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In some markets, offerings become riskier over time as producers introduce new versions that are made more affordable by increasing their risk. Existing theories suggest consumers adopt riskier versions either because they become more risk tolerant or they trade higher risk for lower price—both of which presume consumers know the risks. We reveal a third explanation: evolving market dynamics that increasingly encourage consumer inattention to risk and produce "collective ignorance." We identify factors of collective inattention and propose a three-stage model of development of collective ignorance by analyzing the case of risk buildup in the Hungarian mortgage market. Data include archival materials and interviews with borrowers, lenders, and regulators. Initially, producers offer low-risk products, and social, cultural, and institutional factors encourage attention to risk. Consumers attentive to and capable of assessing risk become early adopters. Over time, increasing adoption and changes in market factors divert consumers' attention from risk, shifting it to price. Under insufficient regulation, risk escalates: producers repeatedly cut price by offering increasingly risky products, while rising collective ignorance leads even risk-averse consumers to adopt them. We offer theoretical contributions to research on the social construction of risk, the attitude–behavior gap, and neoliberal responsibilization. [ABSTRACT FROM AUTHOR]

AbstractThis study explores the impact of New Deal-era redlining in the form of Home Owners Loan Corporation (HOLC) evaluations on the racial and ethnic makeup of U.S. cities decades later. We draw upon a sample of 172 cities across the United States from the Mapping Decline project and historical Census data collected by the Integrated Public Use Microdata Series (IPUMS) and the Longitudinal Tract Database (LTDB), addressing a gap in the literature by directly measuring whether the HOLC grades predict the subsequent local distribution of Black, Hispanic, and Asian populations. Our findings reveal a discernible yet diminishing connection between HOLC redlining and future Black populations, with the relationship with future Hispanic populations varying depending on whether the HOLC grade was a C or D. Only some correlation is observed between HOLC redlining and future Asian populations. This study highlights the intricate and evolving dynamics of race influenced by historical housing policies. [ABSTRACT FROM AUTHOR]

According to the uncertain geographic context problem, a lack of temporal information can hinder measures of bias in mortgage lending. This study extends previous methods to: (1) measure the persistence of racial bias in mortgage lending for Black Americans by adding temporal trends and credit scores, and (2) evaluate the continuity of bias in discriminatory areas from 1990 to 2020. These additions create an indicator of persistent structural housing discrimination. We studied the Boston-Cambridge-Newton and Dallas-Fort Worth metropolitan statistical areas to examine distinct historical trajectories and urban development. We estimated the odds of mortgage denial for census tracts. Overall, all tracts in Boston-Cambridge-Newton (N = 1003) and Dallas-Fort Worth (N = 1312) displayed significant change, with greater odds of bias over time in Dallas-Fort Worth and lower odds in Boston-Cambridge-Newton. Historically redlined areas displayed the strongest persistence of bias. Results suggest that temporal data can identify persistence and improve sensitivity in measuring neighborhood bias. Understanding the temporality of residential exposure can increase research rigor and inform policy to reduce the health effects of racial bias. [ABSTRACT FROM AUTHOR]

This study fills a significant research gap in Malaysian government-led homeownership and affordability. Centered on crucial market attributes influencing these initiatives, insights from low-income groups were obtained. The primary aim of this study was to assess the importance of various market attributes on government homeownership initiatives in Malaysia. The data were collected from low-income groups using a structured questionnaire, providing valuable insights into the unique challenges faced by this demographic. A Relative Importance Index (RII) was employed to analyze the data, revealing that Financial Market Factors, Household Financial Capacity, Housing Affordability and Accessibility, and Government Housing Policies were the market attributes of the highest importance in shaping government homeownership efforts. The results of the exploratory factor analysis demonstrated that the Financial Market Factor was the most influential component, as indicated by its mean rank. This study sought to incorporate the valuable perspectives of respondents regarding integrating future value into financing models. Respondents' opinions reflected a significant level of support for such innovative approaches. This study examines the crucial market attributes influencing government homeownership initiatives in Malaysia. The findings underline the potential of incorporating future value into financing models to enhance housing affordability for low-income groups and promote broader homeownership objectives. [ABSTRACT FROM AUTHOR]

Housing precarity as a condition referring to housing insecurity and unaffordability has been on the rise over the last decade across Europe and beyond. While various studies discuss the character of housing precarity and its links to (subprime) mortgage loans, the role of specific moral economies of debt in enacting housing policies which reinforce housing precarity is less developed in relation to other kinds of loans or the experience of debt enforcement. This article analyses fifty narrative interviews—thirty with debtors and twenty with institutional actors—and employs a processual methodology to highlight the performativity of personal debt and local housing policies. Performativity, enacted and modulated by moral economies of effort, (un)deservingness and (ir)responsibility, contributes to the remaking of housing precarity among indebted people, creating a vicious housing precarity-indebtedness loop. In the conclusion, we highlight the contingent and selective application of local housing policies which exclude the overindebted from municipal housing and discuss possible political and policy actions for overcoming the housing governance which generates this precarity. [ABSTRACT FROM AUTHOR]

This article makes a key contribution to the comparative political economy literature by accounting for the macroeconomic role of household finance. Based on post-Keynesian theories of finance and the financialization literature, we place house prices and mortgage credit squarely at the center of the macroeconomy, as speculative house price cycles can facilitate homeowner consumption via the use of equity release mortgages. Through an econometric evaluation of eighteen advanced economies from 1980 to 2019, we demonstrate that household debt is determined by house price inflation, and that rising household debt contributes to GDP growth, while business debt has negative growth effects. These results are consistent across countries with different growth models and financial systems. This suggests that the varieties of capitalism's focus on corporate finance is misplaced and that the growth models approach needs a theory of house prices, mortgage credit, and financial cycles to adequately conceptualize how debt-driven growth operates across advanced economies. [ABSTRACT FROM AUTHOR]

