intervention for the Italian
nation, because it is compliant with the need of all the actors playing in the start-
up field. The Law 221/2012 is not a simple law making, but rather a highly
organized policy. Moreover, it is also very dynamic in the sense that it is being
updated and enriched over and over again. More recently indeed, the “Lavoro”
Decree in 2013 (in Italian: Decreto “Lavoro”51) or the “Investment Compact”52 in
2015, simplified and enlarged the access requirements for being an innovative
start-up declared by the “Decreto Crescita 2.0”, in order to foster innovative
entrepreneurship.
51 Law Decree 76/2013, become Law on August 9th 2013.
52 Law Decree 3/2015, converted to Law two months later – 33/2015.
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6.2. Definitions and guidelines of the Law
The major filter applied by the regulation is a technology matter. The policy does
not focus on a specific sector, on the contrary, the primary prerequisite asks the
company to be operative in the innovation technology field. It is worth to notice
that this does not imply any sector restriction, becauseit is actually open to all the
productive universe.
The definition of innovative start-up, as the Law clarifies, is the following: the
supporting measures are limited only to those limited companies, including
cooperatives, whose shares or representative shares are not listed on a regulated
market or on a multilateral trading system, and that present the following
peculiarities:
� They are active since less than 5 years.
� They are located in Italy, or in another nation memebr of the EU or in
nations sharing the deal on the European economic area, as long as they
have a subsidiary or a productive branch in Italy.
� Their annual revenues are inferior to Euro 5 million.
� They have null payout ratio.
� Their sole or main business purpose is the development, the production and
the commercialization of products or services of high technological value.
� They are not results of a merger, a corporate split up or a divestiture of a
corporate or a corporate branch.
� The innovative nature of the company is identified by one of these criteria:
○ R&D activities account for at least 15% of the major figure between
revenues and costs
○ the overall labour force is organized either with 1/3 of doctoral
candidates, research fellows or researchers, otherwise with at leat 2/3
of shareholders (or any kind of partners) owning a second level
bachelor degree (the italian equivalent of “laurea magistrale”)
○ the company is the owner, the custodian or the licensee of a
registered patent or the owner of a registered original calculator
program.
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Companies that satisfy these parameters and that were born before the Law had
entered into force (December 19th 2012), can still subscribe to the innovative start-
up register and access to the benefits for a period lasting 4 years when the firm is
2 years old, 3 years when the firms is 3 years old and 2 years when the firm is 4
years old.
The law defines a further particular entity, the “certified business incubator”:
according to the regulation, this type of incubator must have specific characeristics
in terms of working location, equipment and, most important, it must prove solid
experience in backing innovative companies in their early phase. Thus, the
screening identifies and strenghten those structures that actually provide effective
incubating services. Certified business incubators benefit from facilitations as
well, such as tax credit, simplified company foundation, exoneration from the
stamp duty and easier and free access to the Central Guarantee Fund.
These two entities, once subscribed to the Companies Register (known in Italian
as “Registro Imprese”) created by the Chamber of Commerce, must respect the
publicity regime imposed by the regulation. The subscription can be made through
a telematic channel, sending a self-certification that states the ownership of the
necessary requirements; in order to allow this high flexibility, there is an ex-post
supervision on the veracity of those statements, companies then must update the
given informations every six months and give, on an annual basis, the confirmation
of owning the expected requirements.
All these data fill the specific register of innovative start-ups that is made public
and available in electronic form. This register is updated on a weekly basis to prove
transparency, publicity and to encourage a widespread monitoring and free debate
about the effectiveness of the policy on economic growth, employment and
innovation. Of course this method have a good advertising effect as well.
The Law is strongly focused on results and evidence-based improvements and for
this reason it applies a structured monitoring and evaluation system coupled with
a periodic communication from the Ministry of the Economic Development to the
Parliament, typically on an annual basis.
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6.3. Instruments of the policy
1. Foundation and furhter modifications through the standard model with
digital signature (Art. 4, comma 10 bis Investment Compact): innovative
start-ups and certified incubators have the chance to make the certificate of
incorporation and further modifications also through a standard model
using a digital signature as it works for web contracts.
2. Relief from Chamber of Commerce royalties and duty stamp: innovative
start-ups and certified incubators do not have to pay the annual royalty to
the Chamber of Commerce, the administration fees and the duty stamp to
the Companies Register.
3. Exceptions to the ordinary company regulation: limited liability innvative
companies (the Italian acronym is “s.r.l.”) can create categories of shares
with particular rights, such as shares with no voting rights or voting rights
not proportionate to the number of shares. Moreover, they can issue
financial instruments with participations and also publicly offer capital
shares. These exceptions make innovative l.l.c.s more similar to limited
companies.
4. Facilitations in paying losses back: start-ups can benefit from a special
regulation on capital stock reduction.
5. Innovative start-ups do not have to take the test that confirm the status of
operative company.
6. (art. 4, comma 11 Investment Compact) exemption to the obligation of the
stamp application in regard to VAT credit compensation up to Euro 50.000;
this brings better liquidity to the start-ups in the phase of investments in
innovation.
7. Tailor made employment regulation: innovative start-ups may hire
personnel with a fixed-term contract lasting from a minimum of 6 months
to a maximum of 36. Within this range, contracts may have different terms
and after 36 months, the contract can be renewed only once to a maximum
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of 12 more months; after 48 months on the whole, the risk of the first period
should be diminished and therefore the collaboration turns into the form of
permanent contract.
8. Flexible remuneration for employees: except for a minimum wage level,
other details in terms of salary are up to the parties, employer and employee,
who decide what accounts for fixed remuneration and what for variable. In
this way, contracts linked to different types of performance indicators are
possible.
9. Remuneration through capital-participation instruments: both innovative
start-ups and certified incubators may reward co-workers with capital-
participation instruments, such as stock options, and external suppliers with
work-for-equity schemes. Those instruments are favorable from the tax
viewpoint.
10. Tax credit available when hiring highly qualified personnel (valid until
December 31st 2014): priority access to benefits is given to innovative start-
ups and certified incubators who hire highly qualified personnel. In
particular, they are provided with a tax credit equal to 35% of the permanent
hiring total costs (this is valid for apprenticeship in the first year of work as
well).
11. Introduction of fiscal subsidies for investments in innovative start-ups by
both natural and legal persons53 in the years 2013, 2014, 2015 and 2016.
Subsidies are valid for both direct and indirect investments through OICR
and other companies investing in start-ups. Subsidies are particularly
favourable54 when investments are made in social vocation start-ups and in
those that develop high-tech product or services in the energetic field.
12. Introduction to equity crowdfunding: the specific regulation of equity
crowdfunding has been outlined by the Consob. Thanks to this measure,
Italy is the first nation worldwide that has regulated the equity
53 Irpef (tax on natural persons’ earnings) deduction of 19% of investments up to Euro 500.000; Ires (tax on companies’ earnings) deduction of 20% of investments up to Euro 1,8 million. 54 Irpef deduction 25%; Ires deduction 27%.
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crowdfunding phoenomenon with a specific regulatory instrument. In
particular, innovative start-ups can launch raising capital campaigns on the
internet, on authorized portals. Regarding this theme, the Law Decree
“Investment Compact” has allowed also SMEs to use such instrument; in
this way, also OICR and other companies investing mainly in start-ups can
diversify the portfolios and reduce the overall risk of retail investors.
13. Innovative start-ups can access to the Guarantee Fund for SMEs directly,
easily and for free: this public fund eases the access to credit through the
lending of guarantees on bank loans. The guarantee covers up to 80% of the
credit issued by the bank to start-ups and certified incubators, with an upper
limit of Euro 2,5 million; moreover, the criteria on which guarantee is given
are very simple and the preliminary activity benefits from a priority
channel.
14. Individual support by ICE Agency to innovative start-ups during the
internationalization process: this offers assistance in the regulatory,
corporate, real estate and credit matters. In addition, start-ups are hosted at
international fairs for free and also at other activities that allow them to meet
potential investors.
15. Fail-fast: there have been introduced a collection of procedures oriented to
alleviate and accelerate the process arising from a start-up that does not
“take-off”. These measures are meant to let the entrepreneur fail and restart
with a new project in a faster and easier way. The great importance of this
“fail-fast” plan comes from the willing to fight the general cultural approach
to failure, that is associated to “disaster” especially in west Europe.
Below, table 6 gives a qualitative overview of the main objectives hit by the single
instrument of intervention. Those interventions that are marked in the “entry”
column, are the strongest ones focused for entry purposes. Generally, since all the
financing aids can influence the cost function, even in the entry stage, not specific
financing needs are not marked also as “entry”.
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Table 6. Overview of the main objectives of the policy (Law 221/2012)
Entry Exit Financing needs Human capital Complementary assets
1 x
2 x
3 x
4 x
5 x
6 x
7 x
8 x
9 x
10 x x
11 x x x
12 x x
13 x x
14 x x
15 x
6.4. Additional measures for fostering innovation
The Ministry of Economic Development also conducts further programmes that
aim to promote innovation.
The first is called “Italia Start-up Visa”. This is a result of a collaboration between
the Ministry of Foreign Affairs, the Ministry of the Interior and the Ministry of
Labour and Social Policies, which have made a new policy to attract innovative
extra-EU entrepreneurs. The programme has been launched on June 24th 2014 and
gives visas to people who want to open an innovative start-up in Italy in a much
faster and easy way.
In line with the previous one, at the end of 2014, the programme “Italia Start-up
Hub” has been launched extending the fast-track procedure (the one of Italia start-
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up Visa) also to extra-EU citizens already in Italy with a fixed-term visa and to
those willing to start an innovative company.
Two last measures that boost technological innovation concern the company
financial structure rather that the founders. The first one is the tax credit for
research and develoment: the recent “Legge Stabilità” 2015 (art. 1, comma 35) has
updated the tax break of the Decree “Destinazione Italia”, extending the benefit to
2019 and giving tax credit to those firms investing in R&D with a maximum of
Euro 5 million for each recipient. The second one is the Patent Box, introduced by
the “Legge di Stabilità” 2015 as well (art. 1, comma 37-45), which allocates for
the first time in the Italian history tax reliefs on earnings coming from exploitation
of intellectual property. This instrument allows companies to leave out of the tax
base the 50% of revenues coming from commercial exploitation of intangible
goods (indutrial patents, companies’ brands).
6.5. Access to the Guarantee Fund for SMEs
The decree that became Law on June 26th 2013 sets a collection of procedures and
parameters meant to simplify the acess to the Central Guarantee Fund for Small
and Medium Enterprises (GFSMEs). In this regard, the decree wants to support
innovative start-ups and certified incubators to find financial resources.
When firms are in the early stage, they are typically constrained from the financial
point of view due to a series of reasons, among which the lack of collateral. Banks
ask for an even more burdensome amount of collateral when companies are in the
start-up phase and the Guarantee Fund aims to alleviate this distortion. On this
purpose, the regulation has streamlined the whole grant process that, otherwise,
would be very slow and hindered by the lack of the balance sheets traditionally
used for the evaluation of the business.
Only two are the prerequisites: first, be an innovative start-up or certified incubator
and second, the financier may not collect any kind of collateral on the financial
operation.
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The fund covers all the types of operations, even when there is not an investment
program, and the guarantee on banking loans is given totally for free with an upper
limit of the guaranteed loan set to Euro 2,5 million per start-up or incubator.
The newness of this intervention lies on the fact that no balance sheet evaluation
is needed for granting the guarantee. This issue has been managed leaving the 20%
of the granted amount to be carried by the financier, so that banks are more
involved and inclined to make an appropriate evaluation with all the documents
they have and the informations they can get.
Furthermore, it is important to underline that the fund does not step in the deal and
the relationship between the bank and the company in the terms of the contract,
such as interest rates and pay-back conditions.
6.6. Company Register-Innovative start-ups:descriptive statistics of
the main results (up to 3rd quarter 2015)
Since its launch, the policy gained more and more importance on national level
thanks to its effectiveness in attracting innovative start-ups toward its supporting
program. Figure 14 below, shows the subscription flow since the very first month
in which the Legislative Decree entered into force.
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The subscription montlhy rate remained on a good and rather stable level of 100
during 2013, 150 in 2014 and it has got even stronger in 2015, with peaks that
exceeded 200 subscriptions a month. Lowest levels belong to the summer months,
especially August, while the greatest peaks came up in the period of launch of the
policy (more than 250 subscriptions during March 2013) and on March 2015
(almost 300 subscriptions).
