sample who fall into each category, not the fraction of people in the preceding category who fall into each subcategory. For example, a value of 0.08 of the registered business owner dummy means that 8 percent of all people own and operate a registered business, not 8 percent of employed individuals.

I create six more dummy variables which split up the employed dummy, the wage earner dummy, and the registered business dummy into low-risk and high-risk registered businesses, using the industry information provided in the ENE and matching it to the low-risk and highrisk/regulated industries as speci...ed by COFEMER. Finally, I also use monthly income as an outcome variable. While the dummy variables are de...ned for everybody in my sample, income is available only for the gainfully employed and is missing for the unemployed, for individuals who are out of the labor force, and for unpaid workers.

The upper panel of Table 4a includes summary statistics for the outcome variables split up by early and late adopter municipalities, where these groups are de...ned as in Table 3 with early (late) adopters adopting the reform between May 2002 (April 2004) and March 2004 (December 2004). The data in Table 4a are for the pre-reform period, including only observations between 2000-II and 2001-IV. The averages in Columns 1 and 2 of Table 4a show that 66 percent of the people in my sample are employed<sup>13</sup> . Individuals who are employed fall into three categories - wage earners (who make up 50 percent of the population), registered business owners (8.4 percent) and non-registered business owners (7.9 percent). Most registered business owners are in low-risk/unregulated industries (7.3 percent), with only 1.1 percent of the population owning registered high-risk/regulated businesses.

The third column of Table 4a reports the di¤erences in pre-reform averages for early and late adopters. The di¤erences are small and not statistically signi...cant, except for log monthly income. Income is 17.7 percent higher in early adopter municipalities. However, as Column 4 of Table 4a shows, none of the outcome variables are systematically increasing or decreasing in the quarter of implementation.

As explained above, the required assumption for my estimations to be valid is that the changes of the outcome variables would not have di¤ered systematically between treatment and control municipalities during the treatment period if the reform had not occurred. While this assumption is fundamentally untestable, it is likely to hold if there are no initial systematic di¤erences in trends. To verify this, I report pre-period changes in outcome variables in Table 4b. The changes are calculated as 2000-IV to 2001-IV changes in municipality averages for each

> 13 Labor force participation is about 68 percent. The unemployment rate is at a low 2 percent. Measured unemployment tends to be low in Mexico since individuals count as employed even if they worked only one hour during the past week. There is also a very small fraction of people who I count as being in the labor force who are neither currenlty employed, nor unemployed, but who have a job lined up that they are planning to start within the next month.

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