Environmental and Security Risk Factors behind Mortgage Arrears in Israel

Borochov, Yosi; Portnov, Boris A.; Biger, Nahum

doi:10.1080/08965803.2020.1806616

Cited by 1 publication

(6 citation statements)

References 37 publications

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“…The Cox proportional hazards regression (Harrell, 2015) was used to identify and measure the effect of various factors on MA incidence. As compared to more commonly used binary logistic models for predicting MA events, such as those used by Borochov et al (2019) and Carter and Signorino (2010), the Cox proportional hazards model accounts not only for the event incidence (yes/no), but also for the duration of time until the event occurrence, thereby helping improve the statistical power of the model and reveal significant covariates (Barros and Hirakata, 2003).…”

Section: Discussionmentioning

confidence: 99%

“…The same with the current LTV, which is also estimated by an appraiser only once, at the time of mortgage issuance. Importantly, the survival model based on Cox regression and used in the paper, take under the consideration the time factor, in contract to many studies based on simple logistic regressions (see e.g., Borochov et al, 2019), which ignore that factor.…”

Section: Discussionmentioning

confidence: 99%

“…In a separate study carried out in Israel, Borochov et al (2019) assessed the effect of various environmental factors on the MA risk. Although the study estimated the odds ratios for several air pollution variables, it did not attempt to calculate environmentally adjusted risk estimates of MAs for different socioeconomic groups of borrowers.…”

Section: Ma Risk-assessment Modelsmentioning

confidence: 99%

“…Since buildings stand in fixed locations, they may be subject to damage due to local environmental conditions, such as flooding and earthquakes, and security risks near the borders. Other environmental factors, such as exposure to air pollution, may also affect the borrower's ability to make regular mortgage payments, because such factors may reduce productivity and increase work absenteeism, thereby making mortgage repayment more difficult (Borochov et al, 2019). While standard MA riskassessment models usually do not incorporate any of these environmental risk factors, our hypothesis is that these environmental factors may increase the MA risk asymmetrically for different groups of borrowers.…”

Section: Introductionmentioning

confidence: 99%

“…Although several previous studies analyzed various environmental risk factors in the context of real estate, most of these studies focused on home values (Gerardi et al, 2013;Wu and Dorfman, 2018;Sayag, 2012). To the best of our knowledge, only one study, by Borochov et al (2019), attempted to assess the effect of environmental factors on the MA risk. Although the study estimated odds ratios for several air pollution variables, it did not attempt to calculate environmentally adjusted risk estimates of MAs for different socioeconomic groups of borrowers, which we calculate in this study.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Environmentally Adjusted Risks of Mortgage Arrears for Different Socioeconomic Groups of Borrowers

Borochov¹,

Boris²

2021

ERSJ

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Purpose:The proper consideration of risk factors that can lead to the failure of a borrower to repay a mortgage is critical for both mortgage borrowers and lending institutions. Models for assessing the risk of mortgage arrears (MA) typically incorporate loan attributes and essential characteristics of the borrower, including net income, family size, age, education, and credit history. However, such standard MA models exclude environmental risk factors, which increase, as we hypothesize, the MA risk. Design/Methodology/Approach: We analyzed 90,000 individual mortgage records obtained from a leading commercial bank in Israel to verify this hypothesis. In the analysis, the mortgage records were geo-referenced by their seven-digit ZIP codes and linked to air pollution data and several other locational attributes. The analysis was performed using a Cox-type proportional hazard model. Findings:The study shows that residential exposure to high levels of air pollution tends to increase the MA risk by about 10%-25%, depending on the type of air pollutant and exposure level. We attribute this finding to the fact that exposure to air pollution may reduce productivity and increase work absenteeism, thus making mortgage repayment more difficult. Practical implications:The importance of the study is due to its three main novelty aspects: First, it suggests an empirical approach to adjusting MA risk estimates by accounting for environmental attributes of residential properties. Second, the analysis shows that borrowers' and mortgage's attributes (such as net monthly income, family size, and LTV ratio) tend to increase the MA risk asymmetrically for different groups of borrowers. Originality: The study demonstrates the utility of adding air pollution variables to the list of MA risk predictors, which helps to introduce important information not captured by other observables. To the best of our knowledge, this is the first study that assesses environmentally adjusted MA risks for different socioeconomic groups of borrowers.

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