Firstly, these indices are designed to act as an indicative tool only. To understand this concern better, let’s consider the instance of an auto-manufacturing firm trying to establish a plant in a particular state that has risen in rank by two spots. What does such a jump in rank convey to the firm? It suggests that the firm’s profitability is likely to be higher if it invests in that particular state. But, the index fails to address, what is equally or perhaps more important to know, by how much more the firms’ return potential or profits would increase owing to the state’s rise in rank. The quantum of improvement, and not merely the direction of improvement, plays a crucial role in the cost-benefit analyses of investors and policymakers alike.
Illustration: Binay Sinha
Secondly, the practice of assigning arbitrary weightage to the different indicators makes it easier for policymakers to game the system. For instance, the state may only reform those areas that are easy to tweak, rather than the ones that prove to be the biggest bottlenecks in changing the industrial setting of a country. Such practices are likely to dilute the value of these rankings to the auto-manufacturing firm or any other potential investor.
Lastly, the recommendations that stem from these rankings seem to be uniform across states. Owing to the vast diversity across the states of India, a one-size-fits-all measure is unsuitable to address the heterogeneity, which in turn leads to unequal growth. This point becomes even more relevant in a post-GST world, where location of industries cannot be driven by tax margins but by comparative advantage of states.
A way to overcome the aforementioned loopholes in the existing indices is to reduce the arbitrariness of factor selection and weights assigned to them. To be specific, the exercise of developing such indices should be more data-driven, where a firm’s productivity in a given state should be correlated with various business environment factors of that state. This exercise will throw up the relative importance of each factor in stimulating a firm’s productivity in the state. A firm’s productivity — the part of the output after the costs of production have been accounted for — is the returns accrued by the entrepreneur/investor, making it a relevant measure of investment potential. Developing such an index would add three values to the existing measure. First, it would guide investors in their cost-benefit analyses of locating investments
in sectors with higher return potential.
Secondly, the relative importance of the pillars, as suggested by the data on firm-productivity, would inform policy-makers to focus on the ones with the highest impact on productivity, thereby reducing the incentive for gaming the system. Finally, since such an exercise can be repeated in different industries across the states, a data-driven index can also shed light on a state’s comparative advantages.
Overcoming information asymmetries for firms and investors is an essential requirement for improving the business operating environment for firms. Current metrics provide some indicators for policymakers and investors, but sadly there are large gaps. This is where a data-driven index which also tells the amount of change, along with direction, could prove to be a far more useful indicator and a more accurate measure of a state’s investment potential.
The writers are associate fellows at NCAER. The views are personal