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Revisiting native and immigrant entrepreneurial activity

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Abstract

Entrepreneurial activity differs substantially across immigrant groups in the USA, but relating self-employment rates in the US to home-country self-employment shares has provided inconclusive results in previous studies. This paper offers new evidence on the relationship between native self-employment and the self-employment decision of immigrants and their descendants. We argue that the previous literature has neglected to account for different proxies of entrepreneurial behavior and for determinants of self-employment in the country of origin. We find mixed evidence of a significant relationship between entrepreneurial activity of US immigrants and two different measures of entrepreneurial activity in their respective countries of origin. Our findings suggest that differences in self-employment across immigrants of different origin are to some degree an expression of the behavior acquired under varying economic and institutional environments.

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Notes

  1. Sources: International Labour Office database (average figures, 1969–2000) of the ILO Bureau of Statistics and the World Bank Group Entrepreneurship Survey and Database (2008).

  2. This measure has also been used, for instance, by Borjas (1986), Evans and Leighton (1989), however, in a different context.

  3. The variable is calculated from the ILO Laborsta database as the share of employers in total active population and relates to averages over the years 1969–2000. Note that the panel from which the average is calculated is unbalanced in the time dimension.

  4. Borjas (1986) finds positive enclave effects for Hispanics in the USA, while Clark and Drinkwater (2000) show that ethnic enclaves decrease the probability to become self-employed in the UK. Further hypotheses are mentioned in the literature, including the sectoral choice model (Fairlie and Meyer 1996) or the tax avoidance hypothesis (Yuengert 1995).

  5. Such an approach has been used, among others, by Carroll et al. (1994), Hendricks (2002), and Osili and Paulson (2008). Hendricks (2002) estimates differences in human capital endowments by measuring differences in labor earnings across US immigrants with identical skills using 1990 US Census data; Carroll et al. (1994) study cultural differences in savings patterns using immigrant data for Canada and the USA; and Osili and Paulson (2008) examine the effect of home-country institutions on the financial behavior of immigrants in the USA. The same data set is used by Michelacci and Silva (2007) to analyze how local entrepreneurship contributes to business creation, see also Yuengert (1995), Fairlie and Meyer (1996), Fairlie and Woodruff (2010).

  6. For ease of calculation, it is restricted to include 100,000 randomly selected US native citizens in the regressions displayed in Table 7 in the Appendix of this paper. The remaining number of observations is 1,324,102. This plays no role with respect to the estimates reported in Sect. 5 (no US natives included).

  7. A few other variables mentioned in the literature that may determine the individual probability of becoming self-employed such as inherited assets and access to funding are not available in the Ruggles et al. (2008) data set and are thus not accounted for.

  8. We do so because some of these individuals—the majority of which are immigrants—also report to be self-employed. This suggests that these observations most likely exhibit a quality bias. We further omit 220 thousand observations that did not indicate the employment status (e.g., employed, self-employed) as well as 4800 unpaid family workers.

  9. We constructed the industry dummies by aggregating dummy variables for those professions that yielded the largest fraction of self-employed persons. The dummies indicate whether a person works in one of the following occupations: agriculture, building and construction, retail, services, transport, and medical. Finally, we also include a dummy variable for household work. Together, these observations cover about half of the sample.

  10. The continental regions are classified as follows. East Asia and Pacific (EAP); Eastern Europe and Central Asia (EECA); Latin America and the Caribbean (LAC); Middle East and North Africa (MENA); North America (NAM); Oceania (OCEA); South Asia (SAS); Sub-Saharan Africa (SSA); and Western Europe (WEU). The results were robust to the inclusion of dummies for dwelling ownership, log investment income, total personal income, state and metropolitan dummies.

  11. Column (1) of Table 7 reports marginal effects of the dummies for country of origin on the probability of being self-employed overall, and on the probability of being incorporated self-employed in column (2). Columns (3) and (4) report the marginal effects excluding US natives. One may argue that there may be variation in entrepreneurial behavior within countries. This may be true for some countries such as the USA—where we account for possible differences by including state dummies in our regressions—or Switzerland. However, we believe that in the majority of countries, the institutional and economic factors that are likely to shape an entrepreneurial culture (e.g., taxes, contract enforcement regulations, etc.) are specific to countries rather than to within-country regions.

  12. Note that there may be risk of type-1 error with respect to the estimates reported in Fig. 3 and Table 7. In addition, the coefficients will likely be biased so that quantitative interpretations should be handled with care. Nevertheless, they allow us to benchmark our estimates to the previous literature with respect to the direction and an approximate interpretation of the estimates and provide evidence for an overall variation in occupation choices according to different countries of origin of immigrants.

  13. Recall from Sect. 2 that the latter variable refers to employers excluding micro-entrepreneurs and may better fit the incorporated self-employment outcome of the Census sample. We include both of them separately in our baseline regressions in order to test the different influences.

  14. We have obtained data about active businesses between 2001 and 2013 in a variety of countries from the GEM database. These data proved qualitatively similar to ILO self-employment shares; hence, they may represent different economic activities compared to the ones in the USA. Results from regressions using these data proved qualitatively similar to the ones using ILO self-employment shares. Note that there has also been increased interest in latent entrepreneurship, or entrepreneurial intentions, across countries (e.g., Blanchflower et al. 2001; Henrekson and Sanandaji 2014; Fitzsimmons and Douglas 2011, GEM database).

