Mortgage Risk Research Articles

Legal Research on the Causes of Mortgage Risk of Pre-Sale Real Estate in Mainland China (II)

Legal Research on the Causes of Mortgage Risk of Pre-Sale Real Estate in Mainland China (II)

Mortgage choice and inflation experiences in the Eurozone

In the Eurozone, households’ mortgage preferences vary widely, both within and across countries. This persistent heterogeneity in the choice between an adjustable rate mortgage (ARM) and a fixed rate mortgage (FRM) two decades after introducing a common currency is a puzzle. We argue that these patterns relate to the long-lasting effect of personal experiences of high-inflation periods. Analysing rich household data across 9 countries, we show that higher lifetime experienced inflation predicts significantly lower probability of holding an FRM: a 1 log-point increase in experienced inflation predicts a 71% decrease in the odds of holding an FRM. We relate our findings to existing theories on household mortgage risk management and argue that Eurozone prepayment penalties heighten the ‘inflation risk’ associated with FRMs. We also find that past personal inflation experiences are associated to risk aversion: households with histories of high and volatile inflation report lower willingness to take financial risk.

A ‘gray area’? Neighborhood decline and reclamation in 1950s and 1960s U.S. urban discourse and legislation

ABSTRACT With a focus on the period between the mid-1950s and mid-1960s, this paper analyses the use of the term gray areas as a descriptor for older neighborhoods in U.S. cities. First, the paper examines how the term gray areas was used in urban debates of the time. It is argued that the term reinforced assumptions of “blight” as a mobile force linked to inevitable decline. Furthermore, in following from stage theories of change, the term gray areas was also used to denote areas that could potentially be reclaimed. Secondly, the paper analyses the connection between gray areas and changes in FHA mortgage risk legislation in historic neighborhoods from “economically sound” to “acceptable risk.” Ultimately, in light of its “plastic” or “fuzzy” meaning, it is argued that the analysis of debates over gray areas highlights the importance of looking at urban change from a less linear, or epistemologically bounded, perspective.

Applying Machine Learning Techniques to Evaluate Climate-Related Risks in Real Estate Mortgage Valuations

Facing the escalating effects of climate change, the real estate industry faces risks from physical perils and shifting towards a low-carbon economic model. These risks have substantial consequences for the assessment and effectiveness of real estate mortgage portfolios. Conventional approaches to evaluating mortgage risk frequently fail to capture the intricate, non-linear connections between climate variables and loan results. In this paper, we present a new machine-learning framework that aims to quantify climate-related risks in real estate finance. We utilize neural networks and gradient-boosting algorithms to forecast the likelihood of mortgage defaults and the potential loss resulting from defaults in different climate stress scenarios. A robust and forwardlooking risk assessment is developed by integrating property-level exposure data, loan characteristics, and macroeconomic indicators. The empirical findings prove that our models perform superior to conventional econometric methods regarding predictive precision and computational effectiveness. The framework offers a robust instrument for investors, lenders, and regulators who aim to effectively address climate risks and enhance their ability to withstand and adapt to an unpredictable future.

Impacts of extreme weather events on mortgage risks and their evolution under climate change: A case study on Florida

We develop an additive Cox proportional hazard model with time-varying covariates, including spatio-temporal characteristics of weather events, to study the impact of weather extremes (heavy rains and tropical cyclones) on the probability of mortgage default and prepayment. We compare the survival model with a flexible logistic model and an extreme gradient boosting algorithm. We estimate the models on a portfolio of mortgages in Florida, consisting of 69,046 loans and 3,707,831 loan-month observations with localization data at the five-digit ZIP code level. We find a statistically significant and non-linear impact of tropical cyclone intensity on default as well as a significant impact of heavy rains in areas with large exposure to flood risks. These findings confirm existing results in the literature and also provide estimates of the impact of the extreme event characteristics on mortgage risk, e.g. the impact of tropical cyclones on default more than doubles in magnitude when moving from a hurricane of category two to a hurricane of category three or more. We build on the identified effect of exposure to flood risk (in interaction with heavy rainfall) on mortgage default to perform a scenario analysis of the future impacts of climate change using the First Street flood model, which provides projections of exposure to floods in 2050 under RCP 4.5. We find a systematic increase in risk under climate change that can vary based on the scenario of extreme events considered. Climate-adjusted credit risk allows risk managers to better evaluate the impact of climate-related risks on mortgage portfolios.

