medium enterprises.<sup>4</sup> The program was open to enterprises that were formally registered with the government and were paying taxes. In response to the advertising, 432 enterprises expressed interest in the program and signed a letter of interest.

Data comes from two sources: first, a baseline and follow-up survey of these interested enterprises was conducted between October and December 2007 (baseline) and between March 2009 and June 2009 (follow-up)<sup>5</sup> . These surveys collected information on enterprise characteristics and performance, as well as on business practices and characteristics of the enterprise’s principal decision maker (typically the owner or manager). Second, from the Mexican Social Security Institute (IMSS), we secured wage and employment data for two pre-intervention years (2005 and 2006) and for three postintervention years (2010, 2011, and 2012).

Using data from the baseline survey, 150 enterprises were randomly selected to participate in the program.<sup>6</sup> The randomization was stratified by sector (manufacturing, services, and commerce) and enterprise size (micro, small, and medium-sized)<sup>7</sup> , and was conducted through a Stata program that was run on the premises of IPPC in the presence of government officials and a public notary, who certified that the assignment to the treatment group was random, i.e., not re-run depending on any particular assignment.

> 4 We do not have data on the channel through which enterprises learned of the program, and thus cannot test any theories of heterogeneity with respect to this.

> 5 The baseline survey was conducted by a local professional survey firm under the supervision of the Mexico country office of IPA. For the follow-up survey, IPA hired surveyors (graduate students and recent graduates) directly. IPA trained the surveyors and our local project staff managed and supervised the implementation of the follow-up survey.

6 We originally had 434 observations in the randomization and assigned 150 of them to treatment, but we later discovered that two firms had expressed interest in the program twice under separate names. For this reason, we had to drop two observations, giving us 432 unique firms. In one of the cases, both separate names were in the control group, and we dropped one of these. In the other case, one name was assigned to the treatment group and the other to the control group. Here, we had to keep the firm in the treatment group since they had already been notified that they had been randomly selected to participate in the program.

7 Within strata, we re-randomized as follows. We first allocated firms to the treatment and control group based on a randomly generated number. Using this allocation, we then calculated the maximum and the average t-statistics on the differences in averages across the treatment and control groups for the following variables: Within Puebla City dummy, business age, total asset value, profit margin, measured risk aversion, entrepreneurial spirit index, currently has a loan from a financial institution dummy, principal decision maker’s hours worked, principal decision maker’s age, principal decision maker’s gender, principal decision maker’s years of schooling, principal decision maker is of indigenous background dummy, as well as two dummies indicating whether the firm has participated in other IPPC programs. If the maximum t-statistic for these variables was higher than 1.25 or the average t-statistic was higher than 0.35, we drew a new random number and allocated firms to the treatment and control group based on this new number. We repeated this process until the maximum t-statistic was 1.25 or lower and the average t-statistic was 0.35 or lower. Research by Bruhn and McKenzie (2009) that was conducted after our randomization finds that this way of re-randomizing is no longer the preferred method. In our data analysis, we make the necessary adjustments for the randomization method suggested by Bruhn and McKenzie, i.e., in our regressions we control for all variables used in the re-randomization.

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