are not correlated with the opening of line B. Furthermore, I also estimate lower bounds of the effect using retrospective questions, and in the quantitative framework, I consider this channel by allowing migration within the city. I use both jobs’ and workers’ informality rates as dependent variables.

I test first for changes in informality in terms of the locations in which the workers live. I use data from the Population Censuses and estimate the following specification relating the transit shock to the change in the ratio between formal and informal workers: where _Lis_ is the number of individuals that live in census-tract _i_ and sector _s_ , T _i_ is one of four different treatment variables: log distance in meters, log distance in walking minutes using the network of roads, a dummy variable indicating whether the closest station is within the 10th percentile of the Euclidean distance, and a dummy variable whether the closest station is within 25 minutes, _δs_ ( _i_ ) are state or municipality fixed effects,<sup>20</sup> and _Xi_ is a vector of census-tract characteristics that include distance controls such as: the area in square kilometers, distance to other stations of public transit, a central business district dummy variable, and some productivity measure in the baseline year in which I include value added per worker and the number of firms to capture how good is the location in terms of jobs. This equation relates the transit shock to the log of the ratio between formal and informal workers.<sup>21</sup> I estimate equation 3.2 for the pool of workers and for different groups based on skills.<sup>22</sup> Table 1 reports the results for different specifications of equation 3.2, while Figure A3 in the Online Appendix depicts the three-point estimates of my preferred specification for the pool of all workers, low-skilled workers, and high-skilled workers, respectively. Overall, the results imply that locations close to the new subway line experienced a decrease in workers’ informality rates. In particular, the ratio of formal to informal individuals increased between 3.0% and 6.9% after the shock. These results are robust to different specifications, for example, to the use of different definitions of the treatment variable or to the use of different sets of fixed effects or controls. In addition, in panels C and D, I control for the change in workers’ composition in terms of skills and report the results only for low-skilled workers. The estimates are very similar to the ones found for the entire pool of workers. For instance, the ratio between formal and informal low-skilled workers increased on average between 4.0% and 7.1%. Moreover, in panels E and F, I report the results restricting the sample to the areas not located in the CBD of Mexico City. The effects should be larger in these locations since more informal workers live in these areas. Overall, I find larger effects for this specification; the ratio between formal and informal workers increased by almost 10% in these areas.

> 20For the municipality fixed effects specifications, I classify locations in the State of Mexico into four different groups: northwestern, northeastern, west central, and east central for a total of 20 municipalities.

> 21Equation 3.2 corresponds to a structural relationship that I will derive from the model in section 5.

> 22One caveat of this specification is that I cannot test for parallel trends due to data constraints because I cannot observe the location of informal/formal residents before the 2000 Census.

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