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FACTORS THAT IMPACT FIRM’S PROFITABILITY: EVIDENCE FROM
EUROPEAN BIOTECH
STUDENT: MARIJA NIKOLIKJ
MSC. IN BUSINESS ADMINISTRATION, MAJOR IN BUSINESS DEVELOPMENT AND PROMOTION
MASTER THESIS DEFENCE
June 21st, 2016
2OUTLINE
BACKGROUND
BIOTECH INDUSTRY
RESEARCH QUESTION AND HYPOTHESIS METHODOLOGY
RESULTS
DISCUSSION
CONCLUSION
QUESTIONS
LITERATURE REVIEW
LIMITATIONS
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3BACKGROUND
STATEMENT OF THE PROBLEM
• To explore the existing findings and conduct an econometric research in order to draw a conclusion on the factors that influence profitability in the European biotech companies;
• To bridge the gap between the academic and the industry research on this topic.
There is a very limited amount of research, on factors that influence profitability, in particular in the European Biotech sector;
PURPOSE OF THIS STUDY
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MAIN CHARACTERISTICS OF BIOTECH INDUSTRY
BIOTECH INDUSTRY
Highly regulated;
Knowledge intensive;
Long time frame to develop a new product;
Highly capital-intensive;
Ethical clearing is essential for human /animal testing;Intelectual property essential for success;Collaboration and alliences with external partners (Universities, other biotech companies etc.);Capital raising is essential.
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Literature Review
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No. Authors Positive Relationship Europe Biotech
Industry1 Branch (1974)2 Chiou and Lee (2011)3 Coad and Rao (2006)
4 Cozza, Malerba, Mancusi, Perani and Vezzuli (2012)
5 Del Monte and Papagni (2002)6 Geroski, Machin and Van Reenen (1993)7 Grabowski, Vernon and DiMasi (2002)8 Hall and Bagchi-Sen (2002)
9 Jefferson, Huanmao, Xiaojing and Xiaoyun (2006)
10 Mank and Nystrom (2001)11 Morbey and Reitner (1990)12 Yang, Chiao and Kuo (2010)13 Nunes and Serrasquiero (2014)
LITERATURE REVIEW
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Hypothesis and
Research Question
8HYPOTHESIS AND RESEARCH QUESITON
Hypothesis 1a: R&D expenses have a positive effect on firm`s profitability in the biotech industry.
? Does firm`s profitability in the biotech sector increase with more investment in the R&D?
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METHODOLOGY
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Defining variables, based on academic literature
Data collection
from ORBIS (Bureau Van Dijk)
Data analysis in
SPSS
Defining the
econometric model
Data re-adjustment
in Excel (variables,
years, winsorising
)
Results interpretati
on
STEPS OF CONDUCTING THE RESEARCH
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11DEFINING VARIABLES
Profitability PROF i,t= EBIT i,t / Total Assets i,t (Pattitoni, Petracci and Spisni, 2014, p. 6);
R&D ExpensesR&D EXP i,t= R&D expenses i,t / Total Assets i,t (Nunes, Serrasqueiro, 2014, p.53);
Outsourcing dummy variable: „1” if the company outsources and “0” if it does not outsource (Ohnemus, 2007, p.9)
Firm’s Size
SIZE i,t=log Sales i,t (Nunes, Serrasqueiro, 2014, p.53);
12DEFINING VARIABLES (cont.)
Firm’s AgeAGE i,t= log of number of years of firm`s existence (Nunes, Serrasqueiro, 2014, p.53);
Firm’s Liquidity
LIQ i,t = Total Current Assets i,t / Total Current Liabilities i,t (Nunes, Serrasqueiro, 2014, p.53);
Long Term Debt
LLEV i,t=Long-term debt i,t / Total Assets i,t (Nunes, Serrasqueiro, 2014, p.53).
13DEFINING VARIABLES (cont.)
Country of firm’s origin
UK is the reference country; Countries are coded as follows:
COUNTRY= coded as “1” if country is France, if other country “0”; coded as “1” if country is Germany, if other country “0”; coded as “1” if country is Sweden, if other country “0”;
coded as “1” if country is Switzerland, if other country “0”; coded as “0” if country is UK, if other country “0”; (Field, 2013, p.420)
14METHODOLOGY
THE ECONOMETRIC MODEL
15ORBIS DATA COLLECTION
12COUNTRIES BY NO.
OF PIPELINES
1. UK2. SWITZERLAND 3. GERMANY4. FRANCE5. SWEDEN
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NO. OF COMPANIES
BY COUNTRY
REPRES. IN THE
SAMPLE
12124
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8229
ORBIS DATA COLLECTION
DATA SET OF COMPANIES OBTAINED AFTER INSERTING ALL CRITERIAS
PRELIMINARY DATA SETTotal number of companies obtained, based on geographic region and industry classification (NACE Rev.2)
8229
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INITIAL NO. OF OBSERVATIONS 300
FINAL NO. OF OBSERVATIONS AFTER DEDUCTING OBERVATIONS WITH MISSING VALUES 17
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Period for data collection : Year 2006-2015
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DATA ANALYSIS
18ASSUMPTIONS OF MULTIPLE LINEAR REGRESSION
LINEARITYWeak positive and non-linear relationship between Profitability and R&D Expenses;
MULTICOLLINEARITYPearson Correlations test shows values below 0.9, in addition VIF values are below 10;
INDEPENDENCE OF ERRORSDurbin-Watson is 2.191 and falls in the range of 1 and 3;
19ASSUMPTIONS OF MULTIPLE LINEAR REGRESSION (cont.)