Overall, the aggregated number of innovative start-ups that have subscribed to the
Register has grown constantly, as the blue line shows in Figure 14.
Table 7 describes specifically the transition from 2nd quarter 2015 to the 3rd quarter,
making also a comparison between start-ups and limited companies on each total
amount and each stated shared capital.
Table 7. Number and dimension of start-ups and limited companies. 2nd quarter 2015 3rd quarter 2015 Var % 2nd – 3rd
quarter 2015 Number of start-ups 4.248 4.705 10,73 Number of limited companies
1.515.626 1.528.539 0,85
Share capital stated by start-ups
212.494.749 € 235.867.445 € 11,00
Share capital stated by companies
3.360.675.544.631€ 3.350.103.713.678€ -0,31
% start-ups on number of limited companies
0,28 0,31 n/a
There is a clear domination of start-ups compared to limited companies in terms
of growth rate: the start-ups figure is more than twelve times higher than the one
related to limited companies.
The capital size of this group of innovative start-ups is displayed in the pie chart
below (Figure 15). The very large majority of them (94,3%) is quite small and
exhibit a capital that is lower than Euro 100.000. This evidence is in line with the
usual size of a general new firm, and the figure holds particularly well in the case
of innovative and high tech firms.
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Furthermore, there is a predominance also in the legal status, where limited
liability companies constitute the 80% on the whole; the figure is even higher than
90% if simplified LLC are included.
Among all these innovative start-ups, is useful to understand when they have been
founded (i.e. their age). Figure 17 reports this data and shows a considerable
majority of companies between one year and 6 months of age.
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If all the companies younger than one year are considered, the figure rises over
2.300, suggesting that the recent policy has boosted the creation of new innovative
start-ups and entrepreneurship.
National reports have counted 4705
innovative start-ups on the Italian
land, up to October 12th 2015. The
regional distribution (Table 8)
mentions Lombardia to be the
region with the highest absolute
number of this kind of companies,
followed by Emilia Romagna and
Lazio.
(Province distribution shows that
Milan, Rome and Turin hold the
first three places, respectively, in
this classification as well).
However, the ranking changes
when, instead of looking only at the total amount of innovative start-ups in a
region, the indicator ponders the number of innovatve start-ups for the total amount
of companies located in the provinces overall. In this way, none of the provinces
of Lombardia are in even in the top ten list: Table 9 displays that the ratio “number-
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of-start-ups on total-number-of-companies” gives to Trento, Trieste and Ancona
the first three places in the rank.
Table 9. Provincial density – Ranking of the first 10 provinces Ranking Province Number of start-ups in
the 3rd quarter % start-ups on total amount of
companies in the province 1 Trento 116 1,21 2 Trieste 45 1,12 3 Ancona 88 0,84 4 Ascoli
Piceno 40 0,68
5 Pordenone 36 0,63 6 Torino 246 0,62 7 Cagliari 90 0,58 8 Macerata 43 0,58 9 Bolzano 50 0,57 10 Modena 121 0,57
Source: national data, www.startup.registroimprese.it.
Table 10. Distribution by economic sector. SECTOR Detail of main
categories 3rd quarter 2015
n. of start-ups
% start-ups of the sector on
the total number in the
area
% start-ups on total number of
limited companies in
the area Agriculture and related activities
TOTAL 14 0,30 0,09
Manufacturing, energetic and mining activities
C 26 Production of computers and electronic products
182 3,87 2,34
C 27 Production of electronic devices
104 2,21 1,21
C 28 Production of machineries
159 3,38 0,75
TOTAL 884 18,79 0,39 Constructions TOTAL 53 1,13 0,02 Commerce TOTAL 198 4,21 0,07 Tourism TOTAL 15 0,32 0,02 Transportations & Logistics
TOTAL 12 0,26 0,03
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Table 10. (continued.)
Insurance and credit
TOTAL 8 0,17 0,03
Services to companies
J 62 Software production, consulting
1403 29,83 5,78
J 63 Information services and other IT services
386 8,21 1,98
M 72 Scientific R&D
725 15,41 21,03
TOTAL 3402 72,32 0,96 Other TOTAL 90 1,91 0,15 Not classified TOTAL 28 0,60 0,01 Total amount TOTAL 4704 100,00 0,31
Source: national data, www.startup.registroimprese.it
Table 10 and the Pie chart of Figure 18 describe with detailed information what is
the partition of these innovative start-ups within the economic sectors. The latter
states that services and manufacturing are for sure the two main sectors populated
by these new companies, with percentages of 76,2% and 18,4% respectively.
Slightly different is the situation when analyzing the production value reported by
the income statements. The available data (51,1%) reveal that about the 70% close
the year with a production value lower than Euro 100.000, while a good 26% do
that with a value between 100.000 and 500.000 Euro. Production values above the
latter number constitute more or less the 5%.
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Evaluating a company in its first steps is surely not easy, especially due to the cost
burden that it has to bear with the initial investments.55 In addition to the production
value, which gives a quick general idea about how the business is going, also the
number of employees and even more its relative growth rate can determine whether
a company is facing a solid development.
On this purpose, Table 11 summarizes the current situation concerning start-ups
and general limited companies, and offers a basis of comparison up to the 2nd
quarter 2015.
Table 11. Personnel employed in start-ups (up to 2nd quarter 2015). Total amount of start-ups Amount of employees - Mean value 2,86
Amount of employees - Median value 2 Number of start-ups with employees 1.710 Total amount of employees in start-ups 4.891
Total amount of limited companies
Amount of employees - Mean value 14,28 Amount of employees - Median value 3 Number of companies with employees 574.366 Total amount of employees in limited companies
8.201.210
Source: national data, www.startup.registroimprese.it
55 See “Valuing young, start-up and growth companies: estimation issues and valuation challenges” (Damodaran 2009)
122
At the same time, Figure 20 give a visual understanding of the distribution of the
innovative start-ups by their personnel entity (the pie chart on the right, sums up
to 39.6%, the percentage of start-ups with data actually available; it is not re-based
to 100).
Table 12 and 13 describe instead some properties of the companies’ ownership
composed of those shareholders that have founded the firm or joined it at a later
stage; the comparison with the group of general limited companies is also
available. In particular, Table 13 gives detailed information about the presence of
female, young and foreign people in the ownership of the start-up; the comparison
with general limited companies is available as well.
Table 12. Shareholders’ presence in start-ups (up to 3rd quarter 2015). Total amount of shareholders Number of shareholders - Mean value 4,08
Number of shareholders - Median value 3
Number of start-ups with shareholders 4.582
Amount of shareholders in start-ups 18.677
Total amount of limited companies
Number of shareholders - Mean value 2,63
Number of shareholders - Median value 2
Number of companies with shareholders
1.402.020
Amount of shareholders in limited companies
3.693.776
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Table 13. Presence and predominance of female, young and foreign persons. 3rd quarter 2015
Female predominance
Young predominance
Foreign predominance
With female
presence
With young
presence
With foreign
presence Absolute values
Start-up 611 1.122 99 2.099 1.890 582 Limited companies
252.829 104.524 61.261 764.635 211.985 156.530
% value Start-up on total start-ups
12,99 23,85 2,10 44,62 40,18 12,37
Companies on total limited companies
16,54 6,84 4,01 50,02 13,87 10,24
Source: national data, www.startup.registroimprese.it
Table 14. Main profitability indicators Start-up Limited company
Total Earnings only Total Earnings only ROI -0,12 0,10 0,03 0,03 ROE -0,27 0,19 0,03 0,03 Financial independence
0,38 0,30 0,37 0,37
Value added/producing goods
0,16 0,33 0,21 0,21
Source: national data, www.startup.registroimprese.it
In the end, the table above (Table 14) offers a report of the main profitability
indicators relative to both start-ups and general limited companies.
Descriptive statistics of the loans granted by the Guarantee Fund.
The tables below show some evidence regarding the activity that the Guarantee
Fund for Small and Medium Enterprises (GFSMEs) has carried out sofar in terms
of guaranteed loans.
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Table 15. Descriptive data on loans granted by the GFSMEs to innovative start-ups. Number of loans granted through the GFSME 733 (189 short term*) Number of innovative start-ups receiving loans through the GFSME
510 (113 short term)
Amount of financing granted through the GFSME received by innovative start-ups
€216.901.239 (s.t. €18.160.500)
Amount of granted financing by the GFSME €170.608.515 (s.t. 13.555.600)
Average amount of financing received by a start-up €295.909 Average duration of loans granted by the GFSME 56
*Short term indicates a number of months inferior to 18. Source: national data, www.startup.registroimprese.it
Table 16. Regional distribution of loans granted by the GFSME. Region Number of loans Amount of financing (€) Abruzzo 15 9.560.000 Calabria 12 1.625.590 Campania 33 7.133.970 Emilia Romagna 83 18.699.438 Friuli Venezia Giulia 47 9.684.640 Lazio 56 12.854.783 Liguria 10 3.995.000 Lombardia 186 91.449.934 Marche 27 4.161.125 Molise 4 510.000 Piemonte 58 10.048.048 Puglia 12 5.375.000 Sardegna 5 1.145.000 Sicilia 26 6.455.180 Toscana 30 4.961.180 Trentino Alto Adige 37 7.333.000 Umbria 5 4.210.500 Valle d’Aosta 3 200.000 Veneto 84 17.498.851 Total 733 216.901.239
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Source: national data, www.startup.registroimprese.it Table 17. Distribution of loans by financing bank type Bank type Number of loans Amount financed (€) A 520 125.671.967 B 56 19.548.563 C 19 2.195.000 D 146 79.715.709 Total amount 741 227.131.239
Source: national data, www.startup.registroimprese.it
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7. RESEARCH HYPOTHESES
The new policy scheme discussed in chapter 6 represents a real innovation for the
Italian policy record. No public scheme has ever been this focused and oriented to
the support of entrepreneurship on such many levels. It acts with many
instruments, from particular regulations shaped for innovative start-ups, to both
direct and indirect support instruments. Moreover, it emphasizes the need for more
entrepreneurship spirit and more courage to take the challenge of following
innovative ideas. In this regard, it applies individual support and recovery
programs (Fail-fast). Many studies underline the great importance of backing
entrepreneurs also from the psychological point of view, because efficient and
well-prepared people do not really seem to easily embrace the risk of starting a
new firm and jump in a complete new dimension of competitiveness and
responibility, compared to a good job offered by a more solid and already
successful company.
Therefore, it is the union of all these actions, financial and cultural, to be directed
to foster the development of the future economic fabric, which sinks its roots in
the high-tech innovative sector.
7.1. A focus on the Italian Venture Capital market
The measures have been designed meticulously and the entrepreneurship market
has also replied with a solid flow of subscription requests as it was shown in the
descriptive statistics. However, the entrepreneurship literature broadly agrees upon
the pivotal role that Venture Capitalists play in this environment.
The Italian VC market has been weaker than it has been in other developed
economies, historically. Nevertheless, the recent trend of its enlargement is
promising.
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A recent study of the AIFI (Associazione Italiana del Private Equity e del Venture
Capital) states that there is a gap in the number of active VC operators and also in
the avavilable capital for investments in start-ups.
Moreover, Figure 22 below displays the different situation among the main
European countries, underlying that Italy faces a large gap in terms of early stage
financing compared not only to the U.S., but also compared to other close
countries. According to the data offered by a study of AIFI and
PriceWaterhouseCoopers, Italy has the lowest number of companies financed by
early stage investments, with a figure that is dramatically below the average
number in most developed Euroepan countries. Despite that, while the average
trend has been a decrease or at least a clear fluctuation, Italy has always registered
positive rates of growth.
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The policy scheme, in fact, has been conceived for strenghtening also this side of
the Italian reality, the VC environment. The instruments applied are supposed to
enhance in a deep and solid way the investment opportunity perceived by early
stage investors. The measures not only lessen the financial burdens faced by new
high-tech start-ups, but also make the structure of the new firm more flexible from
the personnel employment point of view and for the organizational procedures as
well.
The situation in Italy has showed limited VC supply, due to its bank-base nature,
and lack of specific targeted policy schemes oriented to high-tech new firms. The
cost of accessing may be too high for most of them and they are proved to be
suffering from financial contraints.
