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Mortgage Default and Bankruptcy: Theory and Empirical Evidence Wenli Li, FRB Philadelphia Michelle J. White, UCSD and NBER.

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Presentation on theme: "Mortgage Default and Bankruptcy: Theory and Empirical Evidence Wenli Li, FRB Philadelphia Michelle J. White, UCSD and NBER."— Presentation transcript:

1 Mortgage Default and Bankruptcy: Theory and Empirical Evidence Wenli Li, FRB Philadelphia Michelle J. White, UCSD and NBER

2 What we do: Examine the interaction of homeowners’ decisions to default on their mortgages and file for bankruptcy. We test: – Whether homeowners are more likely to default versus file for bankruptcy when they gain financially from either, and – Whether homeowners are more likely to default versus file for bankruptcy when they are liquidity-constrained. We use new data that combines information on mortgage debt and other types of debt. – Previously, the literatures on mortgage default and bankruptcy were separate because of lack of combined data.

3 How are mortgage default and bankruptcy decisions related? Bankruptcy helps homeowners avoid mortgage default/keep their homes by discharging unsecured debt. Bankruptcy helps homeowners keep their homes by delaying foreclosure and allows homeowners to repay mortgage arrears over five years. But bankruptcy helps homeowners with high income or high assets less, since they must use repay from future income and assets. Default helps homeowners preserve access to credit card loans—some choose default/avoid bankruptcy. Bankruptcy helps homeowners give up their homes by discharging deficiency judgments.

4 Homeowners’ predicted mortgage default and bankruptcy decisions

5 Notes: Diagram is separately calculated for each homeowner. As shown it assumes that bankruptcy reform is in effect (means test), mortgage debt is fixed, and unsecured debt is fixed and high. Homeowners are predicted to default and file for bankruptcy only when it is in their financial interest. – D/B predicted when house value is low and income is low. (House value is low enough that the cost of renting < cost of owning.) – D/NB predicted when V is low and Y is high. – ND/B predicted when V is higher and Y is high. (Here the income boundary between B and NB shifts to the right because of homeowners’ gains from filing for bankruptcy.) – ND/NB applies when V and Y are both high and when V is very high and Y is low. (Best not to default because must repay unsec debt from sale proceeds of the house.)

6 Same, but some homeowners default due to liquidity constraints

7 Notes: Now some additional homeowners default even when it is against their financial interest b/c V is high. They default because of liquidity constraints.

8 Data: We merge three datasets: – LPS: large sample of mortgages with information from the mortgage application, plus monthly updates on payment and bankruptcy. – Equifax: sample of individuals with information about all types of debt, plus quarterly updates on payment, credit scores, debt-to-income ratio. – HMDA: use it to merge LPS and Equifax based on date/location/principal of mortgage.

9 Final dataset: All mortgages originated They are followed quarterly until the mortgage is paid off or transferred, the homeowner defaults or files for bankruptcy, or at the end of Currently, we include only prime, fixed rate mortgages. Each quarter, we also have: – Amount owed and payment record for second mortgages, credit card debts, student loans, auto loans, and installment loans. (Half of each debt if homeowner married.) – Updated credit score and debt-to-income ratio. – Income at origination and homeowner’s age, sex, marital status.

10 Specification: We estimate a multi-probit model explaining: – Default/no bankruptcy (aD/NB). – No default/bankruptcy (aND/B). – Relative to no default/no bankruptcy (aND/NB). – We drop simultaneous default/bankruptcy because it’s very rare (aD/B). Main variables of interest are the predicted decision variables D/NB, ND/B, D/B. Control variables, quarter and state dummies. Errors clustered by mortgage.

11 Predicted signs: D/NB actualND/B actual D/NB predicted Own effect (+)Cross effect (-) ND/B predictedCross effect (-)Own effect (+) D/B predictedSequence effect (+) Sequence effect (-)

12 Summary statistics (quarterly) PredictedActual D/NB ND/B D/B ND/NB

13 Results w/o liquidity constraint: (% change when prediction changes) D/NB actualND/B actual D/NB predicted38%*** (own effect) -60%*** (cross effect) ND/B predicted-38%*** (cross effect) 42%* (own effect) D/B predicted50%*** (sequence eff.) -36%** (sequence eff.)

14 Add liquidity constraint: Rerun the model with an additional dummy variable for homeowners who are liquidity- constrained—combined debt payments are more than 50% of income. % of observations that are liquidity- constrained? Everything else remains the same.

15 Results with liquidity constraint: D/NB actualND/B actual D/NB predicted47%*** (own effect) -52%*** (cross effect) ND/B predicted-54%*** (cross effect) 99%*** (own effect) D/B predicted4%*** (sequence eff.) -57%*** (sequence eff.)

16 Conclusions: Homeowners’ mortgage default and bankruptcy decisions respond strongly to financial benefit. are related. The two decisions are related—homeowners are more likely to file for bankruptcy. Liquidity constraints make homeowners more likely to do both.

17 Future work: Examine subprime mortgages and adjustable rate mortgages. Compare results when default and bankruptcy decisions are independent.


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