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AN INVESTIGATION OF STRATEGIC BEHAVIOR IN CONSUMER DEFAULT

Wang, Hui
http://rave.ohiolink.edu/etdc/view?acc_num=osu1338317059

Abstract Details

2012, Doctor of Philosophy, Ohio State University, Economics.
In this dissertation, I investigate in the individual “strategic” default behavior and the aggregate default rate along the business cycle both theoretically and empirically. There are three major parts in this work: (i) a theoretical analysis of a structural dynamic model of heterogeneous agents subject to both idiosyncratic and systemic unemployment shocks on “strategic” credit card default; (ii) an empirical analysis of “strategic” consumer default given both mortgage debt and consumer debt using a new national household data set covering the period from 2006 through 2011; and, (iii) an empirical analysis of debt default and consumers’ debt stress levels using the same data set as in part (ii). In the first part of this dissertation, I build a structural dynamic model of a population of heterogeneous agents subject to both idiosyncratic and systemic unemployment shocks. I derive the steady-state distribution of wealth for credit-worthy and -unworthy agents and aggregate net savings, credit worthiness, and loan default rates in the absence of cyclical movements in the economy. One of the major contributions of this part is a deeper understanding of strategic default behavior of borrowers. Specifically, the model produces non-monotonic, non-convex optimal savings/borrowing policies for credit-worthy agents that exhibit three distinct regimes in which the agent will: i) make the minimum required interest payment on her debt, if any, thus remaining credit-worthy; ii) default on her debt, thus being labeled credit-unworthy and being permanently barred from borrowing in the future; or iii) “max-out” her credit card, taking out the maximum allowable debt in anticipation of defaulting in the following period. I then introduce a business cycle with two states of the economy, a “normal state” of relatively low aggregate unemployment and a “recession state” with relatively high aggregate unemployment. I calibrate the model to match historically observed credit card charge-off rates 1990 to 2011. Simulations of the business cycle version of the model suggest that the charge-off rate is not affected immediately when a recession hits, but increases dramatically in the second and third period of a recession. When the recession is over, high default rates persist for one more period and subsequently declines. In the second part of this dissertation, I examine “strategic” default behavior for U.S. households that hold both mortgage and consumer debt. I use a new national-level household data set, the Consumer Finance Monthly, covering the period from 2006 through 2011 to empirically investigate the strategic decision to default on a mortgage as opposed to consumer loans. There are four main findings in this part. (1) A higher current loan-to-value ratio increases the probability of default on both mortgage debt and consumer loans. (2)When a house mortgage passes into underwater territory, the propensity to default on mortgage debt increases dramatically, but mortgage default does not change much thereafter as the house falls deeper under water. (3) As the liquidity provided by credit cards decreases, both mortgage and consumer loan defaults increase. However, as the remaining available credit card credit continues to shrink, consumers act aggressively to preserve liquidity to meet their day-to-day needs; and at certain point the propensity to default on consumer loans begins to decline while the propensity to default on mortgage debt continues to increase. (4) Deterioration in the housing market, as captured by changes in the state level house price index, increases default on both mortgages and consumer loans. Moreover, the state-level unemployment rate is positively related to mortgage default, but not to consumer loan default. The third part of this dissertation, I focus on the relationship between the experience of debt stress and consumer default. In particular, using the same data set as in the second part, I examine the aggregate debt stress trends from 2006 to 2011 and the factors contributing to individual debt stress and anxiety level. Both the Aggregate Debt Stress Index (ADSI) and the individual level Debt Stress Index (DSI) are constructed using the survey data set. The major finding of this part challenges the traditional view that mortgage default experience make homeowners more stressed than consumer loan default. I find that default on consumer debt could have a greater impact on an individual’s overall stress level, which may be related to liquidity of consumer loans and the debt colleting process. I also find that homeowners’ home equity position, captured by current LTV, is closely related to the individual experience of debt stress, and that higher LTV leads to a greater stress level. In addition, the stress reported by consumers increases with the number of credit cards they possess and the number of cards carrying maximum debt.
Lucia Dunn, PhD (Advisor)
Mario Miranda (Committee Member)
Donald Haurin (Committee Member)
123 p.
Economics; Finance
Strategic Default; Consumer Debt; Mortgage; Max-Out; Heterogeneous Agent

Recommended Citations

Citations

  • Wang, H. (2012). AN INVESTIGATION OF STRATEGIC BEHAVIOR IN CONSUMER DEFAULT [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338317059

    APA Style (7th edition)

  • Wang, Hui. AN INVESTIGATION OF STRATEGIC BEHAVIOR IN CONSUMER DEFAULT. 2012. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1338317059.

    MLA Style (8th edition)

  • Wang, Hui. "AN INVESTIGATION OF STRATEGIC BEHAVIOR IN CONSUMER DEFAULT." Doctoral dissertation, Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338317059

    Chicago Manual of Style (17th edition)

osu1338317059
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© 2012, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.