Where we have substituted _Ai_ by a set of sector (NACE 2-digit) fixed effects and district fixed effects . and a stochastic residual _ui_ . Standard errors are clustered by the broad sector-district at which our sample ss dd ff θθ was stratified. The estimation output for OLS regression is presented in columns (1) to (3) of Table 5, where management score is presented as a z-score. Results with the original management score are presented in Annex Table A.3.

# _4.1 Management matters for firm performance_

The results in table 4 suggest that management capabilities are positively and significantly associated with firm performance, whether measured as gross sales per worker, TFP, value added per worker or employment growth. When looking at unconditional correlations (columns 1, 5, 9 and 13), a one standard deviation (SD) increase in management score is associated with a 0.327 increase in log sales per employee, 0.051 SD increase in log TFP and 0.114 increase in log value added per employee and 0.069 SD increase in log employment growth. In terms of elasticities, a 10-percentage point increase in the management score is associated with an increase of 18 percent in sales per worker, 2.6 percent in TFP and 6 percent in value added per worker (see Annex table A.4). These correlations are robust to the use of sample weights to control for selection bias (see Annex tables A.8 and A.9). Table 5 compares the coefficients of similar unconditional correlations across these countries in both elasticity and z-score format suggesting that the findings in Russia are within a comparable range of the countries where MOPS has been conducted. For example, in the United States, a similar change in management score is associated with a 14.5 percent increase in sales per worker (Bloom et al., 2019a). The associated increase in value added per worker is 9 percent in the United States, 12 percent in Pakistan and 15 percent in Mexico.<sup>31</sup> As the evidence presented in this paper comprises of simple association between firm performance and better management practices, it is natural to have concerns regarding endogeneity in adoption of better management practices. For example, it is possible that more productive and efficient firms develop more sophisticated management capabilities as a part of learning by doing, rather than other way round. Due to limitations in our survey data (e.g. information on management practices are based on one year of data collection), we are unable to test for the causality of management practices with superior firm performance in Russia. Nonetheless, the literature on other countries has shown that indeed there is a causal relationship going from improved management practices to increased productivity. For example, in the case of post-war Italy Giorcelli (2018) finds long term effects of better management practices on performance of firms (e.g. productivity, sales, and survival) relative to machinery purchases or technology. The key channel through which skills improved firm performance was by helping managers make better investment decisions— investing in new plants or new machines, for example—which made their production more efficient. The fact that the coefficients obtained from our analysis are similar to those found in the existing literature (see Table 5), reassuring in that better management practices in Russia will likely drive positive effects on firm performance.

Another interesting finding in Table 4 is that the type of management practices affects the productivity indicator in distinct ways. Columns 2, 6, 10 and 14 of Table 4 show the unconditional correlation of the two sub-types of management practices – those related to data driven performance monitoring and those relating to incentives and targets. Data driven performance monitoring has a stronger association with increased sales per worker and employment growth, whilst the latter have a stronger association with

> 31 The specifications in columns 8 and 9 exclude intensity of intermediate inputs as regressors because intermediate inputs are included in the computation of value added, which is defined as sales minus cost of intermediate inputs.

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