Chile, Colombia, Dominican Republic, Panama, and Peru can be attributed mainly to differences in returns to endowments, possibly reflecting barriers to migration due to shortages of affordable formal housing in these countries’ leading cities.<sup>21</sup> Only in Paraguay, the skilled income gaps can be attributed to differences in the endowments of the skilled households in the leading area and the rest of the country.

The rural income gaps with leading areas (Figure 7, Panel C) are much larger than the average (Figure 4) and the urban income gaps (Figure 7, Panels A). In most countries, these gaps can be primarily explained with deficits in portable endowments, especially education. Only in Bolivia and Peru, the gaps mainly reflect differences in returns to endowments rather than differences in portable household characteristics. In Brazil, the gaps are large and can be explained both by differences in endowments and differences in the returns to these endowments. Consequently, only in these three countries, there is still some scope for lifting incomes through rural-urban migration.

In most countries, the income gaps with the leading areas are insignificant or very small among the bottom 40% (B40) of households (Figure 7, Panel D). The gaps are negligible in Argentina, Chile, Costa Rica, Dominican Republic, and Uruguay and close to or below 25% in Colombia, Ecuador, Honduras, Mexico, and Paraguay. Only in Bolivia, Brazil, Panama, and Peru, the income gaps among the B40 are around 50% and can be explained mostly with differences in returns to endowments, not differences in endowments, indicating potential benefits from migration to the leading areas.

4.4.3 Income gaps with leading areas by gender One way to explore whether there are systematic differences in the income gaps with the leading areas between men and women is to estimate regression models (4) and (5) at the individual level for men and women, estimate (6) by gender, and compare the female and male income gaps in each country.<sup>22</sup> The results suggest that the differences between the male and female urban income gaps were relatively muted in the early 2000s (Figure 8, Panel A), except in Brazil, Mexico, and Uruguay. By the end of the 2010s, female urban income gaps widened in Bolivia, Colombia, Ecuador, Peru, and Paraguay, but only in Colombia, they deteriorated relative to the early 2000s.

The growing gender disparities in the income gaps with the leading areas cannot be explained with growing gender disparities among the skilled workers (Figure 8, Panel B). Among the B40, female income gaps became significantly larger than male income gaps only in Colombia, Mexico, and Uruguay (Figure 8, Panel D). In Colombia and Mexico, where we have information on individuals residing in rural areas, this development can be attributed to the increase in the female rural income gaps with the leading area. Female rural income gaps also opened in Paraguay and grew in Ecuador, Panama, and Peru. These results are consistent with evidence from the migration literature, which documents no change in the preferences of young migrants for large cities (Rodríguez and Busso 2009; Rowe, 2013), but a shift in the sex and education composition of domestic migrants to leading areas towards migrants who are male and educated (Rodríguez, 2004).

> 21 See Bastos (2017), who shows that in Brazil the deficit in formal housing has been growing, and potentially deterring skilled workers who might be more reluctant than unskilled workers to live in poor quality informal housing.

> 22 While the SEDLAC data are representative only at the household level, it is possible to conduct the analysis at the individual level for the purpose of comparing the income gaps by gender.

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