Although, using the pooled data we find no evidence of significant agglomeration economies, the estimated elasticity of the city premium with respect to population density is both positive and statistically significant for Peru, Brazil, Ecuador, and Dominican Republic, as exemplified by the estimated 95 percent confidence intervals, which are shown by the blue lines in panel (a) of figure 5. In contrast, we estimate a significant negative elasticity for Chile and Nicaragua.

Meanwhile, for market access, the positive effect estimated in the pooled data is mainly driven by four countries: Ecuador, Brazil, Nicaragua, and Costa Rica. For the remaining 10 countries for which we report effects in figure 5, the impact of market access on city premium is not significantly from zero.

Finally, regarding human capital, the effect of average years of schooling on underlying productivity is positive and statistically significant for all countries. Even here, the estimated strength of human capital externalities varies dramatically across countries. Hence, we estimate extremely strong human capital externalities in Bolivia, but comparatively weak externalities in El Salvador, Nicaragua and the Dominican Republic. The effect of the percentage of workers with completed higher education is also positive in most countries, but it is not significant for some of the countries in Central America (Dominican Republic, Honduras and Nicaragua) and in Bolivia.<sup>35</sup> These elasticities are significantly larger than those corresponding to the variables representing the other two success theories.

We hypothesize that the heterogeneity in human capital coefficients may be related to educational quality. We estimate the linear relationship between the estimated human capital coefficients and PISA grades and find a significant positive relationship that would be consistent with this hypothesis (figure 6).<sup>36</sup> Unfortunately, not all the countries in our sample take the PISA exam, so we cannot test this relationship for the full sample. Additionally, we report the relationship between the human capital externalities effect and educational expenditure per capita<sup>37</sup> , which supports the idea that this quality, and hence the effect of human capital externalities, can be increased with public expenditure on education. The extent to which the estimated variations in the strength of human capital externalities are attributable to educational quality differences is an important area of future research.

> 35All results based on the percentage of workers with completed higher education are available upon request from the authors.

> 36PISA (Programme for International Student Assessment) is a triennial international survey which aims to evaluate education systems worldwide by testing the skills and knowledge of 15 and 16-year-old students. In the 2015 version, 28 million students in 72 countries took this exam. Only students at school are tested, not home-schoolers. A higher grade represents better performance. This exam is administered by the OECD. To fulfill OECD requirements, each country must draw a sample of at least 5,000 students (although most countries use a much larger sample). The dotted line is a line.

> 37This measure is obtained by dividing the current $US expenditure on education by the population of inhabitants younger than 14 years old. Education expenditure refers to the current operating expenditures in education, including wages and salaries and excluding capital investments in buildings and equipment and comes from the United Nations Statistics Division’s Statistical Yearbook, and the UNESCO Institute for Statistics online database. Population is based on the United Nations Population Division’s World Population Prospects.

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