Abstract 16956: Historical Neighborhood Redlining and Bystander CPR Disparities in Out-of-Hospital Cardiac Arrest

Introduction: Out-of-hospital cardiac arrest (OHCA) is associated with low survival rates. Bystander cardiopulmonary resuscitation (CPR) is essential for improving outcomes, but its utilization remains limited, particularly among racial and ethnic minorities. Historical redlining, a practice that classified neighborhoods for mortgage risk in the 1930s, may have lasting implications for social and health outcomes. Hypothesis: This study sought to investigate the influence of redlining on the provision of bystander CPR during witnessed OHCA. Methods: We conducted an analysis using data from the comprehensive Cardiac Arrest Registry to Enhance Survival (CARES), encompassing 736,066 non-traumatic OHCA cases across the United States. The Home Owners' Loan Corporation (HOLC) map shapefiles were utilized to categorize census tracts of arrests into four grades (A signifying “best”, B “still desirable”, C “declining”, and D “hazardous”). Multivariable hierarchical logistic regression models were employed to predict the likelihood of CPR provision, adjusting for various factors including age, sex, race/ethnicity, arrest location, calendar year, and state of occurrence. Additionally, we accounted for the percentage of Black residents and residents below the poverty level. Results: Among the 43,186 witnessed cases of OHCA in graded HOLC census tracts, 37.2% received bystander CPR. The rates of bystander CPR exhibited a gradual decline across HOLC grades, ranging from 41.8% in HOLC grade A to 35.8% in HOLC grade D. In fully adjusted model, we observed significantly lower odds of receiving bystander CPR in HOLC grades C (OR 0.89, 95% CI 0.81-0.98, p=0.016) and D (OR 0.86, 95% CI 0.78-0.95, p=0.002) compared to HOLC grade A (Figure). Conclusions: Redlining, a historical segregation practice, is associated with reduced contemporary rates of bystander CPR during OHCA. Targeted CPR training in redlined neighborhoods may be imperative to enhance survival outcomes.

Taming the housing roller coaster: The impact of macroprudential policy on the house price cycle

Employing an agent-based model of the Spanish housing market, this paper explores the main drivers behind the large amplitude of the Spanish house price cycle—as compared to most other European countries—, as well as the scope for macroprudential policy to reduce this amplitude. First, we exploit the availability of a previous calibration to the UK, characterised by a smaller house price cycle, to show the prominent role played by the distributions of various mortgage risk metrics: loan-to-value, loan-to-income and debt-service-to-income ratios. Second, we use the model to calibrate both a hard loan-to-value and a soft loan-to-income limit to smooth the Spanish house price cycle and match the amplitude of the UK equivalent. Finally, we characterise the effects of these calibrated policies over the different phases of the cycle, finding both instruments to reduce credit and price growth during the expansionary phase as well as to reduce their decline during the contractionary phase. Moreover, both instruments lead to a compositional shift in lending: the loan-to-value policy from first-time buyers to buy-to-let investors and the loan-to-income policy from both first-time buyers and home movers to buy-to-let investors.

Prepayment and Default Risks of Mortgage-Backed Security Collateral Pools

Mortgage-backed securities (MBS) are structured financial products that are produced via securitization of mortgage loans. Due to the nature of securitization, all risks of mortgage loans are transferred from originators to MBS investors. Prepayment and default risks of mortgages lead to uncertainty in MBS cash flows and create a complex problem for valuation of these instruments. Therefore, estimating these mortgage termination risks has become the focus of valuation of MBS collateral pools. This study explores two questions by using a publicly open dataset provided by Fannie Mae. First, two machine learning algorithms (Random Forest and Multinomial Logit Regression) are used for classification to predict whether a mortgage loan is likely to be prepaid, defaulted or current. Afterwards, Competing Risks Cox Regression Analysis is performed to see determinants of when mortgage termination risks are likely to happen. It is found that not all mortgage borrowers behave optimally in their prepayment and default decisions. Therefore, in addition to refinancing incentive and negative equity which depend on variations in prevailing mortgage interest rates and housing prices, heterogeneity in mortgage borrowers’ behaviors and loan characteristics, and also local economic factors are significantly important in estimating mortgage termination risks. It is worth noting that prominence role of mortgage payment delinquencies in particularly predicting defaults emphasizes the essential need of monitoring payments by servicers to keep safety of MBS investors and financial markets.

