# **. 5 4 The effect of access to infrastructure on employment and specialization**

We now turn to the estimation of the direct impact of local road improvements using measures of access to infrastructure that do not involve population or income. The focus on infrastructure only allows us to avoid the structural endogeneity problem of market access and market potential regressors. In these regressions, we also introduce measures of access to international markets to contrast the effects of local and international accessibility. Following Baum-Snow et al. (2017) and Emran and Hou (2013), we regress our dependent variable—employment or specialization—on both measures of accessibility. For the local access variable, we consider our measure of road efficiency units. For access to external markets, we calculate two complementary measures: the minimum travel time or the minimum travel cost to a major port and to the u.s. border.<sup>26</sup> To correct for the non-random placement of roads, we also instrument local accessibility by applying the doughnut approach (i.e., we instrument our road efficiency measure with a doughnut of efficient roads). Finally, we also run a cross-section regression where our infrastructure metric is instrumented by the 1949 efficient road length.

As in the previous section, first stage estimated coefficients are positive and significant, which means that our efficient road length measure is predicted by the appropriate instrument. Table 10 reports the estimates in the regression of employment on road length efficiency, where road is instrumented the Better local access efficient length using doughnut approach. to roads has a positive and statistically significant effect on employment. These effects are large: a 10 percent increase in efficient road length leads to a 6.7 percent increase in total employment. There are also heterogeneous effects across sectors: the increase in employment in the commerce sector (7.1 percent) is greater than in the services sector (6.0 percent) or in manufacturing (4.3 percent).

As for access to external markets, a decrease in travel costs to the nearest u.s. border is positively associated with an increase in employment in each sector. We find that a 1 percent reduction in travel costs to the nearest u.s. border leads to a 1.9 percent increase in manufacturing employment, a 1.2 percent increase in commerce, and a 0.7 increase in services. These results are supported by the fact that the United States is, by far, Mexico’s leading partner in merchandise trade, and most of the Mexico-u.s. trade is through trucking. Note, however, that the impact of a reduction in travel costs to the nearest port is not positively associated with an increase in employment but with a decrease (for manufacturing in particular). An could be that travel costs to the u.s. facilitates and attracts em- explanation reducing exports ployment, whereas reducing travel costs to ports exposes industries to more competition and has a depressing impact on employment, especially in the manufacturing sector. Interestingly, when interacting with the nafta dummy (see Table 16 in Appendix C), we find that these two

> 26Minimum travel cost is calculated using the same calibrated trade cost function as in our market potential formula.

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