productivity (Panel A) and log sales (Panel B) on formality status and controls for industry and urban location. The horizontal lines in the pictures are OLS coefficients (measuring conditional correlations at the mean of the distribution), while the green lines plot the quartile regression coefficients. The shaded areas are the conditional confidence intervals. The graphs suggest that both coefficients are positive all along the distribution. The figures might suggest that the coefficients may be larger at the low end of the distribution for log productivity and at the top of the distribution for log sales.

To assess whether this is the case, several tests of equality of coefficients were carried out:

- For log productivity, equality of the coefficients at the 10<sup>th</sup> and 50<sup>th</sup> percentiles is rejected at the 5 percent level. However, this conclusion needs to be qualified because the number of formal firms in the lowest decile is very small (3 to be exact). Equality of coefficients at 10<sup>th</sup> and 90<sup>th</sup> percentiles, at 25<sup>th</sup> and 75<sup>th</sup> and 25<sup>th</sup> and 90<sup>th</sup> cannot be rejected.

- For log sales, none of the tests of equality can be rejected.<sup>10</sup>

Overall, evidence therefore suggests that the productivity and sales gaps between formal and informal firms are quite uniform across the distributions of productivity and sales. It is interesting to note that the formality/informality composition of firms changes sharply in different deciles of productivity and sales. For example, while out of 51 firms in the top productivity decile, 62 percent are formal (32 firms), this ratio drops to 6 percent (3/53) in the bottom decile. Further evidence on the average gaps in performance between formal and informal firms is provided in section 4.

# **_3.4 Formal versus informal employment_**

Informal workers are typically defined as those who do not have a formal employment contract. The RIA data allow a description of the prevalence of this type of firm as well as a characterization of their performance relative to firms that offer at least some of their workers a written employment contract. Out of the 517 firms in the full sample, just under one-half (249 or 48%) employ at least one full-time employee. Of these, as highlighted in Table 3, just over 10 percent (33 out of 249 or 13%) offer a written employment contract, denoted as “formal worker-employing firms”. Interestingly, roughly 20 percent of these firms (7 out of 33 or 21%) are informal firms, that is, unregistered at local and/or national levels.

**Table 3: Distribution of employment (in)formality variable across worker-employing firms**

||Has at least 1<br>employee with formal<br>contract?||
|---|---|---|
|For firms with 1+ workers|No<br>Yes|Total|
|informal firms|110<br>7|117|
|formal firms|106<br>26|132|
|Total|216<br>33|249|

Note: Unweighted data. The question is: “How many of your employees have a written employment contract?” 10 Quantile regressions were carried out at finer intervals as well. For log productivity, when regressions are carried on the quintiles of the distribution (20 intervals), results suggest that the productivity gap between formal and informal firms are larger at the bottom of the distribution relative to the middle and the top. We have more confidence in the results reported in the text because as the intervals get smaller, the number of formal firms at the bottom becomes very small.

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