following Bloom et al. (2019a). Survey data on managerial practices, mark-ups, technology adoption and innovation are merged with other firm performance data such as profits, sales per employee and TFP from the FINA database.

One objective of this survey is to provide robust evidence on the link between management and firm performance in Croatia and in Eastern Croatia (or Slavonia).<sup>3</sup> The overall analysis may not allow to causally relate management capabilities to performance of firms but provides support for specific interventions aimed at improving firm productivity and for piloting policies and programs. For example, our analysis helps benchmark management capabilities in Eastern Croatia and in Croatia overall compared to other countries, the types of management practices that seem more relevant for firms, and the characteristics of enterprises whose management capabilities help explain further differences in performance.

We present some stylized facts for firms in Eastern Croatia and compare them with other regions in Croatia. We find that, _first,_ when benchmarking management scores in Slavonia and in Croatia against the United States, it is noteworthy that the average management score, just like TFP, is higher in the United States than it is in Croatia, and even higher than in Slavonia (Tables 1a and 1b). The average manufacturing firm in Eastern Croatia scores 0.532 in adopting advanced management practices, a value very similar to that in the rest of Croatia (0.542) but behind the one in the United States (0.615, Bloom et al., 2019a). Comparing Croatia’s management practices with those in Russia (Grover and Torre, 2019) and Mexico (Bloom et al., 2019b), other countries for which comparable data are available, we find that an average manufacturing firm in Croatia is better managed than its counterparts in Russia (average score, 0.43) and Mexico (average score, 0.39).<sup>4,5</sup> _Second,_ weaknesses in management practices particularly relating to data-driven performance monitoring cripples the overall management score in Croatia as well as Eastern Croatia. Data-driven performance monitoring includes specific practices that help managers define their key performance indicators (e.g. inventory, sales, absenteeism) and appropriately track them periodically over time, while incentives management practices relate to how managers and non-managers are awarded bonuses and promotion. The result for Croatia regarding the weaknesses of these subindices is similar to that in Russian manufacturing, that is, the monitoring aspect of structured management is weaker. By comparison, this finding is different from that in the United States and Mexico, where manufacturing firms are stronger in monitoring vis-à-vis structured management practices relating to workers’ incentives and target setting.

_Third,_ an interesting finding of this survey data is that services firms are farther from the frontier when it comes to adoption of structured management practices. Services firms were included in a MOPS framework survey for the first time in Mexico, where, as in the case of Slavonia and Croatia, it was also found that adoption of structured management practices is weaker relative to that in manufacturing (Bloom et al., 2019b). They attribute the lower management score in services to a lack of pro-competitive environment, which lowers the pay-off from adopting better management practices. In Eastern Croatia, an average services firm scores 0.519 on the adoption of the most advanced management practices, compared to 0.535 in manufacturing. As in Bloom et al. (2019b), we also conjecture

> 3 We use the terms Eastern Croatia and Slavonia interchangeably. ‘Slavonia’ is used as a shorthand for the region of Slavonija, Baranja & Srijem, consisting of five counties in Eastern Croatia. These five counties are: Brod-Posavina county, Osijek-Baranja county, Pozega-Slavonia county, Virovitica-Podravina county, and Vukovar-Srijem county.

> 4 Apart from data availability, it makes sense to compare Slavonia with the federal districts covered in Russia because, in both cases, the regions are part of a transition economy in Europe, although arguably Russian districts are much larger in size as well as in per capita GDP terms than any region in Croatia. Comparison with Mexico is also revealing in the sense that Mexico’s per capita GDP is closer to Slavonia (but lower than Croatia), but has a strong manufacturing base, and thus offers another perspective for comparison, apart from the United States, which is the benchmark frontier economy (upper bound). In fact, to minimize error margin, we took advantage of access to Mexican survey data on management capabilities at the sample stratification stage and the count of firms to be interviewed by sector within each region is based on an analogous comparator state in Mexico. For example, the sample distribution across sectors in Dalmatia is based on Quintana Roo, a state in Mexico with similar economic structure and relative income ranking as Dalmatia. Likewise, the target sample distribution of firms in Zagreb is based on Mexico City.

> 5 We are concerned that the higher score in Croatia may be a result of a low response rate and a likely selection bias. However, it should be noted that we did not find a significant selection bias based on observable characteristics of firms such as size, age, sector and export status.

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