The widespread usage of machine learning systems and econometric methods in the credit domain has transformed the decision-making process for evaluating loan applications. Automated analysis of credit applications diminishes the subjectivity of the decision-making process. On the other hand, since machine learning is based on past decisions recorded in the financial institutions' datasets, the process very often consolidates existing bias and prejudice against groups defined by race, sex, sexual orientation, and other attributes. Therefore, the interest in identifying, preventing, and mitigating algorithmic discrimination has grown exponentially in many areas, such as Computer Science, Economics, Law, and Social Science. We conducted a comprehensive systematic literature review to understand (1) the research settings, including the discrimination theory foundation, the legal framework, and the applicable fairness metric; (2) the addressed issues and solutions; and (3) the open challenges for potential future research. We explored five sources: ACM Digital Library, Google Scholar, IEEE Digital Library, Springer Link, and Scopus. Following inclusion and exclusion criteria, we selected 78 papers written in English and published between 2017 and 2022. According to the meta-analysis of this literature survey, algorithmic discrimination has been addressed mainly by looking at the CS, Law, and Economics perspectives. There has been great interest in this topic in the financial area, especially the discrimination in providing access to the mortgage market and differential treatment (different fees, number of parcels, and interest rates). Most attention has been devoted to the potential discrimination due to bias in the dataset. Researchers are still only dealing with direct discrimination, addressed by algorithmic fairness, while indirect discrimination (structural discrimination) has not received the same attention. [ABSTRACT FROM AUTHOR]

Background: Interventions aimed at upstream factors contributing to late‐stage diagnoses could reduce disparities and improve breast cancer outcomes. This study examines the association between measures of housing stability and contemporary mortgage lending bias on breast cancer stage at diagnosis among older women in the United States. Methods: We studied 67,588 women aged 66–90 from the SEER‐Medicare linked database (2010–2015). The primary outcome was breast cancer stage at diagnosis. Multinomial regression models adjusted for individual and neighborhood socio‐economic factors were performed using a three‐category outcome (stage 0, early stage, and late stage). Key census tract‐level independent variables were residence in the same house as the previous year, owner‐occupied homes, and an index of contemporary mortgage lending bias. Results: In models adjusted for individual factors, higher levels of mortgage lending bias were associated with later stage diagnosis (RR = 1.10, 95% CI 1.02–1.20; RR = 1.31, 95% CI 1.16–1.49; RR = 1.41, 95% CI 1.24–1.60 for least to high, respectively). In models adjusted for individual and neighborhood socio‐economic factors, moderate and high levels of mortgage lending bias were associated with later stage diagnosis (RR = 1.16, 95% CI 1.02–1.33 for moderate and RR = 1.18, 95% CI 1.02–1.37 for high). Owner occupancy and tenure were not associated with later stage diagnosis in adjusted models. Conclusions: Contemporary mortgage lending bias demonstrated a significant gradient relationship with later stage at diagnosis of breast cancer. Policy interventions aimed at reducing place‐based mortgage disinvestment and its impacts on local resources and opportunities should be considered as part of an overall strategy to decrease late‐stage breast cancer diagnosis and improve prognosis. [ABSTRACT FROM AUTHOR]

This paper examines the influence that community bank residential mortgage lending has on regional housing prices and ultimately the housing price bubble that culminated with the Great Recession of 2007–09. Previous research suggests that community bank lending is influenced by financial intermediation frictions, such as difficulty attracting uninsured deposits and limited access to the bond market. Such frictions cause bank liquidity to play an important role in the ability of community banks to navigate swings in the local economy as well as real estate prices. We take these frictions as the starting point in our analysis and contribute to literature by focusing on the impact that community banks exert on housing prices. Specifically, we find that while community bank residential mortgage holdings are marginally related to housing price cycles, their mortgage lending does not contribute in an economically meaningful way to housing price bubbles. Even though bank liquidity, defined as the ratio of securities-to-assets, plays a role in the degree of community bank residential mortgage lending, it is not sufficiently strong enough to influence housing prices. [ABSTRACT FROM AUTHOR]

In the 1930s, rural Jiangsu was faced with financial exhaustion, which was manifested in the outflow of capital, widespread indebtedness and the prevalence of usury. Financial relief became a priority, and some private commercial banks were also involved in the financial relief of rural Jiangsu, among which the Shanghai Commercial and Savings Bank was the very representative. The bank not only set up an agricultural loan department, but also cooperated with the local government in Jiang鄄 su to establish a farmers' mortgage lending office. It issued agricultural loans through credit cooperatives, farm warehouses, and production and marketing cooperatives, offering relatively lower interest rates, which was positive in easing the pressure on rural capital. However, the nature of agricultural lending by private banks was actually to seek outlets for surplus funds, thus leaving obvious limitations for them to mediate financial flows. [ABSTRACT FROM AUTHOR]

This study explores the potential of utilizing alternative data sources to enhance the accuracy of credit scoring models, compared to relying solely on traditional data sources, such as credit bureau data. A comprehensive dataset from the Home Credit Group's home loan portfolio is analysed. The research examines the impact of incorporating alternative predictors that are typically overlooked, such as an applicant's social network default status, regional economic ratings, and local population characteristics. The modelling approach applies the model-X knockoffs framework for systematic variable selection. By including these alternative data sources, the credit scoring models demonstrate improved predictive performance, achieving an area under the curve metric of 0.79360 on the Kaggle Home Credit default risk competition dataset, outperforming models that relied solely on traditional data sources, such as credit bureau data. The findings highlight the significance of leveraging diverse, non-traditional data sources to augment credit risk assessment capabilities and overall model accuracy. [ABSTRACT FROM AUTHOR]

