# **5.1 Does Apex assistance promote new exporters?**

Due to the fact that Apex’s data starts in 2007, I have no information on firms’ treatment status for the previous years. Hence, in the baseline specification I focus on firms that received their first assistance after 2007.<sup>50</sup> Let us start with a pooled OLS (ordinary least squares) estimation (see table 5). Columns (1) and (2) show the marginal effect of Apex’s treatment for the propensity to export in _t+1_ on a sample of non-exporting firms.<sup>51</sup> Due to the nonlinearity in the outcome, I compared the predictive margins between control and treated groups at the mean. Under pooled OLS the effect of Apex without additional covariates (column 1) is 3.4 percentage points (pp). The propensity to export in the full sample of non-exporting firms is very low (0.78%) and the estimation suggests that Apex’s assistance increases by 4.37 times the chance of a non-exporting firm to become an exporter. If additional covariates are included (column 2) the treatment effect accounts for 2.36 times the chance of becoming an exporter. Columns (3) and (4) show that when controlled for firms’ fixed effects (FE) the coefficient of Apex is remarkably smaller than in the pooled OLS. In this case, the treatment Apex increases the propensity to export in 0.9 pp, which is approximately 54% (column 3). When additional covariates are included, it increases the export propensity by 105%.

Columns (5) and (6) show the pooled OLS estimation for the contemporaneous effect (propensity to export in the year that firms received the treatment). Apex’s treatment increases the export propensity in period _t_ in 3.4 pp and 2.4 pp respectively for the specifications without and with additional covariates. This accounts for 4.3 and 2.6 times the chance of export, if compared with the control group. For the contemporaneous effect, the FE estimator is slightly smaller when there are no additional covariates at the firm level - columns (5) and (7) - but it is larger when all covariates are included - columns (6) and (8). Moreover, the magnitude of the coefficients for the pooled OLS or FE estimators are relatively similar under contemporaneous effect, which may be expected due to the exclusion restriction.<sup>52</sup> The specifications in columns (7) and(8) account for an increase of about 2.6 and 2.9 times the chance of exporting. Most of the coefficients are positive and statistically significant at 1%.

> 50This procedure allows me to exclude firms that received the program in period _t-1_ from the control group. In section 7.3 of the Appendix, I present results keeping the treated firms in 2007 under the assumption that those firms did not receive the program in the previous year.

> 51Firms that had not exported in the previous two periods.

> 52Because my population of interest is composed of non-exporting firms, I imposed a parallel trend on previous exporting status. If we assume that the main issue regarding selection bias is due to firms’ characteristics that are unobservable to an econometrician and can affect both the outcome and the treatment status, this exclusion restriction itself already aims to deal with the selection issue.

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