The study of Colombo, Grilli and Verga (2007) is one of the few that analyzes the
determinants of New Technology Based Firms access to public direct subsidies
and venture capital. In particular, their paper investigates whether the receipt of
public funds by a NTBF exerts some type of signalling effect toward VC investors
and evaluates the possible presence of important substitution effects in high-tech
markets. Their findings of the econometric analysis partially confirm the relevance
of founders’ competencies as important drivers of VC investments decisions,
pointing to the multifaced nature of human capital and to the possible presence of
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some type of self-selection out of the market by high-tech start-ups, or inefficient
screening procedures implemented by VC investors. Moreover, regarding the
technology policy side, they do not find any significant effect exerted by policy
measures on the NTBFs’ likelihood of accessing VC financing, even though their
estimates are in line with the occurrence of relevant substitution effects generated
by direct public policy subsidies towards NTBFs. Therefore they exclude the
existence of any significant certification effect associated with the receipt of public
subsidies.
7.2. The research hypothesis
This work aims to follow a study similar to the one developed by Colombo, Grilli
and Verga (2007). It takes into consideration the innovative start-ups as the object
of analysis and it investigates whether the receipt of funds thanks to the Guarantee
Fund for Small and Medium Enterprises (GFSMEs or GF) by an innovative start-
up exerts some kind of signalling effect toward VC investors, evaluating the
possible presence of significant substitution effects in the market. In other words,
the paper studies whether the receipt of loans from the GF influences VC investors
and, vice-versa, if being backed by a VC increases the chances of being financed
by a bank through the GF model.
The study will also distinguish between classic VC, intended as independent VC,
and Captive VC (CVC), intended as the other possible forms of VC, which are
Governmental VC, Banking VC and Corporate VC.
Moreover, the determinants of innovative start-ups access to the GF and VC
financing will be investigated with a further specific focus on the characteristics
of the human capital present in the shareholder base.
First of all, a large sample of innovative start-ups will be analyzed in order to
estimate the possible complementary or substitution effect provoked by VC and
public aid on each other. This investigation will rely on financial indicators and
other characteristics related to these latter. Given the broadly accepted fact that
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new high tech firms are financially constrained, and also that VCs effectively relax
these constraints, the aim is to verify whether the GF actually helps start-ups to
obtain VC back-up. We expect that the public support carried out by the Guarantee
Fund through the facilitation of getting a bank loan could exert a positive signal
effect towards VCs, communicating to these latter a clearer good opportunity of
investment. Therefore we posit the following hypothesis:
H1: Innovative start-ups that have received support by the GF are then expected
to have more chances to be backed by a VC in the future.
Secondly, the human capital will be included in the same analysis. As the extant
entrepreneurial literature highlights, human capital characteristics are important
for a new firm to succeed and overcome the early stages, and it is also acknowledge
that VCs, as well as public institutions, do rely on screening procedures that
consider human capital features. In addition to the financial characteristics that are
often not enough to evaluate the value of a new firm, we expect the human capital
to play a key role in the high-tech sector when it comes to win a financier over,
either a private or a public one. If the founder base of a firm exhibits high education
and/or large work experience, we expect these characteristics to exert a significant
effect on the evaluation of the two investors. Moreover, since the start-ups
involved are active in the high-tech and innovation area, technical skills are
expected to have a positive impact. On the basis of these considerations, the
following hypotheses are then introduced:
H2a: Human capital characteristics play a relevant role in the access to VC.
H2b: Human capital characteristics play a relevant role in the access to GF.
H2c: Technical skills of founders are expected to have a positive impact on the
access to external financing.
In the end, the considerations made so far about the VC as a valid financier and
guide for innovative start-ups should hold especially for those VCs that are private,
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in other words Independent Venture Capitalists (IVCs). This latter is recognized
to be the most effective financier among their peers, in particular compared to
governmental and corporate VCs. Therefore, isolating IVC from the other types of
Captive VC, the same results supposed by H1 and H2 are expected to remain valid,
showing the last hypothesis:
H3: H1 and H2 are expected to hold also when IVCs are isolated in the analysis
from Captive VCs.
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8. DATA
8.1. Sample construction
This research analysis makes use of two samples. The first one gathers all the
innovative start-ups that were on the Company Register list up to December 8th
2014, therefore two years after the Decree became Law.
At that time, the total amount of registered firms was equal to 3004. Starting from
that set, two different samples have been composed: the first is the larger (the
“large sample” from now on), it includes all the innovative start-ups just mentioned
and it offers all the available data up to November 2nd 2015. Therefore, this sample
contains the companies that were registered on December 2014, but the infos have
been updated through 2015 in order to keep the most from the available
information, since many recent companies had not deposited any balance sheet and
financial statement yet at the end of 2014. Thanks to this constant update, the start-
ups with available data are 2526 out of 3004 (84,1%), which translates in an
acceptable percentage to consider the study to be solid.
The sources through which data have been collected for the large sample are
mainly two: AIDA (Analisi Informatizzata Delle Aziende, Digitized analysis of
companies) and Telemaco (telemaco.infocamere.it; registroimprese.it). In
addition, other websites, such as ISTAT (www.istat.it), have completed other
informations about macroeconomic indicators and national development
indicators not firm-specific (e.g. entrepreneurial density, GDP growth).
This set of firms reports the identity details and all the financial informations stated
by the company with the official documents of financial statement and balance
sheet, gathered in a unique hand-collected longitudinal dataset wich covers all the
available years since the single company has been founded. In addition, it is
available the number of managers active in the firm in a certain year.
A more detailed description of the data included will come later, in the section
where all the variables are explained.
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The second sample (“small sample” from now on) is a subset of the large one, but
with more info for each company.
The population of this dataset has been hand-collected through a collaboration
between Edoardo Girelli and Danilo Sesana.
In particular, in addition to all the information of the large dataset, the small one
includes also a remarkable and large amount of informations with regard to the
founders of each firm. In other words, human capital informations have been
registered in detail manually: for each shareholder of the companies included in
the small sample, personal info about education and work experience have been
searched and checked with the use of the social network LinkedIn.
This sample is made of 590 innovative start-ups, which translates into more than
2.000 shareholders' personal info registration.
(For each founder/shareholder, the infos registered are the following: name,
surname, fiscal code, age, email address, entry date in the firm, exit date,
percentage of shares owned, PhD details, master details, bachelor details, work
experience, R&D work experience, engineering work experience, commercial
work experience, production work experience, sectorial work experience, extra-
sectorial work experience, academic research experience, managerial experience;
data are included when available).
The philosophy underlying the filter applied to the large sample that led to the
small one, has followed a sector logic: only the firms operating in the two sectors
manufacturing and services have been selected. These two sectors are the most
relevant within the distribution of innovative start-ups and they are the largest
subsets, as the descriptive statistics proves. Furthermore, manufacturing is found
to be one of the sectors most constrained when innovating.
The human capital informations that the small sample offers is related to their
education and work experience. More specifically, the former includes information
about the education degrees that a shareholder has got, in terms of bachelor, master
and PhD degrees. It also distinguish between technical and economic education.
For what concerns the work experience instead, the sample takes note of the
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specific kind of work experience, that can be R&D, engineering, production,
commercial, sector specific of the firm, extra-sector and managerial.
In this way, it has been possible to record specific guidelines of both education and
working skills of each shareholder/founder, which have fulfilled the general
criteria broadly aknowledged to make a difference when it comes to overcoming
screening procedures and external evaluations.
Both samples have been completed with a deeper check of the shareholder base in
order to find venture capitalists. For each one of these latter, the specific business
has also been check for accuracy reasons. In this way, the datasets distinguish also
between the different types of VC, wheter they are IVC, BankingVC,
GovernmentalVC and/or CorporateVC. The last three are gathered in one category
named Captive Venture Capitalists. Finally, the entry year of the single VC has
been recorded for keeping track of the transitions.
For what concerns the loans granted by the Guarantee Fund, the database includes
the year at which the loan has been granted and to which start-ups. Therefore, there
are complete transitions info on different years of activity for both VC and GF.
The small sample used in the present work consists of 590 firms with augmented
info that come from the large sample. χ2 tests show that there are no statistically
significant differences between the distributions of the small dataset and the
corresponding distributions of the population of the large sample from which it
was drawn. In particular, the small one is very representative of the large one under
all the financials indicators/company characteristics and presence of external
investors (χ2(0.667)=1 and χ2(0.96)=0.62).
Even if smaller, the second dataset is sufficiently large and it exhibits considerable
heterogeneity as to the variables of interest.
It is important to remark that the list of start-ups declared in the Company Register
only includes firms that were active and that satisfied all the pre-requisites to be
marked as “innovative start-ups” at current time. This means that there is no track
of the companies that have been excluded from the list for multiple different
reasons, among which financial constraints and business failure.
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The construction of the main variables related to human capital characteristics are
explained later in the section of descriptive statistics.
8.2. Descriptive Statistics of the samples
8.2.1. Large Sample
The large sample is composed of 2526 innovative start-ups with available and
reliable data. It is an earlier version of the Company Register list of italian
innovative start-ups that has been analyzed and descripted in chapter 5, which was
updated to October 12th 2015. The version that originated the large sample is up to
December 8th 2014, when this research study has started with the data collection
phase.
At that time, the number of registered firms was 3004. As it has been underlined
previously, the growth rate of the start-up list has been historically high, with
hundreds of subscription per month. As a consequence, many of the included
companies correspond to very recent established firms that have just started their
business and had not deposited any official financial document at that moment,
therefore the access to their financial status was not possible or they did not even
have a fiscal year to report. The issue has been overcome by keeping the database
updated periodically, with the latest update that dates back to November 2nd 2015.
Figure 23 shows the number of available years of activity that have been recorded
for each firm in the dataset. From the distribution, it is clear that the majority of
companies are very young: almost 1.000 of them deposited financial documents
related to the previous fiscal year only once. This also holds with Figure 24 that
gives a distribution by age, because start-ups with only one year of life are still
numerous, as well as those with two years; firms 2 years old may have reported
only one year of data.
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The forthcoming figures describe financial indicators in regard to the large sample.
There is a mediocre proportion between the central shares that include companies
with a total assets value between Euro 15.000 and Euro 500.000. On the contrary,
the ones outside that range are fewer.
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The total assets value, as one could expect, is definitely not representative of the
revenues. The largest slice of the pie chart shown in Figure 26 belongs to the firms
with no revenues (30%), then the remaining 70% is shared between start-ups that
profit more or less than their peers. The explanation of this picture is ascribable to
the nature of their business, since innovation and R&D take time to make proper
profits, and to their young age.
A leading indicator generally accepted as a mirror of a new firm’s wealth is the
number of employees that it hires. Usually, a new or young company has its
shareholders, or part of them, as main workers at the starting point. Then, if the
business takes off and grows, they progressively hire employees. The Law
221/2012 “Decreto Crescita 2.0” also acts on this matter, making the hiring process
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easier and less constrained by general regulations. Generally, when a firm increses
the personnel base, the business is growing.
From this point of view, the large sample is mainly characterized by firms with no
employees with a 58% share displayed in Figure 27. This slice is supposed to
represent the very young firms and also those still in a starting phase, while the
remaining percentage belong to those that have proved some growth. However,
the numbers are very low, since only 10% of the start-ups employ more than three
people.
Finally, still concerning the large sample, Figure 28 offers a specific focus on the
main matter handled by this work: the presence of venture capitalists and granted
loans (Governmental Fund for SMEs) within the innovative start-ups environment.
In particular, the large sample reports almost the same percentage of VC-backed
start-ups and GF-backed ones (around 13%). Of those backed by all types of VC
(321), more than half are supported by independent VC (IVC).
It is worth to notice that, out of 179 IVC-backed companies, 110 are found to have
had the support of the VC since the very beginning, which translates into an
increase of VC support equal to 62,7%. This leaves some space to interpretation,
because it could mean that start-ups could actually benefit from the Law 221/212
which directly attracts VC with its facilitating measures, or that the growth of VC
support is particularly pushed by the availablility of the Guarantee Fund for SMEs.
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Table 18. VC an GF distribution in the sample and relative evolution.