Association Between Historical Neighborhood Redlining and Cardiovascular Outcomes Among US Veterans With Atherosclerotic Cardiovascular Diseases

In the 1930s, the government-sponsored Home Owners' Loan Corporation (HOLC) established maps of US neighborhoods that identified mortgage risk (grade A [green] characterizing lowest-risk neighborhoods in the US through mechanisms that transcend traditional risk factors to grade D [red] characterizing highest risk). This practice led to disinvestments and segregation in neighborhoods considered redlined. Very few studies have targeted whether there is an association between redlining and cardiovascular disease. To evaluate whether redlining is associated with adverse cardiovascular outcomes in US veterans. In this longitudinal cohort study, US veterans were followed up (January 1, 2016, to December 31, 2019) for a median of 4 years. Data, including self-reported race and ethnicity, were obtained from Veterans Affairs medical centers across the US on individuals receiving care for established atherosclerotic disease (coronary artery disease, peripheral vascular disease, or stroke). Data analysis was performed in June 2022. Home Owners' Loan Corporation grade of the census tracts of residence. The first occurrence of major adverse cardiovascular events (MACE), comprising myocardial infarction, stroke, major adverse extremity events, and all-cause mortality. The adjusted association between HOLC grade and adverse outcomes was measured using Cox proportional hazards regression. Competing risks were used to model individual nonfatal components of MACE. Of 79 997 patients (mean [SD] age, 74.46 [10.16] years, female, 2.9%; White, 55.7%; Black, 37.3%; and Hispanic, 5.4%), a total of 7% of the individuals resided in HOLC grade A neighborhoods, 20% in B neighborhoods, 42% in C neighborhoods, and 31% in D neighborhoods. Compared with grade A neighborhoods, patients residing in HOLC grade D (redlined) neighborhoods were more likely to be Black or Hispanic with a higher prevalence of diabetes, heart failure, and chronic kidney disease. There were no associations between HOLC and MACE in unadjusted models. After adjustment for demographic factors, compared with grade A neighborhoods, those residing in redlined neighborhoods had an increased risk of MACE (hazard ratio [HR], 1.139; 95% CI, 1.083-1.198; P < .001) and all-cause mortality (HR, 1.129; 95% CI, 1.072-1.190; P < .001). Similarly, veterans residing in redlined neighborhoods had a higher risk of myocardial infarction (HR, 1.148; 95% CI, 1.011-1.303; P < .001) but not stroke (HR, 0.889; 95% CI, 0.584-1.353; P = .58). Hazard ratios were smaller, but remained significant, after adjustment for risk factors and social vulnerability. In this cohort study of US veterans, the findings suggest that those with atherosclerotic cardiovascular disease who reside in historically redlined neighborhoods continue to have a higher prevalence of traditional cardiovascular risk factors and higher cardiovascular risk. Even close to a century after this practice was discontinued, redlining appears to still be adversely associated with adverse cardiovascular events.

Housing market trends: analyzing housing dynamics, evaluating mortgage risk, and understanding the impact of filtering on affordability

Housing market trends: analyzing housing dynamics, evaluating mortgage risk, and understanding the impact of filtering on affordability

Bank Regulatory Capital Arbitrage: Evidence from Housing Overappraisals

The overstatement of asset collateral values reduces bank capital requirements. We identify this novel form of regulatory arbitrage by studying housing overappraisals, the difference between housing collateral values computed by appraisers and actual transaction prices. We leverage granular loan-level data from Spain and a kink in the scheme of residential mortgage risk weights to show that tighter regulatory requirements cause larger overappraisals. This bias depends on the relationship between appraisers and banks; appraisers inflate mortgage collateral values only for their major customer banks. On average, overappraisals lower risk-weighted mortgages by 9%. Mortgage overappraisals allow banks to free up regulatory capital to support additional risk-taking in the corporate loan market. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4805 .

