Daniel Kim

Daniel Kim

Contact Information

  • office Address:

    2332 Steinberg-Dietrich Hall,
    3620 Locust Walk
    Philadelphia, PA 19104

Research Interests: Empirical Corporate Finance; Corporate Bankruptcy; Asset Pricing; Applied Econometrics

Links: Personal Website, CV

Overview

I am a Finance PhD candidate at The Wharton School at the University of Pennsylvania with research interests in empirical corporate finance, corporate bankruptcy, asset pricing and applied econometrics.

My job market paper, entitled “Shareholder Recovery and Leverage” estimates shareholder’ recovery rate in default and studies its implication.

I am on the job market this year and will be available for interviews at the AEA/AFA meetings in Atlanta, Georgia (Jan 4-6, 2019)

 

Matriculation Year: 2013

Prior Degrees:
M.S. in Quantitative Finance, Carroll School of Management, Boston College, 2013
M.Eng in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2006
B.S. in Applied Mathematics / Electrical Engineering, Massachusetts Institute of Technology, 2005

Work Experience:
Project Leader / Senior Application Engineer, Oracle Corporation, 2007-2012

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Research

Shareholder Recovery and Leverage (Job Market Paper) view
– presented at 2017 AFA Ph.D. Poster Session, 2018 Trans-Atlantic Doctoral Conference, 2018 Wharton PhD Finance Seminar, 2018 INSEAD-Wharton Doctoral Consortium

Abstract: According to the absolute priority rule (APR), firm shareholders should recover nothing in default unless creditors are paid in full. However, historically, shareholders have sometimes received a positive payoff in default. In this paper, I develop a dynamic model to estimate shareholder recovery rate and examine its implications. A positive recovery rate makes shareholders more willing to default, which increases borrowing costs. In response, firms lower leverage ex-ante. This channel helps to match distributions of both leverage and default probabilities. Structural estimation reveals a dramatic change over time in the U.S. bankruptcy system: shareholder recovery rate increased from roughly zero to 29% around the Bankruptcy Reform Act of 1978, and has gradually decreased back to zero. Finally, I show that a positive shareholder recovery rate has a quantitatively large effect on leverage, default probabilities, firm value, and government tax revenue.

Measurement Error in Multiple Equations: Tobin’s q and Corporate Debt, Investment, and Saving, with Karim Chalak. view
-presented at 2018 North American Summer Meeting of the Econometric Society, 2018 Wharton PhD Finance Seminar, 2018 Western Economic Association, 2018 Southern Economic Association, 2018 Triangle Econometrics Conference (Duke)

Abstract: We econometrically characterize the identification regions for the coefficients in a system of linear equations under the classical measurement error assumptions. We demonstrate the identification gain that results from jointly considering the equations, as opposed to separately. We apply this framework to COMPUSTAT data and analyze the effects of cash flow on the investment, saving, and debt of firms when Tobin’s q is used as an error-laden proxy for marginal q. The linear regression estimates suggest that cash flow affects investment positively, saving positively, and debt negatively. These results are incompatible with some economic theories and the literature, sometimes, attributes this discrepancy to the measurement error in Tobin’s q. Using our framework, we document a considerable identification gain that results from analyzing the investment, saving, and debt equations jointly. Further, the measurement error in Tobin’s q can reconcile the discrepancy with the theories if, and only if, Tobin’s q is a noisy proxy for marginal q. If a researcher maintains that Tobin’s q is a moderately accurate proxy for marginal q, then a more elaborate theory or specification must be considered.

Measurement Error without Exclusion: the Returns to College Selectivity and Characteristics, with Karim Chalak. view
R&R at Journal of Business and Economic Statistics

Abstract: This paper studies the identification of the coefficients in a linear equation when data on the outcome, covariates, and an error-laden proxy for a latent variable are available. We maintain that the measurement error in the proxy is classical and relax the assumption that the proxy is excluded from the outcome equation. This enables the proxy to directly affect the outcome and allows for differential measurement error. Without the proxy exclusion restriction, we first show that the coefficients on the latent variable, the proxy, and the covariates are not identified. We then derive the sharp identification regions for these coefficients under any configuration of three auxiliary assumptions. The first weakens the assumption of no measurement error by imposing an upper bound on the noise to signal ratio. The second imposes an upper bound on the outcome equation coefficient of determination that would obtain had there been no measurement error. The third weakens the proxy exclusion restriction by specifying whether the latent variable and its proxy affect the outcome in the same or the opposite direction, if at all. Using the College Scorecard aggregate data, we illustrate our framework by studying the financial returns to college selectivity and characteristics and student characteristics when the average SAT score at an institution may directly affect earnings and serves as a proxy for the average ability of the student cohort.

