In the business growth equations we will estimate in section 3, we chiefly rely on subjective ratings as regressors, the main exception being that we use hard financial data as indicators of problems of access finance. Part of the reason for this is that they are faithful to the picture provided by objective indicators such as those given in table 4. Part is that survey response rates happen to be much higher for questions inquiring about subjective ratings compared to those asking for objective indicators. We therefore obtain more reliable impact estimates and make more reliable inferences than could be possible if we worked exclusively with data on objective indicators. We offer more formal evidence of the faithfulness of subjective ratings to objective indicators in table 5, which shows marginal effects obtained from the estimation of a probit models of a firm identifying labor regulation, power shortages, poor access to finance or corruption as constraints to its growth. In relating a rating to an objective indicator we control in each case for line of business, state of location, year of observation, and the size and age of the business. Given all of these, the probability that a business rates labor regulation as a constraint increases significantly with the number of labor inspection visits it gets per year. Reported sales loss due to power outages is a significant predictor of the rating of power shortages in the same sense, as is the payment of bribes of the rating of corruption as an obstacle to growth.

Before turning to the relationship between business growth rates and institutional determinants, we note that, on average, businesses grow faster in quadrant I states than in quadrant II states, and in the latter than in quadrant III states. Although our hypothesis is that better institutional quality or better business environment would mean higher average business growth, our business environment indicators do not map into our development categories of states as neatly as this might suggest. For example, high-income states do not score better than low-income states on all four of our indicators, just as we cannot say that high-growth states have a better business environment in all respects than lowgrowth states. We can nonetheless say that, on the whole, the institutional environment of quadrant I states (or advanced regions) is significantly better than that of quadrant III states (or lagging regions). The only qualification to this statement is that labor regulation is less of a problem in quadrant III states than it is in quadrant I states on the subjective as well as objective indicators of it that we report in tables 3 and 4 respectively. On the other hand, both the subjective indicators of table 3 and the objective indicators of table 4 indicate that the business environment of quadrant I states is better in all the other three areas. In particular both indicators suggest that corruption is a more serious problem in quadrant III states than it is in quadrant I states. This has to be seen in the light of greater importance we attach to corruption than we do to labor regulation or the other two indicators in the light of our interpretation of the incidence of corruption as a proxy for the quality of property rights institutions, and the latter’s primacy over contract institutions as determinants of long run economic outcomes. Both power shortages and problems of access to finance are also more severe in quadrant III states than in quadrant I states (table 3), again on subjective as well as subjective indicators (table 4) 9