Harmonized Learning Outcome); (2) the Enterprise Survey indicator on access to bank finance (Overdraft) and the Global Competitiveness indicator on Financial Development (or the _Doing Business_ on Getting Credit); or (3) the Enterprise Survey indicator on Land Access Obstacle and the _Doing Business_ score on Dealing with a Construction Permit.

The mild or nonexistent correlation of related indicators from various sources suggests that they likely differ in their explanatory power for firm performance. The lack of correlation between different sources could also indicate that these measures capture different aspects (such as formal schooling and on-the-job training) of a theme (such as skills).

# **4. Associations between firm performance and de jure and de facto measures of the business environment**

We estimate the association between the business environment and firm performance, as captured by firm employment growth and the labor productivity level. These two measures capture both dynamic and static performances of firms. We focus on firm employment growth for two reasons. First, firm growth is a key source of overall national economic growth, and a country in which firms are failing to grow is unlikely to develop. Firm growth is especially important for the path to prosperity for developing countries because the vast majority of firms are small , yet relatively larger firms in developing countries are significantly more productive (Hsieh and Olken 2014). Furthermore, there is evidence that cities featuring a sufficiently large share of relatively larger firms (those with more than 50 employees) tend to facilitate firm employment growth (Clarke, Li, and Xu 2016) and firm productivity growth in relatively lowincome countries (Reyes, Roberts, and Xu 2017). Because growth rates are heavily influenced by outlier issues,<sup>10</sup> we follow Davis, Haltiwanger and Schuh ( 1996 ) by calculating mid-point growth rates by dividing the change in employment (or labor productivity) between the survey year and three years earlier by the simple average of employment (or labor productivity) in the beginning and ending years. This bounds the resulting growth rate between –2 and +2, thereby significantly reducing the influence of outliers.<sup>11</sup> Labor productivity is measured as sales

> 10 Consider a firm whose employment grows from 10 to 100 workers compared to one whose employment grows from 100 to 200 workers.  Both firms increase employment by 100 workers.  However, whereas the growth rate of the former is 900 percent, the growth rate of the latter is only 100 percent.

> 11 Because the dependent variables are bound between -2 and +2, a nonlinear Tobit estimation of equation (1) may be used. However, it is not necessary when one is mainly interested in the marginal effect. The Tobit model requires “commitment to functional form and distributional assumptions, about which we do not usually feel strongly” (Angrist and Pischke 2009, 197–98,), while the ordinary least squares (OLS) method has the virtue of “simplicity, automation, and comparability across studies” (Angrist and Pischke 2009, 197). We experimented with estimation using the Tobit model, and found qualitatively similar results to those based on OLS.

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