ASSUMPTION OF HOMOSCEDASTICITY AND LINEARITY OF ERRORSScatterplot shows the data funnel out which is a sign of heteroscedasticity, showing an increasing variance across the residuals;ASSUMPTION OF NORMALLY DISTRIBUTED ERRORSHistogram shows a normal distribution of residuals, with a slight level of leptokurtosis; Central Limit Theorem;
UNUSUAL CASES
Cook’s distance is .177, below 1.
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RESULTS
21REGRESSION RESULTS
MODEL SUMMARY
• R 2 =.471, adj. R2=.446, F=18.590, p=.000. • 47.1% of the variability in PROFi,t, is explained by the
independent variables in the model;• Model is a moderate predictor of the variability in the
dependent variable;• Adjusted R-square of .446, shows that if the model was
derived from a population instead of a sample it would account for approximately 2.5 % less variation in the outcome.
22REGRESSION RESULTS (cont.)
ANOVA
• Model predicted PROFi,t, F (8,167) =18.590, p = 0.000;
• The model is a significant fit of the data overall.
23REGRESSION RESULTS (cont.)
B Beta t Sig. (Constant) -.587 -6.995 .000 RDEXP i,t .115 .067 1.124 .263 SIZE i,t .140 .644 9.677 .000 AGE i,t -.098 -.148 -2.500 .013 LIQ i,t .004 .063 1.031 .304 LLEV i,t -.425 -.256 -4.361 .000 FranceDummy -.056 -.069 -1.087 .279 GermanyDummy .170 .187 3.050 .003 SwedenDummy .098 .143 2.203 .029
PROFi,t=-0.587 + (0.115 RDEXPi,t) + (0.140SIZEi,t) + (- 0.098 AGEi,t)+ (0.04 LIQi,t) + (-0.425 LLEVi,t) + (- 0.56 FranceDummy) + (0.170 GermanyDummy) + (.098 SwedenDummy).
24REGRESSION RESULTS (cont.)
• Not enough evidence that R&D expences have positive impact on firm’s profitability;
• Based on regression results,I I fail to reject null hypothesis;
• The answer to the research question is as follows: “Higher level of R&D investment does not provide a statistically significant relationship with the higher level of profitability”.
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LIMITATIONS
26LIMITATIONS
• NACE Rev.2 industry classification;• ORBIS database does not provide information for
the outsourcing activities;• Missing values account for 40% of the total
number of observations:• Assumption of linearity is breached;• Assumption of homoscedasticity is breached ,
could be an indication of possible systematic relationship between the errors in the results;
• Time horizon of 10 years, does not capture the time frame to develop a product in the biotech industry;
27LIMITATIONS (cont.)
• innovators position, market awareness, niche operations, internationalization (Qian and Li, 2003);
• market orientation (Appiah-adu and Ranchold, 1998);
• firm`s growth, opportunity cost of capital, shareholders commitment level (Pattitoni, Petracci and Spisni, 2015);
• financial risk (Golec and Vernon, 2007);• firm`s market share, gearing ratio (Goddard,
Tavakoli and Wilson, 2005);• union density, import penetration, industry
concentration, real wage inflation (McDonald, 1999) ;
• organizational factors (Hansen and Wernerfelt, 1989).
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DISCUSSION
29DISCUSSION AND RECCOMENDATIONS
Recommendation: Future research should incorporate productivity level as part of the model;
Relationship between Profitability and R&D Expenses depends on the productivity level (Morbey and Reitner (1990, p.14);
R&D expenses are not always good proxy for engagement in R&D and innovation (Cozza et al., 2012, p.1968);
Recommendation: Future research should use at least one proxy for R&D expenses (possible combination of qualitative and quatitative research;
30DISCUSSION AND RECCOMENDATIONS (cont.)
Recommendation: Future research should incorporate a use of dynamic estimators;
OLS regressions do no tell the whole story in the relationship between two or more variables (Nunes and Serrasqueiro (2014, p.52);
Using R&D expenses of the current year, provides little association with the current year profitability performance Del Monte and Papagni (2003, p.1011);
Recommendation: Future research should use a lagged R&D variables in order to better associate the relationship between R&D expenses and profitability;
31DISCUSSION AND RECCOMENDATIONS (cont.)
The model modestly predicted the dependent variable PROF i,t, meaning that a large part of the variation in the model remains unexplained.
Recommendation: Future research should use additional variables to better explain the dependent variable PROFi,t;
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CONCLUSION
33CONCLUSION
The purpose of this research is to provide an evidence of the impact of R&D expenses on firm`s profitability in the European biotech industry;
Hypothesis: R&D expenses have positive impact on firm`s profitability, based on the majority of previous academic findings;
This research uses multiple linear regression to measure the impact of R&D expenses on firm`s profitability, at the same time controlling for outsourcing, firm`s size, age, liquidity, long-term leverage and country of origin;
34CONCLUSION (cont.)
The results of this research show that there is not enough evidence that R&D expenses contribute to higher level of profitability. This finding is contrary previously stated findings in a number of studies;
In order to better explain the relationship between the R&D and firms profitability, future studies should incorporate both qualitative and quantitative techniques and a use of dynamic estimators, as well as additional measures for R&D in companies.
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QUESTIONS?
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THANK YOU
