relationships for firms operating in industries with severe contracting problems. However, the existing firm-level studies have generally focused either on institutional differences within a single exporting country or across destination markets. We make use of the Exporter Dynamics Database, the first and the only database that provides detailed comparable information on the micro-structure of trade flows between countries across a large number of countries, to explore the effects of institutional differences across countries. This represents an advance with regard to the existing firm-level studies, which rely on a single exporting country.

# **3 Empirical Specification**

In this section, we describe the empirical models and estimation procedures. In this regard, we closely follow Manova (2013). The basic model we use to estimate the effects of institutions on export is given by: where _Xjist_ is a measures of trade flow from country _j_ to country _i_ in sector/industry _s_ in year _t_ ; _Qjt_ is the institutional quality of country _j_ in year _t_ , and _zs_ is the contract-intensity of industry _s_ ; _αj, αi, αs_ and _αt_ are the exporter, importer, industry and time fixed effects; _α0_ is the constant term and _εjist_ is the idiosyncratic error term; and

**_Z_** is a vector of additional control variables including traditional sources of comparative advantage (such as physical capital, human capital and natural resource endowments – _Kjt_ , _Hjt_ and _NRjt_ – along with their interactions with the corresponding factor intensities – _ks_ , _hs_ and _ns_ ) as well as those variables at the heart of the gravity equation (exporter GDP, importer GDP and the distance between them), and **_γ_** the vector of corresponding coefficients.

In the baseline specification where we are interested in measuring the total effect of institutional quality on trade, captured by _∂X∂Q_ <u>jjtist</u><sup>=</sup><sup>_β_0+</sup><sup>_β_1</sup><sup>_zs_, the left-hand-side (LHS) variable</sup><sup>_Xjist_is the total value</sup> of exports. As we are particularly interested in the effect on the pattern of trade (and not in the volume effect) of institutional quality, our parameter of interest is _β1_ . As our first testable hypothesis, we expect that _β1 >_ 0. That is, the effect of institutions on exports is increasing in the institutional-intensity of the industry. Put differently, improving institutions leads to a more than proportionate expansion of exports in the institution-intensive sectors – establishing institutions as a source of comparative advantage.

It should, however, be noted that estimating this model leads to dropping a large number of observations with zero trade, and thus the estimate of _β1_ does not give the true effect of interest. Instead, it gives the effect of institutions on the pattern of trade for the sample of country-pairs with non-zero trade only, which is a biased estimate for the true (population-wide) effect of institutions in the face of selection bias. A solution to this problem of selection-bias is to estimate Equation 1 along with a selection model. The latter entails estimating a probit or logit model and gives the influence of institutions on the probability of exporting a positive value, which constitutes one among the several definitions of 5