below 80 percent); in Italy from a low of 47 percent in Trento to a high of 75 percent in Lombardia; in Poland from a low of 44 percent in Lodzkie to a high of 75 percent in Mazowieckie (by far the largest region); and in Romania from a low of 82 percent in Bucharest‐Ilfov to a high of 95 percent in West. Notice that we did not adjust the sample four our tests. Notice that we did not find systematic differences in terms of coverage between lagging and on‐lagging regions.

Table 1: Average number of firms by country in Eurostat and Orbis, period 2008‐2013.

||Number of firms with<br>|at least 10 employees<br>||
|---|---|---|---|
||Eurostat|Orbis|_Coverage_|
|Spain|148,138|123,398|_83%_|
|Italy|181,755|123,179|_68%_|
|Poland|96,834|55,832|_58%_|
|Romania|55,173|48,969|_89%_|

_Note: This table reports the average number of firms in Eurostat and in our Orbis sample, firms with at least 10 employees, years 2008‐2013. Last column reports the coverage ratio of Orbis._ For the analysis, we focus only on manufacturing firms to ensure better comparability across firms, and exclude firms selling local non‐tradables.<sup>8</sup> Our sample includes only firms with at least 10 employees at any point over the period, to exclude microenterprises. In the main specifications, we also include only firms that were established prior to 2006 to ensure comparability – i.e. all firms are incumbents. The focus on incumbents also allows us to avoid any endogeneity issue in the estimation, which can arise when good firms locate in better regions. However, it is important to recognize an important limitation in the analysis is that, whether or not we look at new or incumbent firms, with this approach we are still restricted to understanding how the business environment affects _existing, individual_ firms rather than how it affects the performance of the aggregate enterprise sector. So, arguably we may be measuring the performance of the set of firms that manage to establish and survive in whatever business environment is present in the region.<sup>9</sup> The implication would not mean firm performance is biased upward, but that differences in performance are likely to be narrowed, potentially lowering the significance of the results.

Table 2 summarizes the main variables from Orbis used in the analysis of firm performance. The analysis focuses on measures of _growth_ performance (sales and employment growth, and fixed assets investment) and of _operational_ performance (productivity growth and return on assets [ROA]), which together would indicate competitiveness and sustainability (i.e. evidence that firms are expanding). We measure all performance results as the average of the prior three years, in order to smooth annual fluctuations. Fixed assets include tangible and intangible assets since firms may invest in both in order to grow.

Table 2: Firm variables from Orbis

|Variable|Description|
|---|---|
|_Growth Performance_||
|Employment Growth|Three year average of Growth in Number of Employees (%)|
|Sales Growth|Three year average of Growth in Sales(%)|

8 The analysis was also run with the full data set, including services firms, and show directionally similar results to what is reported for manufacturing firms in this paper. Results are available from the authors.

> 9 To paraphrase Hausmann (2008) we risk being guilty of studying the camels in the desert and not the hippos.

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