DISCUSSION PAPER SERIES

IZA DP No. 940

What Makes an Entrepreneur and Does It Pay? Native Men, Turks, and Other Migrants in Germany
Amelie Constant Yochanan Shachmurove Klaus F. Zimmermann November 2003
Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor

Amelie Constant

University of Pennsylvania and IZA Bonn

Yochanan Shachmurove

City University of New York and University of Pennsylvania

Klaus F. Zimmermann

IZA Bonn, University of Bonn and DIW Berlin
Discussion Paper No. 940 November 2003
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IZA Discussion Paper No. 940 November 2003
ABSTRACT What Makes an Entrepreneur and Does It Pay? Native Men, Turks, and Other Migrants in Germany
This paper focuses on the entrepreneurial endeavors of immigrants and natives in Germany. We pay closer attention to Turks, since they are the largest immigrant group with a strong entrepreneurial tradition, and the self-employed Turks in Germany represent about 70% of all Turkish entrepreneurs in the European Union. We identify the characteristics of the selfemployed individuals and understand their underlying drive into self-employment. At the same time we investigate how immigrant entrepreneurs fare in the labor market compared to natives. Employing data from the German Socioeconomic Panel 2000 release we find that the probability of self-employment increases significantly with age for all groups albeit at a decreasing rate. Among immigrants, Turks are twice as likely to choose self-employment as any other immigrant group. The age-earnings profiles of self-employed German and immigrant men are concave and surprisingly similarly shaped. While for self-employed German men hours of work and Treiman prestige scale scores increase their earnings, for self-employed immigrant men it is the longevity of the business that makes a difference. Everything else equal, the earnings of self-employed Turks are no different than the earnings of the self-employed Greeks, Italians, Spaniards, ex-Yugoslavs, Polish or other East Europeans, including those immigrants who have become German citizens.

JEL Classification: Keywords:

J23, M13, J24, J61, J31

entrepreneurship, self-employment, occupational choice, immigrants, wage differentials
Corresponding author: Klaus F. Zimmermann IZA and Bonn University P.O. Box Bonn Germany Tel.: +Fax: +Email: Zimmermann@iza.org
An earlier version of this paper was presented at the Middle Eastern Economics Association (MEEA) session of the Allied Social Science Association (ASSA) 2003 meeting in Washington, DC. We thank conference participants for many useful comments.
1. Introduction Entrepreneurship has been enmeshed in the American culture and is the epitome of the American dream for natives and immigrants alike. Business ownership and selfemployment, as an effective form of entrepreneurship, may be a risky venture but it has an intrinsic appeal by offering individuals the sense of independence, of higher self-worth, and life satisfaction. Entrepreneurship not only injects new dynamism into an economy but it is also of great importance for the economic prosperity and the future economic development of a country. Entrepreneurship is also a significant element in combating unemployment and welfare drain through job creation, at the very least for the selfemployed themselves. Small entrepreneurs, in particular, have contributed in the creation of revolutionary businesses and they account for the majority of the employed workers. Although entrepreneurship flourishes in the US and other immigrants countries, for any ethnic group, entrepreneurial activities in Germany are comparatively very low. Recently, nascent enterprises show that there is a growing business culture in Germany, and they have attracted the governments attention to ensure their boost. The conjecture of the neoclassical human capital theory is that immigrants are a self-selected group of rational individuals who are willing to undertake risks in order to maximize their lifetime earnings and better their lives. They are characterized by a strong incentive to invest in human capital and have the inner drive to succeed in the host countrys labor market. By virtue of their willingness to assume the risk of migration (both pecuniary and psychic) and undertake this new and often risky venture they become the first entrepreneurs1. Put differently, immigrants as risk takers, are more dynamic and
By definition, an entrepreneur is an individual who organizes, operates, and assumes the risks of a business venture.