This article illustrates the development and characteristics of two customary forms of mortgage lending by analyzing a total of 3,630 mortgage cases found in four lineage communities in rural Hong Kong during the period 1905–1965 under British colonial rule. Two major findings are presented. First, there was a progressive decline of the dian 典 form, in sharp contrast to the increasing popularity of the diya 抵押 form. Second, while dian practices distinctly followed prevailing kinship-based moral values and obligations to help needy agnates, agnatic ties were not a significant factor in determining the terms of diya loans. This suggests that needy villagers did not feel disinclined to get a loan from lineage outsiders who could offer reasonable or attractive terms. The popularity of the diya practice demonstrates the existence of a strategic balance between self-interest and communal moral values and mutual obligations in lineage communities. [ABSTRACT FROM AUTHOR]

The article talks about the beginning of a library tradition citizen-associative based. Focousing on the funding process form three public libraries from Uruguay interior in the period 1873-1874. Throughout the study of diverse documents, mainly primary and secondary sources, the cases of "Biblioteca de la Asociación de Amigos de la Educación Popular de Nueva Palmira” (1873), "Biblioteca Popular de la Colonia" (1874) and foundational collection from "Biblioteca Popular Mac Eachen” from Paysandú" (1874) are analyzed. The uruguayan public library is due to the great cultural movement started in 1868 by the “Sociedad de Amigos de la Educación Popular” leading by José Pedro Varela Berro and created in Montevideo but fast branched in many towns from the interior of the country. Letter’s analysis, press articles form the epoque, speeches and regulations enable to identify the ideas and known people who made the existence form the first libraries possible, conceived to complement the conquered goals from public education. The strategies are identified to push indeed their creation and innovations installed in the cultural environment such as the home loan and its tie to the reading as socio-cultural practise leading for first time to the development of readers formation at the beginning of the “Modernity” in Uruguay. [ABSTRACT FROM AUTHOR]

The article presents a dossier on the symptoms of the crisis in contemporary Spanish novels. It mentions that the financial crisis in Europe began with the collapse of the American bank Lehman Brothers in 2008, but it was already being announced in the United States due to subprime mortgages and the inability of many citizens to pay their mortgages and loans. In Spain, the crisis is related to the real estate bubble and the granting of loans without guarantees by banking entities. The crisis affects the banking sector and has repercussions in the labor market, causing layoffs, an increase in unemployment, and a drastic decrease in consumption. [Extracted from the article]

This article examines whether, and if so to what extent, a lender can engage in the algorithmic personalised pricing of consumer credit products (PP) under the Unfair Contract Terms Directive (UCTD) and the Consumer Credit Directive (CCD). To this end, the author first analyses the economic literature to discuss the mechanics of PP and the economic impacts on different consumer groups. This overview is followed by an examination of the UCTD and the CCD, in the broader context of EU regulatory law, as these Directives apply to the practice and the contractual terms. Subsequently, the author applies the considerations of the European Court of Justice (CJEU) in the jurisprudence regarding price terms in credit and mortgage agreements to personalised price terms. Finally, the author concludes that the Directives indeed limit the extent to which a lender can engage in PP, but that the frameworks in the broader EU regulatory context would be better suited than the Directives to address the negative economic impacts of the practice. [ABSTRACT FROM AUTHOR]

Unequal homeownership access is a major component of ethno-racial stratification. Previous studies have demonstrated substantial ethno-racial disparities in access and outcomes throughout the homeownership process. In addition, prior research has assumed that mortgage applicants have a similar age distribution across ethno-racial groups. This paper draws on annual data from the 2018 and 2019 Home Mortgage Disclosure Act (HMDA) to assess variation in ethno-racial disparities in loan outcomes associated with different ages. I show that ethno-racial disparities in loan outcomes vary tremendously when considering the age of the applicant. I demonstrate that loan rejections and high-cost loan originations are highest among Latino and Black borrowers across age groups compared to Whites. Black borrowers have worse adverse loan outcomes than Whites, regardless of age. Depending on the adverse loan outcome, Asians perform similarly or underperform compared to Whites. In addition, older applicants are more likely to be denied a mortgage loan than younger applicants, while the trends for high-cost loans vary considerably across ethno-racial groups. When examining high-cost loan originations, Latinos above 65 years old (who are the best performing Latino sub-group) underperform Whites regardless of age. [ABSTRACT FROM AUTHOR]

In post‐socialist Budapest, gentrification has remained modest for decades after the regime change (1989) due to politically controlled economic relations besides marketisation. Political control was transformed but maintained after 2010 in the illiberal Orbán regime. Populist housing privatisation for tenants, insufficient regulation of rental housing, mortgage policy and urban rehabilitations with systemic corruption caused moderate level of housing market commodification. However, gentrification accelerated from 2014. Among other factors, the restriction of mortgage lending and the unplanned expansion of tourism increased the commodification of real estate market. Similar contextual issues were mentioned in the gentrification literature before; however, they remained external modifying effects of the assumed nomothetic political economic mechanisms behind rent gaps under neoliberal governance assumed everywhere. We suggest connecting institutional, social and political factors with dynamics of land rent through the concept of commodification and its effects on potential ground rent to include them within the mechanisms of gentrification. [ABSTRACT FROM AUTHOR]