N° of start-ups Year 0 Last year
Total Number of start-ups 2526
Number of start-ups with VC
Number of start-ups with GF
Number of start-up with GF and VC
242 321
133 337
13* 64**
Transtition (1,0)-(1,1): VC → VC+GF 48
Transtition (0,1)-(1,1): GF → VC+GF 1
Transtition (0,0)-(1,1): null → VC+GF 15
*of which 6 backed by CVC and 7 by IVC. ** of which 29 backed by CVC and 37 by IVC (2 are backed by both IVC and CVC).
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8.2.2. Small Sample
The small sample is originally drawn from the large one. More specifically, it
includes the start-ups with available data that belong to the two most populated
sectors of the whole group: industry/manufacturing and services.
This first filter led to a subset composed by almost 600 complete elements.
Furthermore, the information basis has been augmented with a full description of
the human capital included in the firm’s shareholder base.
The dataset reports both financial information and characteristics of the human
capital. In regard to this latter, every shareholder/founder of each company of the
sample has been catalogued filling out a self-made standard model of data
registration that takes note of his education path and work experience, in addition
to basic personal info.
Notwithstanding the smaller size, this sample offers a much richer pool of
informations, which turns out to be very important, as the human capital is seen as
an essential key to success, and interesting to analyze.
After some starting graphs similar to the ones related to the large sample, that are
useful to make a comparison, other specific figures will display a complete
analysis of the human capital structure.
Figure 29 shows how the distribution of the firms by the number of years with
financial informations is in line with the large sample, except for the first column,
namely the firms with only one year of available data. This difference is not
considered as a weakness, because this study relies more on companies with
multiple years of activity in order to track the actual transitions; the deeper are the
time series, the better. Overall then, this second sample has an appropriate
distribution suitable with the underlying study, considering also that it analyzes a
set of companies that are new and with few available years by definition.
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The distribution by age is in Figure 30, with a good predominance of companies
two and three years old.
Figure 31 and 32 report financial indicators: total assets value and revenues. It is
quick to notice here, just like in the large sample, that there is a great portion of
start-ups performing worse than their total asset value would declare; this is in line
with the expectations. A further remark goes to the upper pie chart, which displays
a great share (40%) of firms with a large amount of total assets. That is explicable
by the fact that more than half of the sample’s members work in the manufacturing
sector, which asks for a considerable assets base compared to service businesses.
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For what concerns the personnel employed, the situation is similar, with a slightly
smaller presence of companies with no personnel, and, on the other hand, a larger
share of those with more than 1 employee.
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Figure 34 is the same graph of figure 28, adapted for the small sample. It gives an
interesting picture of the presence of VCs and GF-backed loans, with a further
specification for IVCs. The small sample includes a significant part of the VC-
backed firms of the large one: indeed, the 76% (245) of the VC-backed firms
included in the large dataset are also included in the small one. This is probably
due to the sector filter: first, the VC category gets the presence of all kinds of VCs,
and corporate VCs weigh significantly on it. Second, the evidence suggests that
corporate VCs often back up start-ups operating in the manufacturing sector. As a
consequence, since the industry/manufacturing area is part of the small sample, the
percentage of VC-backed companies overall is increased.
Moreover, in this case, the number of companies with an IVC in their first year of
activity is 54, while the companies that have obtained an IVC support afterwards
are 50; this could suggest that a considerable portion of firms have generated some
interest over the VC market in the time span the Law 221/2012 has been operating
in.
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Concluding the general description of the small sample, before moving to the part
related to human capital features, there are two last figures: Figure 35 and 36. The
former simply shows with an apple pie the share owned by the manufacturing
sector versus the one owned by the services one, that are almost 70% and 30%,
respectively. The latter instead, distinguishes between the location of the firms on
the Italian land; in particular it separates those located in the southern regions of
Italy from the other ones.56 Less than the 18% of the sample’s elements is located
in the South of Italy.
56 One of the control variables that the econometric model will specify is a dummy variable (DSouth) that is supposed to get a possible effect exerted by the location of the startup. This dummy is commonly used especially when the policies studied are oriented to support depressed areas.
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The following section describes the human capital data collected for the firms that
fill the small sample up.
Many personal information about the founders and shareholders have been
collected, from the age and the fiscal code to the overall work experience and
education through their whole life.
Starting with some general characteristics, Figure 37, first of all, gives an idea of
the size of the shareholder base in the sample’s elements. Almost 40% of the
sample owns only one shareholder, while on average the size is higher. It is
important to underline that start-ups with only one shareholder include also those
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companies that are founded/composed by more than one person, but the other
components of the group were not reachable through the research sources
available. That is because most of times, those additional people are family
members or people not strinctly related to the business but own equity shares.
The age of these shareholders varies in a large range (see Figure 38), going from
very young entrepreneurs following their innovative ideas after a probable solid
academic path, to adult entrepreneurs with a deep working experience earned
through dozens of years. In fact, an innovative start-up is exactly a common match
between fresh and proactive young men and experienced, wise entrepreneurs with
managerial skills. The business angel role is based on this logic after all.
The graph below displays the average age within a single firm and the blue line
outlines the average value of these “average age” values.
There is not a definite and expected upper limit to the age, because this latter does
not follow any underlying rule and it can ben considered a random value bound
only to the human limits imposed by the old age. On the other hand, the young
portion is actually subject to an educational constraint: the threshold is related to
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the university degree, in fact, there are almost no young shareholders lacking at
least a bachelor degree (excluding those people found to have joined the team
because family members). Moreover, the “Decreto Crescita 2.0” includes in the
multiple-choice pre-requisites the presence of highly educated human capital in
the company group.
Figure 39 gives another view of the shareholder base size and it shows that, on
average, this latter is made of three or four people.
The following two histograms reports a broad vision on the working experience of
the human capital. The model of experience registration used to collect the data
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distinguishes between different categories of experience: managerial, general,
total, sectorial, R&D, engineering, production and commercial.
The first (Figure 40) shows the distribution of the working years stockpiled and
distributed by categories. For instance, the first category “sum management
experience” states that almost half of the start-ups population owns no managerial
experience at all, a rough 7-8% has one to five years, more than 20% has six to
twenty years, 10% from 21 to 50 years and the rest more than 50 years of
managerial experience. It is important to note that a figure for example of 50 years
of managerial experience records the sum, for each shareholder of the firm, of the
years in which he has fulfilled a managerial position. Therefore if there are three
shareholders with 6 years of experience each, the value will be 18 years of
managerial experience for that start-up.
The higher is the green column for a specific work category, the lower is the overall
presence of that kind of work experience. It is clear from the graph that working
areas such as commercial or production are found to have a very low presence.
Moreover, a solid share of the people involved in this sample, are found to have
experience in fileds strictly related to the business of their start-up. This finding is
no surprise, since it is more common that an entrepreneur with experience in a
specific sector starts a new business in the same area. However, as the VC theory
teaches, this is not the rule, because an entrepreneur could definitely join a new
start-up because of his managerial experience or his large working experience in
general. The commercial side of the business is essential to reach success and it is
often handled by experienced professionals.
The highest relevant rates are held by years of experience in managerial and
sectorial areas. The average start-up often has young educated entrepreneurs
coupled with experienced people. However, given their young age the former do
not have much experience and this mainly cause the height of most of the column
shown in the graph below.
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Figure 41 is very similar to figure 40, it displays the same categories with
histograms as well. What changes is the way experience years are calculated. In
this graph, years are not summed up, but it reports the average number of years in
the specific area of experience for each start-up. Then, linking back to the previous
example, if there are three people with 6 years of managerial experience each, the
value resulting will be still 6, 18 divided by 3.
The situation does not change much, since results are always expressed in
percentage values, however there are some differences due to the size of the
shareholder base. The commercial category for instance is subject to a strong
change and unbalance between the blue and the yellow columns, 1 to 5 and 5 to 10
years of experience respectively. If in figure 40 these two bars have an equal
weight, in figure 41 the blue one gains a lot of ground from the yellow one. This
basically suggests that in the commercial field, the shareholder base often has more
than one person with 1 to 5 years of commercial experience each.
Another difference is clear from the sector category. The yellow bar almost
remains unchanged, meaning that usually the sectorial experience is solid and
based on multiple years (5 to 10). While the blue one takes some value from the
green one, in comparison to the ones in figure 40, because when it comes to have
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10 to 15 years of experience in a specific sector, it is more common that these years
are split on multiple people, instead of being one single person with that much of
amount of experience. This logic is valid on average, of course there are cases
when a single shareholders has more than 15 years of experience.
In the end, the last four figures (42,43,44,45) describe the educational background
of the human capital analyzed in the sample. The data have been hand-collected
for each single shareholder, taking note of all his degrees. In other words, each
profile of the human capital population, reports whether the person has a bachelor
degree of three or five years, if he has a master of science and if he has a PhD. For
all of them, there is also the specification of the degree type (law, different kinds
of enginering, economics, finance, etc.) in order to be able to distinguish between
technical degrees and economic ones.
The first histogram of Figure 42, explains the diffusion of the four different kind
of education degrees. For what concers the lowest level of degree, the three years
bachelor, the graph shows that more than 70% of the start-ups have people with
this type of bachelor, and more than 10% have more than five bachelors in their
group. Most of them have one or two people with a bachelor of three years.
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Firms with five years bachelor instead, are less but still numerous. Comparing it
to the histogram of three years bachelor, it is possible to see that, on average, when
a person completes a three years degree, he gets also the five years one.
Moving to the higher levels, there is a predominant lack of masters, even though
start-ups with at least one master are almost the 30% of the sample. On the other
hand, the last histogram related to PhDs suggests that there are more people with
a PhD than the ones with a master. This could mean that there is a strong presence
of human capital that comes from the academic path, namely people who have
undertaken the research and doctoral route, after having concluded the five years
bachelor. Therefore, it seems more common that people either stop after a full
bachelor degree or continue with a PhD. Maters seem to be chosen when there is
willing to specialize in a specific field most probably for working reasons. In fact,
the evidence shows that maters are usually related to economic topics, most of
times they are masters in business administration held by experienced
professionals.
Figure 43 shows the absolute division among start-ups by the number of degrees
in their shareholder base. It is relevant to remark that the largest share of the pie
goes to the firms with more than six degrees and, overall, the great majority of the
start-ups are led by educated and, in a smaller part, highly educated human capital.
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Figure 44 separates technical education from economic one. From the comparison
of the two histograms, it is clear to see that there is a predominance of technical
education on a general basis. Moreover, while the start-ups with one or two degrees
in their group have similar values in terms of number of degrees for both
categories, the ones with higher and the highest amount of educational degrees are
strongly focused on the technical field. This suggests that when a company exhibits
a high level of education, it is very probable that the education has a more technical
nature.
In conclusion, the last histogram (Figure 45) does not distinguish between
technical and economic education, on the contrary, it combines them in order to
give an idea of the general educational level inside the sample’s start-ups, giving
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different weights to the four degrees of education. The underlying idea is that a
shareholder with a PhD, through the count of his number of studying years, will
get a higher value than the one with a lower level degree such as a master or a
bachelor.
The figure illustrates a large predominance of those firms with a relative low
education, then there is a mediocre amount of those with an average-high level and
finally there is a larger share of those firms with very high level of education. This
finding implies that there is a gap between those companies with a basic
educational level and those with a very high level, meaning there could be a
possible trend of being either a normal educated start-up or a very high educated
one.
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9. THE ECONOMETRIC MODEL
9.1. The econometric framework
The econometric model follows in the footsteps of Mosconi and Seri (2006), also
used by Colombo, Grilli and Verga (2007). It models the access of start-ups to the
Guarantee Fund for Small and Business Enterprises (GFSMEs) and Venture
Capital as a bivariate discrete-time binary process Yt ={ YAt, YB
t}. More specifically,
the model defines: yAi,t = 1 if firm i got access to VC funding by time t; yB
i,t = 1 if
firm i received public support by time t; with t =[t E …T]57. t Ei is the foundation
year of the firm i, while T is the last year of the observation period (2014). At any
time t, the state space of Yt is given by the following states: 0 = [0,0]; 1 = [1,0]; 2
= [0,1]; 3 = [1,1]. Firms in state 0 did not obtain either VC funds or public support
through the GFSMEs. Firms in state 1 are VC-backed but did not receive any
public support, while the opposite applies to firms in state 2, therefore they are not
VC-backed but obtained public support. Last, firms in state 3 received both private
and public support (i.e. they are VC-backed and have benefited from the public
support).
