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Three Essays on the Credit Card Debt...

Wu, Di.

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Three Essays on the Credit Card Debt Puzzle, Income Falsification, and Numerical Approximation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Three Essays on the Credit Card Debt Puzzle, Income Falsification, and Numerical Approximation./
Author:	Wu, Di.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	123 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-05, Section: A.
Contained By:	Dissertations Abstracts International81-05A.
Subject:	Economics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27712114
ISBN:	9781392634356

Three Essays on the Credit Card Debt Puzzle, Income Falsification, and Numerical Approximation.
Wu, Di.

Three Essays on the Credit Card Debt Puzzle, Income Falsification, and Numerical Approximation. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 123 p.

Source: Dissertations Abstracts International, Volume: 81-05, Section: A.

Thesis (Ph.D.)--The Ohio State University, 2019.

This item must not be sold to any third party vendors.

This dissertation is composed of three chapters on the credit card debt puzzle, income falsification, and numerical approximation. The first chapter explores a puzzle that many card users carry significant credit card debts while keeping low yielding liquid assets in their checking and savings accounts at the same time. Past studies often attribute this puzzle to consumers' inconsistent preference (Shui and Ausubel (2004); Bertaut et al. (2008); Meier and Sprenger (2010)). However, the violation of no-arbitrage theory is not well explained. To explore this phenomenon under a rational expectation framework, we are the first to use a theoretical model to show that consumers hold liquidity and carry credit card debt simultaneously because of the risk aversion to defaulting on mortgage payments. Further, we calibrate our model to match the household level data and provide empirical evidence to support the hypothesis of risk aversion to default. Our findings supplement Telyukova's (2008 & 2013) theory of precautionary saving, which proposes that liquidity constraint plays an important role in the puzzle. Due to risk aversion, a home owner prefers to finance his/her consumption through credit cards and keep the limited liquid assets as precautionary savings for mortgage payments. In addition, we find that a home owner who has a mortgage is more likely to hold liquid assets and revolves credit card debt, such household also searches for credit cards with lower APR to reduce interest charges. Our finding is consistent with the common view that consumers make an effort to defend their properties. The second chapter investigates the income overstatement on mortgage applications prior to the 2008 crisis. While most researchers focus on the impact of income falsification on mortgage performance, few have investigated the relationship between the prevalence of fraudulent income reporting and lending standards at the market level. We measure the degree of income overstatement on mortgage applications across counties in the U.S. In our examination of the relation between income overstatement and lending decision, we find that prior to the 2008 crisis, lenders' approval decisions were not responsive to widespread income falsification when lenders faced changes in the borrower pool and deteriorating information quality. On the other hand, lower Debt-to-income (DTI) ratios are associated with higher degrees of income overstatement. However, such a change in the DTI ratio is most likely to be an indication of lax screening by lenders. These findings shed light on mortgage fraud and the important role that information quality plays in the validity of the underwriting metric. The third chapter introduces a new way to solve the dynamic programing problems using multidimensional piecewise-linear interpolation. Models with occasionally binding inequality constraints or discrete choices often introduce kinks into the shape of value functions, which leads to difficulties in implementing numerical approximation. We introduce an innovative way to combine piecewise linear interpolation with new advances in mixed integer linear programming. This method does not use the Euler equations and can achieve a numerical solution close to global optimality even when the value function has kinks. To test the new method's feasibility, we apply it to a classic example of the Real Business Cycle with a lower bound on investment that is a model with an occasionally binding constraint. We show that the numerical policy function derived by our algorithm has the desirable characteristics imposed by the model.

ISBN: 9781392634356Subjects--Topical Terms:

517137
Economics.

Three Essays on the Credit Card Debt Puzzle, Income Falsification, and Numerical Approximation.
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300 $a 123 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-05, Section: A.
500 $a Advisor: Sam, Abdoul;Cai, Yongyang.
502 $a Thesis (Ph.D.)--The Ohio State University, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a This dissertation is composed of three chapters on the credit card debt puzzle, income falsification, and numerical approximation. The first chapter explores a puzzle that many card users carry significant credit card debts while keeping low yielding liquid assets in their checking and savings accounts at the same time. Past studies often attribute this puzzle to consumers' inconsistent preference (Shui and Ausubel (2004); Bertaut et al. (2008); Meier and Sprenger (2010)). However, the violation of no-arbitrage theory is not well explained. To explore this phenomenon under a rational expectation framework, we are the first to use a theoretical model to show that consumers hold liquidity and carry credit card debt simultaneously because of the risk aversion to defaulting on mortgage payments. Further, we calibrate our model to match the household level data and provide empirical evidence to support the hypothesis of risk aversion to default. Our findings supplement Telyukova's (2008 & 2013) theory of precautionary saving, which proposes that liquidity constraint plays an important role in the puzzle. Due to risk aversion, a home owner prefers to finance his/her consumption through credit cards and keep the limited liquid assets as precautionary savings for mortgage payments. In addition, we find that a home owner who has a mortgage is more likely to hold liquid assets and revolves credit card debt, such household also searches for credit cards with lower APR to reduce interest charges. Our finding is consistent with the common view that consumers make an effort to defend their properties. The second chapter investigates the income overstatement on mortgage applications prior to the 2008 crisis. While most researchers focus on the impact of income falsification on mortgage performance, few have investigated the relationship between the prevalence of fraudulent income reporting and lending standards at the market level. We measure the degree of income overstatement on mortgage applications across counties in the U.S. In our examination of the relation between income overstatement and lending decision, we find that prior to the 2008 crisis, lenders' approval decisions were not responsive to widespread income falsification when lenders faced changes in the borrower pool and deteriorating information quality. On the other hand, lower Debt-to-income (DTI) ratios are associated with higher degrees of income overstatement. However, such a change in the DTI ratio is most likely to be an indication of lax screening by lenders. These findings shed light on mortgage fraud and the important role that information quality plays in the validity of the underwriting metric. The third chapter introduces a new way to solve the dynamic programing problems using multidimensional piecewise-linear interpolation. Models with occasionally binding inequality constraints or discrete choices often introduce kinks into the shape of value functions, which leads to difficulties in implementing numerical approximation. We introduce an innovative way to combine piecewise linear interpolation with new advances in mixed integer linear programming. This method does not use the Euler equations and can achieve a numerical solution close to global optimality even when the value function has kinks. To test the new method's feasibility, we apply it to a classic example of the Real Business Cycle with a lower bound on investment that is a model with an occasionally binding constraint. We show that the numerical policy function derived by our algorithm has the desirable characteristics imposed by the model.
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