1. INTRODUCTION
Since 1990, consumer bankruptcy filings as a percentage of total filings have been steadily increasing. In 1990, the number of filings was approximately 718,000 (92 percent of all filings), which doubled in 2009 to 1.4 million filings (accounting for 96 percent). Over the same time period, aggregate health care expenditures have risen from around 12 percent of GDP to about 17 percent of GDP1. By 2017, the Center for Medicare and Medicaid Services projects that health care will account for about 20 percent of GDP. This paper questions the extent to which consumer bankruptcy filings and health care expenditures are correlated, and whether there is a causal relationship between the two. In particular, the paper tries to identify the extent to which a household’s medical debts cause a personal bankruptcy filing2.
Our results suggest that in households where medical debts are not the primary form of debt, there is a 36 percent increase in the probability of filing for bankruptcy when the debt level goes up by 10 percent, while in households with primarily medical debts, the probability of filing goes up by 27 percent. Hence medical debts influence bankruptcy filings differently depending upon the total debt composition of the household. We use household level data from the Panel Study of Income Dynamics (PSID) to estimate the impact of illnesses and medical debts on the probability of filing for bankruptcy. This is the first paper to use longitudinal household data to identify the impact of medical bills (and other health related factors) on bankruptcy. We extend our analysis to further study the post-bankruptcy situation for individuals. Using data on home ownership and labor supply in the PSID, we conclude that individuals who have filed for bankruptcy are significantly less likely to own homes, while they are significantly more likely to increase labor supply to accumulate savings.
The empirical literature on this topic is mixed. Studies based on surveys of bankruptcy filers, such as Himmelstein, Warren, Thorne, and Woolhandler [1] using data from the Consumer Bankruptcy Project, claim that families with medical problems and medical debts account for more than half of all bankruptcy filings3. However, their classification of a medical bankruptcy is too broad4. Further, methodologically, a big drawback of the study is that it does not include non-filers in the sample. This leads to a sample selection bias. In effect, by including only people with a bankruptcy filing, the authors are overstating the incidence of medical debts. Our study corrects for this by including both filers and non-filers, and people with and without medical debts. In addition, we include other types of debts as well as other household and economic characteristics that might drive families to file for bankruptcy.
According to another survey, the Health Care Costs Survey [2], close to 23 percent of Americans had problems paying medical bills in the previous year5. Around 19 percent experienced other financial consequences due to medical bills, such as having to borrow money, being contacted by a collection agency, or even having to file for bankruptcy. Another study based on the Commonwealth Fund Biennial Health Insurance Survey reveals that an estimated 77 million (37 percent) Americans aged 19 and older have difficulty paying medical bills, have accrued medical debt or both6. Domowitz and Sartain [3] find that “high” medical debt also contributes positively to bankruptcy, though credit card debt is the single largest contributor to bankruptcy filings at the margin. Medical debt is included in a binary form with a positive value indicating expenses in excess of 2 percent of income. This classification is arbitrary and the authors make no attempt to explain why they used this measure. Further, the study is based on cross-sectional data and does not have demographic information. Thus it is unable to account for dynamic changes in household or state level conditions such as state incomes, unemployment rates etc.
The Office for United States Trustees (in the US Department of Justice), on the other hand, found that medical debt was not a major factor in the majority of bankruptcy cases filed in 20007. More than 50 percent of filers reported no medical debt at all, while only 11 percent had medical debt in excess of $5000. Further, only in 5 percent of the cases was medical debt one-half or more of total unsecured debt. On average, medical debt was only about 6 percent of all unsecured debt. In compareson, credit card debt comprised about 40 percent of all unsecured debt. More than half the cases reported credit card debt in excess of 50 percent of all debt.
