Cultural proximity and credit market efficiency

We present evidence that shared codes, religious beliefs, ethnicity - cultural proximity - between lenders and borrowers improves the efficiency of credit allocation. We identify in-group preferential treatment using dyadic data on the religion and caste of bank officers and borrowers from a bank in India, and a rotation policy that induces exogenous matching between officers and borrowers. Cultural proximity increases lending on both intensive and extensive margins and improves repayment performance, even after the in-group officer is replaced by an out-group one. Further, cultural proximity increases loan dispersion and reduces loan to collateral ratios. Our results imply that cultural proximity mitigates informational problems that adversely affect lending, which in turn relaxes financial constraints and improves access to finance.

From a new paper by Fisman, Paravisini, and Vig (May 2012).

The paper concludes:

In this paper, we have measured the extent of differential treatment in the loan market of those with a shared cultural background. Our empirical context provides a near-ideal setting for assessing differential in-group treatment: since we have data on both lender and borrower group affiliations, we may distinguish between own-group preferences versus differential treatment of minorities. Further, exogenous officer rotation allows us to identify in-group preferences from changes in officer branch assignments. Finally, since we focus on credit markets we may distinguish between explanations based on information, enforcement, and collusion by analyzing loan outcomes. Overall, our findings indicate that better screening and enforcement explain in-group preferential treatment.

Our study has a number of implications for theories of discrimination as well as economic policy. First, we note that the preferential treatment we uncover can itself perpetuate income inequality among minorities. In our context, 74.4% of the officers belong to the General Class category. This implies that the probability that a backward caste borrower (SC, ST, or OBC) will face unfavorable loan conditions is nearly 75%, purely for reasons of cultural affiliation.

Further, our findings suggest one possible mechanism through which statistical discrimination against minorities can arise. Minorities will be infrequently “matched” with a loan officer of their own group and hence have inferior loan outcomes on average. As a result lenders may form what are ultimately self-confirmatory beliefs about the creditworthiness of minorities if they rely on past average group performance to generate lending rules (Kim and Loury, 2009).

Finally, our findings have several policy implications. In the Indian context, targeted reservation policies that impose a larger proportion of backward caste officers in regions with a high concentration of backward caste borrowers may improve efficiency and reduce inequality of loan allocation. The reason, however, is different than the preference-based rationales for political reservations (see, for example, Chattopadhyay and Duflo, 2004). Our analysis suggests that reservations may improve contracting outcomes because they reduce information asymmetries between bureaucrats and their communities. Further, policies aimed at reducing cultural differences across groups - for example, by teaching a common language may lead to improvements in cross-group contracting. However, further research is required to identify which dimensions of cultural heterogeneity have a first-order effect on reducing the ability to exchange information across group boundaries.

See a related paper on price discrimination (May 2012).