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Birthplace diversity and economic prosperity


We propose an index of population diversity based on people’s birthplaces and decompose it into a size (share of immigrants) and a variety (diversity of immigrants) component. We show that birthplace diversity is largely uncorrelated with ethnic, linguistic or genetic diversity and that the diversity of immigrants relates positively to measures of economic prosperity. This holds especially for skilled immigrants in richer countries at intermediate levels of cultural proximity. We address endogeneity by specifying a pseudo-gravity model predicting the size and diversity of immigration. The results are robust across specifications and suggestive of skill-complementarities between immigrants and native workers.

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  1. 1.

    See Ozden et al. (2011) for a picture of the evolution of international migration over the last fifty years, and Docquier and Rapoport (2012) for a focus on high-skill migration and its effects on source and host countries.

  2. 2.

    That is, a 17-% increase. 22 out of 27 OECD countries saw increases in the diversity of their skilled workforce between 1990 and 2000 (the only exceptions being Estonia, Greece, New Zealand, Poland and Slovakia).

  3. 3.

    This inverted u-curve for cultural proximity mirrors the results of Ashraf and Galor (2013a) on genetic diversity.

  4. 4.

    Bellini et al. (2013) apply the same methodology to European regions and find broadly consistent results for Europe as well.

  5. 5.

    See also Bandiera et al. (2013) and Abramitzky et al. (2012, 2013), respectively, on the measurement of entry and return flows and on migrants’ self-selection.

  6. 6.

    See Laitin and Jeon (2013) for a recent overview of social psychology research on the effects of diversity.

  7. 7.

    See ADOP (2015) for more details.

  8. 8.

    We conduct a robustness check restricting our OLS and IV models to non-estimated observations only. The results (available upon request) remain virtually unchanged.

  9. 9.

    This also holds in first differences: the correlation between changes in size and diversity of skilled immigration 1990–2000 is low and even negative at \(-\)0.14.

  10. 10.

    See McKenzie and Rapoport (2010) and Bertoli (2010) for micro evidence on the role of migrant networks in determining self-selection patterns, and Beine et al. (2011) for macro evidence.

  11. 11.

    See the online appendix for details on the definitions and sources for all variables.

  12. 12.

    Following Ashraf and Galor (2013a) we also include a squared term for genetic diversity.

  13. 13.

    See, e.g., Hall and Jones (1999), Gallup et al. (1998), Rodriguez and Rodrik (2001), Sachs (2003), Rodrik et al. (2004).

  14. 14.

    We use the standard measure of trade volume: real trade openness (exports + imports) in percentage of GDP in real PPP prices. This indicator correlates most robustly with GDP growth (Yanikkaya 2003).

  15. 15.

    This definition follows the literature on trade concentration. See, e.g., Kali et al. (2007) for the effect of trade concentration on income or Frankel et al. (1995) on transportation costs.

  16. 16.

    Typical countries that drop out of this sample are small island states or territories.

  17. 17.

    See the Online Appendix, Table 13, for a specification sequentially introducing covariates in a model of skilled birthplace diversity.

  18. 18.

    The difference in \(Div_{mig}\) (skilled) between the rich and poor country subsample is significant at the 1 % level (unlike the diversity of unskilled migrants).

  19. 19.

    Still, we obtain qualitatively similar results in our rich country subsample when using country fixed effects (see Appendix).

  20. 20.

    This test relies on the assumption that selection on observables from a basic model towards a full model is proportional to selection on unobservables.

  21. 21.

    See the Online Appendix Table 13 for a similar analysis for the full sample. It shows that the full sample model is relatively more susceptible to a remaining positive omitted variables bias than our main results for rich countries only.

  22. 22.

    The sample thus includes all countries with patenting activity as covered by WIPO (2010). Hence, our estimates are best interpreted as effect on the intensive margin of patenting.

  23. 23.

    Note that Ozden et al. (2011) do not provide a skill decomposition of immigration in 1960, we hence rely on diversity of immigrants of all skill groups.

  24. 24.

    In particular, we test for robustness to continental fixed effects as employed by Ashraf and Galor (2013a).

  25. 25.

    See Grogger and Hanson (2011) for a deeper discussion on such sorting across destinations.

  26. 26.

    In line with our priors, in a basic model as in Table 11, column (2), both indices hold independent explanatory power and correlate highly positively with income (available upon request).