57 The following notation is used through the paper: [Yt] denotes a stochastic process, Yt being the value of the process at time t ; [yt] represents the corresponding realizations.
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The model is represented by the diagram in Figure 46: each block corresponds to
one of the four possible states, while arrows indicate transitions between states.
Transitions from state 0 to states 1 or 2 are defined as first transitions; transitions
between states 1 or 2 to state 3 are defined as second transitions. Overall, there are
only five transitions probabilities. In fact, the model is defined as an absorbing
states model with survival data, which implies that transitions between states are
assumed to be irreversible and indeed transitions to previous states are not allowed.
In more formal terms, under this absorbing state assumption, the states with Y Ji,t =
0 are not accessible from the states with X Y Ji, t-1 = 1, j = A,B and the probability
of being VC funded at time t, once y Ai,t-1 = 1, is equal to 1 V (P{Y A
i,t = 1|Yi,t-1 =
(1,0)}=1). Similarly, P{Y Bi,t = 1|Yi,t-1 = (0,1)}=1.
In accordance with the latent regression approach, it has been assumes that firm i
gets access to funds of type j if a latent continuous random variable y*ji,t crosses a
threshold level, which with no loss of generality is set equal to null.
Furthermore, y*ji,t is assumed to depend on the state of firm i at time t-1, so as to
model the binary process as a first-order Markov chain. In particular, firms’ access
to external capital depends on foregoing events, therefore it is necessary to model
the path dependency of the process. Following Mosconi and Seri (2006), the path
dependency is modelled assuming that Yt is a first-order Markov process, so that
the information relevant to the probabilities to change status in time t is
summarized by the state of the process in time t-1:
P{yi,t | yi,t-1, yt-2 ..., yi,1} = P{yi,t | yi,t-1}.
In addition, the stationary assumption of transition probabilities implied by the
first-order Makarov process hypothesis is relaxed by modeling access to external
funds, both private and public, as a function not only of past realizations of the
endogenous variables, hence of the state in which a firm happens to be at time t-1,
but also as a function of a set of covariates xi,t , which can be time dependent or
time independent. In order to alleviate possible reverse casuality problems
(Colombo, Grilli, Verga 2007; Mosconi, Seri 2006), time dependent firm-specific
explanatory variables which may be influenced by firm’s access to private or
156
public support, have been lagged. Finally, in order to use all the available relevant
information concerning first transition probabilities in the event that firms receive
external private and/or public capital during their foundation year, the dummy
variable DSeed has been defined as follows: DSeed gets the value 1 if t=t Ei , while
it values 0 if t > t Ei . In other words, this dummy indicates firms that are less than
1 year old. By construction lagged time dependent firm-specific explanatory
variables (e.g. size) are not defined before firm’s foundation. The same applies to
the lagged endogenous variables of the model, as before foundation firms cannot
be assigned to any state. Therefore these variables, which are included in vector k
ji,t-1, cannot influence firms’ probability of accessing external funds at t = t E
i . In
the specification of the model they are multiplied by (1- DSeed ).
Another set of explanatory variables included in vector z ji,t , is formed by those
time dependent and time independent covariates which can meaningfully be
defined at foundation time and so may exert an impact on firms’ access to both
types of capital sources even in the foundation year. In particular, this vector
includes variables capturing founders’ human capital, firm-specific characteristics
(e.g. number of manager), industry-specific characteristics, and variables catching
macroeconomic conditions. All these variables are not multiplied by (1-DSeed ),
and are included in the regression function also at t = t E. Hence for a firm that was
not financed by a VC investor and did not obtain any public support (i.e. it starts
from state 0), the latent regression system is:
y*Ai,t = αT
A [ z Ai,t , (1- DSeed )k A
i,t-1] + ε Ai,t
y*Bi,t = αT
B [ z Bi,t , (1- DSeed )k B
i,t-1] + ε Bi,t
As it is usual in the setting, a standardized bivariate normal distribution for (ε Ai,t ,
ε Bi,t) is assumed:
157
with
It follows that the probability of moving to state j, j = 1,2,3 at time t, provided that firm i
is in state 0 in time t-1, can be modelled through a bivariate probit model.
This results in:
P{yi,t|Yi,t-1 = (0,0), xi,t } = Φ2
where x Ai,t and x B
i,t indicate the entire set of covariates (i.e. those included in z ji,t
and k ji,t-1 , with these latter being multiplied by (1-DSeed ).
For a start-up which has already accessed VC funds (i.e. it is in state 1), the only
possible transition is the one that refers to the receipt of a public support (i.e. from
state 1 to state 3). Hence, the latent regression underlying Y Bt can be written as
follows:
y*Bi,t = αT
B [z Bi,t , (1-DSeedi)k B
i,t-1 ] + βB (1-DSeed )y Ai,t-1 + ε Bi,t ,
giving rise to the univariate probit model:
P{ y Bi,t | Yi,t-1 = (1,0), x B
i,t} = Φ1(αTB x B
i,t + βB ; 0,1).
The same holds for the passage from state 2 to state 3 as defined by the latent
regression model:
y*Ai,t = αT
A [z Ai,t , (1-DSeedi)k A
i,t-1 ] + βA (1-DSeed )y Bi,t-1 + ε Ai,t
which leads to the folliwng univariate probit model:
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P{ y Ai,t | Yi,t-1 = (0,1), x A
i,t} = Φ1(αTA x A
i,t + βA ; 0,1).
Two basic remarks are in order. First, parameter βA ( βB ) captures the increase in
the probability of getting VC (public support) once a firm has obtained public
support (VC). Hence, the analysis of the coefficients βA and βB provides an
immediate test of the Granger casuality58 relationships between VC financing and
access to public support by start-ups. Second, the hypothesis that simultaneous
recourse to VC financing and public support is more likely than recourse to each
source financing in isolation can be tested through a Wald test fot the parameter γ,
which drives the correlation coefficient ρ (see Mosconi and Seri, 2006, p.403).
9.2. The Econometric Models
This study applies four different econometric models, using the same framwork
with different regressors.
The models are dividend into two main categories, Model 1 and Model 2. Each of
them is divided into another two categories, A and B. Therefore, there are Model
1A, Model 1B, Model 2A and Model 2B.
Model 1 works on the large sample, while Model 2 works on the small one.
Table (19) in the following page explains the structure of the econometric models.
58 The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another, first proposed in 1969. Ordinarily, regressions reflect "mere" correlations, but Granger argued that causality in economics could be tested for by measuring the ability to predict the future values of a time series using prior values of another time series. A time series X is said to Granger-cause Y if it can be shown, usually through a series of t-tests and F-tests on lagged values of X (and with lagged values of Y also included), that those X values provide statistically significant information about future values of Y.
159
Table 19. Structure of the applied econometric models.
Model 1 (Large Sample)
Model 2 (Small Sample)
Model 1A Model 1B Model 2A Model 2B
Independent
variables
Guarantee Fund � � � �
Venture Capital � �
Independent
VC
� �
Control
Variables
Firm specific � � � �
Location
specific
� � � �
Human capital � �
In order to pursue the research hypothesis, it has been applied one model that
makes use of the largest number of companies available, implementing firm-
specific and location-specific as independent variables. Afterwards, it has been
applied a second model that makes use of the small sample, which offers also
human capital-specific data, in addition to the categories listed for model 1.
In particular, models labeled with letter “A” use as dependent variable of the
bivariate model the broad category of VC, which includes both IVC and Captive
VC, in addition to GF. While models labeled with letter “B” implement, as one of
the two dependent variables, the sole Independent VC category.
The distinction between VC and IVC made through “B” models, lets the study
investigate on Hypothesis 3.
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9.3. Variables of the model
Table 20. Definition of explanatory variables
Variable Description
Firm Specific
DSeed One if t is the firm’s foundation year (Aget =1)
Aget Age of the firm at time t
Total_Assetst-1 Logarithm of firm’s total assets at t-1
Leveraget-1 Firm’s Debtt-1 on Equityt-1 ratio at t-1
Profitabilityt-1 EBITDA t-1 on Salest-1 at t-1
Employeest-1 Number of employees at t-1
N_Managert Number of operative managers at time t
Location Specific
DSouth One for firms located in the South of Italy
Entrepr_density Entrepreneurial density of region in which the firm is
located (Number of firms / 100 citizens)*
Pct_incid_on_ItaVA Percentage incidence of the region on the Italian value-
added*
Eco_infr_indicator Economic infrastructure indicator of the region in which
the firm is located*
Time specific
Deficit/GDPt Italian budget deficit compared to the national GDP at
current market prices at time t (source: Eurostat)
GDP_Growtht Italian real GDP growth rate at time t (source: Eurostat)
Human Capital Specific
Tech_Edu Average number of years of scientific and/or technical
education of founders at graduate and post-graduate level
Eco_Edu Average number of years of economic and/or managerial
education of founders at graduate and post-graduate level
NDegrees Number of degrees owned by the founders team
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Manager_Exp Average number of years of managerial work experience
of founders
Sector_Exp Average number of years of work experience of founders
in the same sector of the start-up before firm’s foundation
Gen_Exp Average number of years of work experience of founders
in other sectors than the one of the start-up before firm’s
foundation
*Sources: Istituto G. Tagliacarne, InfoCamere, Istat; http://www.trail.unioncamere.it/osservatoriregionali.asp#cat9; http://ec.europa.eu/eurostat/data/database.
162
Table 21. Determinants of Start-up access to Venture Capital and Guarantee Fund – Models 1A and 1B
Model 1A Model 1B
First Transitions Venture Capital (YA) Guarantee Fund (YB) Indep.Venture Capital (YA) Guarantee Fund (YB)
αconst const -5.1003 (0.87921)*** -3.1091 (0.21236)*** -4.0578 (0.71194)*** -3.1192 (0.21208)*** α1 DSeed 1.8152 (0.52668)*** 3.0964 (0.34278)*** 1.4122 (0.44783)*** 3.0515 (0.34018)*** α2 Total_Assetst-1 0.081541 (0.046938)* 0.3193 (0.030011)*** 0.091768 (0.038508)*** 0.31395 (0.02961)*** α3 Employeest-1 0.07644 (0.027035)*** -0.034164 (0.019222)* 0.018727 (0.017445) -0.035898 (0.019144)* α4 N_Managert 0.19221 (0.015694)*** 0.028053 (0.016864)* 0.16978 (0.017579)*** 0.024771 (0.016895) α5 Leveraget-1 -0.088749 (0.054071)* -0.018098 (0.044643) -0.17617 (0.062215)*** -0.015018 (0.044711) α6 Profitabilityt-1 -0.18238 (0.040009)*** -0.049932 (0.036484) -0.21834 (0.048027)*** -0.045186 (0.036585) α7 Aget 0.067938 (0.038129)* -0.31997 (0.029663)*** 0.019009 (0.039441) -0.31889 (0.029635)*** α8 DSouth 0.027593 (0.093112) -0.10784 (0.099211) 0.17761 (0.10793)* -0.10988 (0.099362) α9 Entrepr_density 0.0056376 (0.026758) 0.10486 (0.033517)*** -0.024875 (0.032049) 0.10501 (0.03357)*** α10 Pct_incid_on_ItaVA 0.00035879 (0.0047083) 0.0085778 (0.0047223)* 0.0036639 (0.0054474) 0.0085218 (0.004729)* α11 Eco_infr_indicator 0.00047791 (0.0010605) -0.0007007 (0.0010981) 0.0021215 (0.0012323)* -0.00072424 (0.0011004) α12 Deficit/GDPt -0.34921 (0.21841) 0.52231 (0.15967)*** -0.084776 (0.22211) 0.50351 (0.15897)*** α13 GDP_Growtht -0.13622 (0.043093)*** 0.39412 (0.049378)*** -0.1461 (0.04359)*** 0.3897 (0.049194)***
Second Transitions
βA → Public Funds -0.33174 (0.49355) - -0.12514 (0.47605) -
βB → Venture Capital - -0.056589 (0.10315) - 0.072927 (0.13069)
Simultaneity
γ Public Funds ↔ VC 0.12777 (0.15069) 0.088608 (0.16537)
*p < 0.10; **p < 0.05; **p < 0.01. All two-tailed tests. Robust standard error in parentheses. Number of observations is 5564.