Background: Racial and socioeconomic disparities in receipt of care for non‐small‐cell lung cancer (NSCLC) are well described. However, no previous studies have evaluated the association between mortgage denial rates and receipt of timely and guideline‐concordant care for NSCLC and patient outcomes. Methods: We identified individuals ≥18 years diagnosed with NSCLC between 2014 and 2019 from the National Cancer Database. Using the Home Mortgage Disclosure Act database, we calculated the proportion of denied home loans to total loans at the zip‐code level and categorized them into quintiles. Our outcomes included receipt of guideline‐concordant care based on clinical and pathologic stage at diagnosis and the National Comprehensive Cancer Network guidelines, time from surgery to chemotherapy initiation, and overall survival. Results: Of the 629,288 individuals diagnosed with NSCLC (median age 69; IQR 61–76 years, 49.1% female), 47.8% did not receive guideline‐concordant care. Residing in areas with higher mortgage denial rates and lower income was associated with worse guideline‐concordant care overall (aRR = 1.28; 95% CI = 1.25–1.32) and for each cancer treatment modality, worse receipt of timely chemotherapy (aHR = 1.14; 95% CI = 1.11–1.17) and worse overall survival (aHR = 1.21; 95% CI = 1.19–1.22), compared with residing in areas with the lowest mortgage denial rate and highest income. Conclusions: Area‐level mortgage denial rate was associated with worse receipt of timely and guideline‐concordant NSCLC care and survival. This highlights the critical need to understand and address systemic practices, such as mortgage denial, that limit access to resources and are associated with worse access to quality cancer care and outcomes. [ABSTRACT FROM AUTHOR]

Some emerging island economies have been fostering foreign direct investments in the real estate market. Given the rise in real estate demand under such contexts, this must have entailed a rise in land demand, and subsequently, land prices could have been affected. This study assesses if the rise in land demand caused by domestic and/or foreign land demand has been influencing residential land prices in Mauritius. To undertake the research, annual data was collected from the year 2000 to 2019 and a structural time series approach was used. It was found that unobserved components, namely the trend level and slope, as well as the cycles were significant in explaining land prices. It was concluded that fluctuations in land prices are significantly explained through latent variables, such as regulations in the land market, fiscal policies concerning mortgage loans, and speculative land buying among others. It was also found that foreign real estate investment (FREI) used as a measure of foreign land demand did not significantly influence land prices. To further probe the factors affecting land prices in Mauritius, domestic demand-side factors were considered and it was found that income, population, unemployment, and real construction costs were significant in explaining land prices. [ABSTRACT FROM AUTHOR]

The continuous growth in life expectancy, besides to the difficult economic and financial situation of the public pension system in Spain, makes reverse mortgages an attractive solution for providing additional income to retirees. However, despite being almost 20 years old, the Spanish market remains immature. Consequently, providers face significant risks, due to factors such as interest rates, housing prices, and longevity. Numerous tourists visit Spain, and many retire there, obtaining legal residence. Therefore, lenders could be interested in marketing reverse mortgages to foreign residents. Nevertheless, the longevity risk faced by these lenders may differ depending on the nationality of the borrower, and profits and losses could vary. Consequently, we propose a methodology for comparing the pricing of reverse mortgages in Spain by considering differences in longevity risk. Specifically, we calculate the amount offered by three types of reverse mortgages to customers of different nationalities, genders, and ages with contracts made in Spain. Our conclusions are pertinent to Spanish lenders since the results indicate that, in general, a Spanish lender would assume a slightly larger risk when lending reverse mortgages to borrowers of the selected nationalities, regardless of other considerations, such as legal issues, which are not addressed in this article. [ABSTRACT FROM AUTHOR]

During the late 1930s, the Home Owners' Loan Corporation (HOLC) developed a series of area descriptions with color-coded maps of cities that summarized mortgage lending risk. We analyze the maps to explain the oft-noted fact that black neighborhoods overwhelmingly received the lowest rating. Our results suggest that racial bias in the construction of the HOLC maps can explain at most 4 to 20 percent of the observed concentration of black households in the lowest-rated zones. We also provide evidence that the Federal Housing Administration had its own mapping strategies when evaluating mortgages and relied relatively little on the HOLC maps. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is transforming the mortgage market at every stage of the value chain. In this paper, we examine the potential for the mortgage industry to leverage AI to overcome the historical and systemic barriers to homeownership for members of Black, Brown, and lower-income communities. We begin by proposing societal, ethical, legal, and practical criteria that should be considered in the development and implementation of AI models. Based on this framework, we discuss the applications of AI that are transforming the mortgage market, including digital marketing, the inclusion of non-traditional "big data" in credit scoring algorithms, AI property valuation, and loan underwriting models. We conclude that although the current AI models may reflect the same biases that have existed historically in the mortgage market, opportunities exist for proactive, responsible AI model development designed to remove the systemic barriers to mortgage credit access. [ABSTRACT FROM AUTHOR]

The New Deal era's Home Owners Loan Corporation (HOLC) programme has garnered notoriety for denying Black communities financial investment based on their race through the practice known as redlining. It is possible that redlining influenced future investment in these neighbourhoods by making them more appealing to gentrifiers through creating a rent gap or increasing the percentage of non-White populations. To explore the link between HOLC redlining and gentrification, we drew upon a sample of 58 cities across the United States from the Mapping Decline project. We also leveraged historical Census data collected by IPUMS and the Longitudinal Tract Database, as well as data on urban renewal from Renewing Inequality to control for intervening factors. Findings indicate that HOLC redlining can either directly or indirectly relate to gentrification depending on when gentrification begins. These findings encourage more consideration of the role of racist government policies in determining when gentrification will occur. [ABSTRACT FROM AUTHOR]

