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What we want to know about entrepreneurship and the data we need for that. Entrepreneurship?. Creation of new businesses Development and growth. Why do we care?. Policy makers - interest in performance Innovation, employment mostly aggregate performance Heterogeneity across businesses
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What we want to know about entrepreneurship and the data we need for that
Entrepreneurship? • Creation of new businesses • Development and growth
Why do we care? • Policy makers - interest in performance • Innovation, employment • mostly aggregate performance • Heterogeneity across businesses • impacts differ • responses to shocks differ • Understand micro-determinants of performance • From individual to aggregate performance
What we want to know • Where do new businesses come from? • Why do people go into entrepreneurship? • What do new businesses do? • What separates those that succeed from those that do not? • What is success? • What happens to those that do not succeed? • What can be done to improve their chances of success? Is this desirable?
What we need • Longitudinal data • entrepreneur • venture • Key agents in support activities (e.g. finance, R&D) • Sources with data on inputs and outputs • Control groups • (Researchers access to micro-data)
Longitudinal data • Where do new businesses come from? • What separates those that succeed from those that do not? • What happens to those that leave entrepreneurship?
Linking inputs and outputs • What separates businesses that succeed from those that do not? • Data sets must contain data on inputs and outputs • Same dataset with data on determinants and performance for the same businesses
Creation of new businesses • Different stages of creation of new ventures • From the idea to the IPO • Individual entrepreneurs • Extended PESD approach • Partnerships • New businesses as result of disagreements? • Intrapreneurship • How companies reward new ideas • Practices that lead to new business • Incubators • Exiting businesses and spin offs
Performance and determinants • Performance - What is success? • Survival, employment, growth • Profit, value added, innovation • Own satisfaction • Ex-ante and ex-post • Example – exit can be associated with success • Sale / closing of existing business with a profit. • Serial entrepreneurs • Wages after entrepreneurial experience
Determinants • History • What the person/venture did • Avoid recall bias • Preferences • define success ex-ante • Actions (e.g. who do they hire) • Institutions (e.g. environment) • Public policies (e.g. public support?)
Motivations - why go into entrepreneurship • Opportunity vs. necessity • Goals • define success (ex-ante) • Preferences • Risk profile, preference for skewness • Loss aversion • Perceptions • Self confidence, • how good do you think you are compared to others • Optimism • what is the probability that your business succeeds
Institutions • European wide data • Different countries, different institutions • Need comparable (?) data • legal definitions • liability, etc. • Providers • Official Statistics • Commercial databases (e.g. Amadeus)
Sources • Official statistics • micro-data • matched data • Own surveys (?) • Experiments • Correlation vs. causality • Controlled conditions • Exogenous variation • Randomization
Data issues • Lab experiments • Convenient samples • Field experiments • Realistic samples • Policy evaluation • Odd (?) questions in surveys • Hypothetical (behaviour) • Exogenous data • Past – youth, etc.