  15. In the data at hand, there are large differences with respect to the time dimension in which these variables have been reported. This implicates that averages refer to rather recent time periods for some and to longer periods for other countries. To address this, we alternatively matched ten-year averages to the time an immigrant has passed in the USA. The results were robust to this procedure.

  16. Other possible and available determinants, including age dependency ratios, literacy, or shares of urban population, are highly correlated with GDP per capita. For this reason, we do not include them in the regressions. Finally, we do not account for income inequality—relative returns to skill may provide another potential determinant of entrepreneurial activity, though not necessarily so if the returns to entrepreneurship are lower compared to paid employment (see also Hamilton 2000; Hyytinen et al. 2013)—as no consistent data covering the period and countries included in our data set are available.

  17. The strong correlations in Fig. 2 confirm the assumption that coverage and quality are sufficient. However, disadvantages of the data at hand are that some important countries such as China, Russia, India, and Cuba are unfortunately missing entirely, and the data include a few suspicious observations. For instance, the reported agricultural employment shares of Argentina and Peru are low. In addition, the unemployment rates of countries such as Bangladesh, Cambodia, Cameroon, Mexico, or Vietnam are very low. This could be due to either low data quality or—and we consider this explanation more likely—to the fact that (because of the absence of social security benefits) job-seeking individuals do not report unemployment or are pushed into self-employment. We also drop Eritrea from the sample regarding the employer share. This country reports one of the highest employer shares, which may be due to measurement error.

  18. Individuals may indicate several—ranked—ancestor countries. This has the advantage that one principal ancestry is given. The disadvantage is that it does not clearly allow us to distinguish between generations in the USA. We therefore have to bear in mind that this potentially produces a bias against finding significant results. Note further that this results in a larger number of observations but not of country groups.

  19. Note that the figures are based on country censuses that may refer to earlier years. The 1949/50 Yearbook contains only overall self-employment. To our knowledge, these figures are the earliest figures available after World War II. Since major immigration occurred after the war, we consider this period an appropriate starting point to our analysis.

  20. These are the earliest years available in the data set at hand. While one could think of sources including earlier figures for GDP, we consider the period at hand to be consistent with the data on self-employment in terms of the time dimension.

  21. A common assertion states that immigrants arrive with a set of cultural values and behaviors different from those in the destination country and are prone to shocks due to language, new institutions, etc. Although it has been shown that transplanted behavior is persistent, it is possible that institutional factors and cultural norms in the country of immigration become more important. As a consequence, home-country effects may fade over time. Although we are not able to identify assimilation effects using the cross-sectional data at hand, we may obtain a tentative idea by examining the evolution of entrepreneurial activity of immigrants over time using interaction terms for the self-employment share with the discrete duration of residence in the USA. Appendix Fig. 5 shows the marginal effect of home-country self-employment shares evaluated at different intervals of years an immigrant has passed in the USA (i.e., the effect of a change in home-country self-employment shares by 1 percentage points with years in the US held constant at different values). The results are qualitatively similar to the ones in Sect. 5.1, with marginal effects that are increasing in the duration of stay in the USA.

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Acknowledgments

We would like to thank Silvia Ardagna for a fruitful discussion at the World Bank Conference on Entrepreneurship and Growth. We are grateful to Matthias Bannert for providing generous advice regarding computational issues. We also received helpful comments from Sule Akkoyunlu, Peter Egger, Richard Jong-A-Ping, Leora Klapper, Sarah Lein, Nora Strecker, seminar participants at the World Bank Conference on Entrepreneurship and Growth, the Beyond Basic Questions Seminar in Zurich, the KOF Brown Bag Seminar, and the Spring Meeting of Young Economists in Istanbul, and two anonymous reviewers.

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  1. Christian Busch

    Present address: State Secretariat of Economic Affairs SECO, Effingerstrasse 1, 3003, Bern, Switzerland

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  1. KOF Swiss Economic Institute, ETH Zurich, G118, Leonhardstrasse 21, 8092, Zurich, Switzerland

    Andrea Lassmann

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Appendix

Appendix

See Fig. 5; Tables 5, 6, 7, 8 and 9.

Table 5 Country correspondence to ISO 3166(−1) ALPHA-3 country codes and continental codes
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Table 6 Descriptive statistics of the 2000 US Census
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Table 7 Probability of being self-employed by country of origin
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Table 8 Descriptive statistics of control variables
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Table 9 Descriptive statistics of control variables (descendants of immigrants)
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Fig. 5
figure 5

Home-country self-employment share and years passed in the USA. Notes: Marginal effects and 95 % confidence intervals from logit regressions with clustered standard errors evaluated at different years an immigrant has spent in the USA, other variables at sample means. The dependent variable is a dummy for being (incorporated) self-employed (immigrants only). The estimations include the following variables not reported above: age, age squared, gender, number of children, dummies for marital status, education, proficiency in English, industry of employment, and state dummies (Ruggles et al. 2008). Self-employment and employer share in total active population: ILO Laborsta, average 1969–2000

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Lassmann, A., Busch, C. Revisiting native and immigrant entrepreneurial activity. Small Bus Econ 45, 841–873 (2015). https://doi.org/10.1007/s11187-015-9665-x

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