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Table 22. Determinants of Start-up access to Venture Capital and Guarantee Fund – Models 2A and 2B
Model 2A Model 2B
First Transitions Venture Capital (YA) Guarantee Fund (YB) Indep.Venture Capital (YA) Guarantee Fund (YB)
αconst const -3.8373 (1.2077)*** -2.9074 (0.38677)*** -3.3895 (0.65952)*** -3.0201 (0.39086)*** α1 DSeed 2.6994 (1.0098)** 5.6058 (0.94532)*** 2.1859 (0.86158)*** 5.6867 (0.94696)*** α2 Total_Assetst-1 0.090558 (0.07374) 0.27146 (0.057099)*** 0.064396 (0.059022) 0.24857 (0.056324)*** α3 Employeest-1 0.059539 (0.036105)* -0.061097 (0.028597)** -0.0049618 (0.020797) -0.065357 (0.028696)** α4 N_Managert 0.25117 (0.026891)*** 0.067499 (0.028956)** 0.17799 (0.027703)*** 0.055659 (0.028939)* α5 Leveraget-1 -0.022877 (0.023728) -0.001744 (0.017111) -0.0094376 (0.019856) 0.0025507 (0.016998) α6 Profitabilityt-1 0.41744 (0.91892) 3.3036 (0.89445)*** 1.2234 (0.87192) 3.5915 (0.8926)*** α7 Aget 0.071276 (0.056694) -0.30364 (0.052491)*** -0.029362 (0.05751) -0.30628 (0.052516)*** α8 DSouth -0.070255 (0.14358) -0.20844 (0.18639) 0.2782 (0.16113)* -0.21508 (0.18499) α9 Entrepr_density -0.0028548 (0.038612) 0.088309 (0.052215)* -0.067039 (0.046482) 0.085154 (0.051053)* α10 Pct_incid_on_ItaVA -0.0030146 (0.0074978) 0.0032506 (0.0085733) 0.0015925 (0.0084995) 0.0026434 (0.0085387) α11 Eco_infr_indicator 0.0011159 (0.0016223) -0.00058034 (0.0018368) 0.0033515 (0.0018819)* -0.00082255 (0.0018415) α12 Deficit/GDPt 0.12095 (0.3038) 1.3031 (0.34115)*** 0.22398 (0.3071) 1.2599 (0.33828)*** α13 GDP_Growtht -0.046711 (0.063293) 0.5268 (0.090154)*** -0.096264 (0.061916) 0.51874 (0.090016)*** α14 Manager_Exp -0.038872 (0.017812)** -0.0057951 (0.021621) -0.033805 (0.021717) -0.0025839 (0.021548) α15 Gen_Exp 0.05704 (0.017915)*** -0.018028 (0.023645) 0.077546 (0.01901)*** -0.022065 (0.023711) α16 Sect_Exp 0.024397 (0.012049)** 0.00091716 (0.014674) 0.01118 (0.013446) -0.00044219 (0.014655) α17 Tech_Educ -0.0079087 (0.0047643)* -0.0020018 (0.0052525) -0.004741 (0.0048841) -0.0017876 (0.0052646) α18 Eco_Educ 0.023437 (0.01236)* 0.017834 (0.010769)* 0.041133 (0.012661)*** 0.015881 (0.011026)
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Table 22. (Continued.)
Second Transitions
βA → Public Funds -0.45892 (0.6191) - -0.082998 (0.57704) -
βB → Venture Capital - -0.21313 (0.14462) - 0.14676 (0.18676)
Simultaneity
γ Public Funds ↔ VC -0.31296 (0.23933) -0.21407 (0.25794)
*p < 0.10; **p < 0.05; **p < 0.01. All two-tailed tests. Robust standard error in parentheses. Number of observations is 1551.
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9.4. Results of the estimates
This section will explain and describe the estimates found through the application
of the four econometric models that are displayed by Table 21 and Table 22 above.
Model 1A and 2A will constitute the richest parts, while 1B and 2B will discuss
whether relevant differences and interpretations can be assumed when running the
models with IVCs. A general consideration about the policy intervention will close
the section.
9.4.1. Model 1A
A further table below shows briefly what are the effects found in the leading model
1A, which runs with financial firm-specific, location-specific and time-specific
covariates, on a sample of 2526 companies.
Table 23. Summary of the effects found in Model 1A
Venture Capital Guarantee Fund
Total_Assetst-1 + +++
Employeest-1 +++ +
N_Managert +++ +
Leveraget-1 -
Profitabilityt-1 ---
Aget + ---
Entrepr_density +++
Pct_incid_on_ItaVA +
Deficit/GDPt +++
GDP_Growtht --- +++
Different number of +/- sign reflects the statistical significance of the variable.
First, it is possible to assert some considerations about the covariates that reflect
the dimension characteristics of the firm. Those are total assets value, number of
employees and also number of managers. All of them are found to have a
significant influence on both private and public investors. It is worth to notice that,
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however, it seems that for VC might be more significant the structural dimension
of the company in terms of human capital and staff, rather that what the financial
statement tells, which is instead what the public actor might look at. This would
be in line with the literature saying the screening procedures between VC and
public sector are very different, in particular, the latter is more superficial.
Anyway, the dimension indicators play a significant role for both of them.
Second, as regards financial and performance indicators, namely leverage and
profitability, the situation changes with significant influences exerted only towards
VC, while no significant effects are found towards GF. Moreover, the effects on
VC have a negative and significant impact, which could be translated into the
general conclusion that VCs are not used to back-up neither firms highly leveraged
on the one hand, nor those ones that already perform very well on the other hand.
Third, age is very significant for both VC and GF, but what is most relevant is that
it has opposite signs: indeed, concerning the VC’s point of view, the more a firm
is stabilized and “old” (old in the start-up environment could mean a couple of
years also) the better it is. On the contrary, the public sector follows the opposite
lead and the youngest firms get the highest chance to be taken into consideration.
A further possibility is that the younger a start-up is, the higher is the probability
that it asks for public support.
It must be underlined that the public intervention that is under the focus of this
analysis, has been made exactly in order to back very young companies. This is
clear also from the fact that it imposes an age restriction among the requisites of
access to the GF.
Finally, location and time variables are found to have no singificant effects on
private investors, while they definitely do on the public one. In particular, this latter
is more motivated to back start-ups up when they are located in developed and
productive regions with a solid entrepreneurial net and when the GDP growth rate
is favourable. The last thing to notice is that the VCs are likely to act when the
economic situation is negative, which is represented by a significant and negative
effect of the GDP growth rate.
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Overall then, VCs are found to support firms that are not able to make a good profit
yet, but show a rather good financial and dimension structure, with a more solid
staff and manager base. The public support is found to be more inclined towards
very young firms, that show at least a basic good financial base, mostly represented
by the total assets owned by them, which could be striclty connected to the
collateral capacity a public figure may be looking at.
9.4.2. Model 1B
As explained before, Model 1B runs with the same covariates of 1A on the same
sample, but considering as one of the two dependent variable only IVCs with GF.
In other words, it excludes Captive venture capitalists composed mostly by
corporate VCs. Table 24 works with the same logic as Table 23.
Table 24. Summary of the effects found in Model 1B
Indep.Venture Capital Guarantee Fund
Total_Assetst-1 +++ +++
Employeest-1 -
N_Managert +++
Leveraget-1 ---
Profitabilityt-1 ---
Aget ---
DSouth +
Entrepr_density +++
Pct_incid_on_ItaVA +
Eco_infr_indicator +
Deficit/GDPt +++
GDP_Growtht --- +++
Different number of +/- sign reflects the statistical significance of the variable.
The estimates are very close to the ones of Model 1A. Differences lie mainly on
the level of significance of some variables that are less strong. From the public side
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the situation does not change much, apart from the Employees indicator that has
assumed a negative sign. This could be explained by the typical growth trend
followed by new companies, which is strictly related to age: new companies
usually have no employees, on the contrary, for the early period the work force is
represented by the founders. This holds especially for innovative and high-tech
firms that are founded by the innovative thinker of a new business idea. Since the
public actor is likely to support the youngest companies, which is stated by the
variable Age, the same companies might have also very often few employees or no
personnel at all.
Switching to the VC side, the results are very similar too: they look at dimension
indicators such as Total Assets and Number of managers (both positive and
statistically significant) in order to ensure to support a company with a solid
starting base. However, Employees loses significance, suggesting that pure VC
might look less at the personnel situation, as long as the management is well
establieshed. IVCs aim to support the company not only from the financial point
of view, but also from the strategic one. Therefore they may consider other drivers
rather the number of employees when it comes to determine the growth and
development potential the firm has, because they can actually be the part of the
growing process. Corporate VCs on the contrary may be more inclined to invest in
more “complete” firms, which already have a launched structure.
In the end, the economic infrastructure indicator has become positive and
significant in model 1B for what concerns the VC equation, suggesting that also
IVCs, like the public sector, actually is influenced by the location. That would be,
indeed, in line with many studies of the entrepreneurial literature saying that
private investors tend to invest in firms located in a developed environment where
these latter can benefit from various services, in addition to a probable broader
potential market close to them. This logic takes back to the idea of incubators and
science parks, where high-tech start-ups actually benefit from the “km-zero”
support and services, as well as IVCs themselves could strongly prefer to be close
to the financed firm in order to give a constant support and at the same time have
good control.
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9.4.3. Model 2A
The second model completes this study, it investigates on human capital
charcteristics in addition to the ones included in model 1. This extension
implements a new set of controlling variables that help to assess a maybe more
correct evaluation of the effects and moreover it investigates on the human capital
matter, which is one of the most relevant area of interest when considering start-
ups survival rates.
Table 25 below shows in the same way of the latest tables, the positive/negative
effects of the covariates and their level of significance.
Table 25. Summary of the effects found in Model 2A
Venture Capital Guarantee Fund
Total_Assetst-1 +++
Employeest-1 + --
N_Managert +++ ++
Profitabilityt-1 +++
Aget ---
Entrepr_density +
Deficit/GDPt +++
GDP_Growtht +++
Manager_Exp --
Gen_Exp +++
Sect_Exp +++
Tech_Educ -
Eco_Educ + +
Different number of +/- sign reflects the statistical significance of the variable.
Overall, the estimates that result from this second model confirm that human
capital characteristics play a relevant role in the start-up access to external
financing: indeed, the general framework of the significant variables has changed.
170
From a quick overview of Table 25, it is easy to notice that there is a solid
difference between what is relevant to the eyes of the two investors, the private
and the public one. In other words, what appears to be relevant for one, it is not for
the other one and vice versa.
First, the variables that act as dimension indicators have lost importance for the
access to VC investor: Total Assets and Age have lost significance. On the other
hand, all the new human capital covariates have taken some of the overall
contribute that leads to receipt of VC financing. In particular, both education and
work experience indicators are significant, some with a positive impact and others
with a negative one.
Work experience is very significant in all the three forms in which it is here
represented: years of managerial experience is found to affect negatively the
chance to access to VC. Therefore, the higher it is the managerial expertise in a
start-up, the fewer are the cases of being supported. According also to the
entrepreneurial literature, venture capitalists support a company in the daily
management of the business, and a company with a solid managerial experience
either does not really need support from the stategic point of view and goes only
for financing aids, or there is hesitancy by venture capitalists to collaborate with
an established management team, probably because they hinder each other when
they do not get along properly. On the contrary, both general experience and
sectorial experience are found to be very significant and exert a positive
contribute. This suggests that the private investor fully evaluates the expertise
inside the firm, which seems to be the decisive and critial factor.
Moving to the education side, both technical and economic education exert a
significant effect. The latter has a positive contribution, suggesting that it is
actually important for a VC that founders and key-people have a basic economic
knowledge undestanding. On the contrary, the former does not help to get external
private funds. One possible explanation of this finding could be ascribed to the fact
that many founding teams in the high-tech and innovative sector are not made of
people with technical background only, but when it comes to found a company
they recruit figures with economic and managerial knwoledge as it is considered
171
essential for success. Therefore, again, those firms may be oriented only to get
financing aid and not further managerial support. The finding is consistent with
the previous and similar study of Colombo and Grilli (2010), who found higher
technical skills to discourage VC investors.
