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Trade, FDI, migration, and the place premium: Mexico and the United States

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Abstract

Large wage differences between countries (“place premiums”) are well documented. Theory suggests that factor price convergence should follow increased migration, capital flows, and commercial integration. All three have increased between the United States and Mexico over the last 25 years. This paper evaluates the degree of wage convergence between these countries during the period 1988 and 2011. We match survey and census data from Mexico and the United States to estimate the change in wage differentials for observationally identical workers over time. We find very little evidence of convergence. What evidence we do find is most likely due to factors unrelated to US–Mexico integration. While migration, trade, and FDI may reduce the US–Mexico wage differential, these effects are small when compared to the overall wage gap.

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Notes

  1. World Bank Development Indicators. See http://data.worldbank.org/data-catalog/world-development-indicators.

  2. See Brown (1992) for a survey of early general equilibrium models of NAFTA.

  3. Several papers document within-country wage responses to price changes that are consistent with Heckscher-Ohlin predictions. See Beyer et al. (1999) for Chile, Robertson (2004) for Mexico, and Michaels (2008) for the United States.

  4. The lack of evidence of factor price equalization generally has prompted many to question the validity of neoclassical HOS-type models. Schott (2003) finds that we live in a “multi-cone” world that precludes factor price equalization. Davis and Mishra (2007) suggest that ignoring important variation between the mix of factors employed in the production of domestic and imported goods obfuscates the possible effect that free trade may depress the wages of workers in relatively labor-intensive domestic industries. Goldberg and Pavcnik (2007) discuss evidence of rising inequality in poorer countries in the wake of many trade liberalizations in the eighties and nineties, which is very much at odds with a standard HOS story of how globalization should unfold. The authors provide numerous reasons why the predictions of the standard HOS theory may not hold in the data such as technology, the pattern of tariff reductions, and within-industry shifts.

  5. It is possible to analyze migration using general-equilibrium trade models. In the HOS framework, immigration is generally analyzed through the Rybczynski and Factor Price Insensitivity theorems. Under the assumptions that the two countries are in the same diversification cone and are small enough for immigration to have no effect on output prices, these theorems predict that immigration has no effect on wages because immigrants are absorbed through changes in the production mix.

  6. In addition to the ENOE, we use its predecessors, the Encuesta Nacional de Empleo (ENE) and the Encuesta Nacional de Empleo Urbano (ENEU).

  7. Readers familiar with the ENOE data used in this paper will recall that the ENOE does, in fact, include rural workers. We merge the ENOE with the earlier incarnations of the labor force surveys (the Encuesta Nacional de Empleo Urbano) that only include urban areas. To generate a consistent series through time, we exclude the rural workers from our ENOE samples.

  8. We also converted Mexican wages to 1990 US dollars by first deflating the wages to 1990 pesos using the Mexican CPI and then converting them to US dollars using the 1990 exchange rate. Overall, this alternative method did not make too much of a difference. We conduct a comparison of these two deflation methods in the “Appendix 2”.

  9. Lustig et al. (2012) argue that the increase in the supply of education in Mexico played a significant role in reducing income inequality in Mexico.

  10. See http://wenr.wes.org/2013/05/wenr-may-2013-an-overview-of-education-in-mexico.

  11. One might be reasonably concerned that workers in the same cells are not comparable across countries. In fact, cell comparability has been contentious in the literature. Alternative matches, such as Mexican workers with 9–11 years of schooling being matched with US workers with 6–8 years of schooling, might be justified using occupation data. Since a thorough analysis of such matches might be worthy of its own study, we consider alternative matches to be beyond the scope of the current paper and instead follow the convention established in these papers.

  12. We also generate the same results using the mean of the person-level log monthly earnings and get basically identical results.

  13. Dussel Peters and Gallagher (2013) argue that China had a significantly negative influence on NAFTA trade.

  14. In unreported results, we also analyze the standard deviation of the earnings differentials across cells. The standard deviation of wage differentials across cells exhibit breaks at the times indicated by the Vogelsang and Perron test statistic. The standard deviation rises steadily until the end of the sample, again supporting the use of multiple structural breaks.

  15. Hours worked per year were obtained by taking usual hours worked per week times the number of weeks that the respondent reported to have worked during the year.

  16. See Zong and Batalova (2014) for an overview of Mexican migration to the United States.

  17. Interestingly, the difference in results is conceptually consistent with urban areas having a more diversified production base and the rural areas more likely to be outside of the relevant diversification cone.

