Table 7: Regression of business environment on firm performance in manufacturing based on contractibility of sectors

||Sales Growth|Employment<br>Growth|Investment<br>Rate|ROA|Productivity<br>Growth|
|---|---|---|---|---|---|
|SDB‐Contract|‐0.136|‐0.036|‐0.399|0.061|‐0.001|
||[‐1.031]|[‐0.546]|[‐0.355]|[0.762]|[‐0.333]|
|High Nunn X SDB‐Contract|‐0.406***|‐0.06|‐2.447**|‐0.185*|‐0.004|
||[‐2.945]|[‐0.969]|[‐2.420]|[‐1.831]|[‐1.627]|
|High Nunn|1.263***|0.327|6.706**|0.774**|0.008|
||[2.586]|[1.599]|[2.135]|[2.035]|[1.096]|

_Note: This table reports the estimates of the firm performance model. High Nunn is a dummy that takes the value one if the Nunn (2007) index of relationship‐specific inputs used in a sector is above median; and SDB‐Contract is the SDB number of days to enforce contracts. High Nunn X SDB‐Contract is the interacted variable. All models include fixed effects for: country, region and firm controls include: (log) age, (log) size, (log) total assets, assets per employee; and financial leverage._ Finally, returning to the main results in Table 6, we look at the measure of regional competition. Like the previous discussion on incumbents versus new entrants, we again need to be careful in interpreting the relationship between market competition and individual firm performance, as the expected positive impact of a competitive market would accrue to the aggregate enterprise environment rather than to individual firms within it, at least in terms of growth and profit; productivity impacts should be observable at the firm level. In any case, the results shown in Table 6 are very clear and strong. In fact, across all performance variables, competition has an even stronger association than does the Doing Business environment.

# 6. Are business environment constraints aggravated in lagging regions?

As a final step in the analysis, we ask whether the relationship between firm performance and the business environment is larger and more significant in lagging regions. Here, we are looking for evidence not simply, for example, that a bad business environment in a lagging region is associated with bad performance of firms in that region, but that a similarly bad (good) environment in two regions – one lagging and the other not – will be associated with a larger negative (positive) performance of firms in the lagging region than in the non‐lagging region. As discussed earlier in the paper, the logic is that the other regional factors discussed in Section 5 interact with a weak business environment to aggravate the impact on firms.

To test this, we interact the SDB‐DTF measure with a lagging region dummy. The results are shown in Table 8. Because of the differences in performance between ‘low growth’ and ‘low income’ regions, we again split the results between Italy and Spain, on the one hand, and Poland and Romania, on the other. To interpret the results, we need to look first at the sign of the interaction term which tells us whether the lagging regions performs better or worse than other regions. But we also need to combine the interaction term and the original term to see the combined effect; thus, the relationship in lagging regions will be the coefficients on _SDB‐DTF X Lagging_ plus _SDB‐DTF_ (whose sign may change). The results provide weak evidence that firms in lagging regions are impacted more strongly by the business environment than firms outside lagging regions. In all cases except for productivity, the interaction variable has a negative association with performance variables, indicating that being in a lagging region amplifies the results of the business environment. However, the results are only significant for profitability (ROA). This suggests that while the main impact of the business environment is regionally agnostic, because firms in lagging regions may already be more vulnerable due in part to weaker demand‐side conditions, additional costs involved in dealing with business environment constraints are 16