inherently more prone to becoming self-employed than any other group. Self-employed individuals are working hard to fulfill their dreams, and in the process they create new jobs and opportunities. On the other hand, impediments to good jobs and to upward occupational mobility as well as unemployment and discrimination in the labor market may impel immigrants to undertake the self-employment avenue. As the literature has shown, entrepreneurship may be the only avenue for their socioeconomic advancement. While the prevalence of self-employment among both immigrants and natives in the labor market has been researched and documented by many studies in the US, research on entrepreneurship and especially immigrant entrepreneurship in Europe, and Germany in particular, has been somewhat scant. Recent surveys on the rising literature on selfemployment in a comparative setting investigating research on Europe, the US and other immigration countries include Le (1999), Blanchflower, Oswald and Stutzer (2001), Audretsch (2002), and Audretsch, Thurik, Verheul and Wennekers (2002). They identify the role of managerial and other individual abilities, family background, occupational status, financial constraints, the nature of work, and ethnic enclaves, among other factors as relevant determinants of self-employment. Blanchflower, Oswald and Stutzer (2001) also study latent entrepreneurship across nations and find that many people would like to be self-employed. However, this preference declines strongly with age and the probability of being self-employed is strongly increasing with age. Self-employed individuals seem to have a much higher job satisfaction than the employed. Interesting recent European studies on entrepreneurship include Taylor (2001) on the role of liquidity constraints in Britain, Pfeiffer and Reize (2000) on start-ups by previously unemployed workers in Germany and Wagner and Sternberg (2002) on the role
of regional differences in Germany. Empirical research on immigrant assimilation has typically found an entry wage disadvantage for immigrants, which narrows over time as immigrants assimilate in the host countrys labor market. The rate of convergence varies among the different immigrant groups. Borjass (1986) study on the self-employment experience of immigrants in the US shows that not only self-employed immigrants have higher annual incomes than salaried workers but they also have higher incomes than comparable self-employed natives. This is extended by Lofstrom (2002), who finds substantial differences between migrant workers and self-employed migrants in earnings and educational attainment. Entrepreneurs have a better education and earn more than other working migrants. However, education has a smaller impact on the self-employment probabilities of migrants compared to natives. The earnings of self-employed immigrants converge quickly to the earnings of the selfemployed natives. Evans and Leighton (1989) examine the self-employment decisions of US white men. They conclude that self-employment is roughly independent of age and total labor market experience and it is more likely to be undertaken with greater access to assets. Wage experience has been found to have a much smaller return in self-employment than in wage work while experience in business has a similar return in wage work as in selfemployment. Unemployed and low-paid workers are more likely to enter self-employment. Also people who perceive that their performance depends largely on their own actions are more likely to start their own businesses. In North America, immigrants have higher self-employment rates than natives (see Yuengert, 1995, for the US and Li, 2001, for Canada). Yuengert (1995) investigates the

determinants of these differences. He finds that immigrants from countries with larger selfemployment sectors have higher self-employment rates. Migrants in the US cluster more in high-tax states, and find greater opportunities for tax deductions and avoidance as entrepreneurs than as salaried workers. The study is not supportive to the ethnicity enclave hypothesis. Fairlie and Meyer (1996) point out that it is of substantial importance to account for the dramatic ethnic and racial differences in self-employment across the US population. These differences prevail even if one controls for broad combinations of groups such as Asians and Hispanics and the standard tool of regressors. They find that ethnic or racial groups that emigrate from countries with high self-employment rates do not have high selfemployment rates in the US. Their results also suggest that the more economically advanced groups have a higher propensity for self-employment than the more disadvantaged migrant groups. There is only scarce evidence about migrant entrepreneurs in Europe and especially in Germany. The findings by Clark and Drinkwater (1998) suggest that self-employment is a way out of discrimination in paid employment for immigrants in Great Britain. Wage work pays does not pay as well for ethnic minorities, compared to natives, and the wage difference has increased over time. The increase in the earnings disadvantage has been correlated with a rise in the self-employment among ethnic minorities. Although there are higher self-employment rates for non-whites than for whites, one nevertheless observes a substantive variance among the ethnic groups. Most ethnic minorities also earn less in self-employment than similar self-employed whites. Borooah and Hart (1999) study the large differences in self-employment between Indians and black Caribbean men in Great Britain. They find that social attributes related
to family formation are at least as important as individual characteristics. Basu (1998) finds no evidence that Asians in Britain were pushed into self-employment to avoid unemployment. Their economic success as entrepreneurs seems to be positively associated with the share of personal capital invested at the beginning and with educational qualifications. The immigration process into Germany has been now well studied (see, for instance, Zimmermann, 1995; Constant, 1998). Germany is known to have a comparatively low rate of self-employment, but migrants exhibit an even lower rate. This is in spite of the fact that the self-employed immigrants reach earnings parity with self-employed natives and earn a premium of 30% over immigrant workers in the blue collar category (Constant, 1998). It is unclear why in a country with a relative high unemployment rate and with a relatively institutionalized labor market entry one does not observe more self-employment among immigrants. An exception is the Turks, the largest foreign ethnic group in Germany with a significant entrepreneurial tradition. In 2002, Turkish entrepreneurs in Germany were representing 69% of all Turkish entrepreneurs in the European Union (Arastirmalar and Vakfi, 2003). This suggests investigating immigrant entrepreneurship in Germany further and studying the Turkish group separately. Therefore, we address the following questions: What factors drive self-employment in Germany among native West Germans, immigrants, and Turks? How do immigrant entrepreneurs fare in terms of earnings if compared to native Germans? Are Turks earning more because they are more self-employed? To answer these questions we analyze the economic and social determinants of the probability to become an entrepreneur and we estimate earnings regressions that gauge the assimilation effect among the self-employed.

