geography, infrastructure and institutional. For easy reference, a summary of the variables is provided in Table 2.

# **_Firm-Specific Controls_**

Firm-specific controls include the productivity, size (sales), age and the type of firm (private domestic, private foreign, public or mixed). The literature suggests that exporters are usually more productive than non-exporters because of two distinct mechanisms - self-selection into export markets and learning-by-exporting. Exporters may be more productive than their counterparts, who only supply the domestic market, simply because more productive firms are able to engage in export activity and compete in international markets. The second mechanism is post-entry productivity benefits, since when firms enter into export markets they gain new knowledge and expertise, which allows them to improve their level of efficiency. While this paper is not concerned with the casual impact of exporting on productivity, it is important to control for the self-selection of more productive firms into exporting. Lagging productivity by one period effectively controls for possible endogeneity, since the decision to ‘start’ exporting takes place only once.

To obtain consistent production function estimates, this paper follows Olley and Pakes (1996) to compute firm-level total factor productivity (  _it_ ). This approach controls for two distinct sources of bias (1) simultaneity between outputs and inputs, which would bias the labor coefficient upward and (2) endogeneous exit of firms from the sample, which would bias the capital coefficient downward. Under fairly general assumptions, Levinsohn and Petrin (2003) show that with simple OLS estimations the labor coefficient will be upward biased and the capital coefficient will be downward biased. This would imply that productivity estimates would be upward biased for more capital-intensive firms, such as exporters. I compute the labor and capital coefficients under simple OLS assumptions and using the Olley-Pakes procedure and report these in Appendix Table A.1. I use data on the firm’s total wage bill as a proxy for the labor input, and on its fixed assets<sup>5</sup> as a proxy for capital. These nominal values are deflated using NIC 2-digit level output and input specific price indices<sup>6</sup> .

# **_Agglomeration Variables_**

The count of other exporters within the district ( exp _jt_ ) and the count of other exporters by industry within the district ( exp _jkt_ ) are weighted by the district population captures the effect of export spillovers. The idea is that proximity to other exporters could result in knowledge spillovers that might help non-exporters to start exporting. In addition more general industrial agglomeration within a location would

> 5 Fixed assets include plant and machinery, computers, electrical installations, transport and communication equipment and infrastructure, fittings and furniture, social amenities and other fixed assets.

6 Since more productive forms are likely to have a lower-than-average firm specific price, the use of industry price indices might systematically underestimate the output of more productive firms and therefore underestimate their productivity. On the other hand, if exporters were more likely to use better quality inputs and materials, then using industryspecific deflators would overestimate productivity. The converse would be true for less productive firms. In the absence of firm-specific prices I am unable to overcome this bias.

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