Publications

When Fair Isn’t Fair:
Understanding Choice Reversals Involving Social Preferences

with J. Andreoni, B. Barton, D. Bernheim and J. Naecker
Journal of Political Economy, 2020, 128 (5)

In settings with uncertainty, tension exists between ex ante and ex post notions of fairness. Subjects in an experiment most commonly select the ex ante fair alternative ex ante and switch to the ex post fair alternative ex post. One potential explanation embraces consequentialism and construes reversals as time inconsistent. Another abandons consequentialism in favor of deontological (rule-based) ethics and thereby avoids the implication that revisions imply inconsistency. We test these explanations by examining contingent planning and the demand for commitment. Our findings suggest that the most common attitude toward fairness involves a time-consistent preference for applying a naive deontological heuristic.

Published Version
Citation
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Supplemental Appendix

Consumption Response to Credit Expansions:
Evidence from Experimental Assignment of 45,307 Credit Lines

American Economic Review, 2022, 112 (1), Lead Article

I design a large-scale field experiment that constructs a randomized credit limit extension isolating selection, anticipation, wealth, and interest rate effects and study the impulse responses on spending, contract choice, and balance sheets. Participants borrow to spend 11 cents on the dollar in the quarter of the limit increase, with a cumulative difference of 28 cents by the third year. The effects extend to those far from the limit, those who had the new limits as available credit, and those with a meaningful buffer of liquid assets. Participants near their limits borrow and spend when limits are relaxed but put off spending and save out of constraints under the counterfactual when limits are tight. The findings provide strong support for a buffer-stock interpretation that emphasizes the importance of precautionary saving.

Published Version
Citation
Working Paper
Slides
Supplemental Appendix
Johns Hopkins Macro Comp

Working Papers

Forbearance vs. Interest Rates:
Experimental Tests of Liquidity and Strategic Default Triggers

I study a randomized debt relief experiment and present three findings regarding default triggers and how relief affects these triggers. First, liquidity is important but not the sole trigger of default: delinquencies are most responsive to a rate reduction despite entailing the smallest payment reduction. Second, compatible with strategic behavior, borrowers default in response to future payments independent of liquidity and accounting solvency. Third, the extent of strategic behavior reflects the extent of borrowing constraints. These findings align with models positing a single strategic default trigger shaped by constraints. I discuss implications for targeting relief and modeling interest rate pass-through.

Working Paper
Slides

Precautionary Debt Capacity

with O. Kim

Firms with ample financial slack are unconstrained… or are they? In a field experiment that randomly expands debt capacity on business credit lines treated small-and-medium enterprises (SMEs) draw down 35 cents on the dollar of expanded debt capacity in the short-run and 55 cents in the long-run despite having debt levels far below their borrowing limit before the intervention. SMEs direct new borrowing to financing investment gradually over time and do not exhibit a measurable impact on delinquencies. Heterogeneity analysis by the risk of being at the credit line limit supports the SME motive to preserve financial flexibility.

Working Paper

Purpose, Intrinsic Incentives, and Output:
a Field Experiment with Investment Advisors

with A. Thakor and R. Thakor

Can intrinsically motivating employees with an organizational purpose (that transcends profit maximization) raise employee productivity and firm profitability? We study this question through a large-scale natural field experiment with a randomized control group within a large multinational financial services firm. Our research design overcomes the usual endogeneity and reverse causality concerns that make it difficult to establish a causal relationship between organizational purpose (and other intrinsic motivators) on performance. The experiment invites 808 investment advisors via a lottery to a workshop that explains, reminds, and connects the employees to the firm’s organizational purpose. We then compare the clearly defined and individually attributable outcomes of the invited group to the 14,191 advisors in the control group, which are indistinguishable from the invited based on ten outcome variables going back four years. We track impulse responses using administrative data on the firm’s bottom line (i.e., assets under management, total profits), employee financial performance (i.e., customer acquisition, bonus eligible profits), productivity (i.e., the likelihood of meeting expectations, progression in the organizational level ladder), client satisfaction metrics, and surveys. Finally, we scrutinize several additional commonly invoked mechanisms through which the effect manifests, such as social preferences, motivation, clarity, and identity, and quantify how much the employees value working for a company with purpose (i.e., in terms of a salary equivalent).

Paper

Work in Progress

Optimal Pricing using Causal Machine Learning

with Janis Skrastins and David Sraer

We introduce a novel approach to pricing consumer loans. Our approach combines structural modeling, experimental identification, and causal machine learning. We use the approach to quantify how much a bank can increase its profits by offering personalized pricing and better understand the extent of adverse selection and how it varies with borrowers’ characteristics. First, we study the pricing problem from the lender’s perspective. The optimal price depends on several key elasticities: how demand (takeup) and costs (missed payments) change as the interest rate changes. Second, we use a randomized pricing experiment alongside instrumental variables techniques to identify these elasticities and then calculate the optimal price and the profits under this price. Third, we devise a novel algorithm that partitions the data to maximize the lender’s profits. In in-sample honest tests, the algorithm substantially improves profits compared to risk-based and homogeneous pricing. We test the profitability of this procedure out of sample by underwriting new loans priced using this method and alternative pricing methods (uniform, risk-based, and homogeneous).

Capital Budgeting and Reallocation in Banks

with Janis Skrastins