  18. This is not reported but is available upon request.

  19. To see this note that \( \frac{ - 2.08}{ - 0.307} \approx 7 \).

  20. It is interesting, however, that during the period of rising inequality in Mexico (1987–1994), we do see divergence of the less-educated groups and convergence of the more educated groups. After NAFTA, however, the differences in convergence/divergence trends are very small.

  21. We define “border” to be all of Mexico’s states that border with the United States which includes Baja California, Sonora, Chihuahua, Tamaulipas, and Coahuila. When we employ the whole sample, we use all wages from these states which include those from rural areas. When we employ the urban sample, we only use selected cities which include large border towns such as Tijuana and Juarez.

  22. It is important to bear in mind that this triple-difference exercise may not fully neutralize the effects of Great Recession if it impacted the border region of Mexico more than the interior. This would mean that this exercise overstates the effects of FDI on wage convergence. However, our conclusion is that FDI does not appear to narrow the Mexico–US wage differential and, so our conclusion would only be strengthened in the presence of this bias.

References

  • Autor, D. H., Dorn, D., & Hanson, G. H. (2013). The China syndrome: Local labor market effects of import competition in the United States. American Economic Review, 103(6), 2121–2168.

    Article  Google Scholar 

  • Autor, D. H., Dorn, D., & Hanson, G. H. (2016). The China shock: Learning from labor market adjustment to large changes in trade (NBER Working Paper 21906).

  • Banco de Mexico (2013). Exchange rate, Pesos per U.S. dollars (Daily). Retrieved from http://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?accion=consultarCuadro&idCuadro=CF102&sector=6&locale=en.

  • Bernard, A. B., Redding, S. J., & Schott, P. K. (2007). Comparative advantage and heterogeneous firms. Review of Economic Studies, 74(1), 31–66.

    Article  Google Scholar 

  • Beyer, H., Rojas, P., & Vergara, R. (1999). Trade liberalization and wage inequality. Journal of Development Economics, 59(1), 103–123.

    Article  Google Scholar 

  • Borjas, G. J. (2003). The labor demand curve is downward sloping: Reexamining the impact of immigration on the labor market. The Quarterly Journal of Economics, 118(4), 1335–1374.

    Article  Google Scholar 

  • Brezis, E., & Krugman, P. (1996). Immigration, investment, and real wages. Journal of Population Economics, 9(1), 83–93.

    Article  Google Scholar 

  • Brown, D. (1992). The impact of a North American Free Trade Area: Applied general equilibrium trade models. In N. Lustig, B. P. Bosworth, & R. Z. Lawrence (Eds.), North American free trade: Assessing the impact. Washington, DC: The Brookings Institution.

    Google Scholar 

  • Bureau of Labor Statistics (2013). Consumer price index. Retrieved May 11, 2013. http://www.bls.gov/cpi/.

  • Card, D. (1990). The impact of the Mariel boatlift on the Miami labor market. Industrial and Labor Relations Review, 43(2), 245–247.

    Article  Google Scholar 

  • Card, D. (2001). Immigrant inflows, native outflows and the local labor market impacts of higher immigration. Journal of Labor Economics, 19(1), 22–64.

    Article  Google Scholar 

  • Chiquiar, D. (2005). Why Mexico’s regional income convergence broke down. Journal of Development Economics, 77(1), 257–275.

    Article  Google Scholar 

  • Chiquiar, D., & Hanson, G. H. (2005). Internal migration, self-selection and the distribution of wages: Evidence from Mexico and the United States. Journal of Political Economy, 113(2), 239–281.

    Article  Google Scholar 

  • Clemens, M., Montenegro, C., & Pritchett, L. (2008). The place premium: Wage differences for identical workers across the U.S. border (World Bank Policy Research Working Paper, No. 4671).

  • Cragg, M. I., & Epelbaum, M. (1996). Why has wage dispersion grown in Mexico? Is it the incidence of reforms or the growing demand for skills? Journal of Development Economics, 51(1), 99–116.

    Article  Google Scholar 

  • Davis, D., & Mishra, P. (2007). Stopler-Samuelson is dead: And other crimes of both theory and data. In A. Harrison (Ed.), Globalization and poverty. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • Deaton, A. (1985). Panel data from time series of cross sections. Journal of Econometrics, 30(1), 109–126.

    Article  Google Scholar 

  • Deaton, A. (1997). The analysis of household surveys: A microeconomic approach to development policy. Baltimore: Johns Hopkins University Press.

    Book  Google Scholar 

  • Dollar, D., Wolff, E. N., & Baumol, W. J. (1988). The factor price equalization model and industry labor productivity: An empirical test across countries. In R. Feenstra (Ed.), Empirical Methods for International Trade (pp. 23–47). Cambridge, MA: MIT Press.