From the side of GF, the drivers for the access to public external funds are very
similar, with the addition of two significant variable that exert a positive influence:
the first is profitability, a performance indicator that is taken into consideration
with the other main financial indices, the second is economic education, which
also in this second equation is found to be relevant. The screening process of the
public sector is traditionally less deep and accurate compared to the one of VCs,
but there is the possibility that among the basic financial charateristics, also
economic education is analyzed as it was a sort of verification that the company is
managed by someone with an economic background.
Overall, there is a clear difference between the firms that are financed by the two
investors: the private one subsidizes those firms with a solid founding team and
management, that looks actually capable to face the challenge of helping the start-
up to overcome the early period. The public one instead seems to give no relevance
to the characteristics of the human capital and subsidize firms with certain
characteristics, which are predominantly of financial kind.
In conclusion, it is reasonable to deduce that there more of a segmentation effect
between VC and GF, as the findings suggest that the firms financed by them exhibit
different characteristics. The drivers for the decision making of the two investors
diverge and their influence shows no substitution or complementary effects.
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9.4.4. Model 2B
The “B” version of model 2, repeats the study of model 2A considering IVCs
instead of the whole set of VCs.
Table 26. Summary of the effects found in Model 2B
Indep.Venture Capital Guarantee Fund
Total_Assetst-1 +++
Employeest-1 --
N_Managert +++ +
Profitabilityt-1 +++
Aget ---
Entrepr_density +
Eco_infr_indicator +
Deficit/GDPt +++
GDP_Growtht +++
Manager_Exp
Gen_Exp +++
Sect_Exp
Tech_Educ
Eco_Educ +++
Different number of +/- sign reflects the statistical significance of the variable.
Once again, contributors to start-up access to GF do not change, except for
economic education that has lost its significance, however, it is considered
consistent with the idea of a public screening precedure that does not take into
consideration human capital characteriscs, but only the financial ones together
with location and time favourable elements.
For what concerns the VC equation, the explanation given for model 2A is valid
and even more stressed. In particular, the fact that IVCs look mainly at the
founding team characteristics holds also in this case, but the decisive variables that
exert a significant and positive effect are number of managers, general work
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experience and economic education, with an addition of a location variables
reflecting a favourable work environment, the economic infrastructure indicator.
This can be explained thinking of IVCs as pure strategic investors, which seek for
good ideas with great potential in order to intervene with financial aid and also
strategic support. From this point of view, what IVCs mainly do is to evaluate the
projects, the business idea, the business plan, and if these are considered
promising, then they make sure of the founding team to have some experience and
to be actually capable to face the business challenges from the managerial point of
view.
9.5. Second transitions implications
Second transitions estimates of all four models are discussed together. The lower
part of both table 20 and 21 reports the estimates of second transition [(1,0)→(1,1);
(0,1)→(1,1)] and simultaneity [(0,0)→(1,1)], which is the transition from having
neither private nor public support, to the receipt of both of them directly.
As the findings show, there are no statistical significant estimates of any of these
transitions in any of the four models. The interpretation of this picture is that
private and public investors do not overlap in their subsidizing processes, because
once a firm has received a financing from one of them, its financial constraints fall
away and it does not need any further support of the other kind. In other words,
private and public funds seems to have neither complementary nor substitution
effect: they subsidize two different kind of companies, with different
characteristics and needs, and unlock their financial constraints in such a way as
those start-ups do not need further different support. Therefore, a more correct term
to identify such effect could be segmentation, in the sense that none of them
influences significantly the other one but, at the same time, they support different
type of firms relaxing their financial constraints.
This interpretation is supported by the results, because the estimates calculated by
both models 1A and 2A, even though not significant, bear a negative contribution
towards the transition to state 3 (1,1), coming from state 1 (1,0) and 2 (0,1). This
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suggests that a firm with no initial support, namely in state 0 (0,0), will not get to
state 3 (1,1) passing through state 1 or state 2, because the receipt of VC (GF) tends
to lower the chances of receiveing afterwards GF (VC) support.
However, this idea is a discussion about the negative signs borne by second
transition estimates, but it must be underlined that those results are not statistically
significant.
Hypothesis verification results
In view of all this results, it is possible to comment the research hypothesis
supposed in this study.
Hypothesis H1 is rejected. No certification effect by any of the two investors has
been found.
Hypothesis H2a is accepted: VC investors are found to rely significantly on the
characteristics of the human capital inside the firm.
Hypothesis H2b is rejected as the public sector does not look at human capital
characteristics when evaluating a company for granting subsidies.
Hypothesis H2c is rejected because technical education is found to have a negative
contribution toward VC investors. The finding is in agreement with previous
studies on the matter.
Hypothesis H3 is generally accepted in a qualitative way: indeed, the leading
significant variables that compose the main determinants of access to VC anf GF
are confirmed also in “b” models.
Policy implications
Overall, the main implication emerging from the findings is that the public
intervention actually hits the share of those financially constrained start-ups that
probably would not be supported otherwise. More precisely, the findings do not
state that, for instance, GF-backed firms would not have been supported by a VC
in the absence of GF support; they only suggest this interepretation indirectly
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because a firm getting a GF-support seems to have different characteristics a priori
that ususally differ from the decision-drivers typical of a VC.
This view frames a situation in which the public policy offered by the Law
221/2012 seems to exert an additional positive effect in supporting a portion of
start-ups with characteristics that do not traditionally match the expectations of
VCs and/or start-ups that are not in need of a solid support such as the one of VCs,
which goes beyond the mere financial needs. However, results confirm this bright
interpretation by analyzing only the access of the companies to these external
financial sources and future investigations probably need to prove it. An interesting
lead for further research could be the investigation on the effect of the support by
each investor. An analysis that studies the performance of these start-ups after the
receipt of external funds would shed some light on the conclusion uncovered by
this research study, proving or rejecting the fact that a support by the GF/VC
removes completely the financial constraints.
Overall, the instruments implemented by the policy are found to be effective in
attracting entrepreneurs and alleviating their financial contraints.
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10. CONCLUSIONS
As it has long been recognized in the economic literature, small and medium
enterprises (SMEs) are considered a fundamental factor for economies’ stability
and growth. According to recent analysis (Asdrubali & Signore, 2015), they
represent the 99,8% of European companies, contributing to almost 60% of GDP
and 70% of the total workforce. Young innovative companies (YICs), which
belong to this category of firms, are found to be strikingly important because they
carry the burden of developing solid and sustainable progress through the
introduction of innovations into the market (Timmons & Spinelli, 2003) in terms
of new products, processes and organizational enhancements. They stimulate and
test existing technological paradigms, play a disciplining role towards established
leaders, open up new market segments and favor the flow of knowledge among
several industries. YICs, more than their larger peers (Schumpeter, 1942), perform
better when it comes to innovate thanks to their structure and features that allow
them to develop important innovations with significant commercial applications
and social value. Indeed, Storey and Tether (1998) find that these firms exhibit a
higher than average survival rate, a faster employment growth and founders with
a better education. However, due to their young age and business nature, these
firms share a common and cumbersome constraint: the lack of access to financing
resources. Evidence from the U.S. (Shane, 2009) shows that the typical start-up is
dead in five years.
YICs draw the attention of many actors in modern economies, first among
everyone the public sector. Since very long time, governments try to design several
types of intervention in order to alleviate those constraints that hamper the growth
of high-potential young innovative companies to let them fulfill their main role:
spawn the scene for new products and markets being the crucial catalyst for
national economies.
Policy makers need to step in, as long as private firms are found to invest less than
social optimum in most of economies. Two main reasons are universally
acknowledged to explain the gap between private firms’ investments and its social
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optimum level: spillovers (Teece, 1986), which jeopardize the survival of YICs
that suffer from inefficient mechanisms of protection (limited appropriability of
new knowledge), and capital market imperfections.
In regard of this latter in particular, their chance of obtaining equity or debt
financing is restricted by the presence of principal-agent conflicts and information
asymmetries (Peneder, 2008), which give rise to adverse selection and moral
hazard problems (Carpnter and Petersen, 2002a)
Young companies are often financially constrained more than others because they
usually lack of stable cash flows, track records and, most importantly, lack of
collateral. Moreover, their innovative nature is based on R&D activity, which is
more expensive than other ordinary investments to be financed (Hall, 2002; Jensen
and Meckling, 1976).
The venture capital industry constitutes a second major supporter for YICs. In
particular, it is known among various descriptions as the free market solution to
the problems of financing innovation. The strength of this private investors is their
ability to face information asymmetries in a better way (Lerner, 2002; Tian, 2011;
Wang and Zhou, 2004). Indeed, they are more capable to select and identify
“lemons” and to address information problems (Gompers and Lerner, 2011).
The venture capital is actually seen as the most effective solution for financing
YICs and also the dominant form of equity financing. Nevertheless, the Italian
landscape does not offer a proper environment suitable for venture capitalists
(AIFI): the labor market is not flexible, private pension funds hardly exists and the
Milan Stock Exchange is quite small compared to other international realities. This
entails a rather poor presence of this kind of investors, which, besides its financial
capacity, exert a relevant coaching function (Baum and Silverman, 2004;
Colombo, Grilli, Bertoni, 2011) towards backed-companies (treatment effect) and
it also communicates a quality signal (Colombo et al., 2006) to outsiders
(certification effect).
Another crucial factor considered essential for firms’ survival goes hand in hand
with the VC: the human capital. There exists a wide literature concerning the role
of human capital in the firm’s life, more precisely, how and to what extent it affects
178
growth. Evidence from several studies (Colombo and Grilli, 2005; Colombo and
Grilli, 2010; Grant, 1996) confirm that one of the two key drivers of success of a
YIC is the human capital, together with access to venture capital.
Indeed, economic/management education and years of working experience are
found to be significant leaders for a superior growth. More often than not, the
commercialization of an innovation is successful when there is a conjunction
between the specific know-how and other capabilities or assets: marketing,
manufacturing, after-sale support and general business management are
specialized complementary assets usually needed. A venture capital can actually
help the firm from this point of view as well, as long as they play an active role in
the management providing competences and resources.
Despite all these considerations, the venture capital may not be the solution to
alleviate YICs’ financial constraints completely. As a matter of fact, there are
relevant obstacles even in the private. First, it is possible that the strategy and
objective of the entrepreneur diverge from the investor ones; VCs often aim at a
profitable exit strategy such as IPOs or a trade sale. Second, as the information
asymmetries are bilateral, the entrepreneur itself may hesitate to divulge key
information to a private external investor that could poach the innovative business
idea. Third, screening and procedural fixed costs are considerably high, so that VC
investors may be restrained from targeting very early-stage financing.
Although the venture capital industry seems to play the most relevant and effective
role when it comes to back YICs up, very often it is not enough. Moreover, the
Italian bank-based system offers a very weak VC market.
There is a strong need for another “hand”, which has to come from the public
sector. However, a broad search of literature shows that the fundamental and
general question of how, and if, governments are able to influence positively
entrepreneurial activity is far from being resolved. When it is the case of
government venture capital funds, for instance, the evidence suggests that these
public funds, born to follow in private funds’ footsteps, are not significantly
effective for several reasons. A better positive result is achieved through the
179
combination of GVC funds and venture capital activity, as long as their synergies
as well exploited (Lukkonen et al., 2013; Schaefer and Schilder, 2006; Grilli and
Murtinu, 2014).
The literature covering the role of public intervention and policy design is sizeable
and the whole line agrees upon most conclusions. There are some general
recommendations applicable to public programs (Lerner, 2002). First, public
officials need to invest in building relationships with the venture capital industry
and get a better understating of it. Second, regulators should consider those
technologies that are not currently popular among venture investors, since these
latter are used to be very sector-focused; they must support the VC industry where
it lacks. Third, federal officials must appreciate the need for flexibility, which is
central to the VC investment process that often presents changes such as shifts in
product market, strategy and management team, all due to the great uncertainty
characterizing the business. Fourth, they should build a better examination
framework to strengthen their scouting capabilities.
The VC is the most effective supporter, and the public sector should act at his side
in order to dissolve those obstacles that hinder it. In this way, also public actions
exert a relevant positive effect. Governments are the only one that have certain
instruments of intervention; therefore, they are deeply needed for operating on
specific regulation levels, which make the business environment more thriving for
both entrepreneurs and private investors.
