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Surnames and ancestry in Brazil

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  • Leonardo Monasterio

Abstract

This paper presents a method for classifying the ancestry of Brazilian surnames based on historical sources. The information obtained forms the basis for applying fuzzy matching and machine learning classification algorithms to more than 46 million workers in 5 categories: Iberian, Italian, Japanese, German and East European. The vast majority (96.7%) of the single surnames were identified using a fuzzy matching and the rest using a method proposed by Cavnar and Trenkle (1994). A comparison of the results of the procedures with data on foreigners in the 1920 Census and with the geographic distribution of non-Iberian surnames underscores the accuracy of the procedure. The study shows that surname ancestry is associated with significant differences in wages and schooling.

Suggested Citation

  • Leonardo Monasterio, 2017. "Surnames and ancestry in Brazil," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
    • Handle: RePEc:plo:pone00:0176890
    DOI: 10.1371/journal.pone.0176890
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    References listed on IDEAS

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    1. de Carvalho Filho, Irineu & Monasterio, Leonardo, 2012. "Immigration and the origins of regional inequality: Government-sponsored European migration to southern Brazil before World War I," Regional Science and Urban Economics, Elsevier, vol. 42(5), pages 794-807.
    2. Gregory Clark, 2015. "The Son Also Rises: Surnames and the History of Social Mobility," Economics Books, Princeton University Press, edition 1, number 10181-2.
    3. Carneiro, Pedro & Lee, Sokbae & Reis, Hugo, 2020. "Please call me John: Name choice and the assimilation of immigrants in the United States, 1900–1930," Labour Economics, Elsevier, vol. 62(C).
    4. Clark, Gregory & Cummins, Neil & Hao, Yu & Vidal, Dan Diaz, 2015. "Surnames: A new source for the history of social mobility," Explorations in Economic History, Elsevier, vol. 55(C), pages 3-24.
    5. Green, Francis & Dickerson, Andy & Saba Arbache, Jorge, 2001. "A Picture of Wage Inequality and the Allocation of Labor Through a Period of Trade Liberalization: The Case of Brazil," World Development, Elsevier, vol. 29(11), pages 1923-1939, November.
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    Cited by:

    1. Monasterio, Leonardo & Lopes, Daniel, 2018. "Brasil sem imigrantes: estimativas de longo prazo baseadas em microdados [Brazil without immigrants: microdata long run estimates]," MPRA Paper 88170, University Library of Munich, Germany.
    2. Dafeng Xu & Yuxin Zhang, 2022. "Identifying ethnic occupational segregation," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(3), pages 1261-1296, July.
    3. Xu, Dafeng, 2019. "Surname-based ethnicity and ethnic segregation in the early twentieth century U.S," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 1-19.
    4. Jens Kandt & Paul A Longley, 2018. "Ethnicity estimation using family naming practices," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-24, August.

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