WPS4249 the other hand, we find that in the typical Latin American country remittances slightly reduce inequality or leave it unchanged depending on the particular specification.

By combining the results on the effects of remittances on growth and inequality with initial country conditions, we find that remittances generally lower poverty. However, the elasticity of poverty reduction with respect to remittances differs significantly by country. For instance, we find that depending on the countries’ different initial levels of inequality and development, the percentage reduction in poverty for a 10 percent increase in the ratio of remittances to GDP could range from about .04 percent (poorer countries) to .5 percent (richer countries). Equivalently, considering than in the Latin American region remittances represent on average 4.9 percent of GDP, these results would imply that for every percentage point increase in the remittances to GDP ratio, poverty in the typical Latin American country would fall by about .37 percent.

As for our micro-econometric results, we find that in 8 out of 10 countries the observed Gini coefficient of per capita household income is smaller than the Gini that would prevail in the absence of remittances, for given non-remittances income. The changes, however, would be generally small, averaging less than 2 percent of the initial Gini<sup>8</sup> for the countries in which inequality is estimated to decrease as a result of remittances, and less than 0.2 percent in those in which it increases. For marginal changes in remittances, we find that in 6 out of 10 countries inequality would increase as a result of small ceteris paribus increases in those flows of income, a result that is driven by the fact that remittances are generally more unequally distributed than non-remittances income and with a few exceptions they have a high correlation with total income.

When imputing non-remittances income in the counterfactual scenario of non-migration, our results suggest that in six countries migration and remittances have an even less equalizing effect. However, in the other four countries, where migrants tend to come from the upper segments of the income and educational distributions, the evidence is quite the opposite, with migration and remittances now reducing inequality much more than before. As for the simulations of the poverty effects of remittances and migration, they show that attempts to estimate the poverty-reducing effect of remittances based only on the analysis of observed nonremittances income grossly over-estimate those effects. On average, when moving from the noremittances to the non-migration counterfactual scenarios, the reduction in extreme poverty as a result of migration and remittances falls from 14 to 3 percent and that in moderate poverty from 8 to 3 percent. Thus, the results based on micro data also indicate a moderate impact of remittances on poverty: on average for the 10 countries in our sample extreme and moderate poverty would fall by respectively 0.37 and 0.4 percent for every 1 percentage point increase in the remittances to GDP ratio, a finding that is surprisingly close to the one obtained on the basis of cross-country regressions.

The rest of the paper is structured as follows. In section 2 we review the empirical strategy adopted in our cross-country estimates, including a discussion on the links between changes in poverty, growth and inequality, and a summary of the challenges involved in the estimation of a dynamic panel data models with country specific effects. Section 3 presents the

> 8 Or about 1 percentage point for a typical Gini of .5.

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