    Google Scholar 

  • Dussel Peters, E., & Gallagher, K. P. (2013). NAFTA’s uninvited guest: China and the disintegration of North American trade. Cepel Review, 110(August), 83–108.

    Google Scholar 

  • Elsner, B. (2013a). Does emigration benefit the stayers? Evidence from EU enlargement. Journal of Population Economics, 26(2), 531–553.

    Article  Google Scholar 

  • Elsner, B. (2013b). “Emigration and Wages: The EU Enlargement Experiment”. Journal of International Economics, 91(1): 154-63.

  • Feenstra, R. C., & Hanson, G. H. (1997). Foreign direct investment and relative wages: Evidence from Mexico’s maquiladoras. Journal of International Economics, 42, 371–394.

    Article  Google Scholar 

  • Giovanni, J., Levchenko, A. A., & Ortega, F. (2015). A global view of cross-border migration. Journal of the European Economic Association, 13(1), 168–202.

    Article  Google Scholar 

  • Goldberg, P. K., & Pavcnik, N. (2007). Distributional effects of globalization in developing countries. Journal of Economic Literature, 45(1), 39–82.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Hanson, G. H. (1996). Localization economies, vertical organization, and trade. American Economic Review, 86(5), 1266–1278.

    Google Scholar 

  • Hanson, G. H. (1997). Increasing returns, trade, and the regional structure of wages. Economic Journal, 107(440), 113–133.

    Article  Google Scholar 

  • Hanson, G. H. (2003). What has happened to wages in Mexico since NAFTA? Implications for hemispheric free trade (Working Paper Series, No. 9563).

  • Hanson, G. H. (2010). Why isn’t Mexico rich? Journal of Economic Literature, 48(4), 987–1004.

    Article  Google Scholar 

  • Hanson, G. H., & Harrison, A. (1999). Trade liberalization and wage inequality in Mexico. Industrial and Labor Relations Review, 52(2), 271–288.

    Article  Google Scholar 

  • Hanson, G. H., Robertson, R., & Spilimbergo, A. (2002). Does border enforcement protect U.S. workers from illegal immigration? Review of Economics and Statistics, 84(1), 73–92.

    Article  Google Scholar 

  • Kennan, J. (2013). Open borders. Review of Economic Dynamics, 16(2), 1–13.

    Article  Google Scholar 

  • Lustig, N., Lopez-Calva, L. F., Ortiz-Juarez, E. (2012). Declining inequality in Latin America in the 2000s: The cases of Argentina, Brazil, and Mexico (Working Paper No. 307). Center for Global Development.

  • Mankiw, N. Gregory, Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107(2), 407–437.

    Article  Google Scholar 

  • Maskus, K., & Nishioka, S. (2009). Development-related biases in factor productivities and the HOV model of trade. Canadian Journal of Economics, 42(2), 519–553.

    Article  Google Scholar 

  • Meltiz, M. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6), 1695–1726.

    Article  Google Scholar 

  • Michaels, G. (2008). The effect of trade on the demand for skill: Evidence from the interstate highway system. The Review of Economics and Statistics, 90(4), 683–701.

    Article  Google Scholar 

  • Minnesota Population Center (2014). Integrated public use microdata series, international: Version 6.3 [Machine-readable database]. Minneapolis: University of Minnesota.

  • Mishra, P. (2007). Emigration and wages in source countries: Evidence from Mexico. Journal of Development Economics, 82(1), 180–199.

    Article  Google Scholar 

  • Office of the United States Trade Representative (2013). Mexico. Retrieved April 8, 2013. http://www.ustr.gov/countries-regions/americas/mexico.

  • Ottaviano, G. I. P., & Peri, G. (2012). Rethinking the effect of immigration on wages. Journal of the European Economic Association, 10(1), 152–197.

    Article  Google Scholar 

  • Perron, P., & Zhu, X. (2005). Structural breaks with deterministic and stochastic trends. Journal of Econometrics, 129(1–2), 65–119.

    Article  Google Scholar 

  • Revenga, A. (1997). Employment and wage effects of trade liberalization: The case of Mexican manufacturing. Journal of Labor Economics, 15(S3), S20–S43.

    Article  Google Scholar 

  • Roberts, B., Hanson, G., Cornwell, D., & Borger, S. (2010). An Analysis of migrant smuggling costs along the southwest border (Working Paper, November). Department of Homeland Security Office of Immigration Studies. https://www.dhs.gov/xlibrary/assets/statistics/publications/ois-smuggling-wp.pdf.

  • Robertson, R. (2000). Wage shocks and North American labor-market integration. American Economic Review, 90(4), 742–764.

