the dummy variables of whether the worker commutes to another municipality; and whether he/she works in Mexico City. The results imply that informal workers spend less time commuting. For instance, the probability of commuting to a different municipality, decreases on average, between 8.0 and 25.0 percentage points for informal workers. Similarly, informal workers are less likely to work in the CBD between 4.0 and 9.0 percentage points. In the fourth column, I show that differences in transportation modes are not driving these effects.

Overall, the results from Table B1 and Figure 2 suggest that informal workers spend less time commuting. One potential interpretation of this result is that informal jobs are easier to substitute across locations than formal ones.<sup>18</sup>

**_Finding 2:_** _Most formal jobs are located in the central areas of the city, while most informal workers reside in the outskirts._

The second finding is that most formal jobs are available in the center and west of the city, while informal workers reside in other, less connected areas. As a consequence, workers that cannot afford the high rents in the center of the city, live in outlying areas with poor access to formal jobs.

Figure 3 presents a heat map of informality rates in Mexico City and adjacent municipalities in the State of Mexico in terms of jobs and the residence of workers. Panel A in figure A10 in the Appendix shows that the west and the center of Mexico City have the highest level of economic activity.<sup>19</sup> Combining these two figures, we see that informality rates are lower in the west and the center of the city than in the east and the periphery of the city. This suggests that workers who live in remote locations usually have poorer access formal employment.

# **3.2.2 Difference-in-Differences Specification**

**_Finding 3:_** _Informality rates decline with transit improvements that improve market access of formal employment to informal workers._

I now exploit the construction of line B of the subway in Mexico City by estimating a series of difference-in-differences specifications. I compare locations close to the new subway line with locations in the rest of Mexico City and test whether those that improved their market access experienced a change in informality rates after the transit shock while controlling for initial characteristics. One feature of line B is that it connects remote locations in the State of Mexico, close to Ecatepec de Morelos, with the city’s center. The identification assumption is that the opening of the new stations is uncorrelated with local demand/supply shocks. The fact that most of the line was planned decades earlier makes this assumption plausible. Moreover, since the construction of infrastructure may be endogenous (Redding and Turner, 2015), I include a set of covariates as controls to compare similar areas. Another potential concern to the identification is sorting given by a change in the residents that prefer to work in the formal sector. I show in the next section that household characteristics

> 18This interpretation would be later corroborated by estimating gravity equations.

> 19Panel B in figure A10 shows that the labor wedge in these locations is higher.

11