THE RIGHT STUFF? PRIOR LABOR MARKET EXPERIENCE AND ENTREPRENEURSHIP

Transcription

1 Paper to be presented at the 25th Celebration Conference 2008 on ENTREPRENEURSHIP AND INNOVATION - ORGANIZATIONS, INSTITUTIONS, SYSTEMS AND REGIONS Copenhagen, CBS, Denmark, June 17-20, 2008 THE RIGHT STUFF? PRIOR LABOR MARKET EXPERIENCE AND ENTREPRENEURSHIP Kari Kristinsson Aalborg University, Department of Business Studies karik@business.aau.dk Abstract: Prior labor market experience is argued to be an important motivator of would-be entrepreneurs. Yet, relatively little is known about the prior labor market states of those who turn to entrepreneurship. We use a large Danish linked employer-employee dataset to trace prior labor market states of individuals who transit into entrepreneurship. We find that transitions to entrepreneurship are rare and that prior entrepreneurial and medium firm managerial experiences increase the likelihood of individuals choosing entrepreneurship. We also find that non-managerial labor market experience is negatively related to the probability that employees transit into entrepreneurship. JEL - codes: M13, -, -

2 The Right Stuff? Prior Labor Market Experience and Entrepreneurship Preliminary version prepared for DRUID 2008 deadline - Please do not quote - Prior labor market experience is argued to be an important motivator of would-be entrepreneurs. Yet, relatively little is known about the prior labor market states of those who turn to entrepreneurship. We use a large Danish linked employer-employee dataset to trace prior labor market states of individuals who transit into entrepreneurship. We find that transitions to entrepreneurship are rare and that prior entrepreneurial and medium firm managerial experiences increase the likelihood of individuals choosing entrepreneurship. We also find that non-managerial labor market experience is negatively related to the probability that employees transit into entrepreneurship. JEL codes: M13, J24, N3 Keywords: Entrepreneurship, human capital, occupation choice, experience 1. Introduction The only source from which an entrepreneurs profits stem is his ability to anticipate better than other people the future demand of the consumers Ludwig von Mises 1 In economics prior labor market experience is argued to be an important motivator of new entrepreneurs (e.g. Lucas, 1978; Lazaer, 2004, 2005). Yet, due too data limitations, little is known about the nature of this labor market experience. Do certain labor market states, such as industry- occupational- or prior entrepreneurial work, increase the likelihood of an employee leaving his job for entrepreneurship? This paper uses a longitudinal nationwide database to examine the impact of several types of prior labor market states on entrepreneurship, thereby contributing to the growing literature on entrepreneur s human capital endowments and improving substantially on previous work. The data compromises of extensive information on individuals, such as their age, sex, education, wealth and a detailed labor market history. These individuals are then linked to firms, on which the dataset also contains basic information. We are thus able to 1 Human Action: A Treatise on Economics (Scholars Edition), p

3 distinguish between different types of labor market experience and paint a much more nuanced picture of entrepreneurs prior labor market experience than seen before. Prior studies have usually measured labor market experience as the individuals current age minus school-leaving age (Parker, 2004). However, there are some well known caveats to the use of age as a measure of experience, including not allowing for breaks in labor force participation and not distinguishing between different types of labor market experience. Thus besides having a large longitudinal sample, the strength of this dataset is that it allows us (1) to measure transitions to entrepreneurship and contrast against other types of labor market mobility, (2) to trace and characterize the types of labor market experience of entrepreneurs and other individuals in the dataset. The available literature identifies a several human capital attributes that are likely to have an effect on the transition to entrepreneurship. Various labor market experiences, especially prior experience in entrepreneurship, have been argued to affect the transition to entrepreneurship. Some authors have argued that the characteristics of the firms in which labor market experience is incurred is important. One such attribute is firm size. Size matters because especially small firms could serve as places of entrepreneurial learning. Employees in smaller firms often work closely with the firms managers and/or founders and could therefore be exposed to entrepreneurial learning; see e.g. Gompers et al. (2005) and the references therein. A contrasting view would be that employees of large bureaucratic firms are pushed into entrepreneurship because their employers have little patience for their entrepreneurial ideas. Managerial ability has also been a reoccurring theme in the entrepreneurship literature. Lucas (1978) develops a model in which individuals managerial ability is positively related to the individuals propensity for entrepreneurship. Jovanovic (1980) also assigns a positive role for managerial ability in entrepreneurial success, but assumes that individuals have not ex ante knowledge of their managerial ability. By investigating occupational choices in the Danish labor market from we explore the effect of prior labor market experience on the likelihood that an employee leaves his job for entrepreneurship. We find that different types of labor market experience have different effect on the transition to entrepreneurship, with prior entrepreneurial experience having the largest positive effect. In line with models developed by Lucas (1978) and Jovanovic (1982), managerial ability (albeit measured as managerial experience) has a positve effect on the transition to entrepreneurship. We also find the non-managerial labor 2