  27. 27.

    See (PISA 2009 results at a glance).

  28. 28.

    See Filmer et al. (2006), for an illustrative review of test score results. They report, among many other examples, that “the average science score among students in Peru [is] equivalent to that of the lowest scoring 5 % of US students”.

  29. 29.

    See the appendix for a simulation. The figures show that the vast majority of countries—even under the assumption that all high-ability math/science students had left—mostly sent non- highly math-skilled people abroad.

  30. 30.

    We build on the trade (e.g., Tinbergen 1962; Frankel and Romer 1999) and migration (e.g., Grogger and Hanson 2011; Beine et al. 2011) gravity literatures.

  31. 31.

    See, Lewer and Van den Berg 2008; Felbermayr et al. 2010; Mayda 2010; Grogger and Hanson 2011; Beine et al. 2013; Ortega and Peri 2009 and 2014.

  32. 32.

    While the use of origin FE largely suffices to account for multilateral resistance in trade, Bertoli and Fernández-Huertas Moraga (2013) show this to hold for migration only under more restrictive distributional assumptions.

  33. 33.

    This bias is particularly salient with data that are heteroskedastic (e.g., due to many zero cells). Overall, the degree of OLS bias relative to PPML depends on the underlying features of the data.

  34. 34.

    To avoid violating the exclusion restriction via inclusion of a lagged measure of population size, we fully rely on the more parsimonious model excluding this variable.

  35. 35.

    As is well known, the Stock and Yogo (2005) critical values are are appropriate under homoskedasticity only. We report heteroskedasticity-robust clustered standard errors, which tend to be higher than those obtained under the assumption of homoskedasticity.

  36. 36.

    F-Tests on the excluded instruments and the joint instruments are well above the respective Stock and Yogo (2005) critical values.

  37. 37.

    Weak instruments could also drive this result. Note, however, that models 3 and 4 are still relatively strongly identified (Kleibergen-Paap exceeding or close to Stock Yogo 15 % maximal IV size critical value).

  38. 38.

    A one standard deviation increase in the birthplace diversity of skilled immigrants generates an increase of about 25 % in long run economic output.


  1. Abramitzky, R., Boustan, L., & Eriksson, K. (2012). Europe’s tired, poor, huddled masses: Self-selection and economic outcomes in the age of mass migration. American Economic Review, 102(5), 1832–1856.

    Article  Google Scholar 

  2. Abramitzky, R., Boustan, L., & Eriksson, K. (2013). Have the poor always been less likely to migrate? Evidence from inheritance practices during the age of mass migration. Journal of Development Economics, 102, 2–14.

    Article  Google Scholar 

  3. Acemoglu, D., Johnson, S., & Robinson, J. (2001). The colonial origins of comparative development: An empirical investigation. American Economic Review, 91(5), 1369–1401.

    Article  Google Scholar 

  4. Ager, P., & Brückner, M. (2013). Cultural diversity and economic growth: Evidence from the US during the age of mass migration. European Economic Review, 64, 76–97.

    Article  Google Scholar 

  5. Alesina, A., Baqir, R., & Easterly, W. (1999). Public goods and ethnic divisions. Quarterly Journal of Economics, 114(4), 1243–1284.

    Article  Google Scholar 

  6. Alesina, A., Devleeschauwer, A., Easterly, W., Kurlat, S., & Wacziarg, R. (2003). Fractionalization. Journal of Economic Growth, 8(2), 155–194.

    Article  Google Scholar 

  7. Alesina, A., & La Ferrara, E. (2000). Participation in heterogeneous communities. Quarterly Journal of Economics, 115(3), 847–904.

    Article  Google Scholar 

  8. Alesina, A., & La Ferrara, E. (2002). Who trusts others? Journal of Public Economics, 85(2), 207–234.

    Article  Google Scholar 

  9. Alesina, A., & La Ferrara, E. (2005). Ethnic diversity and economic performance. Journal of Economic Literature, 43(3), 762–800.

    Article  Google Scholar 

  10. Alesina, A., Michalopoulos, S., & Papaioannou, E. (Forthcoming). Ethnic inequality. Journal of Political Economy.

  11. Alesina, A., Spolaore, E., & Wacziarg, R. (2000). Economic integration and political disintegration. American Economic Review, 90(5), 1276–1296.