In particular, in order to ease the access to financial resources, policies usually
make their selection from the following fan of instruments: direct funding of firms
targeted to SMEs and high-tech startups, fiscal incentives for investors oriented to
classes of assets, stimulation of capital markets through regulatory reforms, equity
programmes and guarantee schemes.
As a matter of fact, young innovative companies need three main elements to
achieve growth and success (Grilli 2014): financial resources, knowledge capital
and complementary assets; the public sector can influence the three of them.
According to Lerner (2010) and Teece (1986), policy makers should take into
consideration interventions that go beyond financial matters. First of all,
180
entrepreneurial activity does not exist in a vacuum, on the contrary, entrepreneurs
are very dependent on their partners. Therefore, it is essential to address not just
the need of capital but also other components of a productive arena in which
entrepreneurs can operate. Second, it is important not to over-engineer the policy
program, remembering also that it is the market to provide direction. Third, since
the cradle of knowledge and innovation is also found to be science parks and
incubators, promoting the local academic scientific and research base is essential.
Fourth, embrace the conformity of global standard. Fifth, accept the long lead time
typical of public venture initiatives. Finally, governments should build education
for each of the three actors involved (entrepreneur, private and public actors) in
order to oil the whole mechanism. Foreign venture investors need to understand
the potential of the local market and its opportunities, entrepreneurs must
understand the expectations of top-tier private investors, while the public sector
would deeply benefit from an understanding of the challenges of entrepreneurship
and venture capital development, so that expensive errors made in the past could
be avoided allowing for a process of continuous improvement.
This study went through all the aspects concerning public and private investments,
offering a detailed explanation of the key success factors of each one and, at the
same time, analyzing limits and obstacles these two actors face. A policy design
guideline is also available, which gathers all the findings, suggestions and
considerations of the main studies concluded so far on this matter. Furthermore,
the study presents a comparison between the European situation (with a specific
focus on some relevant European countries) and the American one for what
concerns both the venture capital market and the policies historical background.
Historically, Italy shows a weak venture capital market and a policy track record
that has not focused on this specific category of companies (i.e. YICs) yet.
Nevertheless, in 2012 the situation has changed. Clear rules of fiscal fulfilment,
labor market flexibility, quick and fluid bureaucratic procedures, a legal system
encouraging entrepreneurship and not tagging failures as disasters or “point of no
return”, the opportunity to raise equity capital: each one of these elements
181
contribute to the creation of a dynamic and prosperous environment, capable of
gaining a good reputation to its country on a global scale. These are the leading
principles on which the Italian government has founded the development of an
innovative policy program: the Decree Law 221/2012, also known as “Decreto
Crescita 2.0”, which entered into force on December 17th 2012.
The Law has been created to foster the birth and the development of young
innovative companies, which are recognized with the new expression “innovative
start-ups”, as the regulation has established a precise meaning to this definition. In
particular, the innovative start-up is a new innovative company with a high level
of technology (i.e. high-tech innovative firm), which presents specific peculiarities
in terms of age, location, object of business and further features fully listed in later
on in this study.
The regulatory framework (art. 25-32) is designed specifically for these kind of
firms without any distinction of sectorial nature or relation to the entrepreneur’s
age. It operates with new instruments and supporting measures that work on the
whole life cycle of the company. In detail, the Law offers to innovative start-ups a
much faster process of foundation, reliefs from royalties and duty stamp,
exceptions to ordinary regulation, facilitations in paying losses back, tailor made
employment regulation, flexible remuneration for employees, tax credit when
hiring qualified personnel, fiscal subsidies for investors, equity crowdfunding,
individual support, a fail-fast program that encourages entrepreneurs and the direct
access to the Guarantee Fund for SMEs.
The aim of giving YICs the access to the guarantee fund is to lessen the difficulties
that these firms suffer from when they seek for debt financing. Banks ask for an
even more burdensome amount of collateral when companies are in the start-up
phase, and the guarantee fund aims to alleviate this distortion.
Starting from these premises, this study investigates on the effects that the Law
actually exerts on innovative start-ups and, at the same time, it analyzes the
relationship between the policy and venture capitalists. In particular, as a first aim
the study investigates whether the receipt of funds thanks to the guarantee fund
exerts some kind of signaling effect toward VC investors, evaluating the possible
182
presence of substitution effects in the markets. In other words, in investigates
whether the receipt of public support influences private investors and, vice-versa,
if being backed by a VC increases the chances of being financed by a bank through
the guarantee fund model.
The second aim of the study is also to understand the role played by human capital
characteristics in terms of education and work experience when it comes to win a
financier over, either a private or a public one.
The research analysis makes use of two samples. The first one gathers all the
innovative start-ups that were on the Company Register list up to December 8th
2014 and that had all the financial data available up to November 2nd 2015; this
translates in a sample of 2526 firms. The second sample is a subset of the first one,
but with an augmented info base for each company. This hand-collected dataset
includes a remarkable and large amount in information with regard to the founders
of each firm: for each founder of the firms included in this second sample, personal
data about education and work experience have been searched and registered.
The econometric model applied in this analysis follows in the footsteps of Mosconi
and Seri (2006). In detail, the study employs a dynamic bivariate survival model,
which allows to model access to both VC and Guarantee Fund support as a
bivariate discrete-time binary process.
The whole study includes four models divided in two categories: one category uses
the large sample, while the other one uses the small one. Therefore, the former
investigates the research objectives using mainly financial firm-specific, time-
specific and location-specific info. The latter adds to the group of variables also
the data describing the human capital characteristics. Moreover, both of them
employ two versions of the model in order to differentiate between a general
category of venture capital, which involves both independent venture capital and
captive venture capital, and the sole category of independent venture capital.
The findings of the first category of econometric analysis suggest that VCs support
firms that are not able to make a good profit yet, but show a rather good financial
and dimension structure, with a more solid staff and manager base. The public
183
support instead, is found to be more inclined toward very young firms that show
at least a basic good financial base, mostly represented by the total assets owned
by them.
For what concerns the category with human capital data, it is found a clear
difference between the firms that are financed by the two investors: the private one
subsidizes those firms with a solid founding team and management, which can
actually look capable to face the challenges of making the start-up overcoming the
early difficult period. Human capital characteristics therefore are found to play a
relevant role. On the other hand, the public investor seems to give no relevance to
the characteristics of the human capital and it supports firms with other
characteristics more of financial kind.
In the end, all the four models find that private and public investors do not overlap
in their subsidizing processes, because once a firm has received a financing support
from one of them, its financial constraints fall away and it does no need any further
aid. This suggests that private and public funds are neither substitutes nor
complementary, on the contrary, there seems to be a segmentation effect between
them, as long as they are found to support different kind of firms.
In any of the four models, there is a significant effect exerted by policy measures
on the YICs’ likelihood of accessing VC financing, leading to the exclusion of the
existence of any important certification effect associated with the reception of
public subsidies.
184
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◊ Ringraziamenti
In quest’ultima sezione si concentrano le parole di gratitudine per tutte le persone
che mi hanno seguito in questo percorso.
Innanzitutto, un sentito ringraziamento va ai professori Luca Grilli e Giancarlo
Giudici. Entrambi hanno svolto un ruolo fondamentale e complementare (tanto per
rimanere in tema con la tesi), dimostrando una disponibilità impeccabile degna di
nota. Attraverso la loro guida sono riusciti a farmi scoprire ed apprezzare il mondo
della ricerca scientifica.
Ringrazio il team multimanager di Aletti Gestielle, che mi ha accolto con prezioso
entusiasmo nella loro realtà facendomi sentire a casa dal primo giorno. Ringrazio
Gianluca per aver creduto in me fin dal principio; Nicola, il collega che tutti
vorrebbero con cui non ti annoi mai grazie alle sue battute “tra realtà e mercati”;
Luca, per la fiducia che dimostra di avere nelle mie capacità quando mi dà
responsabilità sempre maggiori; Davide, per non aver mai smesso di incoraggiarmi
e avermi dato una marcia in più condividendo con me le sue idee smart; infine
Adolfo, il capo migliore che una persona possa desiderare quando si rompe il
ghiaccio con il mondo del lavoro.
Ringrazio le persone con cui ho stretto le amicizie più sincere in questi ultimi anni.
In ordine cronologico parto con Andre e Lore, i miei colleghi di “relax” dei primi
anni; anche le lezioni più importanti con voi sono state terreno fertile per
un’abbondante dose di casino, alla fine di questo percorso posso dire di essere
felice di aver preferito le risate con voi a mezzo punto in più sulla media esami.
Continuo con il mein deutsches Team: Andre, Sergio, Yalim e Nutelloz, compagni
erasmus con cui in sei mesi ho costruito un rapporto raro e con cui sarò sempre in
contatto, nonostante i chilometri. Chiudo il gruppo universitario con Thomas e
Andrea, due amici fondamentali con cui ho condiviso un mare di emozioni e due
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compagni di teamwork con cui il successo per ETA è assicurato. Prima o poi ci
scappa la start-up e non sapremo dove parcheggiare gli elicotteri.
I miei amici storici voglio ringraziarli per aver piantato le radici nella mia vita.
Lucy, l’amica che non manca mai e che mi copre sempre le spalle nel torto e nella
ragione; in tutti questi anni mi hai accompagnato attraverso i mille casini che ho
combinato, grazie per essermi stata sempre accanto e aver avuto le parole giuste
per me in ogni occasione. Non ringrazierò mai abbastanza Pippo, che da cinque
anni si dimostra ogni giorno un amico sempre più fedele e premuroso quando il
mio cervello decide di scioperare, oltre ad essere il compagno ideale per creare il
degrado più totale anche per festeggiare anche la cosa più piccola.
Gabba, Necla e Carla, il loro turno di ringraziamenti è il più difficile, perché siamo
abituati ad esprimere il nostro affetto attraverso insulti e battute. Grazie per essere
le tre persone con cui sono sicuro avrò lo stesso rapporto spontaneo e naturale fino
all’ultimo dei miei giorni, un rapporto che sconfigge il tempo e la distanza, un
rapporto che è una delle cose di cui vado più orgoglioso.
Ringrazio una delle persone che più mi ha supportato in questi anni, Chiara. Grazie
per essermi stata accanto ogni secondo di questo ultimo periodo, se non sono
impazzito è grazie a te che hai annullato la montagna di stress che accumulavo nei
momenti più duri. Hai sempre creduto in me più di chiunque altro, più di quanto
ci abbia creduto io stesso, ripetendomi che non esiste nulla che io non possa fare.
Se ho voluto dare sempre di più è stato anche per poter essere il migliore ai tuoi
occhi. Le tue parole mi hanno dato spesso la grinta necessaria per diventare la
persona che sono oggi.
Infine, la mia famiglia. Ringrazio il mio bro, che da quando ne ho memoria è
sempre stato la mia valvola di sfogo per scappare dai doveri ordinari. Un enorme
grazie va a mia zia Francesca, che si preoccupa per me e mi segue da sempre; è
grazie a lei che ho potuto scrivere liberamente una tesi in inglese e potrei farle i
ringraziamenti in tedesco. La mia nonna Marta merita un grazie indelebile per
avermi trattato da sempre come il suo principe. Ho iniziato a capire come renderti
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fiera di me quando alle medie ti divertivi a farmi risolvere il problemi di logica sul
giornale; scriverti il messaggino della vittoria quando raggiungo un obiettivo
importante mi riempie di soddisfazione.
Mia sorella Carlotta, l’uragano di entusiasmo della famiglia. Grazie per rendere
ogni cosa più bella, con il lato artistico che hai ereditato dipingi il mondo con dei
colori più accesi e sono felice di far parte anch’io di questo mondo.
Mamma, ogni volta che penso alla persona stupenda che sei mi commuovo, perché
non riesco nemmeno a visualizzare bene il confine delle tue qualità e mi sembra
incredibile di aver avuto la fortuna di essere tuo figlio. Grazie per essere la mamma
all’avanguardia con cui posso parlare di tutto.
Papà, sei semplicemente il mio modello di persona da sempre. Crescere sotto la
tua ala ha radicato in me i valori più importanti con cui affronterò tutta la mia vita,
se sono qui oggi lo devo ai tuoi sacrifici e alla tua guida quotidiana. Renderti
orgoglioso di me è il mio modo di ringraziarti di tutto. Questo è sicuramente un
traguardo molto importante, ma è solo l’inizio.
Milano, 18 dicembre 2015
