International at the University of Minnesota. In both cases, the census questionnaires include a module on income in addition to the standard questions on household and individual characteristics. Furthermore, the harmonization protocol ensures the comparability of geographical units across census years. In all other country cases, we use the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), which includes country harmonized household surveys jointly constructed by the Center for Distributive, Labor and Social Studies (CEDLAS) at the Universidad National de La Plata and the World Bank’s Poverty Group for the Latin America and the Caribbean region.<sup>11</sup> Most countries have conducted the surveys on an annual basis since 2000, but the frequency varies by country.<sup>12</sup> Only in Colombia, the analysis at the 2<sup>nd</sup> administrative level relies on per capita value-added data for the last ten years from the National Administrative Department of Statistics (DANE). Since neither the value-added data source, nor SEDLAC provides household information, it is impossible to estimate place productivity premia after sorting in Colombia.

The criteria for selecting survey years included the availability of information to harmonize geo-codes across survey years at the lowest possible administrative level and maximize the number of surveyed locations across time. Two to three consecutive surveys were selected to have adequate coverage at three specific time periods in the past twenty years: the early 2000s, the late 2000s, and the late 2010s. Thus, the sample includes only countries with enough information to identify sub-national administrative units, ensure comparability across space and time, and minimize standard errors of point estimates at lower administrative levels.

In some instances a particular survey was not used for reasons not mentioned above. A decision was made to exclude the 2000 Panama survey to minimize location re-coding. From 2001 onwards, Panama’s administrative units remained stable up to 2017. El Salvador was also excluded from the analysis because of potential issues related to the switch in currencies in the early 2000s. Choosing 2005 as the initial period did not help because this resulted in a substantial decline in the number of surveyed locations available in 2005 and at the end of the 2010s, which biases the estimation of the location premia. Appendix Table A2 summarizes information on data sources, level of geographic detail, and time coverage.

The income gap analyses employ only household survey data, which, unlike the census data, extend all the way to the end of the 2010s. In most countries, we are able to match the first and last periods in the income gap analyses with the first and last periods in the estimation of location premia. By linking the two types of analyses, we are able to perform consistency check (7).

We deflate labor earnings to address price variations across time and space and to ensure that the results are comparable both within and across countries. First, we convert labor income into constant 2011 US$ PPP. We then adjust the converted income to reflect differences across subnational regions, and whenever possible different types of areas within subnational regions (i.e., rural versus urban). Appendix Table A3 provides information on the data used to calculate the deflators.<sup>13</sup> Descriptive

> 11 See https://www.cedlas.econo.unlp.edu.ar/wp/en/estadisticas/sedlac/

> 12 Appendix Table A5 provides information on the year and sample size by country. In the case of Argentina, the surveys cover only urban areas so the categories are reduced to all urban residents, the bottom 40% of urban residents, and skilled urban residents. In the case of Uruguay, the surveys cover primarily urban areas.

> 13 In the absence of a deflator for a particular year, the deflator for the next closest year was used (case of Ecuador 2004, Panama 2010 and 2012). https://statistics.cepal.org/portal/cepalstat/index.html?lang=es.

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