The Asset Pricing Implication of Equity Capital Constraint, with Amir Yaron

Description: To understand the crisis, He and Krishnamurthy (2013) have adopted the equity capital constraint to derive price dynamics for the intermediary-held assets. Our work shows that equity capital constraint, by itself, is insufficient to explain the joint price dynamics of intermediary-held assets and household-held assets, which, we argue, is necessary to truly understand the financial crisis.

  • Daniel Kim, Shareholder Recovery and Leverage.

    Abstract: According to the absolute priority rule (APR), firm shareholders should recover nothing in default unless creditors are paid in full. However, historically, shareholders have sometimes received a positive payoff in default. In this paper, I develop a dynamic model to estimate shareholder recovery rate and examine its implications. A positive recovery rate makes shareholders more willing to default, which increases borrowing costs. In response, firms lower leverage ex-ante. This channel helps to match distributions of both leverage and default probabilities. Structural estimation reveals a dramatic change over time in the U.S. bankruptcy system: shareholder recovery rate increased from roughly zero to 29% around the Bankruptcy Reform Act of 1978, and has gradually decreased back to zero. Finally, I show that a positive shareholder recovery rate has a quantitatively large effect on leverage, default probabilities, firm value, and government tax revenue.

  • Daniel Kim and Karim Chalak (Working), Measurement Error in Multiple Equations: Tobin’s q and Corporate Debt, Investment, and Saving.

    Abstract: This paper studies identifying the coefficients in a system of linear equations with a mismeasured explanatory variable. We characterize the identification regions for the coefficients under the classical measurement error assumptions and demonstrate the identification gain that results from considering the equations jointly as opposed to separately. We then derive the identification regions under either or both of two auxiliary assumptions. The first weakens the assumption of "no measurement error" by imposing an upper bound on the net of the covariates "noise to signal" ratio. The second assumption weakens the assumption that the covariance matrix of the disturbances is diagonal by restricting the sign of the cross-equation disturbances. For inference, the paper implements results from the intersection bounds literature. Using data from COMPUSTAT, the paper applies its framework to study the effects of cash flow on the investment, saving, and debt of corporate firms in the US when Tobin's q is used as an error-laden proxy for a firm's marginal q. We find that the effects of cash flow on investment, saving, and debt can be zero if and only if Tobin's q is a noisy proxy for marginal q. Otherwise, cash flow affects investment and saving positively and debt negatively.

  • Daniel Kim and Karim Chalak (Under Revision), Measurement Error without Exclusion: the Returns to College Selectivity and Characteristics.

    Abstract: This paper studies the identification of the coefficients in a linear equation when data on the outcome, covariates, and an error-laden proxy for a latent variable are available. We maintain that the measurement error in the proxy is classical and relax the assumption that the proxy is excluded from the outcome equation. This enables the proxy to directly affect the outcome and allows for differential measurement error. Without the proxy exclusion restriction, we first show that the coefficients on the latent variable, the proxy, and the covariates are not identified. We then derive the sharp identification regions for these coefficients under any configuration of three auxiliary assumptions. The first weakens the assumption of no measurement error by imposing an upper bound on the noise to signal ratio. The second imposes an upper bound on the outcome equation coefficient of determination that would obtain had there been no measurement error. The third weakens the proxy exclusion restriction by specifying whether the latent variable and its proxy affect the outcome in the same or the opposite direction, if at all. Using the College Scorecard aggregate data, we illustrate our framework by studying the financial returns to college selectivity and characteristics and student characteristics when the average SAT score at an institution may directly affect earnings and serves as a proxy for the average ability of the student cohort.

Teaching

Teaching Assistant, The Wharton School, University of Pennsylvania

FNCE921 (PhD: Empirical Methods in Finance) for Amir Yaron (2015,2016)
FNCE 219/719 (International Financial Markets) for Urban Jermann (2015)
FNCE 219/719 (International Financial Markets) for Amir Yaron (2016)
FNCE 208/731 (International Corporate Finance) for Karen Lewis (2016,2017)
FNCE 393/893 (Global Monetary and Financial Institutions: Theory and Practice) for Zvi Eckstein (2016)

Awards and Honors

Jacobs Levy Equity Management Center Grant (2017,2018)
Dean’s Fellowship for Distinguished Merit (Wharton) (2013-2019)
Rodney L. White Center for Financial Research (Wharton) (2016,2017,2018)
Russell Ackoff Doctoral Student Fellowships (Wharton) (2015)
George James Term Fund (2017)

    Activity

    Latest Research

    Daniel Kim, Shareholder Recovery and Leverage.
    All Research