I choose the ENE data as my outcome data since it has ...ve important features for this study. First, it covers almost all municipalities that implemented the reform. Second, the quarterly frequency of the data allows me to exploit the staggered implementation of the reform in the identi...cation strategy. Third, the ENE includes detailed questions about a person’s economic activity (including self-employment). Fourth, the ENE captures and distinguishes between formal and informal employment and ...rms. Fifth, the panel structure of the ENE allows me to investigate who is a¤ected by the reform.

It is important to point out that the way the ENE sample is constructed implies that a municipality-year average is not necessarily representative of the municipality in that year. The sample selection procedure randomly selects households at a geographic unit, the AGEB (Basic Geo-Statistical Area), that is smaller than the municipalities in my sample. All AGEBs within a state are ...rst strati...ed by socioeconomic characteristics. Within each strata, a certain number of AGEBs is chosen at random. Then, households are chosen at random within the AGEB. This procedure implies that it could happen that only some socioeconomic groups get selected in a given municipality in a given year. However, since the strata are randomly chosen, this remains in expectation a random sample of the households in a municipality, so that the estimate should remain unbiased. Moreover, the survey includes several di¤erent strata for most of the municipalities in my sample.

An alternative to using ENE data would have been to use administrative data from business registries. This data is, however, not readily available for Mexico since municipalities do not follow a uni...ed system of recording registered ...rms. Many records are paper records held only at the local registry and are not publicly available. Moreover, some municipalities updated to an electronic system after the reform, suggesting that the reform also impacted record keeping, which may make pre- and post-reform records incomparable. Finally, unlike the ENE, registry data would not include pre-registration information on ...rms, such as whether they existed in the informal sector.

Since I am looking at labor market outcomes, I keep only individuals of working age (between the ages of 20 and 65) in my sample. I construct three of my main outcome variables by creating dummy variables for each person in the sample, which indicate whether the person a) is employed, b) is a wage earner, and c) owns a registered business<sup>12</sup> . The later dummies encompass subcategories of the earlier dummies, in the sense that everybody who is employed can either be a wage earner or a business owner (I include the self-employed in the category business owners). Business owners can either be registered or unregistered. However, since all dummies are de...ned for the whole sample, they denote the fraction of all individuals in my

> 12 The Appendix includes a description of how I constructed these dummy variables, paying particular attention to the way business registration is measured in the ENE and explaining some caveats.

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