endowment is constructed from the human capital index, employment and average hour worked variables in version 9.0 of Penn World Tables (PWT) (Feenstra et al. 2015). The product of persons employed and average hours worked per person is multiplied by the human capital index they constructed from years of schooling to give a measure of effective (or augmented) labor – human capital endowment. Data on endowment of (physical) capital, defined as the value of capital stock at 2011 constant national prices and converted to millions of US dollars, are also from PWT. The number of days, number of procedures, and monetary costs (as percent of income per capita) needed for business startup, used in the probit models, come from the Doing Business database (last updated 03/01/2017, and available at http://www.doingbusiness.org). For each of the three variables, we used the average of the entries for men and women. Distance between exporter-importer pairs refers to the geographical distance in kilometers between the most populated cities and the data are from CEPII’s GeoDist database (see Mayer & Zignago 2011).

**Industry-specific Measures** Data on the contract-intensity of industries are from Nunn (2007). His measure of institutional intensity has two definitions. Both definitions refer to the weighted average of the proportion of relationship-specific inputs used in the production of the product concerned, where the weights are the value of the input relative to the value of all inputs. The difference is that whereas the first definition counts only inputs that are neither sold on exchange nor reference priced as relationshipspecific, the second one additionally includes inputs that are reference priced. Each of these definitions has two estimates: liberal and conservative. We used the first definition because it displays more variation (in terms of both range and standard deviation) than the second. Also, the correlation between liberal and conservative estimates is stronger for the first definition than for the second (0.9799 versus 0.8951). Between the two estimates of this preferred definition, the conservative estimate is given preference over the liberal one as the former has more variation than the latter (standard deviation and range of 0.209 and 0.828 as compared to 0.206 and 0.801, respectively). Nonetheless, all the four statistics (from the two definitions, and the two estimates per definition) are positively and (statistically highly) significantly correlated with one another, and the main results are robust to the use of alternative definitions. Data on other factor intensities (i.e., capital, human capital and natural resource intensity) of the industries are from Manova (2013). Table A.2 provides the average factor-intensities of the 28 industries used in the analysis.

Table A.1 reports summary statistics for these variables. Our main independent variable is the interaction between institutional quality (a country-specific measure) and contract-intensity (an industryspecific measure).

# **5 Results**

We are interested in the effects of institutions on overall trade flows, and the mechanism through which it operates. In this section, we first examine the effect of institutions on main outcomes of interest (probability of exporting, trade volume, product scope, export destination, and export survival rate) using country and industry level characteristics (Subsection 5.1). We then investigate our main hypothesis using more disaggregated data which come from the firm-level database (Subsection 5.2). Even though the estimations in both subsections are done using alternative techniques, we wind up the 9