The cost and process when financing manufactured homes (MHs) are the greatest barriers to owning them. MHs are considered personal properties and do not qualify for conventional real estate loans with lower interest rates than personal (chattel) loans. The resulting higher financing costs present a major obstacle to the lower-income demographic, who are the predominant purchasers of MHs. Recently, strategies have been implemented to permit MHs to be considered real property; therefore, making them eligible for a conventional mortgage. However, most MHs do not qualify for conventional loans and must apply for higher-interest chattel loans. To the best of the authors' knowledge, this area has not been investigated by academia or industry. Therefore, there is a gap in the literature on financing an MH. This study reviewed various methods for financing MHs and their corresponding loan terms, interest rates, down payments, and advantages or disadvantages. This study included Federal Housing Administration (FHA), chattel, and conventional loans. The aim was to identify the best approaches to reduce the cost of financing an MH that was based on specific conditions, such as the land ownership of the property and the type of foundation. Strategies, such as providing land lease communities for MHs to qualify them as real properties, were discussed. Recommendations were made to reduce ownership costs for manufactured houses to benefit the homeowners, MH industry, and mortgage companies. [ABSTRACT FROM AUTHOR]

As both a vibrant industry and necessity for people's lives, housing has attracted much attention in recent years. This article examines the efficacy of both loosening and tightening policies on mortgage lending in different priced housing markets in Shanghai, China, from 2014 to 2018 using daily average sale prices across 1,824 neighborhoods, with price-classified cluster analysis and policy-informed hedonic regressions. The results show that (1) the effects of mortgage lending policy interventions varied significantly and the overall spatial distribution gravitated toward subway networks and varied throughout the years; (2) the effects of interventions were time lagged but varied by different priced neighborhoods; and (3) although the accumulated number of both loosening and tightening policies were both significant, only the effects of tightening policies were significant overall. This article contributes to the existing literature by combining the spatial-temporal component in policy studies, providing detailed mortgage lending policy intervention variables, and expanding the scope of study from housing prices to housing transaction frequencies. [ABSTRACT FROM AUTHOR]

The article examines the impact of mergers and acquisitions in the Farm Credit System (FCS) on agricultural banks in the United States. It highlights concerns about the concentration of FCS and commercial banks due to mergers, discusses the potential effects on agricultural credit availability and prices, and explores how FCS mergers may have influenced strategic decisions and operations of agricultural banks.

According to IVS 2023 the terminal value of a DCFA can be calculated in respect of the three fundamental appraisal approach: market, income and cost. Specifi- cally, "Where the asset is expected to continue beyond the explicit forecast period, valuers must estimate the value of the asset at the end of that period. The terminal value is then discounted back to the valuation date, normally using the same discount rate as applied to the forecast cash flow" (IVS 105 Valuation Approaches and Methods, para 50.20). Although academic and professional normally refer to direct capitalization to calculate the exit value (scrap value, going out value) different approaches are possible. In particular it is possible to calculate the exit value using the market approach. The present work starts from an original model of Discounted Cash Flow Analysis proposed by Simonotti (2006) to propose possible alternative to the original formula. The model proposed, as defined for the paper "Prudential Value DCFA Formula (PVF)" provides methodological alternatives to the original model in order to apply the method in different property market conditions allowing the appraiser to represent even property market in recovery or falling market phase, or prudential assessment of worth and opinion of value. In particular the proposed model replace the compound growth of the property value included in the traditional Simonotti's model, with a linear growth or even a combination of both. The paper emphasize how property valuation standards can not be considered as immutable but they may be considered in constant evolution. In delivering an opinion of value for mortgage lending purposes the approach of professional academician and real estate analyst need to be able to respond to change of external conditions, in consideration of the sustainability of the cash flows in the long term, for the entire duration of the loan (and therefore for the purpose of identifying the long-term sustainable value of the asset). The approach is functional, inter alia, for the purpose of identifying the "prudential value" as defined by the innovative banking regulation (Basel 3) according to the definition of loan-to-value (LTV) ratio for loan origination and monitoring. [ABSTRACT FROM AUTHOR]

The mortgage lending value (MLV) is a type of value different from the market value (MV). The MLV appraisal is normally required in loans secured by real estate (collateral) context. In Italy, this appraisal is often made in percentage terms or with subjective criteria that do not consider the reference principles also defined by the valuation standards. This paper, starting from the analysis of the German procedure to appraise the MLV, which is the first country to introduce the concept of a security value in the context of property valuations, aims to propose a more precise procedure than the German one by adopting calculation methodologies typical of the income approach which are based on the principles derived from the definition of mortgage lending value and from market trends. The case is made that the proposed methodology and calculation procedure provide a more objective method to appraise the MLV compared to the current ones, in accordance with both national and international valuation standards, and that it represents a useful tool in the professional field. [ABSTRACT FROM AUTHOR]

This article provides a conceptual understanding of the processes of financialization based on the concept of the biopolitics of housing financialization. Drawing on the Foucauldian categories of disciplining and regulation, we elaborate an empirical analysis of the mechanisms that, in Mexico, propagated the aspiration of various sectors of the population with limited resources to have access to a home of their own through mortgage loans. The construction of the notion of biopolitics of the financialization of housing is based on an empirical research conducted at two different times (2017 and 2020) and consisting of semi-structured interviews with owners of affordable housing in the periphery of the Metropolitan Area of the Valley of Mexico. It shows that, far from benefiting borrowers, their insertion in credit relations undermines income and negatively impacts their quality of life. The present discussion is articulated through five devices of the financial biocapitalism of housing --the discourse of personal wealth, socio-territorial stratification, the fallacy of social credit, the reality of peripheral life, and the reality of indebted lives--, which help to explain the epistemic violence inherent to a financialized model of economic and territorial development that produces economic and political gains for a few people, to the detriment of those who are supposed to benefit from housing policies. The analysis reveals that the devices implemented reflect the subtlety of the exercise of power in the financialized provision of housing. [ABSTRACT FROM AUTHOR]

