line with the literature, exporting firms present specific characteristics that distinguish them from their non-exporting counterparts (see for example the discussion by Bernard and Jensen (2007)). In particular, they tend to be older, larger and more productive, and this is also broadly verified across all five export industries.

Table 1: Selected Characteristics of Firms by Exporter/Importer Status and by Export Industry

||||Exporters|||Non-Exporte|rs|
|---|---|---|---|---|---|---|---|
||All Sample|All Exporters|Importing<br>Exporters|Non-Importing<br>Exporters|All Non-<br>Exporters|Importing<br>Non-Exporters|Non-Importing<br>Non-Exporters|
|||**Aggre**|**gate Manufa**|**cturing Industry**||||
|Number of frms|16,475|5,407|4,349|1,058|11,068|4,551|6,517|
|_% of sample_|100%|30.0%|73.7%|26.3%|70.0%|35.6%|64.4%|
|Age (years)|19|23|23|20|17|20|16|
|Size (nb. of employees)|114|246|287|130|58|103|33|
|TFP|1.75|1.91|1.94|1.84|1.68|1.85|1.58|
||**M**|**anufacture of **|**Food, Bever**|**age and Tobacco**|**Products**|||
|Number of frms|3,471|959|768|191|2,512|886|1,626|
|_% of sample_|100%|22.94%|80.8%|19.2%|77.1%|38.7%|61.3%|
|Age (years)|23|31|32|27|21|22|21|
|Size (nb. of employees)|144|258|286|138|110|206|49|
|TFP|157|186|193|156|149|160|140|
||.<br>**M**|.<br>**anufacture of **|.<br> **Textile and **|.<br> **Leather-Related **|.<br> **Products**|.|.|
|Number of frms|4,489|1,896|1,468|428|2,593|846|1,747|
|_% of sample_|100%|38.6%|68.6%|31.4%|61.5%|27.7%|72.3%|
|Age (years)|16|18|19|16|15|18|14|
|Size (nb. of employees)|174|347|424|181|65|131|39|
|TFP|1.63|1.70|1.62|1.86|1.60|1.67|1.57|
|||**Manufac**|**ture of Woo**|**d-Related Produ**|**cts**|||
|Number of frms|1,224|265|200|65|959|399|560|
|_% of sample_|100%|21.7%|66.1%|33.9%|78.3%|30.7%|69.3%|
|Age (years)|20|24|23|26|19|22|17|
|Size (nb. of employees)|48|87|101|57|37|78|20|
|TFP|1.75|2.15|2.27|1.87|1.62|1.90|1.51|
|||**Manufacture**|**of Minerals**|**, Metals and Ch**|**emicals**|||
|Number of frms|5,232|1,697|1,469|228|3,535|1,818|1,717|
|_% of sample_|100%|31.6%|78.7%|21.3%|68.4%|44.2%|55.8%|
|Age (years)|20|24|24|23|18|20|17|
|Size (nb. of employees)|103|213|242|107|52|77|33|
|TFP|1.94|2.05|2.12|1.74|1.88|2.01|1.77|
|||**Manuf**|**acture of A**|**dvanced Product**|**s**|||
|Number of frms|2,059|590|444|146|1,469|602|867|
|_% of sample_|100%|24.5%|73.2%|26.4%|75.5%|33.2%|66.8%|
|Age (years)|17|23|24|20|15|19|13|
|Size (nb. of employees)|58|141|167|66|31|50|22|
|TFP|1.69|1.85|1.77|2.05|1.64|1.90|1.51|

Notes: Authors’ calculations based on the World Bank Enterprise Surveys. Descriptive statistics computed using survey weights, except for the number of firms. Sample restricted to firms that reported a positive or null number to question d3c _”What percentage of this establishment’s sales were direct exports?”_ and to those that replied yes or no to question d13 _”Were any of the material inputs or supplies purchased [...] imported directly?”_ of the Manufacturing Module. Included firms are those located in the 48 developing countries retained in the empirical analysis (see Section 2.2 and Table A1 in the Appendix). _Age_ is the number of years since the firm began operations; _Size_ is the number of permanent, full-time employees; _TFP_ stands for total factor productivity.

The explanatory variable of interest is captured by the interquartile range of the average number of days to clear imported material inputs or supplies through Customs and other border control agencies, computed over a representative population of manufacturing firms at the country-sector-year level.<sup>19</sup> We

> 19More precisely, question D.14 from the Manufacturing Module of the WBES reads _“In [the last] fiscal year, when this_

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