dummy variables indicating whether locations are close to the new stations within some range (i.e., 2100 meters or 25 minutes). Furthermore, in columns five to eight, I include municipality-time fixed effects and the results hold, suggesting that even after I compare locations to those within the same municipality, census tracts closer to new stations experienced a change in informality rates after the shock.<sup>23</sup> . Overall, the results suggest that informality rates decrease between 5.0 and 8.0 percent after the transit shock.

Table B5 in the Online Appendix reports the results for the share of informal firms. The results are similar to the ones for the share of informal workers. In particular, after the transit shock, informality rates decrease between 1 and 2.5 pp., which corresponds to a 2 to 3 percent decrease in informality rates when the mean in 1999 is used as a baseline. There are some issues with parallel trends since there are small effects but significant for 1999.<sup>24</sup> In the next two sections, I test the robustness of my results and show that in terms of observed covariates, there is a negligible change in the composition of households, which is a potential concern of my identification strategy. I also construct bounds using retrospective questions that ask where were you living before.

# **3.2.3 Robustness Checks**

For the robustness checks, I compare locations close to line B of the subway with locations near subway expansions that the Government planned to build in the 1980s or actually built years later. In particular, panel b of Figure 1 plots a map of Mexico City highlighting the three lines that I will compare in this section: Line B, which is the infrastructure project that I’m studying; line C, a feeder line, similar to line B, that was to connect northwestern locations in the State of Mexico with the center of Mexico City, but was never built; and Line 12, which is the latest subway line, opened in 2012.

I estimate the same difference-in-differences specification from equations 3.3 and 3.2. The only difference is that the treatment variable corresponds to a dummy variable indicating whether the centroid of the census tract is within some buffer zone of line B (i.e., 1500 meters), and similarly, the control group consists of locations within some buffer zone of line C and/or line 12. I run these regressions for four different buffers: 1500, 2000, 2500, and 3000 meters.

Figure A4 in the Online Appendix depicts the point estimates for the log of the ratio between formal and informal workers from equation 3.2. I find a similar pattern to the previous results. The log of the ratio between formal and informal workers increases by approximately 10% when I compare treated locations with census tracts close to the other two lines. As shown, in the graph, this finding is robust to the use of different buffer zones and is very stable.

> 23I also find similar results restricting the sample to census tracts with a centroid that is farther than 600 meters from one of the new stations. I also show that the results are similar if the dummy variable is constructed using a walking range of 20 minutes (Figure A11)

> 24One reason that may explain the effects in 1999 is that the Government announced the construction of the line in 1994.

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