schooling to the four health indicators measured above. In addition to this basic specification, we estimate a modified version of equation (4), where the indicator for remittances recipients is interacted with a dummy variable for the second quintile of the income distribution – using the counterfactual income prior to migration – and a dummy for households located in the third to fifth quintiles.<sup>12</sup> Table 10 reports the corresponding results, including the coefficients on free-standing dummy variables for the second through fifth income quintiles. As confirmed by our estimates, both weight- and height-for-age indexes tend to increase monotonically and significantly with household income, and so does the likelihood of doctor-assisted deliveries in the case of Nicaragua. Moreover, controlling for pre-migration income, children from households that report receiving remittances tend to exhibit higher health outcomes than those from non-recipients households with similar demographic and socio-economic characteristics. While the relatively small sample sizes make most of the estimated interactives between remittances and income quintiles non-significant from a statistical point of view, in most cases the results clearly indicate that the impact of remittances on children health is concentrated on low-income households located in the first quintile of the income distribution.

**<u>Table 10. Remittances and Health Outcomes</u>**

|Country||Guat|emala|||Nica|ragua||
|---|---|---|---|---|---|---|---|---|
|||||Child||||Child|
|Dependent Variable|Weight-for-<br>Age Z-Score|Height-for-<br>Age Z-Score|Received All<br>Vaccines|<br>Delivered by<br>Doctor|Weight-for-<br>Age Z-Score|Height-for-<br>Age Z-Score|Received All<br>Vaccines|<br> <br>Delivered by<br>Doctor|
|2nd Income Quintile|0.117**|0.141**|0.011|0.006|0.154*|0.230**|-0.028|0.104*|
||(0.058)|(0.060)|(0.011)|(0.015)|(0.085)|(0.091)|(0.047)|(0.060)|
|3rd Income Quintile|0.233***|0.385**|0.016|0.054***|0.077|0.327***|-0.011|0.085|
||(0.060)|(0.067)|(0.013)|(0.025)|(0.099)|(0.109)|(0.054)|(0.070)|
|4th Income Quintile|0.325***|0.479**|0.010|0.023|0.263**|0.594***|-0.126|0.168*|
||(0.073)|(0.076)|(0.016)|(0.023)|(0.117)|(0.113)|(0.062)|(0.079)|
|5th Income Quintile|0.594***|0.686**|0.026|0.013|0.352**|0.594***|-0.102|0.263**|
||(0.091)|(0.098)|(0.018)|(0.025)|(0.138)|(0.136)|(0.078)|(0.082)|
|Remittances|0.211**|0.213|0.065**|0.255***|0.306|0.289|0.119|0.297**|
||(0.089)|(0.228)|(0.021)|(0.160)|(0.394)|(0.347)|(0.225)|(0.090)|
|Remittances*Q2|-0.327|0.084|-0.082|-0.034*|-0.370|-0.079|0.034|-0.463*|
||(0.283)|(0.264)|(0.079)|(0.007)|(0.457)|(0.421)|(0.275)|(0.225)|
|Remittances*Q3-Q4-Q5|-0.423|0.004|-0.041|-0.036***|-0.252|-0.148|0.071|-0.623***|
||(0.272)|(0.253)|(0.071)|(0.006)|(0.418)|(0.385)|(0.252)|(0.114)|

Notes: *** Significant at 1% level. ** Significant at 5% level. * Significant at 10% level.

Regressions include the same set of controls as in Table 5. Source: Author’s calculations based on household surveys.

# **V. Conclusions**

This paper has explored the development impact of remittances in eleven Latin American countries. If we were to summarize the results of the paper into a few main messages they would be the following: (i) In general remittances appear to lower poverty levels in recipient countries.

> 12 We group the 3rd through 5th quintiles due to the relatively small sample size for some of the estimations.

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