A Quantitative Theory of the Credit Score

S-Tier
Journal: Econometrica
Year: 2023
Volume: 91
Issue: 5
Pages: 1803-1840

Authors (4)

Satyajit Chatterjee (Federal Reserve Bank of Philad...) Dean Corbae (University of Wisconsin-Madiso...) Kyle Dempsey (not in RePEc) José‐Víctor Ríos‐Rull (not in RePEc)

Score contribution per author:

2.018 = (α=2.02 / 4 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

What is the role of credit scores in credit markets? We argue that it is, in part, the market's assessment of a person's unobservable type, which here we take to be patience. We postulate a model of persistent hidden types where observable actions shape the public assessment of a person's type via Bayesian updating. We show how dynamic reputation can incentivize repayment. Importantly, we show how an economy with credit scores implements the same equilibrium allocation. We estimate the model using both credit market data and the evolution of individuals' credit scores. We conduct counterfactuals to assess how more or less information used in scoring individuals affects outcomes and welfare. If tracking of individual credit actions is outlawed, poor young adults of low type benefit from subsidization by high types despite facing higher interest rates arising from lower dynamic incentives to repay.

Technical Details

RePEc Handle
repec:wly:emetrp:v:91:y:2023:i:5:p:1803-1840
Journal Field
General
Author Count
4
Added to Database
2026-01-25