How Public Information Affects Asymmetrically Informed Lenders: Evidence from a Credit Registry Reform (with Ali Choudhary), March 2020, Journal of Development Economics. [PDF]
We exploit exogenous variation in a firm’s public information available to banks to empirically evaluate the importance of adverse selection in the credit market using a Pakistani banking reform that reduced public information. Originally, the central bank published credit information about the firm and (aggregate) credit information about the firm’s group. After the reform, the central bank stopped providing the aggregate group-level information. We construct a measure for the amount of information each lender has about a firm’s group using the set of firm-bank lending pairs prior to the reform. We show those banks with private information about a firm lent relatively more to that firm than other, less-informed banks following the reform. Remarkably, this reduction in lending by less informed banks is true even for banks that had a preexisting relationship with the firm, suggesting that the strength of prior relationships does not eliminate the problem of imperfect information.
A Model of Intermediation in a Walrasian Framework (with Robert Townsend) [pdf], April 2021, Economic Theory.
We present a tractable model of platform competition in a general equilibrium setting. We endogenize the size, number, and type of each platform, while allowing for different user types in utility and impact on platform costs. The model is applicable to the recent growth in digital currency platforms. The economy is Pareto efficient because platforms internalize the network effects of adding more or different types of users by offering type-specific contracts that state both the number and composition of platform users. Using the Walrasian equilibrium concept, the sum of type-specific fees paid cover platform costs. Given the Pareto efficiency of our environment, we argue against the presumption that platforms with externalities need be regulated.
Corporate stress and bank nonperforming loans: Evidence from Pakistan (with Ali Choudhary), [pdf], (forthcoming), Journal of Banking and Finance.
Using detailed administrative Pakistani credit registry data, we show that banks with low leverage ratios are both significantly slower and less likely to recognize a loan as nonperforming than other banks that lend to the same firm. Moreover, we find suggestive evidence that this lack of recognition impedes loan curing, with banks with low leverage ratios reporting significantly higher final default rates than other banks for the same borrower (even after controlling for differences in loan terms). Our empirical findings are consistent with the theoretical prediction that classifying a nonperforming loan is more expensive for banks with less capital. A previous version of this paper was called “Bank lending to (zombie?) firms.”
Finance and Inequality: The Distributional Impacts of Credit Rationing. (with Ali Choudhary), Revision requested.
We analyze reductions in bank credit using a natural experiment where unprecedented flooding differentially affected banks that were more exposed to flooded regions in Pakistan. Using a unique dataset that covers the universe of consumer loans in Pakistan and this exogenous shock to bank funding, we find two key results. First, banks disproportionately reduce credit to new and less-educated borrowers, following an increase in their funding costs. Second, the credit reduction is not compensated by relatively more lending by less-affected banks. The empirical evidence suggests that adverse selection is the primary cause for banks disproportionately reducing credit to new borrowers.
What limits bank lending in emerging markets? An experiment testing informational and contractual frictions, [pdf] (with Ali Choudhary)
Credit access is limited in rural areas, especially in developing economies. Using a novel three-stage experimental design in Pakistan, first, we document that bank lending only serves a small fraction of rural credit demand. Second, we test the importance of information and enforcement technology frictions for limiting bank lending by randomly varying loan contractual terms across farmers. We find that enforcement technology is the primary friction for limiting bank lending. Third, using a final survey, we document that farmers tend to correctly identify the financial consequences of non-repayment. Fourth, our results suggest one possible solution to overcome this financial friction—a motivated and interlinked intermediary.
Financing Repeat Borrowers: Designing Credible Incentives for Today and Tomorrow, [pdf] (with Piruz Saboury)
We analyze relationship lending when borrower cash flows are not contractible and the costs of intermediation vary over time. Because lenders provide repayment incentives to borrowers through the continuation value of the lending relationship, borrowers will condition loan repayment on the likelihood of receiving loans in the future. Therefore, the borrower’s beliefs about the lender’s future liquidity become an important component of the borrower’s repayment decision. Consequently, the possibility of high lending costs in the future weakens repayment incentives and causes an inefficient under-provision of credit. Moreover, as the likelihood of a prolonged period of high liquidity cost increases, the adverse effect of future liquidity constraints on today’s lending decisions exacerbates. We discuss the application of our model to the case of microfinance.
Identifying the marginal borrower under adverse selection: A simple model, [pdf]
This paper presents a simple model of financial intermediation between a monopolist lender and credit-constrained entrepreneurs with private information. To specifically examine heterogeneity in credit outcomes, we introduce different groups of entrepreneurs that vary in the likelihood of repaying a loan both within groups and across groups. Our paper’s main result is that as we increase the lender’s funding cost, those entrepreneur groups that have a higher degree of adverse selection are more affected. That is, the reduction in credit is larger and the increase in interest is higher for these groups. The intuition for this result is that as the lender increases the interest rate, the share of “bad” borrowers rises faster for those groups with a higher degree of adverse selection. In turn, this forces the lender to increase the interest rate more for these groups, and consequently, causing a larger credit reduction.
Efficient Public Good Provision in Networks: Revising the Lindahl Solution [pdf]
Abstract: The provision of public goods in developing countries is a central challenge. I examine a model where each agent’s effort provides heterogeneous benefits to the others, inducing a network of opportunities for favor-trading. I focus on a classical efficient benchmark — the Lindahl solution — that can be derived from a bargaining game. Does the optimistic assumption that agents use an efficient mechanism (rather than succumbing to the tragedy of the commons) imply incentives for efficient investment in the technology that is used to produce the public goods? To show that the answer is “no” in general, we give comparative statics of the Lindahl solution which have natural network interpretations. We then suggest some welfare-improving interventions.