for the year 1989 – 2008<sup>12</sup> . After cleaning the data, the final dataset contains 6,296 firms. Since there is limited data for other district-level variables, the analysis is restricted to fewer years (1999-2004). The analysis is limited to the manufacturing sector (i.e. National Industrial Classification 2-digit unit 14 to 36). I also exclude firms for which data on sales, gross assets and wages is missing, since these are crucial to the computation of firm-level productivity. Of the firms in the final dataset, 3,638 firms enter the export market at least once over the period of study. There is also a large degree of firm heterogeneity in terms of size and age.

However, some caveats should be mentioned here. It is not mandatory for firms to supply data to the CMIE, and one cannot tell exactly how representative of the industry is the membership of the firms in the organization. Prowess covers 60-70 percent of the organized sector in India, 75 percent of corporate taxes and 95 percent of excise duties collected by the Government of India (Goldberg et al 2010<sup>13</sup> ). Large firms, which account for a large percentage of industrial production and foreign trade, are usually members of the CMIE and are more likely to be included in the database. And so, the analysis is based on a sample of firms that is, in all probability, taken disproportionately from the higher end of the size distribution. As Tybout and Westbrook (1994) point out, a lot of productivity growth comes from larger plants, which are also more likely to be exporters, providing confidence in the comprehensive scope of the study.

Measures of agglomeration are constructed using unit-level data for the years 19992004 from the Annual Survey of Industries (ASI), conducted by the Central Statistical Office of the Government of India. The ASI covers all factories registered under the Factories Act of 1948 that employ 20 or more workers, or that employ 10 or more workers and use electricity. Although the ASI data has a large sample size, certainly larger than Prowess, and it contains data on firm-level characteristics, it cannot be used to study firm-level export behavior. This is because even though the ASI provides information on whether a firm exports or not, the database does not follow firms over time. In other words, firms are sampled afresh every year and it is not possible to create a panel of firms over time. Data on the number of units, i.e. the plant or the factory, is used in the analysis since employment-level data is often scarce or missing. As ASI collects data for primarily the manufacturing sector, agglomeration measures do not account for the activities of services enterprises. This is a shortcoming of the analysis since service sector activity and clustering within a location might be strongly associated with the availability of essential inputs that might reduce entry costs into export markets. Data on market access is constructed using district-level population drawn by various surveys of the National Sample Survey Organisation (NSSO).

Data on measures of infrastructure, such as education, electricity and communications infrastructure, and on wages and wealth within the district are also drawn from the household surveys of the NSSO. These data are only available for 3 Rounds: Round 55.10 (July 1999 - June 2000), Round 60.10 (June 2004) and Round 61.10 (July 2004 - June 2005). The specifications with infrastructure variables thus refer to fewer years than those for firm-level and economic geography variables. And lastly, as mentioned

> 12 More recent data is also available, but the data extracted by the author stops at 2008. 13 Quoted in earlier version of NBER working paper.

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