Econometrica

Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jul, 2024, Volume 92, Issue 4

Searching for Approval

https://doi.org/10.3982/ECTA18554
p. 1195-1231

Sumit Agarwal, John Grigsby, Ali Hortaçsu, Gregor Matvos, Amit Seru, Vincent Yao

This paper theoretically and empirically studies the interaction of search and application approval in credit markets. Risky borrowers internalize the probability that their application is rejected and behave as if they had high search costs. Thus, “overpayment” may be a poor proxy for consumer sophistication since it partly represents rational search in response to rejections. Contrary to standard search models, our model implies (1) endogenous adverse selection through the search and application approval process, (2) a possibly non‐monotone or non‐decreasing relationship between search and realized interest, default, and application approval rates, and (3) search costs estimated from transaction prices alone are biased. We find support for the model's predictions using a unique data set detailing search behavior of mortgage borrowers. Estimating the model, we find that screening is informative and search is costly. Counterfactual analyses reveal that tightening lending standards and discrimination through application rejection both increase equilibrium interest rates. This increase in realized interest rates is in part due to strategic complementarity in bank rate setting.


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Supplemental Material

Supplement to "Searching for Approval"

Sumit Agarwal, John Grigsby, Ali Hortaçsu, Gregor Matvos, Amit Seru and Vincent Yao

Appendix A includes additional tables and figures showing the robustness of our core results. Appendix B presents evidence that inquiries are the best available proxy of search in the mortgage market using data from HMDA and the (NSMO). Appendix C describes the additional robustness figures of Appendix A. Appendix D presents additional details on the estimation and simulation of the model, including a detailed derivation of the likelihood function. Appendix E explores the robustness of the theoretical results if search is simultaneous rather than sequential.

Supplement to "Searching for Approval"

Sumit Agarwal, John Grigsby, Ali Hortaçsu, Gregor Matvos, Amit Seru and Vincent Yao

The replication package for this paper is available at https://doi.org/10.5281/zenodo.10713249. The authors were granted an exemption to publish their data because either access to the data is restricted or the authors do not have the right to republish them. However, the authors included in the package a simulated or synthetic dataset that allows running their codes. The Journal checked the synthetic/simulated data and the codes for their ability to generate all tables and figures in the paper and approved online appendices. However, the synthetic/simulated data are not designed to reproduce the same results.