اثرات سوگیری عرضه و تقاضا از اطلاعات مربوط به بازار های اعتباری

We utilize a unique pair of experiments to isolate the ways in which reductions in asymmetric information alter credit market outcomes. A Guatemalan microfinance lender gradually started using a credit bureau across its branches without letting borrowers know about it. One year later, we ran a large randomized credit information course that described the existence and workings of the bureau to the clients of this lender. This pairing of natural and randomized experiments allows us to separately identify how new information enters on the supply and the demand sides of the market. Our results indicate that the credit bureau generated large efficiency gains for the lender, and that these gains were augmented when borrowers understood the rules of the game. The credit bureau rewarded good borrowers but penalized weaker ones, increasing economic differentiation.

Asymmetric information problems bedevil credit transactions, and these problems are particularly severe in poverty-focused credit markets where borrowers lack collateral and credit histories. A broad range of social capital-based lending mechanisms have emerged in recent years to overcome these problems, helping more than a hundred million previously unbanked borrowers enter credit markets over the past decade. Ironically, this surge in lending is increasingly undermining the very mechanisms that made such lending possible, as competing lenders reduce each others' ability to contract without formal collateral. In this environment, credit bureaus can become an attractive means for reducing asymmetric information. We use a unique confluence of data and identification methods to analyze how lending outcomes have responded to the introduction of a credit bureau in Guatemala's microfinance market. In August of 2001 a major microfinance lender began to install hardware permitting branches to communicate information with the bureau, a process that was completed in ten waves over the course of 18 months. The lender did not inform borrowers of the use of the bureau, however, and we found knowledge of it to be almost non-existent in a survey of borrowers implemented after the rollout of the bureau was complete. We therefore conducted a randomized training campaign in which we informed 5000 borrowers of the use of the system, how the bureau worked, and the opportunities and risks that it presented for them. We then used institutional data from the lender and from the bureau itself to track how a variety of lending outcomes emerged from this unusual structure in which asymmetric information was reduced on the two sides of the market at two different points in time. We are thus able to disentangle the supply- and demand-side impacts of credit market information. A new experimental literature has sprung up in recent years working to separate the effects on credit markets of moral hazard and adverse selection as they operate through the price mechanism. Karlan and Zinman (2010) use a two-stage experiment in which borrowers are first offered randomized interest rates in order to measure adverse selection effects, and then among those who come for loans the rate is further randomized downward by surprise in order to isolate moral hazard. This provides an experimental decomposition of the impact of interest rates on hidden information and hidden actions, a relationship originally posited by Stiglitz and Weiss (1981). What we offer here, however, is the estimation of a more primal relationship, because we are able to see how asymmetric information alters outcomes in credit markets directly, rather than via the indirect mechanism of interest rates. That is to say, rather than holding the overall amount of asymmetric information constant and using prices to alter who ends up on the credit market, bureaus offer lenders a vehicle through which they can improve selection and alter behavior based on a first-order reduction in the quantity of asymmetric information in the marketplace.1 Before the existence of the bureau, borrowers were supposed to disclose information about past defaults and current debts on their loan screening forms. The improved screening ability generated by use of the bureau results in large increases in profitability for the lender, indicating that there was strategic behavior by potential clients over past loan information and that it was indeed creating a substantial adverse selection problem for the lender. The specific sequence through which the bureau was rolled out for use by the lender and information about the bureau randomly provided to borrowers allows us to identify separately the roles of adverse selection, moral hazard, and incentives on group composition. This two-fold experiment — natural and randomized — allows to perform this identification that is, to our knowledge, new to the literature. To formalize these tests, we first develop a simple theoretical model of the lender's credit scoring problem, and use it to understand the effects of the new information revealed in the bureau. We capture in the model an unusual feature of microfinance credit bureaus, which is that they report on the behavior of groups rather than individuals when loans are made to jointly liable borrowers. Because the lender can observe and correlate demographic characteristics and outcomes from its own clientele in a scoring model, the new information revealed by the bureau is orthogonal to what could previously be predicted. Despite this, we show that the probability of the lender selecting a borrower in (out) as a result of the bureau is increasing (decreasing) in the pre-bureau score, and that the variance of the prediction error on the client quality is an increasing function of the size of the group in which a borrower takes loans. We then specify how borrowers respond to the bureau both through a reduction in moral hazard and through altering the process by which they screen new members in joint liability groups. We find impacts of informational changes on both sides of the market. In terms of adverse selection, the ejection rate rises by 15% when the lender first uses the bureau, but this impact on the size of the loan portfolio is more than compensated for by new loans made to borrowers to whom the institution had never previously lent. Borrowers selected using the credit bureau are better clients, with better repayment performance and higher growth of future loans. Ongoing clients who are not ejected are able to take larger loans but their performance exhibits a small deterioration. The selection process benefits more women than men. In terms of moral hazard, the repayment performance shows a modest and temporary improvement when borrowers become aware of the bureau. Groups then also exhibit an adverse selection effect, ejecting some worse-performing members, and unexpectedly it is now women who lose access to credit more than men. We use data from the bureau itself to demonstrate that the training induces a 10% jump in the probability that a client will take a loan from an outside lender, and we see sharp differences across borrower types in the ability to handle this surge in total debt. Overall, the bureau permits a substantial expansion of credit among lenders in the system while simultaneously driving down delinquency.