There is a long history of gender and ethno‐racial stratification in access to homeownership. Previous research highlights unequal treatment of minorities and women in the mortgage market. However, prior studies focus on single loan applicants when assessing the roles of both gender and race and ethnicity in their analysis. Because of this, it is unclear how mortgage lending disparities differ when considering the intersection of gender and race and ethnicity across single and co‐applicants. This paper draws on annual data from the 2018 and 2019 Home Mortgage Disclosure Act (HMDA) to assess gender and ethno‐racial disparities in loan outcomes. I document two diverging trends. On the one hand, single applicant women generally perform similarly or outperform single applicant men in the mortgage market even across ethno‐racial groups. On the other hand, women‐headed co‐applicants are more likely to experience an adverse loan outcome compared to male‐headed co‐applicants. The gender gap is substantially larger for black and Latino co‐applicants than for white co‐applicants. This is particularly true for black women‐ and Latina‐headed co‐applicants when examining mortgage denials. The results for Asian co‐applicants are mixed, as gender disparities differ across mortgage outcomes. Implications for gender and ethno‐racial stratification are discussed. [ABSTRACT FROM AUTHOR]

Inequality in homeownership is a major component of ethno‐racial stratification. Previous studies demonstrate large ethno‐racial differences in access and outcomes throughout the home buying process at both the individual and neighborhood levels. An underlying assumption in these studies is that neighborhood ethno‐racial disparities in lending are similar across neighborhood spatial types. However, mortgage lending disparities are unclear when examining the neighborhood's racial composition across urban, suburban, and rural communities. This paper draws on annual data from the American Housing Survey and the Home Mortgage Disclosure Act (HMDA) from 2018 and 2019 to assess loan outcome disparities by neighborhood type and racial composition. I show that applicant disparities in loan outcomes vary when factoring the neighborhood's spatial type and racial composition. Borrowers seeking a mortgage in predominantly minority rural communities are more likely to be denied a mortgage than borrowers applying across all other neighborhood type and racial composition. The trends for urban communities are similar to suburban communities across adverse loan outcomes. When comparing the community's racial composition and neighborhood type, the observed lending pattern provides evidence of constrained mortgage access in rural areas, especially among minority rural communities. [ABSTRACT FROM AUTHOR]

(1) Background--Under the background of rural revitalization strategy, the research on credit rationing of forest rights mortgage loans of the farmers in collective forest areas is not only the internal requirement of promoting the rural revitalization strategy, but also the basic need of realizing the increase of the farmers' forestry management income in collective forest areas. (2) Methods--The research data came from a questionnaire survey of 420 rural households in Sanyuan District, Jiangle County, Jianning County and Taining County, Sanming City, Fujian Province, in August 2021. Using DEM and descriptive statistics, this paper interpreted the types and generation mechanism of credit rationing of the farmers' forest rights mortgage loans, and then identified and measured the credit rationing. (3) Results--First, from the perspective of credit rationing of the farmers' forest rights mortgage loans, the proportion of lack of credit demand for forest rights mortgage loans in collective forest areas in Fujian Province under the background of rural revitalization is relatively high, which is 50. 82%. Second, the farmers facing demand-type credit rationing of forest rights mortgage loans account for 85. 11% of the total credit rationing, while the farmers facing supply-type credit rationing of forest rights mortgage loans account for only 14. 89% of the total credit rationing. The farmers in collective forest areas are faced with more severe credit rationing of forest rights mortgage loans. Third, demand-type credit rationing of forest rights mortgage loans mainly includes self-imposed credit rationing, transaction cost credit rationing and risk credit rationing. Fourth, most of the farmers who apply for forest rights mortgage loans from financial institutions can get corresponding loans, but the farmers in collective forest areas can get less amount of forest rights mortgage loans because of the small mortgage area of "Certificate of Forest Rights". (4) Conclusions and Discussions--First, the farmers generate self-imposed credit rationing because of the cognitive deviation of forest rights mortgage policies, form risk credit rationing because of the endowment effect of the forestlands, and face new transaction cost credit rationing because of high transaction costs. Second, the family management with pure forestry of the small farmers in collective forest areas is still the main type of forestry management in China. However, the degree of part-time employment of the forest farmers in collective forest areas is constantly increasing, there is a phenomenon of forestry management and non-forest employment, and the income comes more from non-forest employment. Third, the proportion of lack of credit demand for forest rights mortgage loans in collective forest areas in Fujian Province under the background of rural revitalization is relatively high. Most of the farmers who have the credit demand for forest rights mortgage loans are still facing more severe demand-type credit rationing. Fourth, the supply-type credit rationing of forest rights mortgage loans faced by the farmers is relatively low. Therefore, in order to fully realize the policy effect of forest rights mortgage loans from the perspective of rural revitalization, the following policy suggestions are put forward: First, improve the farmers' financial literacy through multiple channels. Second, achieve multi-department data integration and credit information co-construction and sharing. Third, strengthen the institutional innovation, alleviate the demand-type credit rationing of forest rights mortgage loans of the farmers in collective forest areas to the maximum extent. [ABSTRACT FROM AUTHOR]

The prediction interval is an important guide for financial organizations to make decisions for pricing loan rates. In this paper, we considered four models with bootstrap technique to calculate prediction intervals. Two datasets are used for the study and $ 5 $-fold cross validation is used to estimate performance. The classical regression and Huber regression models have similar performance, both of them have narrow intervals. Although the RANSAC model has a slightly higher coverage rate, it has the widest interval. When the coverage rates are similar, the model with a narrower interval is recommended. Therefore, the classical and Huber regression models with bootstrap method are recommended to calculate the prediction interval. [ABSTRACT FROM AUTHOR]