    Article  Google Scholar 

  • Robertson, R. (2004). Relative prices and wage inequality: Evidence from Mexico. Journal of International Economics, 64(2), 387–409.

    Article  Google Scholar 

  • Robertson, R. (2005). Has NAFTA increased labor market integration between the United States and Mexico? The World Bank Economic Review, 19(3), 425–448.

    Article  Google Scholar 

  • Robertson, R., Kumar, A., & Dutkowsky, D. (2009). Purchasing power parity an aggregation bias in a developing country: The case of Mexico. Journal of Development Economics, 90(2), 237–243.

    Article  Google Scholar 

  • Ruggles, S. J., Alexander, T., Genadek, K., Goeken, R., Schroeder, M. B., & Sobek, M. (2010). Integrated public use microdata series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota.

  • Schott, P. K. (2003). One size fits all? Heckscher–Ohlin specialization in global production. American Economic Review, 93(3), 686–708.

    Article  Google Scholar 

  • Tombazos, C. G., Yang, X., & Zhang, D. (2005). A Neo–Heckscher–Ohlin model of trade with endogenous production patterns. Economic Record, 81, S71–S81.

    Article  Google Scholar 

  • United States Census Bureau (2013). Trade in goods with Mexico. Retrieved April 8, 2013. http://www.census.gov/foreign-trade/balance/c2010.html.

  • Vogelsang, T. J., & Perron, P. (1998). Additional tests for a unit root allowing for a break in the trend function at an unknown time. International Economic Review, 39(4), 1073–1100.

    Article  Google Scholar 

  • Yeaple, S. R. (2005). A simple model of firm heterogeneity, international trade, and wages. Journal of International Economics, 65(1), 1–20.

    Article  Google Scholar 

  • Zong, J., & Batalova, J. (2014). Mexican immigrants in the United States. Migration Policy Institute. http://www.migrationpolicy.org/article/mexican-immigrants-united-states.

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Acknowledgments

We thank participants at the University of Hawaii Applied Micro Workshop, the Pacific Conference for Development Economics at UCLA, The LBJ School at the University of Texas at Austin, Tulane University, the Bush School at Texas A&M, the Chicago Fed and the Western Economic Association 2015 meetings in Honolulu for useful feedback. Finally, we would like to thank Kristin Butcher, John Kennan, and David McKenzie for useful discussions. This paper we previously circulated under the title “Globalization and Wage Convergence: Mexico and the United States”.

Author information

Authors and Affiliations

  1. Uppsala University, St. Olofsgatan 10 A, Uppsala, Sweden

    Davide Gandolfi

  2. Department of Economics, University of Hawaii at Manoa, Honolulu, HI, USA

    Timothy Halliday

  3. University of Hawaii Economic Research Organization, Honolulu, HI, USA

    Timothy Halliday

  4. IZA, Bonn, Germany

    Timothy Halliday & Raymond Robertson

  5. Texas A&M University, 1032 Allen Building, 4220 TAMU, College Station, TX, 77843-4220, USA

    Raymond Robertson

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  1. Davide Gandolfi
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Correspondence to Raymond Robertson.

Appendices

Appendix 1

See Table 8.

Table 8 Alternative wage measurements in the Mexican census
Full size table

Appendix 2: Alternative wage measurements

In the paper, we convert Mexican wages to 1990 dollars by, first, converting the wage to US dollars using the nominal exchange rate for that year and then by deflating the wage to 1990 US dollars using the US CPI. An alternative (and equally viable) procedure would have been to deflate the Mexican wages to 1990 pesos using the Mexican CPI and then converting the wage to 1990 dollars using the nominal exchange rate from 1990. We call the wage that results from the former method MX Wage 1 and the wage that results from the second method MX Wage 2.

The comparisons of MX Wage1 and MX Wage2 using the census data are reported in Table 9. The comparison of the mean value across cohorts of the two measures over time are shown in Fig. 11. As can be seen, the wages are very similar using the two methods of comparison. The raw correlation between the two in the census data is 0.9985 and 0.6936 in the household data indicating that it makes little difference if we use MX Wage 1 or MX Wage 2.

Table 9 Mean US wages including and excluding Mexican migrants
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Fig. 11
figure 11

Comparing two deflating measures in the household data. Notes The deflated Mexican pesos is the mean of the log of the Mexican monthly earnings deflated by the Mexican price index. The deflated US Dollars is the dollar value of Mexican monthly earnings deflated by the US CPI (1990 = 1)

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Gandolfi, D., Halliday, T. & Robertson, R. Trade, FDI, migration, and the place premium: Mexico and the United States. Rev World Econ 153, 1–37 (2017). https://doi.org/10.1007/s10290-016-0260-2

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