# **2.1 Sampling and characteristics of the ICSs**

The sampling of the ICSs is based on a World Bank template used in a large number of countries and customized in collaboration with regional statistical agencies to reflect country-specific issues and policy areas of interest. In order to ensure proper representation of the sectors of interest,<sup>13</sup> respondents are carefully selected. The sampling process is normally based on national industry databases and census of firms or establishments,<sup>14</sup> which provide the necessary information on the particular population of establishments. To ensure proper representation of firms, stratification is usually done based on three standards: size, sector and location.<sup>15</sup> The information contained in the ICSs is composed of a wide set of around 400 variables. Eventually, the number of variables likely to be used in regression analysis is reduced to around 120-200.<sup>16</sup> The Investment Climate Surveys provide information regarding firms’ experience in a range of areas related to economic performance: financing, governance, corruption, crime, regulation, tax policy, labor relations, conflict resolution, infrastructures, supplies and marketing, quality, technology, and training among others. The ICSs also provide information on the productivity (or production function) variables, sales output (sales are used as measure of output), employment, intermediate materials, capital stock and labor cost. The resulting panel information is short in the time dimension, since it includes only 2 or 3 years of productivity data (in our case 2 years for Turkey and 3 for India, South Africa and Tanzania), and has 1 year of information for the investment climate variables. Finally, it is important to note that all information is based on recall data and not on book values or accounting.

# **2.2 The missing information problem at first glance**

Figures 1.1 to 1.4 show the complex and unbalanced patterns of missing values observed in the PF variables in the four countries considered. The most common case is finding observations with information for all the PF but one. In India, the percentage of establishments reporting information for all the PF variables except capital is 16.3%. In the rest of the countries, this percentage is slightly lower but significantly high too. It is less common to observe data on all the PF variables except sales, materials or employment, although in Tanzania the percentage of firms reporting all the figures except sales is relatively important, 9.8%. The cases for which data is collected for only two PF variables represent, in all the countries, less than 1% of total data. Finally, it is very common to have data collected only for labor; this percentage represents 13.3% in India, 27.9% in Turkey, 5.5% in South Africa and 15.7% in Tanzania.

> 13 Here we focus only on the manufacturing sector. By classifying the establishments by their ISIC code we generally end up with establishments from the following eight sectors: a) Food and beverages; b) Textiles and apparel; c) Chemicals; d) Non-metallic mineral products; e) Metallic products; f) Machinery and equipment; g) Electrical machinery; h) Transport equipment. 14 The unit of reference in the ICSs is the establishment, although in this paper we refer indistinctively to both establishments and firms. 15 Concretely, the establishments are selected according to a random sampling by industry and region. Taking into account this issue we use standard errors allowing for clustering by industry and region (apart from the conventional correction for heteroskedasticity _a la_ White). In some surveys there is also oversampling of large firms.

> 16 We understand by _“likely to be used in regression analysis”_ all those variables describing the investment climate in which firms operate and likely to be related to firms’ economic performance.

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