Table 7: Heterogeneous effects of determinants of location premium productivity across sub-groups of workers<sup>a</sup>

||Young|Old|Male|Female|Private|Public|Formal|Informal|
|---|---|---|---|---|---|---|---|---|
|Population|-0.001|0.004|0.006|-0.001|0.002|0.012|0.004|-0.002|
|density (ln)|||||||||
|Avg. years|0.466***|0.580***|0.541***|0.495***|0.548***|0.172*|0.559***|0.401***|
|schooling (ln)|||||||||
|Market|0.014***|0.01|0.011*|0.008|0.018***|-0.001|0.019***|0.004|
|access (ln)|||||||||
|Constant|-2.554***|-2.392***|-2.356***|-2.281***|-2.586***|-0.804***|-2.349***|-1.565***|
|n|3,756|3,757|3,758|3,754|3,758|3,440|3,758|3,732|
|Adj. _R_<sup>2</sup>|0.79|0.744|0.689|0.675|0.717|0.68|0.668|0.687|

> a _∗∗∗p <_ 0 _._ 01 _, ∗∗ p <_ 0 _._ 05 _, ∗p <_ 0 _._ 1. In all columns, country effects have been controlled for and standard errors have been clustered by country. In all columns, the dependent variable is the estimated location premium (measured in natural logs) from a series of country-level first-stage regressions after controlling for observable worker characteristics within the broad sample (all wage/salary employees aged from 14 to 65 years old) and survey-year fixed effects. Worker characteristics include age, age-squared, marital status, gender, and years of schooling. The source of the population data is the Gridded Population of the World (GPW), v4.

smaller than for Private -v- Public Sector and Formal -v- Informal workers, differences can also be observed in the estimated elasticity of the city premium with respect to average years of schooling for Young -v- Old and Male -v- Female workers. Old workers appear to experience stronger human capital externalities than Young workers, while Male workers benefit from stronger human capital externalities than Female workers.

In the case of market access, the estimated elasticities are close to zero for public sector and informal workers, and statistically insignificant. Market access benefits more the productivity of workers in Formal and Private firms. This would be consistent with these types of firms selling to other regions in the country more and benefitting more from cheaper inputs brought from elsewhere. Market access also has an insignificant impact for both Old and Female workers. However, the estimated elasticities in both cases are much closer to those estimated for Young and Male workers respectively, which are statistically significant at the 10 percent level or better.

Finally, population density exerts a negligible, and statistically insignificant, impact on city premiums for all sub-groups of workers.

# **5 Conclusions**

This paper contributes to filling a knowledge gap on agglomeration effects and the determinants of sub-national spatial variations in productivity for developing countries by providing estimates of city sector that cannot be fully explained by worker characteristics. Brassiolo et al. (2016) find that the gap remains even when other unobservable characteristic, like motivation for public service and effort, are taken into account, for the same countries that we study here (except for Dominican Republic, Guatemala, and Nicaragua). Furthermore, they show that the public sector in Latin America exhibits more non-wage benefits and stability, more stable wages as careers progress, fewer performance based contracts, and more non-market regulations that govern their evolution, which further suggest the structurally different relationship between productivity and wages in the private and public sectors.

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