We utilized an unusual pair of experiments which allowed us to decompose the impacts of a new credit bureau into two parts: what happens when a lender observes new information about borrowers, and what happens when borrowers become aware that lenders can observe this new information. We find that the new information in the hands of the lender has stark impacts. There is a large increase in the turnover of the client base, particularly in the 6 months after introduction of the bureau to a branch. Large numbers of individual and SG clients are ejected, and the categories of clients ejected are indeed those with lower average repayment performance (males, more educated borrowers) and larger variance in performance (males). There is a dramatic improvement in the repayment performance of new individual clients and in the size of the loans made to new SG borrowers. The new individual borrowers are better future clients in that they are more likely to take subsequent loans and have faster growth in their borrowing. For Solidarity Group borrowers, the bureau induces a strong swing toward smaller groups and allows the lender to increase loan sizes without causing repayment problems. At the level of the lender, there is a huge increase in employee efficiency, with the average credit officer selecting 63% more new individual borrowers over an average of 6 per month, increasing the number of loans by 27%, and this without any deterioration in portfolio performance. The reduction in adverse selection from improved credit market information therefore presents strong benefits for lenders, generating more clients, larger loan portfolios, and improved repayment. When group borrowers learn of the bureau and what it implies for them, we also see significant impacts on borrowing. Informed Solidarity Groups show an immediate improvement in repayment performance, with a sharp decline in delinquent final payments, solely due to reduction in moral hazard. Subsequent loans also exhibit a sharp decline in delinquency due to reduction both in moral hazard and adverse selection in group formation. There are, by contrast, no impacts of information about the credit bureau on the repayment performance of CB. For SG, there are important group compositional shifts, with a decline in female membership. Female SG members have less delinquent loans, but they have more intermediate repayment problems, which are documented by the credit bureau, to their detriment. Both SG and CB clients use their knowledge of the bureau to start getting access to credit from outside lenders. For CB members, outside loans taken by good clients do not lead to repayment problems. This is not the case for the less experienced clients for whom taking more loans leads to repayment difficulties. Ironically, in several ways the impact of the credit bureau experiment confirms the efficacy of group lending in combating asymmetric information. First, the improvement in the lender's screening ability is larger for individual borrowers than for SG borrowers, indicating that the degree of asymmetric information was lower for group loans to begin with. Solidarity Groups become smaller when bureau information is available, suggesting that the bureau acts as a substitute for information and incentives otherwise provided by larger groups. The trainings have no impact on the inside repayment performance of Communal Bank borrowers, where group incentives should have been the strongest to begin with. And finally, those less experienced CB borrowers who increase their net indebtedness run into repayment problems, indicating that the credit system in the absence of the bureau was providing as much credit as these clients could manage without default. Hence, while our results show that outcomes can be improved with the use of a bureau, they also highlight the value of group lending in enabling lenders to combat asymmetric information. Genesis is a well-respected lender that used standard best practices for MFI loan screening prior to introduction of the bureau. Despite this, our results demonstrate that substantial asymmetric information remained in this market, because the bureau was highly effective at improving credit market outcomes. Since bureaus are a relatively low-cost institutional innovation, this implies that they should be made a part of efforts to achieve financial deepening in developing countries. Their use appears to be clearly to the benefit of lenders, and in a competitive market, this should lead to lower interest rates for borrowers over time. The losers from the introduction of a bureau are those borrowers who are screened out as a result of the information, and ongoing borrowers who may lose insurance opportunities as a result of the decline in solidarity group size. We show that group reporting can in fact reinforce the group mechanisms that underlie microfinance lending. The ultimate outcome is efficiency gains for the innovating institution, gains for the more capable borrowers, and increased economic differentiation across agents.