Table 1: Trade-Specific Effect of Institutions on Export

|**_Dependent Variable:_**|||_ln_(_Ex_|_port_)_jist_|||
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Rule of law|0.090<sup>_∗∗∗_</sup>|0.098<sup>_∗∗∗_</sup>|-0.096<sup>_∗∗∗_</sup>|-0.086<sup>_∗∗∗_</sup>|-0.252<sup>_∗∗∗_</sup>|-0.247<sup>_∗∗∗_</sup>|
|Rule of law x Inst-Int|0.231<sup>_∗∗∗_</sup>|0.193<sup>_∗∗∗_</sup>|0.228<sup>_∗∗∗_</sup>|0.192<sup>_∗∗∗_</sup>|0.461<sup>_∗∗∗_</sup>|0.433<sup>_∗∗∗_</sup>|
|lnESTABLISH||0.051<sup>_∗∗∗_</sup>||0.048<sup>_∗∗∗_</sup>||0.053<sup>_∗∗∗_</sup>|
|lnGDPE|||1.216<sup>_∗∗∗_</sup>|1.193<sup>_∗∗∗_</sup>|1.929<sup>_∗∗∗_</sup>|1.901<sup>_∗∗∗_</sup>|
|lnGDPI|||0.122<sup>_∗∗∗_</sup>|0.124<sup>_∗∗∗_</sup>|0.104<sup>_∗∗_</sup>|0.106<sup>_∗∗_</sup>|
|lnH|||||-0.193<sup>_∗∗_</sup>|-0.170<sup>_∗_</sup>|
|lnH x H-Int|||||0.091<sup>_∗∗∗_</sup>|0.082<sup>_∗∗∗_</sup>|
|lnK|||||-0.709<sup>_∗∗∗_</sup>|-0.728<sup>_∗∗∗_</sup>|
|lnK x K-Int|||||-0.152|-0.147|
|NR|||||-0.003|-0.003|
|NR x N-Int|||||-0.015<sup>_∗∗∗_</sup>|-0.015<sup>_∗∗∗_</sup>|
|No. of Observations|1188591|1188591|1116491|1116491|736412|736412|
|F-Statistic|66.625|61.177|234.284|195.256|90.380|85.552|
|Prob _>_ F|0.000|0.000|0.000|0.000|0.000|0.000|
|R<sup>2</sup>|0.676|0.676|0.675|0.675|0.693|0.693|
| ̄_R_<sup>2</sup>|0.671|0.671|0.670|0.670|0.689|0.689|

_∗ ∗∗ ∗∗∗ p <_ 0 _._ 1, _p <_ 0 _._ 05, _p <_ 0 _._ 01. Each regression includes an unreported constant term, and coefficients for a full set of dummies for exporter-importer pair, sector and year. Standard errors are clustered by exporter-importer pairs for all regressions.

is robust to the use of other commonly used variables – the number of procedures (Column 2) or monetary cost of business startup (Column 3) – instead of (or in addition to) the number of days. While Columns 1-3 use _Rule of Law_ as the measure of institutional quality, Columns 4-6 employ _Contract Enforcement_ instead. The results remain intact. This relationship is also robust to the inclusion of a number of controls: the full set of exporter, importer, year and sector fixed effects (dummies); total GDP of both exporters and importers (to capture market size); and the distance between exporter and importer. Time-invariant country and sector-specific characteristics are subsumed into sector, exporter and importer fixed effects. Global trends and/or shocks common to all countries are captured by year dummies. Following Manova (2013), errors are clustered by exporter-importer pairs to account for “unobserved variation in bilateral trade costs”, which could include factors such as cultural/language barriers in the current context.

Across all the columns, the likelihood of a country exporting a contract intensive product increases with its level of institutional quality. Similarly, the probability that a country exports a product that is intensive in human capital rises with the country’s human capital endowment. Natural resource endowment has also a favorable effect on the probability of exporting resource-intensive manufactures (although it loses statistical significance in some cases). That is, the likelihood of exporting natural resource intensive products rises as the natural resource endowment of countries rises. On the other hand, physical capital endowment does not favor the chance of exporting capital intensive products over the less intensive ones. However, multicollinearity is likely to be behind the unexpected sign of physical capital endowment (more on this below). Consistent with expectations, the economic size of the exporter (as measured by its GDP, _lnGDPE_ ) has a robust positive effect on the probability of trading. Importer’s economic size ( _lnGDPI_ ) has the expected positive sign, but its statistical significance is not robust. Similarly, the distance between exporter and importer has a robust effect of hampering trade.

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