divided by the number of employees, expressed in constant US dollars. We also experimented with using total factor productivity (TFP) as a measure of productivity, which is often viewed as a cleaner measure of efficiency. However, the Enterprise Survey does not have data on capital stock for a large share of firms (including all those in service sectors). To preserve sample size, and with the knowledge that the results based on TFP and labor productivity tend to be similar, we rely on labor productivity to measure firm productivity. The specification we use is as follows: Yi i = ESi α1 + DB α2 + GC α3 + X β1 + Wi β2 + θ + η + εi i . (1) Here, Yi i is firm performance. When the outcome is employment growth, the unit is in ii ii ii ii ii ii ii percentage points (that is, one means one percentage point). Subscript ii _i_ stands for firm; _c_ for city; _j_ for industry; _k_ for country; and _t_ for survey year. ESi is a vector for city-industry level Enterprise Survey indicators. DB and GC are vectors for country-level _Doing Business_ and Global Competitiveness indicators. All sets of BE indicators in the regressions are standardized, ii ii so the coefficient should be interpreted as the effect of a one-standard-deviation increase of the BE indicators on firm performance. Wi is the country-level control variable vector, including GDP per capita, population, and population density (all in logarithms). θ and η are industry and survey year fixed effects, respectively. X is a vector for firm-level control ii ii variables, including the ownership share of the largest owner; two dummy variables indicating ii firm size (being middle-sized, with the number of employees three years ago between 20 and 100; being large-sized, with the number of employees three years ago exceeding 100); two firm age indicators (firm age of 6–10 years; firm age of 11<sup>+</sup> years); being an exporter; being a foreign firm; and the share of foreign ownership. We also include indicators of competition faced by a firm.<sup>12</sup> In the ES data set, firms are asked the number of competitors they face. Based on their responses, we construct two indicators of competition: the firm facing one competitor in its market, and the firm facing more than one competitor in its market, with the firm facing no competitors as the base group.<sup>13</sup>

> 12 The inclusion of this variable does not affect our main results.

> 13 The survey contains richer information about competition than we utilize here. The number of competitors can be classified as no competitors, one competitor, two to four competitors, and five or more competitors. Moreover, the number of competitors is specific for the types of market in which the firm is involved (mainly with the local market, with the national market, and with the international market). We have experimented with more nuanced classification of the number of competitors, and found that the effect of competition tends not to differ much when the number exceeds one. Moreover, controlling for the dummies for the extent of the market (being in national market or being in international market, relative to the base category of the local market) does not matter for the effect of competition. In our base specification and all main specifications, we do not control for the dummies related to the extent of the market because it is too endogenous—better-performing firms are in larger markets.

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