infrastructure services such as the “Electricity Regulatory Governance Index” developed by Andres et al. (2008) or the data on the degree of autonomy of different electricity regulators collected by Cubbin and Stern (2006). But the number of available observations for both data sets is so small (19 countries in the case of the “Electricity Regulatory Governance Index” and 28 in the case of the “Regulatory Autonomy” data) that we do not present the results here.

Second, we examine the relationship of the new indicator with other measures of government bureaucracy as reflected in a set of three Doing Business time and motion indicators: the number of procedures, time and cost to start a business, register a property and to deal with construction permits. For this analysis, we use the Doing Business data as of the Doing Business Report 2012 for all three indicators. The data cover 183 countries and the period from July 2010 to June 2011, just like for the Getting Electricity data. The Dealing with Construction Permits indicator records not only the process of obtaining construction permits and registering a new building, it also includes procedures, time and cost estimates related to connecting a new construction to utilities such as water, telecommunications and electricity. In order to avoid multi-collinearity with the Getting Electricity data, we adjust the data for the Dealing with Construction permits indicator by excluding all procedures, time and cost estimates related to utility connections from the original data set.

Third, we test the relationship of the new indicator with measures of enterprise performance. All data for this part of the analysis come from the Enterprise Surveys data set. This data set provides firms level data on firms’ characteristics and several measures of the business environment (for instance, trade, infrastructure and finance). The data is collected on a 3-year rotation, meaning that each developing country is visited every 3 years, but the cycle varies country by country (so the data collected for different countries is done in different years). For each country only one year of data was kept (the most recently available year). No data before 2006 were included since the new electricity data is as of 2010/11. Furthermore, only 108 countries of Enterprise Surveys match our sample of 183 economies. The 108 countries surveyed include 38 countries from Sub-Saharan Africa, 30 from Eastern Europe and Central Asia, 25 from Latin America and the Caribbean, 10 from East Asia and the Pacific, 4 from South Asia and one from the Middle East and North Africa region (i.e. Yemen). The richest countries in the Enterprise Survey sample are Slovenia and the Bahamas (as measured by real GDP per capita), the country with the lowest income is the Democratic Republic of Congo.

As outcome variables we use total sales and sales per worker. Nominal values are deflated using the GDP deflator from the World Development Indicators database. All values are presented in 2000 constant US dollars and the exchange rate is taken from the International Monetary Fund’s International Financial Statistics database. As dependent <mark>variables, we use past</mark> sales, average labor input (measured by the number of employees), capital input (proxied by investment), average international trade engagement (measured by the percentage of firms that export directly at least 10% of their sales, import directly at least 10% of their inputs or both of these in industry j country 9