    Article  Google Scholar 

  12. Alesina, A., & Zhuravskaya, E. (2011). Segregation and the quality of government in a cross section of countries. American Economic Review, 101(5), 1872–1911.

    Article  Google Scholar 

  13. Andersen, T., & Dalgaard, C.-J. (2011). Flows of people, flows of ideas, and the inequality of nations. Journal of Economic Growth, 16(1), 1–32.

    Article  Google Scholar 

  14. Anderson, J., & Van Wincoop, E. (2003). Gravity and gravitas: A solution to the border puzzle. American Economic Review, 93(1), 170–192.

    Article  Google Scholar 

  15. Arbatli, C., Ashraf, Q., Galor, O. (2015). The nature of conflict. NBER Working Paper No. 21079.

  16. Artuc, E., Docquier, F., Özden, C., & Parsons, C. (2015). A global assessment of human capital mobility: The role of non-OECD destinations. World Development, 65, 6–26.

    Article  Google Scholar 

  17. Ashraf, Q., & Galor, O. (2011). Cultural diversity, geographical isolation, and the origin of the wealth of nations. NBER Working Paper No. 17640.

  18. Ashraf, Q., & Galor, O. (2013a). The out of Africa hypothesis, human genetic diversity and comparative economic development. American Economic Review, 103(1), 1–46.

    Article  Google Scholar 

  19. Ashraf, Q., & Galor, O. (2013b). Genetic diversity and the origins of cultural fragmentation. American Economic Review, 103(3), 528–533.

    Article  Google Scholar 

  20. Bandiera, O., Rasul, I., & Viarengo, M. (2013). The making of modern America: Migratory flows in the age of mass migration. Journal of Development Economics, 102(May), 23–47.

    Article  Google Scholar 

  21. Barro, R., & Lee, J. (2013). A new data set of educational attainment in the world, 1950–2010. Journal of Development Economics, 104, 184–198.

    Article  Google Scholar 

  22. Beine, M., Docquier, F., & Rapoport, H. (2007). Measuring international skilled migration: New estimates controlling for age of entry. World Bank Economic Review, 21, 249–254.

    Article  Google Scholar 

  23. Beine, M., Docquier, F., & Özden, C. (2011). Diasporas. Journal of Development Economics, 95(1), 30–41.

    Article  Google Scholar 

  24. Beine, M., Docquier, F., & Schiff, M. (2013). Migration, transfer of norms and home country fertility. Canadian Journal of Economics, 46(4), 1406–1430.

    Article  Google Scholar 

  25. Bellini, E., Ottaviano, G., Pinelli, D., & Prarolo, G. (2013). Cultural diversity and economic performance: Evidence from European regions. In R. Crescenzi & R. Percoco (Eds.), Geography, institutions and regional economic performance, advances in spatial science (pp. 121–141). Berlin and Heidelberg: Springer Verlag.

    Chapter  Google Scholar 

  26. Bertoli, S. (2010). Networks, sorting and self-selection of ecuadorian migrants. Annales d’Economie et de Statistique, 97–98, 261–288.

    Google Scholar 

  27. Bertoli, S., & Fernández-Huertas Moraga, J. (2013). Multilateral resistance to migration. Journal of Development Economics, 102, 79–100.

    Article  Google Scholar 

  28. Boeheim, R., Horvath, G., Mayr, K. (2012). Birthplace diversity of the workforce and productivity spill-overs in firms. WIFO Working Papers No. 438.

  29. Brunow, S., Trax, M., & Suedekum, J. (2015). Cultural diversity and plant-level productivity. Regional Science and Urban Economics, 53, 85–96.

    Article  Google Scholar 

  30. Cavalli-Sforza, L. L., Menozzi, P., & Piazza, A. (1994). The history and geography of human genes. Princeton: Princeton University Press.

    Google Scholar 

  31. Collier, P. (1999). On the economic consequences of civil war. Oxford Economic Papers, 51, 168–183.

    Article  Google Scholar 

  32. Collier, P. (2001). Ethnic diversity: An economic analysis of its implications. Economic Policy, 32, 129–166.

    Google Scholar 

  33. Desmet, K., Ortuño-Ortín, I., & Wacziarg, R. (2012). The political economy of ethnolinguistic cleavages. Journal of Development Economics, 97(2), 322–338.