We control for the standard human capital variables, such as years of education, vocational training, language proficiency, and years of residence in Germany. Moreover, we add variables to account for labor market characteristics, demographics, social, and psychological ties. For the empirical analyses we employ data from the German Socioeconomic Panel (GSOEP) 2000 release to study the factors that influence the self-employment decisions. Our results highlight the differences between Germans and immigrants both in their decision to choose self-employment and in their self-employment remuneration. For both groups we find that the probability of self-employment increases significantly with age at a decreasing rate, and Turks are twice as likely to choose self-employment as any other immigrant group. While wealth, marital status, and financial worries are important determinants for Germans they are not for immigrants. This suggests that Germans and immigrants face different labor market opportunities, and their decisions are also guided by different aspirations, motives, and life strategies. Further, we find that the age-earnings profiles of self-employed German and immigrant men are very similar and have the familiar inverted U-shape, everything else equal. Self-employed German men earn more when they work more hours per week, have higher Treiman prestige scores, and are married. On the other hand, self-employed immigrants earn more with a longer tenure in their business but they face a wage penalty for marriage. The wages of the self-employed immigrants also decrease at an increasing rate with additional years in Germany. Everything else equal, the earnings of self-employed Turks are no different from the earnings of the self-employed Greeks, Italians, Spaniards, ex-Yugoslavs, Polish or other East Europeans, including those immigrants who have become German citizens. The rest of the paper is structured as follows: In Section 2 we provide a brief 7
discussion of our data, the theoretical framework and the variables employed in the analyses. Section 3 explains the methodological approach, presents the econometric evidence and discusses the results of our analyses. We draw our concluding remarks in Section 4.
2. Self-employed and salaried workers in Germany In this section, we provide an overview about the basic characteristics of self-employed and salaried workers in Germany by ethnicity. In this analysis, we concentrate on comparing the performance of the migrants with those of the West Germans and hence exclude East Germans. Even a decade after unification, East Germans do not have significant experiences with self-employment. Migrants still predominantly cluster in West Germany, and avoid the less-developed east with the much higher unemployment rates. The group of migrants studied here contains the traditional former guestworkers, namely those from Greece, Italy, Spain, former Yugoslavia, and Turkey, who or their parents were hired especially in the early sixties to meet a demand for blue collar workers. However, we use also data on the new immigrants from the eighties and nineties, who came mainly from Eastern Europe, among them mostly ethnic Germans from Poland, Romania, and states from the former Soviet Union (ex-USSR). While we will compare migrants to West Germans as the relevant native reference group, we will separately investigate the Turks, who are the largest foreign ethnic group in Germany. Section 2.1 will present the data source, discuss the major definitions of the variables used and outline basic hypotheses concerning the probability to be self-employed and the determinants of earnings among them. In section 2.2, we present and discuss the major characteristics of the sample populations and highlight the situation of 8