This research estimated the effect of real wage and exchange rate fluctuation on the demand for residential housing in African countries. This paper selected ten African nations and applied pooled Mean Group (PMG) method to identify the effects of real wage and exchange rate fluctuation together with movements in interest rates on demand for residential housing among African countries between 2008 and 2020. The results display that the low level of the real wage together with FX market variation in Africa hurt the holding of residential buildings in these countries. Real wages contribute positively but less significantly to holding a residential building in Africa. In effect, when real wages are minimum and insufficient, the acquisition of residential buildings becomes unaffordable. And this could result in a cyclicality of declining purchasing power considering the upward dynamism that goes with demand for residential housing which most often in the long run, results in another round of price inflation. Variations in exchange rates had significantly hindered demand for residential housing in Africa in the period covered by the study. Interest rates also contributed significant adverse impact on holding residential housing. Changes in interest rates were found to have negatively influenced the purchase of residential properties. The reason is that with highly volatile short-term bank lending rates, the cost of acquiring a mortgage to purchase a residential building becomes highly overpriced. This in turn creates a lower demand for residential housing. The speed of adjustment of the demand for residential housing function to equilibrium in the case of disequilibrium in the short run is 72.9%. We do advocate for policies capable of removing the import-dependence status of these countries to reduce the exchange rate fluctuations and hike in inflation rates to avoid a likelihood of cyclicality considering the dynamism that goes with demand for residential housing. [ABSTRACT FROM AUTHOR]

In the present work, it is proposed to investigate the particularities that the Spanish housing problem assumes, emphasizing the experience of struggle and work of the Platform of People Affected by Mortgage. From a research stay developed in the city of Madrid, the centrality that the platform assumes will be addressed to stress the hegemonic narrative regarding the housing crisis and enable collective processes so that the people who participate can stop blaming themselves, conceiving themselves as victims. In this way, it is interesting to analyze the ways in which this category is mobilized in the claim of the right to housing and in the generation of a political commitment with housing demands that are inscribed in the public scene. [ABSTRACT FROM AUTHOR]

Mortgage discrimination alters the distribution of investment, opportunity, and economic advantage—key contributors of health disparities. Leveraging Home Mortgage Disclosure Act data, we assessed mortgage denial risk in 380 U.S. urban areas. We estimated the risks by census tract–relative to the urban-specific average—using a Bayesian spatial model with conditionally autoregressive distributions fitted with integrated nested Laplace approximation. This approach borrows information through spatial and non-spatial smoothing, resulting in stable estimates in the presence of sparse data. The method, publicly accessible, allows researchers to apply our approach, fostering deeper insights into mortgage lending discrimination and systematic neighborhood disinvestment. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between home mortgages and neighborhood mental health across the 18 largest metropolitan statistical areas (MSAs) in the United States. Home mortgages, a primary avenue to homeownership, contribute to housing security and stability. Moreover, their issuance reflects local investment and potential improvements in the built environment, hypothesized to positively influence community mental well-being. Using census tract-level data from multiple sources, we employed a spatial econometric approach, specifically spatial error modeling, to account for spatial dependency and estimate the association between home mortgage lending (2011 to 2020) and the prevalence of self-reported poor mental health in 2020. Our findings indicate a statistically significant negative association between mortgage issuance and self-reported poor mental health across all 18 MSAs, suggesting that increased mortgage lending is associated with improved neighborhood mental health. Comparisons between standard linear models and spatial error models highlight the influence of unmeasured, spatially correlated factors on neighborhood mental health outcomes. This study underscores mortgage lending as a crucial factor in community well-being and emphasizes the necessity of addressing spatial dependency in neighborhood health studies for accurate estimations. The findings offer valuable insights for researchers and policymakers aiming to enhance community mental health and address health disparities through informed housing policies. [ABSTRACT FROM AUTHOR]

The study aims to shed light on the operations of mortgaging and borrowing shares, and the legal rulings associated with them. Mortgaging a share is a consequence of the legality of the activity practiced by the institution or the person who owns the share. The shares of liquor, usury, and pork selling companies, as well as some types of preferred shares, may not be mortgaged because they are the result of commercial activities that are prohibited by Sharia, in addition to other legal determinants, including that the source of the company's capital is lawful. While investigating what is lawful, and being careful not to fall into forbidden actions, every lie, betrayal, false rumors, monopoly, or gambling with shares, keeping away from suspicions, as many of them lead to the forbidden . As for the legal ruling related to lending shares, there is a difference of opinion among the scholars of the nation regarding it, but whoever ruled on the legitimacy of lending shares made it according to specific conditions related to the type of share, in terms of rights and duties, and the legality of the source of the share. Among the recommendations of the study: attaching a body or office to the legitimate markets that explains and interprets the legal aspects and legal limits with regard to dealing with shares, in terms of selling, mortgaging and lending, so that this office specializes in collecting information related to shares in terms of their type, source, and clarifying their legitimacy. [ABSTRACT FROM AUTHOR]

The study aimed to examine the impact of inflation on the real estate market using Polish panel data for the last 13 years. It is based on a panel model, where price changes of one square meter of housing are determined as a function in changes of inflation, the central bank's base rate, dwellings built, as well as new mortgage loans. The quarterly dynamics of the average price of 1 square meter of housing in Poland's eight largest cities in the 2009-2021 period was studied. This price was modeled and predicted using one of the Box-Jenkins time series models: the Holt-Winter model of exponential smoothing with a damped trend. The forecasting results showed a small (up to 4%) relative error in comparison with the actual data. In addition, the moment (2017) of the price trend change was found. Therefore, piecewise linear regressions with high regression coefficients were used when modeling the impact of inflation changes on the real estate market indicators under consideration. The results obtained provide valuable insight into the relationship of real estate market indicators, allowing consumers to predict available options and make decisions in accordance with their preferences. [ABSTRACT FROM AUTHOR]

