Market Structure and Competition in Transition: Results ...€¦ · al. 2010) Contribution: I ﬁrst empirical evidence on (changes of) market conduct ... @P @N Q(1 + L") = @P @N

BACKGROUND METHODOLOGY RESULTS OUTLOOK

Market Structure and Competition inTransition:

Results from a Spatial Analysis

Martin Lábaj† Karol Morvay ‡ Peter Silanic ‡

Christoph Weiss† Biliana Yontcheva†† Vienna University of Economics and Business

‡ University of Economics in Bratislava

8. Geoffrey J.D. Hewings Regional Economics WorkshopAustrian Institute of Economic Research

September 3-4, 2015


TRANSITION AND ENTRY: TESTABLE HYPOTHESESHypothesis 1: Entry barriers have been lowered.The perceived fixed costs of establishing a firm decreasedand the perceived per- capita profitability increased afterSlovakia entered the EU.

Hypothesis 2: Competition intensified.Competition from new/potential entrants pushes the mark-up for local monopolies to competitive levels.

Hypothesis 3: Spatial spill-overs decreased.As market coverage improves, firms struggle to attract con-sumers from neighboring areas. The importance of neigh-borhood profitability diminishes and service provision con-verges to a national average across all regions.


TRANSITION ECONOMIES: ENTRY AND COMPETITION

“Transition economies make a particularly good laboratory forunderstanding the dynamics of market evolution.” Estrin, 2002

Entry and competition in industries from the services sector:I Market size and mark-ups (Bresnahan, et al. 1991,

Asplund, et al. 1999)I Entry and regulation (Schaumanns, et al. 2006, Noailly, et

al. 2010)

Contribution:I first empirical evidence on (changes of) market conduct

in a transition economyI specific attention to potential spill-over effects between

regional markets and the spatial dimension of competition.


DATASET

Data is available on:I firm counts for competitive retail industries: automobile

dealers, electricians, plumbers, restaurants, and regulatedprofessional industries: pharmacies, doctors and dentists(Register of Economic Subjects in Slovakia)

I the total population per-town (excl. towns with apopulation above 15 000)

I average wage, unemployment rate (Regional StatisticsDatabase)

I share of young individuals in the populationI share of seniors in the population (Urban and Municipal

Statistics)for 2843 towns in Slovakia in 1995, 2858 towns in 2001, 2926towns in 2010.


NUMBER OF ELECTRICIANS PER TOWN, 1995

0

1

2

3

4

5

6

7+



0

1

2

3

4

5

6

7+



0

1

2

3

4

5

6

7+


ENTRY THRESHOLD ANALYSISBresnahan and Reiss (1991): on markets with homogeneous firmswith constant marginal costs and representative consumers, to-tal variable profits (VN) decrease with entry only if prices de-crease: ( proof )

∂VN

∂N=∂P∂N

Q(1 + Lε) =∂P∂N

Q(1− 1N

)

The per-firm break-even market size (threshold population) isproportional to the relationship between fixed costs and totalper-capita profits:

πN =VNSBE

N− f = 0

sBEN =

SBE

N=

fVN

ETRN =sBE

N

sBEN−1

=VN−1

VN


AN ORDERED PROBIT MODEL OF FIRM ENTRY

Schaumans and Verboven (2011): per-firm profits on a marketwith N firms are equal to:

πN =VNS

N− f = vNS− f

Free entry condition:y = N if πN+1 < 0 ≤ πN

y = N if vN+1S− f < 0 ≤ vNS− f

y = N if ln vN+1f + lnS < 0 ≤ ln vN

f + lnS

y observed number of firmsπN per-firm profits in the presence of N firms on market ivN variable profits per-capita (mark-up)S population


ESTIMATING FIXED COST COVERAGE PER CAPITA

We estimate the logarithm of the ratio of the per-capita profitsand the fixed costs using data on market characteristics:

lnvN

f= Xβ − θN + ε

X market characteristics, which determine the total producer rent(wages, unemployment rates, % young and elderly)

θN fixed effect for N firms, which reduces the profitability

The model is thus:

y = N, if θN ≤ y∗ < θN+1

y∗ = Xβ + lnS + ε

Implication: Market profitability is determined solely by localmarket characteristics.


