equation (3) with selection controls for formality. In columns 6, 7, and 9, identification comes from the variation in time and information costs of formalizing, proxied by the self-reported distance to the municipal office, the nearest tax office, and whether the firm has had an inspection in the past year.<sup>16</sup> Because the profit equation (1) already controls for the parish-level averages of these variables—which should capture the distance to markets and major clients as well as the likelihood that a firm is located in an inspection-prone area—the firm-level variables should determine a firm’s formality status without having a direct impact on its profitability. However, because the instruments come from information reported by the firm itself, there is still a possibility that they are correlated with the unobservable determinants of profitability. In order to limit this possibility, column 8 of Table 1 shows the results of estimating a specification where parish-level average distances and whether or not a firm has had an inspection are used as instruments to limit a potential bias where less formal firms would tend to report distances less accurately. The results show that the relationship between formality and profitability remains robust, although the standard error of the formality coefficient is larger because the parish-level variables do not capture each firm’s individual circumstances as accurately. It should be mentioned, however, that none of the instruments are fully satisfactory because, unlike similar studies in Bolivia (World Bank, 2009) and Peru (World Bank, 2008), GPS equipment was not available to independently measure the distances to the municipal and tax offices.

The IV estimates reveal that several variables, such as education and guild membership, affect profitability mainly through their impact on formality. For example, unlike OLS estimates, only the highest level of education has a significant impact on profits. However, results from the first stage of analysis reveal that each level of education, beginning with complete secondary, is a statistically significant determinant of formality and the probability of formalizing rises with higher levels of education. Therefore, it appears that education affects profits mostly indirectly, through its effect on increasing the likelihood of formalizing. Similarly, guild membership does not significantly affect profits once its impact on formality—i.e., firms who are members of a guild are significantly more likely to be formal—is taken into account.

Formality is also positively associated with higher labor productivity. Column 10 of Table 1 provides the final robustness check on the results presented so far by regressing the log of revenue per worker—a crude measure of labor productivity—on the same set of independent variables as in the previous profitability regressions. Although the explanatory power of this model is much lower than the model of profitability, the significant positive relationship between formality and firm performance (in this case measured by output per worker) remains robust.<sup>17</sup>

> 16 The distance to the municipal office and the nearest tax (SRI) office was reported by the respondents themselves in hours and minutes of travel time, which is more comparable across the four surveyed cities (or even within cities) than geographic distance. In cases when respondents did not know the location of the nearest office or the travel time to reach it, they were assigned the maximum reported travel distance for their particular city. However, the results do not change substantially—i.e., the formality variable remains significant with a similar coefficient—if instead firms who reported not knowing the location or the distance are assigned the average distance to the municipal and SRI offices reported by other firms in the parish (see column 7 of Table 1).

> 17 Although Table 1 only shows the 2SLS results, the positive relationship between formality and output per worker also holds in OLS regressions.

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