4 market experience has, for all firm sizes, a negative effect on the likelihood that employees transit to entrepreneurship. Surprisingly, our dataset reveals that medium firm labor market experience has more negative effect than both small and large firm experience. In sum, our findings are in line with the theory that managerial ability has a positive effect on the transition to entrepreneurship. We also reject the idea that employees of larger bureaucratic firms are pushed into entrepreneurship. The rest of the paper is organized as follows. Section two presents the theoretical framework and section three the related literature. Section four describes the data and definitions of entrepreneurship and human capital used in this paper. Section five puts forth the main results and section six concludes. 2. Theoretical Framework Similar to the theoretical framework on comparative advantage used by Evans and Leighton (1989), Gimeno et al. (1997) and Taylor (1999), we assume individuals choose their labor market state dependent on the expected utility of that choice. Paid employees are thus choosing between continuing with their current employment and switching to entrepreneurship. E (U E ) = f (a, k, r, D, X) E (U A ) = g (w, a, X) Where the expected utility from entrepreneurship, E (U E ), is a function of entrepreneurs ability a, available capital k, the interest rate r, the level of demand in the economy D and individual tastes and preferences X. Likewise the expected utility of alternative employment is a function of the wage w and X. In contrast to the Jovanovic (1982) model, where individuals ability is assumed to be unknown by both the individual and other agents, the comparative framework assumes that ability is signaled through general human capital endowments such as education and labor market experience. Thus the wage on offer for paid employment will depend on part on the individuals education and labor market experience. 3

5 We would thus expect an employee to change to entrepreneurship if the expected utility of staying employed falls below the expected utility of the entrepreneurial option minus the switching cost, i.e. the employee would choose entrepreneurship if: E (U A ) < E (U E ) C The conceptual strength of the comparative advantage framework is that it has wide ranging implications, e.g. given this framework it follows that employees might choose to switch to entrepreneurship, even though their wage is above the current market rate. They may thus choose transit into entrepreneurship because of their expectation that this might net more utility. However, the weakness of this framework is that all behavior is consistent with it as utility is not observed. As variables such as education and labor market experience will affect the income of the entrepreneur in both states, it is difficult to disentangle the separate effects. While the comparative advantage model cannot be tested directly it offers a framework for discussing possible explanatory variables and their effect on labor market state. 3. Related Literature Several authors have argued that prior labor market experience can positively influence the transition to entrepreneurship. Experienced individuals might have had more time to accumulate human capital and to identify unexhausted opportunities. Thus more experienced people might have gathered the human capital requirements for entrepreneurship. There might also exist a type of human capital that is both productive when working for others as well as in self-employment. This human capital might even be most effectively acquired by initially working for others (Lucas, 1978). Although prior experience could have a positive effect on the transition to entrepreneurship, the amount of experience a person has is also a factor of a persons age, and older individuals might be more risk averse and be less capable of working long hours often required for entrepreneurship. In most econometric investigations on human capital impact on entrepreneurship, labor market experience has been measured as the current age minus school-leaving age (Parker, 4

6 2004). These studies have mostly been done using cross-section data and have in general supported the idea of a significant positive relationship between experience (age) and selfemployment (e.g. Schuetze, 2000; Fairlie, 2002; Blanchflower et.al., 2001). A minority of these studies has however found insignificant effects (e.g. Taylor, 1996; Evans and Leighton, 1989; Evans and Jovanovic, 1989). The use of age as a proxy for experience is usually done because of data limitations, as there are some well known caveats to the use of age as a measure of experience. First, this measure takes no account of breaks in labor force participation. Second, there is a chance of cohort effects being mixed up with experience effects (Parker, 2004). Third, by using age as a proxy for labor market experience, no distinction is made between different types of labor- or occupational experience. It is therefore necessary to distinguish between age and experience when trying to explain the transition to entrepreneurship. While both age and experience are usually found to have a positive relationship with entrepreneurship, it is important to note that experience is a more accurate proxy for human capital endowments. Some studies have tried to distinguish between different types of labor market experience. Using a sample of white male Americans, Evans and Leighton (1989) find a positive and significant impact of previous self-employment experience on the probability of entering self-employment, but no impact of previous employment experience. This result is consistent with a model by Jovanovic (1982), where entrepreneurs have imperfect information about their innate abilities which they can only learn about by gaining some experience in entrepreneurship. Lin et.al. (2000), working on Canadian data, find that both prior employment experience and prior self-employment experience are associated with a higher likelihood of entering self-employment. Using US data, Boden (1996) found a greater propensity of employees of small firms (defined as less than 100 employees) to become entrepreneurs ceteris paribus than employees of large firms. Managerial ability, as a specific type of human capital, has been recognized in the literature as having a possible role in the transition to entrepreneurship. Lucas (1978) develops a model in which individuals managerial ability is positively related to the individuals propensity for entrepreneurship. Jovanovic (1980) also assigns a positive role for managerial ability in entrepreneurial success, but assumes that individuals have not ex ante knowledge of their managerial ability. The empirical side on role of managerial ability for entrepreneurship has however been mostly neglected in economics. However studies by 5

