uncertainty. Figure 2 thus implies that for an importer operating in a particular sector and in a specific region, for example Latin America and the Caribbean, the effective clearance time might be significantly longer than suggested by a simple average. Cross-country disparities are further investigated in Figure A1 in the Appendix. We find evidence of significant differences in the distribution of import clearance times, with countries such as Albania or Romania displaying close-to-zero interquartile ranges whereas 50 percent of Ivorian importing firms reported experiencing 13 to 60 days of delay in clearing imported inputs through Customs. Consistent with Volpe Martincus (2016) who argues that using distributions rather than point estimates allows improvements to the measurement of border clearance times given the heterogeneity of border times across observations, these stylized facts clearly suggest that relying on a single, average-type measure of time to import is not appropriate to fully grasp the uncertainty that firms face when importing their inputs.

# **2.2 Export Dynamics**

We match the WBES with a rich array of variables drawn from the Exporter Dynamics Database (EDD). The latter contains measures of the degree of product and market export diversification, firm dynamics in terms of entry, exit and survival in export markets, as well as the average unit prices of the products they export over the period 1997-2014 (Fernandes, Freund, and Pierola, 2016). Our analysis focuses on the export dynamics of manufacturing firms at the country-destination-sector-year level.<sup>21</sup> More specifically, we investigate whether uncertainty in import clearance times affects firm entry, exit as well as first-, second- and third-year survival rates in export markets. Out of the 72 developing countries originally present in EDD, 48 were successfully matched with the WBES. Since the latter are only conducted every four to six years and data collection takes over a year, we allow matching EDD data with up to three years backward or forward relative to the WBES to enhance the size of the final dataset. Table A2 in the Appendix displays the list of countries included in the analysis along with the corresponding time adjustments, if applicable.

Figure 3 presents preliminary evidence of the relationship between uncertainty in the duration of the import process and firms’ export dynamics in developing countries. Once country, destination, sector and year fixed-effects are accounted for, increases in import uncertainty appear to be significantly associated with higher exit rates of exporters and lower probability of entering exporters to survive past the first year of exports, thereby hinting at a potential adverse effect on firms’ exporting status. However, Figure 3 also suggests a positive correlation between import uncertainty and firm entry rates in export markets. Taken together, these scatter plots seem suggestive of export experimentation and failure leading to a substantial turnover rate or churning as firms enter and exit export markets, yielding low survival rates (Brenton, Saborowski, and von Uexkull, 2010; Brenton, Cadot, and Pierola, 2012). We hypothesize that such dynamics are driven by uncertainty in the time to import. Specifically, we conjecture that unpredictability in border clearance times for key inputs disrupts the production process, making the importing exporter likely to miss delivery deadlines. If such incident happens frequently, exporting firms risk losing their credibility as reliable suppliers, and time-sensitive buyers may decide to terminate

> 21We thank Ana Margarida Fernandes and Hibret Belete Maemir for kindly computing the EDD statistics at the countrydestination-sector-year level.

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