    Article  Google Scholar 

  34. Docquier, F., & Rapoport, H. (2012). Globalization, brain drain and development. Journal of Economic Literature, 50(3), 681–730.

    Article  Google Scholar 

  35. Easterly, W., & Levine, R. (1997). Africa’s growth tragedy: Policies and ethnic divisions. Quarterly Journal of Economics, 112(4), 1203–1250.

    Article  Google Scholar 

  36. Espinova, N., Ray, J., & Srinivasan, R. (2011). The world’s potential migrants. Gallup. Retrieved from, Accessed 23 March 2015.

  37. Esteban, J., & Ray, E. (1994). On the measurement of polarization. Econometrica, 62(4), 819–851.

    Article  Google Scholar 

  38. Esteban, J., & Ray, E. (2011). Linking conflict to inequality and polarization. American Economic Review, 101(4), 1345–1374.

    Article  Google Scholar 

  39. Esteban, J., Mayoral, L., & Ray, E. (2012). Ethnicity and conflict: An empirical study. American Economic Review, 102(4), 1310–1342.

    Article  Google Scholar 

  40. Fearon, J. (2003). Ethnic and cultural diversity by country. Journal of Economic Growth, 8(2), 195–222.

    Article  Google Scholar 

  41. Fearon, J., & Laitin, D. (2003). Ethnicity, insurgency, and civil war. American Political Science Review, 97(1), 75–90.

    Article  Google Scholar 

  42. Feenstra, R., Lipsey, R., Deng, H., Ma, A., & Mo, H. (2005). World trade flows: 1962–2000. NBER Working Paper No. 11040.

  43. Feenstra, R., Inklaar, R., & Timmer, M. (2013). The next generation of the penn world table. Retrieved from,

  44. Felbermayr, G., Hiller, S., & Sala, D. (2010). Does immigration boost per capita income? Economics Letters, 107(2), 177–179.

    Article  Google Scholar 

  45. Fershtman, C., Hvide, H., & Weiss, Y. (2006). Cultural diversity, status concerns and the organization of work. Research in Labor Economics, 24, 3–38.

    Article  Google Scholar 

  46. Filmer, D., Hasan, A., Pritchett, L. (2006). A millennium learning goal: Measuring real progress in education. Center for Global Development Working Paper 97.

  47. Frankel, J., & Romer, D. (1999). Does trade cause growth? The American Economic Review, 89(3), 379–399.

    Article  Google Scholar 

  48. Frankel, J., Stein, E., & Wei, S. J. (1995). Trading blocs and the Americas: The natural, the unnatural, and the super-natural. Journal of Development Economics, 47(1), 61–95.

    Article  Google Scholar 

  49. Gallup, J., Sachs, J., & Mellinger, A. (1998). Geography and economic development. In B. Pleskovic & J. E. Stiglitz (Eds.), Annual world bank conference on development economics. Washington, DC: The World Bank.

    Google Scholar 

  50. Glaeser, E., La Porta, R., & Shleifer, A. (2004). Do institutions cause growth? Journal of Economic Growth, 9(4), 271–303.

    Article  Google Scholar 

  51. Greenberg, J. (1956). The measurement of linguistic diversity. Language, 32, 109–115.

    Article  Google Scholar 

  52. Grogger, J., & Hanson, G. (2011). Income maximization and the selection and sorting of international migrants. Journal of Development Economics, 95, 42–57.

    Article  Google Scholar 

  53. Hall, R., & Jones, C. (1999). Why do some countries produce so much more output per worker than others? Quarterly Journal of Economics, 114(1), 83–116.

    Article  Google Scholar 

  54. Hambrick, D., Seung Cho, T., & Chen, M. J. (1996). The influence of top management team heterogeneity on firms’ competitive moves. Administrative Science Quarterly, 41(4), 659–684.

    Article  Google Scholar 

  55. Hatton, T., & Williamson, J. (1998). The age of mass migration: Causes and economic impact. Oxford: Oxford University Press.

    Google Scholar 

  56. Head, K., Mayer, T., & Ries, J. (2010). The erosion of colonial trade linkages after independence. Journal of International Economics, 81(1), 1–14.