ACCOUNTING FOR REGIONAL EFFECTS (SAR OP)

Local markets in Slovakia are closely distributed with a highprobability of purchase outside town boundaries:

y = N if θN < y∗ < θN+1

y∗ = ρWy∗ + Xβ + lnS + ε, where ε ∼ N(0, 1)

wij =

1/dist2

ij if distij ≤ 30km0 otherwise

where distij is the distance between towns i and j.

y∗ ∼ TMVN(µ,Ω)

µ = (I − ρW)−1(Xβ + lnS)

Ω = [(I − ρW)′(I − ρW)]−1


INTERPRETATION OF ρThe conditional distribution of ρ is equal to:

p(ρ|β, y∗) ∝ |In−ρW|exp(−12

[y∗−ρWy∗−Xβ−lnS]′[y∗−ρWy∗−Xβ−lnS])

Wy∗ increases if:I Firm density increases, as truncation implies that

y∗N < y∗N+1 → ρ measures competitive effects.

y∗ ∼ TMVN(µ,Ω)

I If market profitability increases without a change in thenumber of firms→ ρ measures demand effects.

µ = (I − ρW)−1(Xβ + lnS)

ρ measures the expectation of entrants regarding the net effectof neighborhood market conditions.


INFORMATION VALUE OF BREAK-EVEN POPULATION

SBEN =

fvN

= eθN−Xβ−ρWy∗ (1)

The break-even population depends on:I Per-capita profitability relative to fixed costs (Xβ) without

competition: the higher per-capita profitability is, thesmaller the population necessary for a new firm tobreak-even

I Competitive pressure (θN): the higher the competitivepressure to push down mark-ups, the larger thepopulation necessary for a new firm to break-even

I Spill-overs from neighboring towns (ρ): if ρ is positivebeing in a profitable neighborhood is likely to lead to extrademand, if it is negative, it implies stronger competition.


BREAK-EVEN POPULATION AND ENTRY BARRIERS

Hypothesis 1: Entry barriers have been lowered.

If there is only one firm on the market, the difficulty of entrywill not depend on competitors and SBE

1 measures per-capitaprofitability relative to fixed costs:

SBE1 =

fv1

=eθ1

eXβ

SBE1(t−1)

SBE1(t)

= 1 → no change in the entry barriers for the first entrant> 1 → decrease in the entry barriers for the first entrant


ENTRY BARRIERS FOR RETAIL COMPETITIVE

INDUSTRIES VS. REGULATED PROFESSIONS

1995 2001 2010Automobile 924 821 502dealers (29) (23) (22)

Electricians 2808 1736 558(338) (101) (21)

Plumbers 2894 1219 670(535) (53) (24)

Restaurants 434 482 508(12) (12) (18)

1995 2001 2010Pharmacies 3845 5921 3335

(292) (634) (243)

Doctors 2360 1931 1532(114) (70) (49)

Dentists 3007 2334 2529(178) (92) (115)


ENTRY THRESHOLD RATIOS

Hypothesis 2: Competition intensified.

The relationship between consecutive thresholds measures theeffect of entry on pricing:

ETRN =sN

sN−1=

VN−1

VN

ETRN =eθN/N

eθN−1/N − 1= eθN−θN−1

N − 1N

ETRN

= 1 if prices do not change due to entry> 1 if entry decreases prices (effective competition)


ENTRY THRESHOLD RATIOS AND COMPETITION

Weaknesses of ETRN = sN+1/sN:I Unclear if lack of change signifies decreased competition

or a conversion to competitive levels.I Few observations with intermediate entry values.

Entry threshold ratios based on differences between monopolyand competitive prices:

ETR = ETR71 =

s7

sN=

V1

V7

ETR

= 1 a monopoly position does not increase mark-ups

compared to a competitive case (contestable markets)> 1 monopolists have market power


s7s1

s7s2

s7s3

s7s4

s7s5

s7s6

s7s7

1

1.5

2

2.5

3

19952001

2010

Automobile dealers

s7s1

s7s2

s7s3

s7s4

s7s5

s7s7

1

2

3

4

5

2001

2010

Plumbers

Automobile dealers Plumbers

1995 2001 2010 1995 2001 2010s7/s1 2.38*** 2.19*** 1.84*** 9.93*** 3.75*** 2.98***

(0.08) (0.07) (0.08) (1.99) (0.19) (0.12)

ρ 0.2954*** 0.1946*** 0.202*** 0.5725*** 0.3832*** 0.3364***(0.0361) (0.0355) (0.0325) (0.0508) (0.0361) (0.0323)