entrepreneurship among natives and migrants in Germany.
2.1 Data and hypotheses For the empirical analysis our data are drawn from the German Socioeconomic Panel (GSOEP), a nationally representative data set that has been conducted annually since 1984 and is provided by the German Institute for Economic Research (DIW Berlin). Here we use data from the GSOEP of the year 2000. This year is unique in that it includes all populations living in Germany. It also includes substantial information on labor force participation, self-employment categories, various aspects of life in Germany, and contains an assortment of attitudinal questions. More important, the 2000 data permit a more detailed analysis of the self-employed. We can, thus, differentiate between those selfemployed in agriculture, in the free-lance or professional sector, and in other self-employed categories including working for a family business (SOEP Group, 2001). Out of the immigrant sample we extracted the Turks as a separate group. We classify as Turks all individuals who were born in Turkey or in Germany and who are Turkish nationals. Because of the idiosyncrasies of the German migration system and the German immigration law, the typical distinction between first and second generation immigrants does not apply in Germany. Immigrants who are born in Germany are not necessarily German citizens, and even if they acquire the German citizenship they are perceived as foreigners and follow separate paths in the labor market. The samples we selected for our analyses exclude those individuals who are enrolled in school, and those in the military, because military personnel follow different trajectories and may skew our estimates. Additionally, we restrict our analysis to individuals aged 18 to 64, a prime age
for self-employment endeavors. Men and women usually follow different paths in the labor market. In Germany females are not fully integrated in the labor market, although the situation is somewhat changing in recent years. Consequently, we ended up with very few observations for selfemployed women. This small female sample could not justify a separate analysis, and thus, our analysis focuses on the self-employment endeavors of men in Germany in 2000. A dummy for self-employment is constructed from a self-reported answer from the GSOEP questionnaire regarding the employment status of the individuals. It includes small and larger scale farming, free-lance processionals, working in other business, and working in family business. For all self-employed, this is their main job. We exclude selfemployment as a secondary job. The salaried workers category includes blue collar, white collar, civil servants, and those registered as unemployed. According to our selection criteria we ended up with 2039 West Germans, 917 immigrants, and 319 Turks. Out of them, 9.9% are self-employed Germans, 4.8% are self-employed (non-Turkish) immigrants, and 6.3% are self-employed Turks. The explanatory variables used in this paper include human capital variables (education, German language proficiency, and health) and labor market variables (Treiman prestige scores, tenure/seniority with a job/business). We also include variables that show socioeconomic attachments to Germany and to the country of origin (citizenship, own a dwelling in Germany), and other attitudinal and control variables. For immigrants we measure the effects of years of schooling and vocational training in the home country and years of schooling and vocational training in Germany separately. That way we control for differences in the initial stock of human capital (education before migration) and render immigrants' education in Germany qualitatively similar to that of Germans and among 10

Up until recently citizenship in Germany was synonymous to nationality and was based on the law of blood. Accordingly, individuals born outside Germany are Germans if their ancestry is German. The new law combines the existing law of blood with the law of soil that is the law in the US, for example. Individuals born in Germany are Germans but they have to decide by the age of 18 which nationality to keep. Naturalization rates increased by 130% in 2000 mainly due to the decreased time limit.
category. The vast majority of self-employed men across all groups lie in the other business category employing. This category includes retail and restaurants. Turks dominate this category, especially in the small scale business. About 24% of the West Germans are in the free-lance professional category followed by 19% of immigrants. This category includes lawyers, doctors, teachers, and the hi-tech computer category. We are amazed not to find any Turks in this category. On the other hand, more Turks than any other group work in the family business. This indicates that Turks rely more on kinship and familial support when they open a new business, in sharp contrast to the other immigrants.
3. Econometric method and results 3.1 Methodology In our methodological framework, the unit of the analysis is the individual. In the first part of the econometric analysis we model the choice behavior of workers as a binomial logit. We assume that individual agents in the host country are facing two alternatives: the option of becoming self-employed versus the option of being a wage or salary worker. Individual agents maximize utility gained from the attributes of that choice. We assume that utility depends on the corresponding financial rewards of the choice. If the expected wages from self-employment exceed the expected wages from other types of employment, the individual workers choose to become self-employed. Such behavior is described in probabilistic terms. We estimate the probability of becoming self-employed based on values of a set of explanatory variables. This probability is not directly observed. Logistic regression model is an advantageous technique for estimating models with a binary dependent variable. Our dependent variable Y is a categorical variable that takes the value

of one if an individual is self-employed and the value of zero otherwise. The choice probability, assuming a logistic distribution, is:
where I indexes the individuals. The parameters $ reflect the impact of changes in X on the probability that Y = 1.3 The virtue of equation (1) is that its inverse (the log odds ratio4) has the following closed form:
The explanatory variables in X consist of a set of human capital (such as years of schooling and vocational training, German language proficiency, and health), individual specific characteristics, and socioeconomic characteristics. We include variables that measure economic, social, and psychological attachments to Germany, as well as attitudinal variables. All these independent variables are expected to affect the individuals probability to become an entrepreneur. The probability of becoming self-employed is also a function of age and its square and of the Years-since-Migration (YSM) and its square. YSM is the key instrument on the analysis on immigrants. The model is solved with maximum likelihood estimation. Since likelihood equations are non-linear in the parameters
$ an iterative algorithm is used for the maximization of the likelihood function. The resulting
estimates, b, are asymptotically unbiased, consistent, normal, and efficient. Finally, the
The parameters of the logit are not necessarily the marginal effects, but vary with the values of x as:. This is why the odds ratio is used. In essence, the estimated coefficient b represents the change in log odds for a unit increase in the independent variable.
The odds are the ratio of two probabilities for any mutually exclusive events or P/(1-P).