7 de Wit and van Winden (1989) and de Wit (1993) try to test Lucas (1978) hypothesis that there is a positive link between ability and entrepreneurship. They use an IQ-score and a scholastic test score in their estimating equation, with the IQ test being significantly positive but the scholastic test being insignificant. Given the detail of the dataset, this paper explores several novel measurements of labor market experience. These include prior entrepreneurship experience as well as employee and managerial labor market experience, which have both been put forth as possible factors in determining the transition to entrepreneurship. 4. Data and Definitions In order to investigate the impact of human capital on entrepreneurship, we rely on a comprehensive dataset of the entire Danish economy. The dataset combines very detailed information on all establishments and all individuals gathered from the official registers of the Danish government. The dataset goes by the name Integreret Database for Arbejdsmarkedsforskning (IDA) which can be translated to Integrated Database for Labor Market Research, and is maintained by Statistics Denmark. IDA is particularly suitable for economic research. First, it contains extensive information on the characteristics of individuals, e.g. age, sex, level of education, work experience, occupation, wages and other income. Second, individuals are linked with establishments and employers, on which the dataset also contains basic information. Third, the dataset is longitudinal and has been updated annually since 1980, which makes it possible to follow individuals and firms from one year to another. The data lists individuals highest completed education as well as their employment relation to specific firms. Each type of education in the Danish education system is represented and connected to individual Danes through personal ID-numbers. Sample Selection To test for the impact of human capital endowments on entrepreneurship, we aimed at constructing a dataset where (a) information on individuals human capital endowments could be collected; and (b) their transition into entrepreneurship could be tracked. Ideally, one would like to follow all individuals over their lifecycle. In this paper, however, we constructed the sample in the following way. Starting with IDA dataset we constructed a 6

8 sample for the current analysis. Specifically, the sample is limited to those who fall within the following criteria. (1) Were between the ages of 30 and 60 in This is necessary, so that the background information collected is from individuals who were at least 18 in The upper limit is however added so not to confuse this study with the studies of entrepreneurship in old age. (2) Individuals who have had no spells of unemployment since (3) Are Danish nationals. From this sample we draw a random sample of individuals in the year 1992, which we then use for estimation. Even though we use a random sample, the sample is not drawn from the all individuals in Denmark. Therefore it is unlikely that data in this paper is representative for the universe of individuals. The results of this paper are therefore only representative of the reported individuals. Dependent Variable Entrepreneurship. Our key variable is the labor market state of the individuals in the sample. Using information from IDA, all individuals in the sample are marked either as employees or entrepreneurs. IDA provides How shall we define individuals as entrepreneurs? As there is little consensus about what precisely makes someone an entrepreneur, this is a difficult question. There is in fact a large literature with conflicting views on this issue. Labor economists often equate entrepreneurs with self-employment. Others however, think this definition is too broad, arguing that only those that coordinate resources (often meaning employees) are really entrepreneurs. IDA supplies a detailed labor force attachment classification scheme. Included in the classification are, among others, categories such as unemployed, in school, not in labor force, employment with established firm and self-employment. This classification scheme includes two categories for self-employment, one for those that are self-employed with no employees and another for those that are unincorporated proprietors with employees. For our purposes we treat entry into either of these categories as a transition to entrepreneurship. This treatment is consistent with the notion that entrepreneurship is the coordination of resources. Explanatory Variables EntExp. Prior experience in entrepreneurship, defined as our dependent variable. 7