Mortgage risk and bank runs

Not only did the collapse of housing prices in the aftermath of the U.S. subprime mortgage crisis of 2008 worsen the balance sheet positions of the banking sector, but it also led to a “bank run” in some cases such as the collapse of Lehman Brothers in September 2008. We develop a theoretical model featuring household debt (mortgages) and banking sector frictions. We show that mortgage risks can potentially lead to a bank run equilibrium. Such an equilibrium exists since mortgage risks reduce the liquidation prices of bank assets. We further show that mortgage market regulations such as loan-to-value requirements reduce the likelihood of bank runs.

Mortgage Risk and Disparate Impact Associated with Student Debt

Mortgage Risk and Disparate Impact Associated with Student Debt

The Legacy of Redlining: A Spatial Dynamics Perspective

This paper investigates the long-term impacts of the federal Home Owners’ Loan Corporation (HOLC) mortgage risk assessment maps on the spatial dynamics of recent income and racial distributions in California metropolitan areas over the 1990-2010 period. We combine historical HOLC boundaries with modern Census tract data and apply recently developed methods of spatial distribution dynamics to examine if legacy impacts are reflected in recent urban dynamics. Cities with HOLC assessments are found to have higher levels of isolation segregation than the non-HOLC group, but no difference in unevenness segregation between the two groups of cities are found. We find no difference in income or racial and ethnic distributional dynamics between the two groups of cities over the period. At the intra-urban scale, we find that the intersectionality of residing in a C or D graded tract that is also a low-income tract falls predominately upon the minority populations in these eight HOLC cities. Our findings indicate that neighborhoods with poor housing markets and high minority concentrations rarely experience a dramatic change in either their racial and ethnic or socioeconomic compositions—and that negative externalities (e.g. lower home prices and greater segregation levels) emanate from these neighborhoods, with inertia spilling over into nearby zones.

Does Automated Collateral Evaluation Lower Mortgage Credit Risk Relative to Home Appraisal Valuations?

Automated valuation models (AVMs) are increasingly being used as a substitute for home appraisals in mortgage origination. This article examines whether there are differences in the credit risk of mortgages originated using AVMs relative to traditional appraisals. This question is explored through modeling the conditional default rates of loans originated through Freddie Mac’s automated collateral evaluation (ACE) program relative to those originated with appraisals. We show that ACE loans have about a 9.6% lower default risk in comparison to otherwise similar loans originated with appraisals. This superior default performance can be explained by the ACE decision logic employing data beyond that found in a traditional appraisal and the more efficient utilization of available information through statistical modeling. These findings are limited to Freddie Mac’s use of its AVM, the Home Value Explorer®, and the algorithmic decision logic in the ACE program.

A Quarter Century of Mortgage Risk

AbstractThis article provides a comprehensive history of default risk for newly originated home mortgages in the USA over the past quarter century. The loan-level source data include the entire guarantee book for Fannie Mae and Freddie Mac. We track many loan characteristics and produce a summary measure of risk. Among our many results, we show that mortgage risk had already risen in the 1990s, planting seeds of the financial crisis well before the actual event. Our results also cast doubt on explanations of the crisis that focus on borrowers with low credit scores. The aggregate series are available for download at https://www.fhfa.gov/papers/wp1902.aspx.

EFFECTS OF MORTGAGE RISK ON MARKET RETURNS OF LISTED COMMERCIAL BANKS IN KENYA

Purpose: The study is focused to determine the effects of mortgage risk on market returns of listed commercial banks in Kenya&#x0D; Methodology: This study utilised Systematic review research design to locate, assemble and evaluate relevant studies that address the dependent and independent variables.&#x0D; Findings: The results indicated that the existing studies had a conceptual framework gap as empirical literature does not offer conclusive results on the applicability of the theories in managing mortgage risk and market returns. Previous studies were majorly conducted at a different time period in other markets presenting a geographical gap.&#x0D; Unique contribution to theory, practice and policy: The study will be beneficial to listed commercial banks in Kenya to adapt effective mortgage risk management strategies to sustain positive market returns. The models developed from this study will aid the government institutions that regulate listed commercial banks in Kenya to develop policies on sustainable mortgage risk management. The study will add new knowledge on mortgage risk management to maximise market returns for listed commercial banks in Kenya.