    Article  Google Scholar 

  57. Hjort, J. (2014). Ethnic divisions and production in firms. Quarterly Journal of Economics, 129(4), 1899–1946.

    Article  Google Scholar 

  58. Hong, L., & Page, S. (2001). Problem solving by heterogeneous agents. Journal of Economic Theory, 97(1), 123–163.

    Article  Google Scholar 

  59. Hoogendoorn, S., & van Praag, M. (2012). Ethnic diversity and team performance: A field experiment. IZA Working Paper No. 6731.

  60. Hsieh, C. T., & Ossa, R. (2011). A global view of productivity growth in China. NBER Working Paper 16778, September 2011.

  61. Kahane, L., Longley, N., & Simmons, R. (2013). The effect of coworker heterogeneity on firm-level output: Assessing the impacts of cultural and language diversity in the National Hockey League. Review of Economics and Statistics, 95(1), 302–314.

    Article  Google Scholar 

  62. Kali, R., Méndez, F., & Reyes, J. (2007). Trade structure and economic growth. Journal of International Trade & Econ Development, 16(2), 245–269.

    Article  Google Scholar 

  63. Laitin, D. D., & Jeon, S. (2013). Exploring opportunities in cultural diversity. Mimeo: Stanford University.

    Google Scholar 

  64. Lazear, E. P. (1999a). Globalisation and the market for teammates. Economic Journal, 109(454), 15–40.

    Article  Google Scholar 

  65. Lazear, E. P. (1999b). Culture and language. Journal of Political Economy, 107(6), 95–126.

    Article  Google Scholar 

  66. Lewer, J. J., & Van den Berg, H. (2008). A gravity model of immigration. Economics Letters, 99(1), 164–167.

    Article  Google Scholar 

  67. Marshall, M., & Jaggers, K. (2012). Polity IV project: Political regime characteristics and transitions, 1800–2012. Center for International Development and Conflict Management, University of Maryland.

  68. Mayda, A. (2010). International migration: A panel data analysis of the determinants of bilateral flows. Journal of Population Economics, 23(4), 1249–1274.

    Article  Google Scholar 

  69. McKenzie, D., & Rapoport, H. (2010). Self-selection patterns in Mexico-US migration: The role of migration networks. Review of Economics and Statistics, 92(4), 811–821.

    Article  Google Scholar 

  70. Michalopoulos, S. (2012). The origins of ethnolinguistic diversity. American Economic Review, 102(4), 1508–1539.

    Article  Google Scholar 

  71. Milliken, F. J., & Martins, L. L. (1996). Searching for common threads: Understanding the multiple effects of diversity in organizational groups. Academy of Management Review, 21(2), 402–433.

    Google Scholar 

  72. Montalvo, J., & Reynal-Querol, M. (2005). Ethnic polarization, potential conflict and civil war. American Economic Review, 95(3), 796–816.

    Article  Google Scholar 

  73. OECD. (2009). OECD Programme for International Student Assessment (PISA), available from:

  74. O’Reilly, C., Caldwell, D., & Barnett, W. (1989). Work group demography, social integration, and turnover. Administrative Science Quarterly, 34(1), 21–37.

    Article  Google Scholar 

  75. Oster, E. (2013). Unobservable selection and coefficient stability: Theory and validation. NBER Working Paper 19054.

  76. Ortega, F., & Peri, G. (2009). The causes and effects of international migrations: Evidence from OECD countries 1980–2005. NBER Working Paper 14833.

  77. Ortega, F., & Peri, G. (2014). Openness and income: The roles of trade and migration. Journal of International Economics, 92(2), 231–251.

    Article  Google Scholar 

  78. Ottaviano, G., & Peri, G. (2006). The economic value of cultural diversity: Evidence from U.S. cities. Journal of Economic Geography, 6(1), 9–44.

    Article  Google Scholar 

  79. Ozden, C., Parsons, C., Schiff, M., & Walmsley, T. (2011). Where on earth is everybody? The evolution of global bilateral migration 1960–2000. The World Bank Economic Review, 25(1), 12–56.

    Article  Google Scholar 

  80. Ozgen, C., Nijkamp, P., & Poot, J. (2013). The impact of cultural diversity on firm: Evidence from dutch micro data. IZA Journal of Migration, 2, 18.

    Article  Google Scholar 

  81. Parrotta, P., Pozzoli, D., & Pytlikova, M. (2014). Does labor diversity affect firm productivity? European Economic Review, 66, 144–179.

