brought investments and increased productivity in lagging, predominantly rural areas and the slowdown in productivity growth in more affluent, urban areas, where employment shifted toward less dynamic, low-productivity nontradables as cities de-industrialized (Jedwab et al., 2022). Convergence also narrowed the income gaps with leading metropolitan areas, including the gaps exploitable through migration to the top locations, especially among the bottom 40 percent. Still, at the end of the 2010s, there were sizable differences in per capita household labor earnings with the leading areas in nearly all countries, mainly reflecting differences in educational attainment, in line with the sorting of skilled workers in leading areas, but in a few countries large differences in the returns to endowments indicate potentially significant reutrns to migration to the leading areas, especially for residents of the poorest, remote regions. Rather than a clear rural-urban-metropolitan divide, the location-premia distributions of different locality types overlapped to a great degree and differences in the average location productivity premia in urban and rural areas were relatively small in most countries. While the places with the highest location premia were not necessarily the leading metropolitian areas, in all cases, they were among the top 25 percent of most productive localities.

The remainder of the paper is organized as follows. Section 2 reviews the literature. Section 3 discusses the methodology and the data, while Section 4 presents the empirical results. Section 5 summarizes the findings and offers conluding remarks.

# **2. The literature**

There is a large literature on the size and evolution of territorial differences in income and welfare in Latin America. Most studies that belong to this literature focus on one country or a limited set of countries, use data up to the early 2000s, and rely on per capita GDP data at the first administrative level (i.e. states, provinces, or departments). Most studies find evidence of absolute convergence at the first administrative level, albeit at a speed below the one observed in developed countries, in Brazil (Azzoni, 2001; Serra et al., 2006), Chile (Serra et al., 2006), Peru (Serra et al., 2006; Iacovone, SanchezBayardo and Sharma, 2015), and Colombia (Serra et al., 2006), but not in Argentina (Serra et al., 2006) and Mexico (Rodriguez-Pose and Sanchez-Reaza 2002; Chiquiar 2005; Serra et al., 2006). In the latter, convergence was observed up to the mid-1980s, but not afterwards. In spatially polarized countries, such as Brazil, Chile and Peru, convergence is found to be stronger within regional clubs.

A strand of this literature explores regional income dynamics by sector. Using sectoral value added data, Iacovone et al. (2015) find absolute convergence in the Peruvian manufacturing and mining sectors, but not in services and agriculture. Iacovone et al. (2015) attribute the lack of convergence in poverty rates across departments to limited reallocation of labor toward the converging sectors, while Sotelo (2020) suggests that this could also be due to substantial regional differences in farm income. He links these differences to spatial variations in trade costs and land quality and the practice of farmers to allocate land to many crops, which differ in land intensity. In Mexico, growth in tourism has also had uneven spatial effects. Faber and Gaubert (2019) show that the local economic effects of tourism are in part driven by significant positive spillovers from manufacturing. However, these local spillovers are mostly offset by reduced agglomeration econonomies in less touristic regions.

Another strand of this literature explores the effects of trade liberalization during the 1990s and early 2000s and increased demand for commodities on regional income dynamics. Chiquiar (2005) shows that NAFTA did not reverse the pattern of divergence in Mexico’s state per capita GDP between 1985 and 2001; it benefited states endowed with better human capital and infrastructure and hurt the states with less productive agriculture in the South. In Brazil, trade liberalization in the early 1990s led 4