Rev. 3.1 code). Of these interviews, more than 90,000 are with top managers and business owners of manufacturing firms, for which we provide TFPR estimates. Factor ratios using labor costs and revenues are provided in the associated dataset for most firms in the sample, including firms in selected services sectors covered by the ES.

To construct TFPR, we need information on sales (Y), employment (L), capital stock (K), and intermediate inputs (M). These variables are proxied using the questions available in the data. More precisely, Y is proxied by total annual sales of the establishment (variable d2); K is proxied by the replacement value of machinery, vehicles, and equipment (variable n7a); L is proxied by the total annual cost of labor (variable n2a); and M is proxied by the total annual cost of inputs (variable n2e). For value-added (VA) specifications (presented below), VA is proxied by the difference between total annual sales of the establishment (variable d2) and annual cost of inputs (variable n2e); K and L are the same as in the gross output specification (also elaborated below). The appendix presents each variable used along with the exact wording of the questions.

# **International Comparability**

All the variables used for the productivity estimation are collected in local currency units (LCUs), which are specific to the survey and year. Consequently, the data span different fiscal years. For the estimation of cross-economy regressions all data must be transformed to a common currency-year. To do this, all variables are first converted into U.S. dollars (USD) using the official exchange rate (period average) from the World Development Indicators (WDI).<sup>2</sup> The data are then deflated to 2009 using the GDP deflator for the United States from the relevant reference fiscal year.<sup>3</sup> Note that information on the closing month of the firms’ fiscal year is used to adjust exchange rates and deflators for each firm.<sup>4</sup>

# **Treatment of Outliers**

In order to minimize sensitivity to extreme values, outlier firms are eliminated from the analysis. More specifically, outliers in d2 (capturing Y), n7a (capturing K), n2a (capturing L), n2e (capturing M), and VA (d2 minus n2e), as well as outliers in ratios n7a/VA and n2a/VA were turned into missing before estimating the production function. To find outliers in levels, we first transform variables as ln( _x_ +1), and group observations by economy and broadly defined sector (more precisely, manufacturing and services). Next, we calculate (unweighted) means and standard deviations of these transformed variables within each group. Observations that are more than three standard deviations away from the mean are then marked as outliers and turned into missing. To find outliers in ratios, we first transform variables as ln( _x_ ), and group observations by industry. The three-standard-deviation rule is then applied (unweighted) and the corresponding observations are turned into missing.

> 2WDI indicator code: PA.NUS.FCRF

> 3WDI indicator code: NY.GDP.DEFL.ZS

> 4The fiscal year and its closing month information are given in variables “ _d_ 2 _~~l~~_ 1 _~~y~~ ear perf_ _~~i~~ ndicators_ ” and “ _d_ 2 _~~n~~_ 3 _~~l~~ ast_ _~~m~~ onth_ _~~f~~ y_ _~~p~~ erf_ _~~i~~ nd_ ” respectively.

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