Who Defaults on their Home Mortgage?

Doviak, Eric; MacDonald, Sean

doi:10.2139/ssrn.1802102

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…They find that the re-default rate declines relatively more when payment reduction is achieved through principal forgiveness as compared to lower interest rates. The empirical analysis of Doviak and MacDonald (2012) also emphasizes the role of modifications that reduce loan balances in preventing default. Mortgage refinancing is shown by Chen et al (2013) to play an important role in consumption smoothing, suggesting there are links within the market for consumption goods and housing.…”

Section: Literaure Reviewmentioning

confidence: 99%

“…The probability of default and prepayments might appear to be influenced by different set of customer and macroeconomic specific factors such as marriage status, income level, occupation, age, lenght of mortgage contract term, housing prices, interest rates, income shocks et al (LaCour-Little, 2008;Doviak & MacDonald, 2012). In general, studies focusing on default and prepayment behaviors use three known variables in their regression analyses: loan to value (LTV), loan to income (LTI) and mortgage payment to income (MTI) ratios.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Analysis of Defaults and Prepayments in the Turkish Mortgage Market

Varlı

Övenç

2019

Sosyoekonomi

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We analyze the determinants of default and prepayment in the Turkish mortgage market by utilizing data obtained from a large commercial bank. Our main findings suggest that default is positively affected by a high loan to value ratio and term length of mortgages, and negatively affected by certain quantitative easing periods, good expectations regarding the future, the ratio of real house prices to the size of the economy and mortgage customer's high school and above level of education and being married. The probability of prepayment rises with the increase in variables such as the gain ratio due to prepayment, high school and above level of education of the mortgage customer, size of the GDP and the ratio of real house prices to GDP. We also find that the likelihoods of both the cases of default and prepayment are locally maximized when nearly 60% of the term is reached.

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Section: Literaure Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Analysis of Defaults and Prepayments in the Turkish Mortgage Market

Varlı

Övenç

2019

Sosyoekonomi

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“…This paper discusses the findings of our analysis of the Full PFF and Short PFF datasets. We discuss our analysis of the combined HMDA-PFF dataset in a separate paper (Doviak and MacDonald, 2011).…”

Section: Introductionmentioning

confidence: 99%

Who Enters the Foreclosure Process?

Doviak

MacDonald

2011

SSRN Journal

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Since February 2010, detailed information on every home mortgage default and foreclosure in New York State must be filed with the New York State Banking Department (NYSBD). The data enables us to identify the financial characteristics that make a defaulted borrower more (or less) likely to enter the foreclosure process.Our analysis of the NYSBD data suggests that borrowers in default who took larger loans are more likely to progress to foreclosure. It also suggests that reducing principal balances may reduce the foreclosure rate, but might have an adverse effect on the mortgage industry.Given the frequent criticism of the Home Affordable Modification Program (HAMP), it is no surprise that defaulted borrowers whose mortgages were modified via HAMP progress to a lis pendens filing a higher rate than defaulted borrowers without a modification or with a non-HAMP modification. After controlling for delinquency length (and other factors) however, we find that the HAMP program may have been effective in helping defaulted borrowers avoid foreclosure.

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The role of neighborhood characteristics in mortgage default risk: Evidence from New York City

Chan

Gedal

Been

et al. 2013

Journal of Housing Economics

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Using a rich database of non-prime mortgages from New York City, we find that census tract level neighborhood characteristics are important predictors of default behavior, even after controlling for an extensive set of controls for loan and borrower characteristics. First, default rates increase with the rate of foreclosure notices and the number of lender-owned properties (REOs) in the tract. Second, default rates on home purchase mortgages are higher in census tracts with larger shares of black residents, regardless of the borrower's own race. We explore possible explanations for this second finding and conclude that it likely reflects differential treatment of black neighborhoods by the mortgage industry in ways that are unobserved in our data.

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Who Defaults on their Home Mortgage?

Cited by 4 publications

References 8 publications

Dynamic Analysis of Defaults and Prepayments in the Turkish Mortgage Market

Dynamic Analysis of Defaults and Prepayments in the Turkish Mortgage Market

Who Enters the Foreclosure Process?

The role of neighborhood characteristics in mortgage default risk: Evidence from New York City

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