Abstract WP187: Longitudinal Discrimination Modifies The Efficacy Of Skills-based Intervention In Stroke Survivors

Introduction: Racial discrimination has existed for centuries in the US and contributes to disparities in stroke and stroke outcomes. Measures of structural racism have been used to quantify these disparities. Our objective was to determine if the efficacy of a skills-based intervention on blood pressure reduction in a cohort of mild/moderate strokes varied by historic redlining, the US Federal government’s sanctioned discrimination in mortgage risk assessment. Methods: The Discharge Educational Strategies for Reduction of Vascular Events (DESERVE) intervention randomized 552 participants to a skills-based intervention or usual care. Participants addresses were geocoded and linked to federally sponsored Home Owners’ Loan Corporation (HOLC) color-coded maps from the 1930s. Participants residing in graded locations (n=279) were given weighted historic redlining scores (HRS) calculated using the proportion of 1930s HOLC residential security grades contained within 2010 census tract boundaries and a discrimination score based current lending practices. The change in systolic blood pressure was modeled linearly with generalized estimating equations used to account for clustering by site. Results: Participants were 34% Hispanic, 31% non-Hispanic Black, 28% non-Hispanic white, and 7% other race. The intervention was most efficacious in areas of persistent (Δ=6.05 mmHg reduction; p=0.003) and declining discrimination (Δ=11.08 mmHg reduction; p=0.007) versus usual care. In areas that were gentrifying, the intervention was least efficacious (Δ=7.33mmHg increase; p=0.022) and minimal in areas of no discrimination (Δ=0.054 mmHg reduction; p=0.903). Conclusions: Historic redlining practices are a form of structural racism that established geographic systems of disadvantage. The efficacy of interventions are impacted by underlying systems of disadvantage such that contextual factors beyond race must be considered when designing trials.

Taming the housing crisis: An LTV macroprudential policy

This paper develops a DSGE framework featuring heterogeneous housing markets, endogenous mortgage defaults, and a banking sector. We find that the idiosyncratic mortgage risk shock plays an important role in explaining the fluctuations of house prices during the 1980s and the years leading up to the financial crisis. The same shock is also an important driving force of household loans. By placing an occasionally binding constraint on the loan-to-value ratio via a counterfactual analysis, we find that the overheating of the housing economy in the early 2000s and the subsequent crash could have been alleviated, if authorities had adopted such a macroprudential policy measure. A comparison of utility gains suggests that such a maximum loan-to-value ratio policy is preferable over an augmented Taylor rule that responds to house price growth.

РИЗИКИ ІПОТЕЧНОГО КРЕДИТУВАННЯ ТА ШЛЯХИ ЇХ МІНІМІЗАЦІЇ В УМОВАХ ФІНАНСОВОЇ НЕСАБІЛЬНОСТІ

The article provides the author's definition of the terms "mortgage loan" and "mortgage lending risk". The classification of mortgage lending risks according to risks related mainly to real estate (systemic, non-systematic, random) and risks related to the capital market (banking risks) is given. The definition of each risk highlighted in the author's risk classification of mortgage lending risks is given. The distribution of risks between participants in mortgage relations (creditor, borrower, issuer of mortgage securities, investor) is presented, depending on the one- and two-level model of mortgage lending. The correlation between the level of risks and the cost of credit services is indicated. A detailed analysis of the following risks was carried out: credit risk, market risk, interest rate risk, liquidity risk, currency risk, operational and technological risks, reputational risks and legal risk. Attention is paid to one of the types of credit risk – the risk of early loan repayment, and an example of its minimization is given. It is described how credit risk directly affects the market value and profitability of the mortgage portfolio. The causes of mortgage lending risks are listed and their consequences for all participants in credit relations are listed. The close relationship between the macroeconomic situation in the country and the effectiveness of mortgage lending is substantiated using the example of real estate price fluctuations. The importance of the correct assessment of collateral property when concluding a credit agreement is explained. The experience of the banks of the leading countries of the world and the leading banks of Ukraine in managing mortgage risks is presented. The methods of risk management given in the classification are considered and proposed, and the ways of improving the effectiveness of the mortgage loan are given. The most adequate monthly payment for a mortgage loan is given as a percentage of the borrower's income to ensure his solvency. Possible scenarios of fraud in the field of mortgage lending are given and recommendations for their prevention are given. Real cases of scams from developers of Ukraine in the context of mortgage lending to the population are given.