    Article  Google Scholar 

  82. Peri, G. (2012). The effect of immigration on productivity: Evidence from US states. Review of Economics and Statistics, 94(1), 348–358.

    Article  Google Scholar 

  83. Putnam, R. D. (1995). Bowling alone: America’s declining social capital. Journal of Democracy, 6(1), 65–78.

    Article  Google Scholar 

  84. Reynal-Querol, M. (2002). Ethnicity, political systems, and civil wars. Journal of Conflict Resolution, 46(1), 29–54.

    Article  Google Scholar 

  85. Rodriguez, F., & Rodrik, D. (2001). Trade policy and economic growth: A skeptic’s guide to the cross-national evidence. NBER Macroeconomics Annual, 15, 261–338.

    Article  Google Scholar 

  86. Rodrik, D., Subramanian, A., & Trebbi, F. (2004). Institutions rule: The primacy of institutions over geography and integration in economic development. Journal of Economic Growth, 9(2), 131–165.

    Article  Google Scholar 

  87. Sachs, J. (2003). Institutions don’t rule: Direct effects of geography on per capita income. NBER Working Paper No 9490.

  88. Santos Silva, J., & Tenreyro, S. (2006). The log of gravity. The Review of Economics and Statistics, 88(4), 641–658.

    Article  Google Scholar 

  89. Spolaore, E., & Wacziarg, R. (2009). The diffusion of development. Quarterly Journal of Economics, 124(2), 469–529.

    Article  Google Scholar 

  90. Stock, J., & Yogo, M. (2005). Testing for weak instruments in linear IV regression. In Donald Andrews & James H. Stock (Eds.), Identification and inference for econometric models: Essays in honor of Thomas Rothenberg. New York, NY: Cambridge University Press.

    Google Scholar 

  91. Tinbergen, J. (1962). An analysis of world trade flows. In Jan Tinbergen (Ed.), Shaping the world economy. New York: Twentieth Century Fund.

    Google Scholar 

  92. U.N. Population Division. (2013). World population prospects: The 2013 revision. Retrieved from,

  93. World Bank Group (2013). World development indicators 2013. World Bank Publications, 2013.

  94. World Intellectual Property Organization. (2010). World intellectual property indicators. Retrieved from,

  95. Yanikkaya, H. (2003). Trade openness and economic growth: A cross-country empirical investigation. Journal of Development Economics, 72(1), 57–89.

    Article  Google Scholar 

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Correspondence to Hillel Rapoport.

Additional information

Our birthplace diversity dataset can be found at

We thank the editor, Oded Galor, and three anonymous referees for excellent comments which greatly improved the paper. We are also grateful to Amandine Aubry, Simone Bertoli, François Bourguignon, Matteo Cervellati, Frédéric Docquier, Jesús Fernández-Huertas Moraga, Gordon Hanson, Frédéric Jouneau, Thierry Mayer, Lant Pritchett, Yona Rubinstein, Joao Santos-Silva, Jacques Silber, Sylvana Tenreyro, Nico Voigtlaender, Ekaterina Zhuravskaya, participants at the 5th AFD-World Bank Conference on Migration and Development, Paris, June 2012, the CEMIR conference at CESifo, Munich, December 2012, the NBER Economics of Culture and Institutions Meeting, Cambridge, April 2013, the 10th IZA Migration Meeting in Jerusalem, June 2013, the 4th TEMPO-CEPR Conference in Nottingham, September 2013, the NBER Conference on High Skill Immigration, October 2013, the workshop on “Deep Rooted Factors in Comparative Economic Development” at Brown University, May 2014, the CESifo workshop on “Demographic Changes and Long-Run Growth” in Venice, July 2014, and seminar audiences at PSE, Louvain, Geneva, Luxembourg, Milan, Hebrew University, Tel-Aviv, EUI, IDC, and the Kiel Institute for comments and suggestions. We also thank Quamrul Ashraf and Frédéric Docquier for sharing their data with us.

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Alesina, A., Harnoss, J. & Rapoport, H. Birthplace diversity and economic prosperity. J Econ Growth 21, 101–138 (2016).

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  • Birthplace diversity
  • Immigration
  • Culture
  • Economic development

JEL Classification

  • O1
  • O4
  • F22
  • F43