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New evidence on the role of remittances on healthcare expenditures by Mexican households


Using Mexico’s 2002 wave of the Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH), we find that international remittances raise health care expenditures. Approximately 6 pesos of every 100 peso increment in remittance income are spent on health. The sensitivity of health care expenditures to variations in the level of international remittances is almost three times greater than their sensitivity to changes in other sources of household income. Furthermore, health care expenditures are less responsive to remittance income among lower-income households. Since the lower responsiveness may be partially due to participation of lower-income households in public programs like PROGRESA (now called Oportunidades), we also analyze the impact of remittances by health care coverage. As expected, we find that households with some kind of health care coverage—either through their jobs or via participation in PROGRESA—spend less of remittance income increments on health care than households lacking any health care coverage. Hence, remittances may help equalize health care expenditures across households with and without health care coverage.

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  1. 1.

    See Migration Policy Institute (2007) for evidence of recent declines in remittance inflows at the Mexican-state level.

  2. 2.

    PROGRESA and Oportunidades transfers are conditioned on recipients’ participation in basic health and nutrition programs, as well as on children’s educational attainment.

  3. 3.

    However, as of 2002, it was still estimated that between 40 and 60% of the Mexican population was “uninsured” (de Salud 2002; Frenk et al. 2003).

  4. 4.

    In 2005, with the purpose of addressing the still large number of uninsured individuals, the Mexican government approved Seguro Popular, a narrower program that is intended to simply focus on increasing access to health care services. There is no condition to participate aside from a small yearly premium, which then gives participants the right to specified health services. By the end of 2007, over 7 million families were covered by Seguro Popular and over time the program is expected to encompass more segments of the population (de Salud 2008 at

  5. 5.

    Table 7 in the appendix contains the descriptive statistics of the variables used in the analysis.

  6. 6.

    We delete those observations in the top 2% of the remittance income and other household income distributions in order to eliminate a number of implausible observations.

  7. 7.

    The division of households into lower-income and higher-income groups is determined by summing all sources of household income, except for remittance income. Households with total incomes (excluding remittance income) equal or below the median are characterized as lower-income households, while those with incomes (excluding remittance income) above the median are considered higher-income households.

  8. 8.

    As noted by Wooldridge (2003, pp. 89–93), the sign of the omitted variable bias depends on the sign resulting from interacting the expected sign of the coefficient that the omitted variable would have in the health care expenditure equation (i.e. βwealth > 0 or βHealth < 0) and the sign of the correlation between remittances and the omitted variables in question (e.g. corr(RE, wealth) < 0 and corr(RE, Health) < 0). Hence, depending on the relevance of various omitted variables in driving both household remittances and health care expenditures, the bias can either be positive (as in the case of missing information on the household’s health stock) or negative (as in the case of missing information on household wealth).

  9. 9.

    For example, in the state of Durango, the MMP indicated that in 2002 about 31% of emigrants resided in California, 28% resided in Texas and 26% in Illinois. Therefore, we compute the average US wage for emigrants from Durango as follows: [0.31 × (California wages in 2002) + 0.28 × (Texas wages in 2002) + 0.26 × (Illinois wages in 2002) + 0.15 × (average US wages in 2002)].

  10. 10.

    For instance, wealthier households to be more likely to place migrants in economically more attractive US states.

  11. 11.

    Results are available from the authors.

  12. 12.

    Using the Breusch-Pagan/Cook-Weisberg test for heteroscedasticity (where: H0:constant variance), we get a test statistic: χ2(1) = 0.27 with P > χ2 = 0.6034 when we do not instrument remittance income and a test statistic: χ2(1) = 0.40 with P > χ2 = 0.5283 when we do. Hence, in both instances, we fail to reject the null hypothesis of a homoscedastic error term.

  13. 13.

    The skewness/kurtosis tests for normality indicate that the log-scale error is not normal with P > χ2 = 0.0000 regardless of whether we instrument or not for remittance income. Hence, in both instances, we reject the null hypothesis of a normally distributed error term.

  14. 14.

    Other findings are as expected. For instance, female headed households, larger families, and households with a larger number of young children or elderly members receive greater remittance transfers. In particular, female headed households receive 105 more pesos per quarter relative to male headed households. Each additional household member raises remittance inflows by 18 pesos per quarter (although elderly members raise household health care expenditures to a greater extent than young children). Additionally, families residing in rural areas, in states that have experienced more out-migration, and in states where emigrants earned higher US wages also enjoy larger transfers. In contrast, richer households, households with more working members, as well as those living further from the US border, receive smaller remittance transfers from abroad than poorer households, households with fewer working members, and households closer to the US border, respectively.

  15. 15.

    As noted earlier, the non-IV estimates are likely to be biased owing to the endogeneity of remittances stemming from omitted variables biases. In this particular case, the non-IV estimates appear to be biased downwards. This means that variables, such as household wealth (in the form of housing, land or similar assets), which are positively linked to health care expenditures, yet inversely related to remittance inflows, play a significant role in downward biasing the non-IV estimates.

  16. 16.

    Other variables also display the expected effects. For instance, increments in other sources of household income also raise health care expenditures as would be expected for a normal good. Female headed households are less likely to incur health care expenditures; however, their health care expenditure amounts do not seem to significantly differ from those of non-female headed households. In contrast, the number of young children and the number of elderly members raise both the likelihood of incurring health care expenditures as well as their levels. It is, perhaps, for the same reason that, while a larger number of working members increases the household’s financial access to health care and, as such, the likelihood of incurring such expenses, a larger number of working individuals—who are less likely to be young children or elderly members—is associated with lower household health care expenditures. Finally, household location matters. Rural households incur smaller health care expenditures than urban households, possibly due to differences in the proximity and availability of health care services. Additionally, households residing in Mexican states with more out-migration are more likely to incur health care expenditures and spend more on such services. This could be, in part, due to the transmission of health knowledge and the dissemination of certain health practices and behaviors by migrants to their families back home (Kanaiaupuni and Donato 1999; Frank and Hummer 2002). Lastly, households in richer states, as captured by their per capita GDP, are also more likely to spend on health care even if, possibly linked to differences in their health practices or access to coverage, their health care expenditures appear to be slightly lower.

  17. 17.

    Because the division of households by income may seem arbitrary, we also distinguish households according to whether their incomes fall below or above the mean. Likewise, we also try limiting the analysis to households in the lowest and highest income quartiles. Our results are robust to these alternative specifications.

  18. 18.

    Complete results are available from the authors.

  19. 19.

    Since our data refer to 2002, no families at the time were enrolled in other government programs described earlier, such as Seguro Popular.


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Correspondence to Catalina Amuedo-Dorantes.



See Tables 7 and 8.

Table 7 Means and standard deviations of variables used in the regression analysis
Table 8 Tobit model of remittance income

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Amuedo-Dorantes, C., Pozo, S. New evidence on the role of remittances on healthcare expenditures by Mexican households. Rev Econ Household 9, 69–98 (2011).

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  • Remittances
  • Household expenditures
  • Healthcare
  • Mexico

JEL classifications

  • F24
  • I1