9 ManExp. IDA uses an several occupational categories to classify individuals. One of these occupational categories is managerial occupation. We thus consider individuals that in this category as having acquired managerial experience. Small, Medium and Large_firm_exp. Our primary explanatory variables are derived from individuals labor market experience. As IDA is a linked employer-employee dataset basic information about the firms that individuals have worked for is available. Using this information we determine the size of the firm through the number of employees. Firms are thus divided into small, medium and large firms. Age. The individuals age Age squared. Salary. Descriptive Statistics Table 1 presents the descriptive statistics. Sampled individuals are between 30 and 60, which have had no spells of unemployment and are Danish nationals. The dataset counts job spells, with entrepreneurial spells representing 3% of the total. As found in other research entrepreneurs tend to be older, are more frequently male and have less salary Insert Table 1 here Empirical Findings Regression Results The results of the GEE and Fixed Effect Conditional Logit Analysis are summarized in table 2. In all, four models were tested. The first model presents the conditional logit analysis without controls. The second model adds controls. As the fixed effect conditional logit analysis cannot handle variables that are constant over time, we only control for salary, age and age squared. Overall the standard error for the GEE estimation is considerably 8

10 lower than the one for fixed effect conditional logit, we therefore rely on GEE for our results. The third model is a GEE estimation without controls. The results show several significant coefficients. An undergraduate degree positively affects the transition to entrepreneurship, while a graduate degree has a negative coefficient. For labor market experience the first GEE estimation shows a significant negative effect on the transition to entrepreneurship on all accounts except prior entrepreneurship experience. Managerial experience is significantly positive for medium firms while positive but not significant for both large and small firms. The fourth model is a GEE estimation that controls for gender, salary and age. The results from the first model hold on most accounts. However, small firm managerial experience becomes positive but not significant Insert Table 2 here Conclusion Economists still have a lot to learn about how the different human capital endowments affect the transition to entrepreneurship. In this paper, we investigate whether different types of labor market experience, have different effect on the transition to entrepreneurship. Until now most research has, due to data limitations, aggregated across different types of labor market experience. However, several theoretical models have indicated that managerial ability and prior labor market experience affect the transition to entrepreneurship (e.g. Lucas, 1978; Jovanovic, 1982) This paper provides strong evidence that by aggregating across different types of human capital endowments, researcher have lost many of the nuances of the effect of human capital endowments entrepreneurship. We find that undergraduate degrees have a significant positive effect on the becoming an entrepreneur. However, graduate degrees have a significant negative impact. Verifying earlier research, we find that prior entrepreneurship 9

11 experience has a positive impact on the transition to entrepreneurship. Using a novel measure for managerial ability we also find that managerial experience in small and large firms has a positive but not significant impact on becoming an entrepreneur. However, medium firm managerial experience has a significant positive effect. 10

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15 Table 1: Descriptive Statistics Variable Employees No. Of observation Mean Std Dev Entrepreneurs No. Of observation Mean Std Dev Education Undergrad Grad Labour Market Exp. Entexp sfexp mfexp lfexp Managerial Exp. SfManExp mfmanexp lfmanexp Controls female age age Salary

16 Table 2: Transition to Entrepreneurship. Panel Estimates Model 1: Fixed Effect Conditional Logit Model 2: Fixed Effect Conditional Logit with Controls Model 3: GEE Estimation Model 3: GEE Estimation with controls N= Variables Coefficient Model 1 Standard Error Coefficient Model 2 Standard Error Coefficient Model 3 Standard Error Coefficient Model 4 Standard Error Intercept -3,547 0,045 *** -11,176 0,339 *** Individual Characteristics Education Undergraduate Degree 0,659 0,713 0,446 0,712 0,259 0,072 *** 0,312 0,076 *** Graduate Degree -0,559 0,568 0,184 0,572-0,103 0,032 *** -0,156 0,033 *** Labour Market Experience Entrepreneur Exp. -1,079 0,026 *** -1,176 0,027 *** 0,526 0,004 *** 0,556 0,004 *** Small Firm Exp. 0,593 0,049 *** 0,497 0,053 *** -0,06 0,004 *** -0,06 0,005 *** Medium Firm Exp. 0,329 0,056 *** 0,252 0,06 *** -0,136 0,005 *** -0,136 0,006 *** Large Firm Exp. 0,237 0,057 *** 0,149 0,061 ** -0,072 0,004 *** -0,061 0,006 *** Small Firm Managerial Exp. -0,188 0,071 *** -0,239 0,072 *** -0,061 0,004 *** 0,024 0,017 Medium Firm Managerial Exp. 0,034 0,133 *** 0,334 0,138 ** 0,079 0,03 *** 0,109 0,031 *** Large Firm Managerial Exp 0,596 0,311 * 0,385 0,314-0,042 0,046 0,018 0,046 Controls Income -0,194 0,533 *** 0 0 *** Age -0,798 0,849 0,402 0,016 *** Age squared 0,009 0,0005 *** -0,005 0,0002 *** Female -0,348 0,029 *** Industry 15