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The Industrial Organization of Financial Markets

Paper Session

Friday, Jan. 4, 2019 8:00 AM - 10:00 AM

Hilton Atlanta, 304
Hosted By: Industrial Organization Society
  • Chair: Vivek Bhattacharya, Northwestern University

Fiduciary Duty and the Market for Financial Advice

Vivek Bhattacharya
,
Northwestern University
Gaston Illanes
,
Northwestern University
Manisha Padi
,
University of Chicago

Abstract

As of 2018, the federal government is involved in the contested process---started under the Obama administration---of expanding fiduciary duties to broker-dealers. This paper uses a transactions-level dataset from a major financial services provider to study the causal impact of fiduciary duty on equilibrium product choice as well as market structure in the financial advice industry, specifically focusing on the annuities market. Utilizing a differences-in-differences approach that exploits variation across state lines and across types of advisers in terms of which advisers are subject to state-level common law fiduciary duty, we document a significant effect on product choice. Advisers with fiduciary duty sell variable annuities at significantly lower rates relative to advisers who do not. There is substantial heterogeneity in the response by gender, race, and experience. We also find some evidence that advisers without fiduciary duty steer consumers to annuities with a narrower set of investment options. We do not see much support for large changes in the number of financial advisers, or large compositional shifts in the set of advisers, as a result of fiduciary regulation. We propose a structural model of selective entry into the market for financial advice to endogenize the market structure and quantify the contribution of sorting across state lines and across adviser types to the estimates of the equilibrium effect of fiduciary duty.

Arbitration with Uninformed Consumers

Mark Egan
,
Harvard University
Gregor Matvos
,
University of Texas-Austin
Amit Seru
,
Stanford University

Abstract

We examine whether firms have an informational advantage in selecting arbitrators in consumer arbitration, and the impact of the arbitrator selection process on outcomes. We collect data containing roughly 9,000 arbitration cases in securities arbitration. Securities disputes present a good laboratory: the selection mechanism is similar to other major arbitration forums; arbitration is mandatory for all disputes, eliminating selection concerns; and the parties choose arbitrators from a randomly generated list. We first document that some arbitrators are systematically industry friendly while others are consumer friendly. Firms appear to utilize this information in the arbitrator selection process. Despite a randomly generated list of potential arbitrators, industry-friendly arbitrators are forty percent more likely to be selected than their consumer friendly counterparts. Better informed firms and consumers choose more favorable arbitrators. We develop and calibrate a model of arbitrator selection in which, like the current process, both the informed firms and uninformed consumers have control over the selection process. Arbitrators compete against each other for the attention of claimants and respondents. The model allows us to interpret our empirical facts in equilibrium and to quantify the effects of changes to the current arbitrator selection process on consumer outcomes. Competition between arbitrators exacerbates the informational advantage of firms in equilibrium resulting in all arbitrators slanting towards being industry friendly. Evidence suggests that limiting the respondent's and claimant's inputs over the arbitrator selection process could significantly improve outcomes for consumers.

Search and Screening in Credit Markets

Sumit Agarwal
,
National University of Singapore
John Grigsby
,
University of Chicago
Ali Hortaçsu
,
University of Chicago
Gregor Matvos
,
University of Texas-Austin
Amit Seru
,
Stanford University

Abstract

We study the interaction of search and the approval process in credit markets. We use a unique dataset that details search behavior for a large sample of mortgage borrowers, and loan application and rejection decisions. Our data reveal substantial dispersion in mortgage rates and search intensity. However, in contrast to predictions of standard search models, we find a novel non-monotonic relationship between search and realized prices: borrowers, who search a lot, obtain more expensive mortgages than borrowers' with less frequent search. We provide evidence that this occurs because lenders screen borrowers' creditworthiness, rejecting unworthy borrowers. This approval process differentiates consumer credit markets from other search markets. Based on these insights we build a model that combines search and screening in presence of asymmetric information. The model rationalizes the facts in the data and reveals that search behavior is determined not only by consumer sophistication but also by the approval process that relies on the underlying distribution of borrower quality. We estimate the parameters of the model and study several counterfactuals. We find that using overpayment by consumers as a proxy for consumer unsophistication may be misplaced since it partly represents rational search in presence of rejections. Moreover, the presence of better models with big data, could endogenously lead to more severe adverse selection in credit markets. Finally, place based policies, such as the Community Reinvestment Act, may lead to higher prices in equilibrium that reflect the endogenous search response rather than increased credit risk.

Regulatory Interventions in Consumer Search Markets: The Case of Credit Cards

Alessandro Gavazza
,
London School of Economics
Manollis Galenianos
,
Royal Holloway University of London

Abstract

Data on U.S. credit card markets display a large dispersion of interest rates at which consumers borrow. To understand this dispersion, we build a search model with two novel features: search effort/inattention and product differentiation. We calibrate the model to match statistics on the interest rate distribution that borrowers pay. The model fits these data well. Our analysis implies that low search effort accounts for almost all the dispersion in interest rates, whereas product differentiation is negligible. We use the calibrated model to study regulatory interventions in credit markets, such as caps on interest rates and higher lenders' entry costs.
Discussant(s)
Neale Mahoney
,
University of Chicago
Andrea Pozzi
,
Einaudi Institute for Economics and Finance
Tobias Salz
,
Columbia University
Glenn Ellison
,
Massachusetts Institute of Technology
JEL Classifications
  • L1 - Market Structure, Firm Strategy, and Market Performance
  • L2 - Firm Objectives, Organization, and Behavior