# **V. Cluster-level Productivity Analysis**

# **Data sources**

The Sri Lanka manufacturing sector data were provided by the National Statistics Office (NSO) in summary format by industry, firm size and provincial location.<sup>6</sup> We use data based on the 2004 Census of Industry, a comprehensive nationwide establishment census which collected data for fiscal year 2003. The data are aggregated by two-digit ISIC code, establishment size (5-9, 1019, 20-39, 40-99, 100+ workers) and nine provinces.<sup>7</sup> Data include counts of total employment, number of employees by gender as well as total output, total raw materials consumed (value added is defined as output minus raw materials), and a compensation bill. All currency accounts have been converted to 2005 USD at purchasing-power-parity.

We match these data to indicators constructed from the 2004 World Bank Enterprise Survey (WBES) dataset, which also covers data from fiscal year 2003. This survey collected detailed data on manufacturing establishment operations and constraints to business and investment for the first time in Sri Lanka. The dataset is comprised of 452 establishments stratified by province and industry.<sup>8</sup> We construct indicators of the business environment based on averages of objective indicators in given industrial ‘clusters’ (defined as firms in a given province, grouping of industries at the 2- digit level, and establishment size class). To ensure an adequate number of establishments in each cluster, we drop one dimension of the cell when there are fewer than five establishments in any given cluster until an adequate underlying number of establishments is reached (that is, we first substitute with location-size clusters, then industry-size to ensure that we have at least our cutoff of five or more establishments per cluster).<sup>9</sup>

> 6 Due to confidentiality restrictions, establishment-level data were not able to be procured through the NSO. 7 The Census of Industry surveyed all plants, although those with 1-4 workers were not included in the dataset. The analysis excludes utilities, mining and quarrying, and a few other industries which, due to the methodology of data collection were available but are commonly thought of as outside the manufacturing sector. To protect the confidentiality of survey respondents, the Department of Census and Statistics have top-coded employment size categories for certain sectors with few very large firms (into an “other” category) to prevent them from being identified in the cell data. This necessitated aggregation of cells in the 100-499 and 500+ size categories into one single 100+ size category. We focus on seven provinces since Northern and Eastern provinces have been omitted due to civil unrest causing questions of data reliability and consistency. Specifically, conflict in these areas precluded the collection of surveys in 1993 and 1998, so we excluded them from all years to maintain a consistent sample.

> 8 The sample size for the 2004 WBES in Table 3 reflects the estimation sample used in the firm-level TFP analysis presented in Section VI. The cluster level indicators, however, are based on the full sample of 452 surveyed establishments.

> 9 A similar approach has been used, among others, by Aterido et al. (2011). While in principle there could be up to 490 possible location-industry-size clusters (14 2-digit industries x 7 provinces x 5 size classes), in practice given available data we are able to construct 322 location-industry-size clusters.

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