NUMBER OF AUTOMOBILE DEALERS PER TOWN, 1995

0

1

2

3

4

5

6

7+


NUMBER OF AUTOMOBILE DEALERS PER TOWN, 2010

0

1

2

3

4

5

6

7+


NUMBER OF PLUMBERS PER TOWN, 1995

0

1

2

3

4

5

6

7+


NUMBER OF PLUMBERS PER TOWN, 2010

0

1

2

3

4

5

6

7+


s7s1

s7s2

s7s3

s7s4

s7s5

s7s6

s7s7

1

1.5

2

2.5

31995

20012010

Electricians

s7s1

s7s2

s7s3

s7s4

s7s5

s7s6

s7s7

1

1.5

2

2.5

3

199520012010

Restaurants

Electricians Restaurants

1995 2001 2010 1995 2001 2010s7/s1 2.75*** 2.37*** 2.10*** 2.45*** 2.19*** 2.13***

(0.35) (0.15) (0.09) (0.07) (0.06) (0.08)

ρ 0.2687*** 0.2205*** 0.2967*** 0.0877*** 0.109*** 0.2742***(0.0655) (0.0452) (0.0315) (0.033) (0.0328) (0.032)


NUMBER OF RESTAURANTS PER TOWN, 1995

0

1

2

3

4

5

6

7+


NUMBER OF RESTAURANTS PER TOWN, 2010

0

1

2

3

4

5

6

7+


s7s1

s7s2

s7s3

s7s4

s7s5

s7s6

s7s7

0.5

1

1.5

2

199520012010

Doctors

s7s1

s7s2

s7s3

s7s4

s7s5

s7s6

s7s7

0.5

1

1.5

2

199520012010

Dentists

Doctors Dentists

1995 2001 2010 1995 2001 2010s7/s1 0.99 0.72*** 0.73*** 1.27*** 1.18*** 1.01

(0.05) (0.03) (0.02) (0.08) (0.05) (0.05)

ρ -0.4082*** -0.4618*** -0.2827*** -0.3623*** -0.4201*** -0.2747***(0.0571) (0.0428) (0.0439) (0.0612) (0.0459) (0.0501)


NUMBER OF DOCTORS PER TOWN, 1995

0

1

2

3

4

5

6

7+


NUMBER OF DOCTORS PER TOWN, 2010

0

1

2

3

4

5

6

7+


NUMBER OF DENTISTS PER TOWN, 1995

0

1

2

3

4

5

6

7+


NUMBER OF DENTISTS PER TOWN, 2010

0

1

2

3

4

5

6

7+


s4s1

s4s2

s4s3

s4s4

0.5

1

1.5

2

19952001

2010

Pharmacies

Pharmacies

1995 2001 2010s7/s1 2.32*** 1.83*** 1.19**

(0.19) (0.21) (0.09)

ρ -0.3573*** -0.332*** -0.161**(0.0631) (0.071) (0.0625)


NUMBER OF PHARMACIES PER TOWN, 1995

0

1

2

3

4

5

6

7+


NUMBER OF PHARMACIES PER TOWN, 2010

0

1

2

3

4

5

6

7+


SUMMARY

1. Did entry barriers decrease?I Competitive industries: strong decreaseI Regulated industries: insignificant decrease

2. Did new entrants result in lower mark-ups?I Cross-sectionally: new entrant decreased mark-ups

significantly for all industries but doctorsI Across periods: market structure differences loose their

significance

3. What were the regional characteristics of firm entry; didfirm interactions across borders change?

I Cross-sectionally: spatial interactions have a significanteffect for all industries

I Across periods: regional differences in coverage decreasedfor all industries but electricians and restaurants


FURTHER RESEARCH

A number of extensions are possible for this research area:I Disentangle competitive regional effects from

demand-side spill-overs: spatial generalized orderedresponse models (Castro et al., 2012)

I Discriminate between entry and exit dynamics (Carree etal., 2007)

I Analyze industry complementarity (Schaumanns, 2006)

I Compare across ETRs across countries with differentlegislature.

I Endogenize market boundaries.


THANK YOU FOR YOURATTENTION

CHANGE IN VN , PROOF

VN = (P(N) − c)q(PN,N)N = (P(N) − c)Qq(PN,N),N

∂VN

∂N=∂P∂N

qN + (P− c)∂q∂P

∂P∂N

qNPqNP

N + (P− c)∂q∂N

N + (P− c)q

∂VN

∂N=∂P∂N

qN + (P− c)∂q∂P

∂P∂N

qNPqNP

N

∂VN

∂N=∂P∂N

Q(1 +(P− c)

P∂Q∂P

PQ

)

∂VN

∂N=∂P∂N

Q(1 + Lε) =∂P∂N

Q(1− qQ

1εε)

∂VN

∂N=∂P∂N

Q(1− 1N

)

ET go home

Documents

Market Structure and Competition in Transition: Results ...€¦ · al. 2010) Contribution: I ﬁrst empirical evidence on (changes of) market conduct ... @P @N Q(1 + L") = @P @N