following equation

gives the predicted probabilities of self-employment for the representative individual in each ethnic group. The actual probabilities can be evaluated either at the sample means of the Xs or at specific values of the Xs. The results from this exercise will give us insights into the self-selection process and the role of the different characteristics of choosing the entrepreneurial avenue. We expect that individuals who are more educated, have more years of residence in Germany, have good health, are married, and do not come from socialist economies will have a higher probability of becoming entrepreneurs. Next, we operationalize the earnings assimilation of entrepreneurs in Germany. The estimation of earnings is given by the following structural equation (Mincerian wage equation):

with j denoting the number of observations. The dependent variable is the natural logarithm of gross weekly income, and X is a vector of socioeconomic characteristics similar to those specified in the logistic analysis but fine tuned to identify earnings. For example, here we include labor market characteristics and labor market structures. Earnings are a function of the same socioeconomic characteristics of all groups with additional variables added to explain the earnings of immigrants. Additional explanatory variables affecting the earnings of immigrants only are years of education before migration and categorical variables for language capability. The vector YSM stands for the key variable in the assimilation estimation, years of residence one has accumulated in Germany. We include the square 19
of YSM to capture any diminishing returns on earnings. The YSM coefficients in (2 measure the experience-aging effect on earnings. For immigrants, the estimates of (2 along with the coefficient on age - measure the pure assimilation effect. Our prediction is that the earnings of immigrants increase with additional years-since-migration to a point where they reach those of Germans. Lastly, ,j is the stochastic error assumed to be independent of the Xs. Following the premises of the neoclassical human capital theory, we expect that the more educated immigrants will have higher earnings than comparable natives. Similarly, we expect the earnings profiles with respect to age to have an inverted U-shape. If selfemployed workers are positively self-selected for their inner drive to be independently successful and to climb the socioeconomic ladder, they should also earn significantly higher wages, all else equal. We estimate both the logit and wage regressions on three groups of self-employed men in Germany, namely, the West Germans, the immigrants, and the Turks. We believe that each group is cohesive and homogeneous and is governed by similar experiences. Yet, there are distinct socio-economic and labor market differences among groups that warrant separate analyses. The heterogeneity among the groups under study is subject to very different influences by the business cycle, government policies, institutional frameworks, and demographics.

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TABLE 1. SELECTED CHARACTERISTICS ON SELF-EMPLOYED AND SALARIED WORKERS BY ETHNICITY WEST GERMANS IMMIGRANTS* TURKS SelfSalaried SelfSalaried SelfSalaried employed Workers employed Workers employed Workers
Weekly wages (in DM) 1 Average weekly hours of work 1 Treiman Occupational Prestige Score1 Length of time with firm/business 1 Age in years Years of schooling & vocational training in Germany Years of schooling & vocational training before migration Speak German all the time (in %) Disability limits work (in %) Years-since-Migration Married (in %) Single (in %) Children in HH < 16 yrs old (in %) Own dwelling in Germany (in %) German Citizen (in %) ex-Yugoslavs EU nationals non-EU nationals Number of Observations Self-employed as % of total group obs 1 Number of Obs with > 0 income 1874.63b 50.64 47.43.63 12.87a 202 1394.04b 42.56 43.42.01 12.37a 1972.84b 52.00 44.43.25 7.83a 3.82a 30.1115.38b 42.22 38.40.63 6.68a 4.17a 25.668 2116.94b 52.69 39.37.05 4.90 5.1081.68 40.70 35.40.12 4.15 5.14 24.299 206
Note: * Includes Greeks, Italians, Spaniards, ex-Yugoslavs, and other Eastern Europeans a The analysis of independent-samples t-test revealed a significant difference between West Germans and the other samples b The analysis of independent-samples t-test failed to reveal a significant difference between West Germans and the other samples Source: Own calculations from GSOEP 2000
TABLE 2. SELECTED CHARACTERISTICS ON CITIZENSHIP AND ATTITUDINAL VARIABLES BY EMPLOYMENT STATUS AND ETHNICITY: MEN IN GERMANY IN 2000
WEST GERMANS SelfSalaried employed Workers German Citizen (in %) Born in Germany (in %)1 Have 2nd Nationality (in %)1 Not born in Germany (in %)1 Not a German Citizen (in %) Born in Germany (in %)3 Apply for German Citizenship (%)3 Apply if allowed dual Citizenship (%)3 Feel that do not Belong (in %) Want to stay in Germany (in %) Worries about finances (in %) Worries about immigration to Germany (in %) Worries about hostility against foreigners (in%) Number of Observations Number of Observations 1837 IMMIGRANTS* SelfSalaried employed Workers 873 TURKS SelfSalaried employed Workers 299

85% 5% 10%

Number of Observations
Figure 1: Wage Distributions of Men in Germany

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