It is well known that self-reported financial information differs from administrative records. This article advances previous studies by using a unique matched representative sample of individual borrowers from the Chilean Household Finance Survey with administrative banking loan records. Our linked dataset allows us to test whether the differences between the two sources are due to the number of nonreported loans or to differences in the reported loan amounts. We show that discrepancies in debt ownership are larger when respondents have a mortgage and are not the highest income member of the family, when respondents have weak financial literacy and do not have confidence in the study, and when respondents live in complex or multigenerational households. However, borrowers report the maturity of their mortgage and installment loans quite accurately. Concerning loan amounts, differences between the two sources decrease with the financial literacy of the respondent. Finally, a simple form of rounding can go a long way towards explaining differences in the middle part of the debt amount and maturity distributions. [ABSTRACT FROM AUTHOR]

The infamous "security maps" made in the 1930s by the Home Owners' Loan Corporation (HOLC), rating supposed mortgage lending risk in urban neighborhoods across the United States, have long been considered the quintessential expression of racist redlining policy. However, a number of misunderstandings and unwarranted speculations about how these maps were made and used have proliferated. Using previously unexamined correspondence, this article establishes that HOLC could not have used the maps for loan denials, did share them with the Federal Housing Administration but not with private industry, and highly improvised their production with numerous methodological inconsistencies, including with regard to race. [ABSTRACT FROM AUTHOR]

Performance measures are crucial in selecting the best machine learning model for a given problem. Estimating classical model performance measures by subsampling methods like bagging or cross-validation has several weaknesses. The most important ones are the inability to test the significance of the difference, and the lack of interpretability. Recently proposed Elo-based Predictive Power (EPP)—a meta-measure of machine learning model performance, is an attempt to address these weaknesses. However, the EPP is based on wrong assumptions, so its estimates may not be correct. This paper introduces the Probability-based Ranking Model Approach (PMRA), which is a modified EPP approach with a correction that makes its estimates more reliable. PMRA is based on the calculation of the probability that one model achieves a better result than another one, using the Mixed Effects Logistic Regression model. The empirical analysis was carried out on a real mortgage credits dataset. The analysis included a comparison of how the PMRA and state-of-the-art k-fold cross-validation ranked the 49 machine learning models, an example application of a novel method in hyperparameters tuning problem, and a comparison of PMRA and EPP indications. PMRA gives the opportunity to compare a newly developed algorithm to state-of-the-art algorithms based on statistical criteria. It is the solution to select the best hyperparameters configuration and to formulate criteria for the continuation of the hyperparameters space search. [ABSTRACT FROM AUTHOR]

The work presents an analysis of the housing construction market in Ukraine. An economic and mathematic model was built to determine that the growth of the volume of housing construction in Ukraine had a positive impact on its GDP, due of a close relation between the two values. It is important to identify factors influencing the volume of housing construction. The obtained results prove that the greatest impact is made by consumer income, deposit rates in foreign currency, and the amount of consumer loans for buying, building and reconstruction of real estate assets; the numbers of marriages, investments in housing construction and interest rates for mortgage credits in UAH also have a significant impact. The elasticity coefficients reveal a positive impact of such factors as an increase of consumer income, growth of investments in housing construction, reduction of interest rates for mortgage credits and deposit rates in foreign currency, reduction of the amount of consumer loans for buying, building and reconstruction of real estate assets, and reduction of the number of marriages. Further development of the housing construction market requires appropriate conditions for the development of the banking sector in Ukraine and the growth of investments in the studied industry. [ABSTRACT FROM AUTHOR]

Based on experience in the United States in recent decades, Rajan (2010) argues that there is an inequality-debt-crisis nexus, that is, income inequality may contribute to banking crises by stimulating the accumulation of household debt. Whether and to what extent Rajan's hypothesis has been confirmed (or refuted) by the literature is investigated in this study. It is shown that the validity of Rajan's theory depends on the level of strictness of the standards that are established to estimate the extent of agreement between theory and evidence. This conditional validity can be attributed to the multidimensional nature of the inequality-debt-crisis nexus, which is overlooked by Rajan. JEL Classification : D31, E51, G21, G51 [ABSTRACT FROM AUTHOR]

We develop a valuation model for mortgage pass-through securities with partial prepayment risk using an intensity-based approach. For the single mortgage contract in a given pool of mortgage loans, the ratio of prepayment amount to outstanding principal at partial prepayment time is described by a stochastic process, and the occurrence time of prepayments is modeled by jump time of a Cox process. Under these conditions, we get the valuation formulas of mortgage pass-through securities without and with regime switching, respectively. Based on these results, we also obtain the expected present value of the cash flow charged by the service agency from the mortgage pool and the valuation formula of the single mortgage contact. Finally, we give some numerical examples to study how parameters affect the valuation. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the tax deductibility of mortgage loans, which is a key measure of housing policies in many countries. Several studies have shown that the distribution of the benefits of this measure runs counter to the vertical equity principle. We contribute to the existing literature by addressing the distribution of the tax deductibility of mortgage loans considering the spatial outcomes of this policy. We use Belgian data to measure the impact of this policy on households' income and inequality and poverty in different types of areas. We show that this measure favours suburban households and subsidizes urban sprawl. Exogenous factors such as past housing policies and homeownership determinants play a key role in this phenomenon. We also simulate the distributional impact of three stylized reforms of the deductibility of mortgage loans in Belgium. These simulations show that the distributional outcomes could be improved on both social and spatial sides. [ABSTRACT FROM AUTHOR]