We believe that a shortcoming with the earlier studies is that they are unable to isolate the impact of medical bills from other problems that the debtor faces, such as job loss, low earnings, and other credit card debts. This makes it difficult to conclude that high costs of medical care are causing the large number of bankruptcy filings. In this paper, we attempt to study the importance of various distinct factors, in particular other debts, such as credit card charges, that the household has incurred. We incorporate into the model both the traditional factors associated with a bankruptcy and the strategic factors such as the exemption levels across states, which affect the financial incentive to file for bankruptcy. We further attempt to control for health related factors including medical coverage. The panel nature of the data allows us to control for all the factors leading to the bankruptcy, rather than focusing only on the period around the time of the bankruptcy. Further, we include in the sample both filers and non-filers, instead of including only people who have already filed. This enables generalizations of results to the larger population as well.
In the next section, we discuss the data and explanatory variables used in the analysis. Section 3 details the empirical methodology and Section 4 presents the empirical results. Section 5 discusses the possible adverse effects of a bankruptcy filing. Section 6 concludes.
2. DATA SOURCE AND DESCRIPTION
2.1. Data Source and Summary Statistics
The data are available from the Panel Study of Income Dynamics (PSID), which is a longitudinal dataset tracking households since 1968. The PSID survey asks questions relating to demographic conditions as well as income, assets and debts of the household. In 1996, the PSID asked respondents whether they had ever filed for bankruptcy between 1996 and 1984, and if so, in what years and which state they filed. We use data relating to the period 1994-1996. Since the PSID is a longitudinal dataset, we include in the sample all heads of household who were in the sample all three years. Each year there are approximately 6000 household heads who are interviewed, thus the overall sample size is 18,259 household heads8. The bankruptcy filing rate among PSID respondents for the period 1994-1996 is approximately 0.4 percent, which is similar to the average national filing rate for that period for non-business filings of about 0.5 percent. The number of filings in our sample is 74.
The PSID asks a detailed set of questions on bankruptcy. These include questions on the primary, seconddary and tertiary reason for filing, given a list of possible reasons, which include medical bills, job loss, injury or illness etc. The largest contributor to bankruptcy filings was high credit card debt. Nearly 42 percent of respondents reported high credit card bills as the primary reason for filing, while an additional 9 percent claimed it as the secondary reason for filing. Other big reasons were job loss (13 percent) and divorce or separation from spouse (12 percent). Only 9 percent of the sample claimed medical bills as the primary reason for filing, and 7 percent claimed it as a secondary reason. Illness and Injury accounted for only 6 percent of the filings. Unfortunately, we are unable to use responses to reasons for filing in the regression, because it is by definition, asked only of those who had actually filed for bankruptcy.
The PSID also asks questions relating to debt levels. A drawback of the PSID dataset is that while it gives information on the total value of debt, it does not provide information on each kind of debt separately. Thus, the key innovation in the paper is to distinguish medical debtors from other kinds of debtors, in order to study the impact of medical debt on the probability of filing for bankruptcy. To do this we exploit a part of the survey that has questions relating to loans taken by the household for various purposes. The survey asks individuals whether they had ever taken loans to repay their debts, and what was the largest component of the loan i.e. what was the most important reason for taking the loan-possible reasons include repaying credit card debts, medical bills, car debts etc. They can also list other secondary or tertiary reasons for taking the loan. This is the main variable of interest, since it allows us to distinguish medical debtors from credit card debtors, or people who had high car or mortgage debt. Hence we can classify households as medical debtors if they listed medical debts as their primary, secondary or tertiary reason for taking a loan. We can further classify households as primarily medical debtors if they listed medical debts as their primary reason for taking the loan. This should help clarify the issue of whether medical debts are the largest component of debt for households that file, or is it mainly other forms of debt, such as credit card debt, that is primarily responsible for a large number of filings.
Other relevant variables available from the dataset relate to the health status of the individual, whether they missed any weeks of work due to illness, whether they had medical coverage, etc.
Table 1 presents sample summary statistics. In terms of demographics, about 70 percent of the population is male, and around 63 percent white. The average annual family income is $43,000, while average annual debts