Combining Theory and Empirics for Causal Inference in Economics: Two Examples | 9am PT, Tues Jan 9, 2024
Grigory Bronevetsky
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Combining Theory and Empirics for Causal Inference in Economics: Two Examples Prof Toni Whited, University of Michigan  Tuesday, Jan 9 | 9am PT Hi all, The presentation will be via Meet and all questions will be addressed there. If you cannot attend live, the event will be recorded and can be found afterward at Abstract: This talk illustrates two ways of combining theory and reduced form statistical techniques to make causal inference. The first example considers the effects of taxes on corporate leverage. Using variation in state corporate income tax rates, we find, contrary to prior research, that corporate leverage rises after tax cuts, mostly for small private firms but to a lesser extent for public firms. We use an estimated dynamic equilibrium model to show that tax cuts result in more distant default thresholds and thus lower credit spreads. These effects outweigh the loss of the interest tax deduction and lead to higher optimal leverage choices, especially for firms with stringent default conditions, such as the small private firms we study. The second example considers the use of a model to understand causal inference about a variable that does not yet exist: central bank digital currency. We estimate a dynamic banking model to quantify the impact of a CBDC on banks. Our counterfactuals show that a one-dollar introduction of CBDC replaces bank deposits by 80 cents on the margin. Lending falls by 25% of the drop in deposits because banks partially replace lost deposits with wholesale funding. This substitution raises banks' interest-rate risk exposure, lowering their resilience to negative equity shocks. If CBDC bears interest or is intermediated through banks, it captures a greater deposit market share, amplifying the impact on lending. CBDC especially affects small banks, which face expensive wholesale funding. Bio: Toni Whited is the Frederick G L Huetwell Professor and Professor of Economics at the University of Michigan. Professor Whited received her B.A. in economics and French, summa cum laude, from the University of Oregon in 1984 and her Ph.D. in economics from Princeton in 1990, working with Ben Bernanke. Professor Whited has taught in a wide variety of areas in finance, macroeconomics, and econometrics at the undergraduate, MBA, and doctoral levels. She has published over 40 articles in top-tier economics and finance journals. Her research covers topics such as the effects of financial frictions on corporate investment, econometric solutions for measurement error, corporate cash policy, structural estimation of dynamic models, monetary policy, and corporate diversification. She has won a Jensen Prize for one of the top articles in corporate finance in the Journal of Financial Economics and twice won a Brattle Prize for one of the top articles in the Journal of Finance in corporate finance. She is the past-president of the Western Finance Association, and she serves as editor-in-chief for the Journal of Financial Economics. More information on previous and future talks: https://sites.google.com/modelingtalks.org/entry/home |
