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Using loan-level data, this analysis considers the intersection of race, subprime home loans, and the current vacancy crisis in St. Louis, Missouri. Borrowers in Black areas in the north of St. Louis City and St. Louis County received subprime home loans at higher frequencies during the subprime boom period of 2003–2007 than those in White areas, with differences in balloon loans especially stark. Specifically, borrowers in Black neighborhoods received subprime loans more frequently than those with equal FICO scores in White neighborhoods. As a result of these differential loan terms, North City and inner ring "First Suburb" areas saw more foreclosure and borrower payment delinquency, which in turn were highly associated with home vacancy, controlling for other risk factors. However, foreclosure was no longer a significant predictor of home vacancy after controlling for demographic factors and FICO score, indicating that the unequal loan terms may have driven much of the increase in home vacancy in the St. Louis area since the Great Recession. [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]

We provide new evidence that mispriced mortgage insurance shifted credit supply and contributed to the mortgage boom and bust of the early 2000s. Original data on private mortgage insurance premiums from 1999 to 2016 reveal that before 2008, premiums did not vary across loans with widely different indicators of default risk. We quantify the mispricing of premiums before 2008 and show that even allowing for more optimistic beliefs, the flat premium structure resulted in cross‐subsidies and substantial adverse selection. [ABSTRACT FROM AUTHOR]

In China, many Internet financial platforms (IFPs) are grappling with sustainability challenges due to elevated default rates, which have triggered widespread investor anxiety. To evaluate the sustainability practices of these platforms, we propose a reputation evaluation model designed to rank IFPs based on their sustainability. The economic sustainability of an IFP is decomposed into three components: scale strength, capital liquidity, and sustainable operating capability. Through an analysis of the correlation relationships between various indicators, we have identified nine significant indicators. Mathematical models are established to quantify these nine indicator variables. Subsequently, the score values of each indicator are integrated to establish a reputation evaluation model utilizing the weighted geometric mean method. Furthermore, the reputation evaluation values for 18 Chinese IFPs were calculated using the developed model, and the sustainability of the platforms was ranked according to the reputation evaluation value. A comparative analysis was also conducted between the sustainable rankings proposed in this study and the development rankings of the "Home of Online Loans" (HOL). The results reveal that our model effectively considers both the current operational strength and the sustainable development capability of the platform. It successfully identifies platforms with poor sustainability, assisting investors in making more informed decisions. Simultaneously, this study identifies key indicators influencing the sustainability of IFPs, providing valuable insights for managers seeking to enhance the sustainable operational levels of their platforms. [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]

Farmland mortgages are expected to drive county agricultural economic growth (CAEG) as a crucial component of furthering the reform of the rural land system and the reform of the rural financial system against the new backdrop of the new era. This study gathers panel data from 2045 Chinese counties from 2011 to 2020 and uses the difference-in-differences method and the synthetic control method to systematically examine the effects of China's farmland management right mortgage loan (FMRML) pilot program on CAEG. The FMRML pilot program was implemented in 2016, and this research is presented as a quasi-natural experiment. The findings indicate that there is a "policy trap" and that CAEG has not been successfully promoted by the FMRML pilot program. The reason for this is because the pilot program has made county resource mismatch worse, making it unable to fully realize the promotional effect on CAEG, rather than significantly activating the three key drivers of agricultural economic growth: people, land, and money. The impact of the FMRML pilot policy on CAEG is not uniform, according to the results of the heterogeneity study, with a substantial "blocking" effect only in the central region and no significant influence in the western, northeastern, or eastern regions. The findings propose that in order to optimize agricultural mortgage policy and advance CAEG, China and other emerging nations can benefit greatly from the insights this study offers. [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]

Using natural disasters as shocks to local economies, we document that a bank branch's ability to set deposit rates locally has real effects. Following disasters, branches with rates set locally increase deposit rates more and experience higher deposit volumes in affected counties. Consistent with imperfect insurance from internal capital markets, banks with more branches setting rates locally relatively expand mortgage lending in affected counties. House prices recover faster in local areas where more branches' rates are set locally. This paper was accepted by Tomasz Piskorski, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4856. [ABSTRACT FROM AUTHOR]

Mortgage default prediction is always on the table for financial institutions. Banks are interested in provision planning, while regulators monitor systemic risk, which this sector may possess. This research is focused on predicting defaults on a one-year horizon using data from the Ukrainian credit registry applying machine-learning methods. This research is useful for not only academia but also policymakers since it helps to assess the need for implementation of macroprudential instruments. We tested two data balancing techniques: weighting the original sample and synthetic minority oversampling technique and compared the results. It was found that random forest and extreme gradient-boosting decision trees are better classifiers regarding both accuracy and precision. These models provided an essential balance between actual default precision and minimizing false defaults. We also tested neural networks, linear discriminant analysis, support vector machines with linear kernels, and decision trees, but they showed similar results to logistic regression. The result suggested that real gross domestic product (GDP) growth and debt-service-to-income ratio (DSTI) were good predictors of default. This means that a realistic GDP forecast as well as a proper assessment of the borrower's DSTI through the loan history can predict default on a one-year horizon. Adding other variables such as the borrower's age and loan interest rate can also be beneficial. However, the residual maturity of mortgage loans does not contribute to default probability, which means that banks should treat both new borrowers equally and those who nearly repaid the loan. [ABSTRACT FROM AUTHOR]

Using the Credit Risk Transfers (CRTs) issued by Fannie Mae and Freddie Mac, we study how, absent government intervention, mortgage markets would price hurricane risk. Currently, such risk is priced equally across locations even if it is location‐specific. We hand collect a novel and detailed database to exploit CRTs' heterogeneous exposure to Hurricanes Harvey and Irma. Using a diff‐in‐diff specification, we estimate the reaction of private investors to hurricane risk. We use the previous results to calibrate a model of mortgage lending. We simulate hurricane frequencies and mortgage default probabilities in each US county to derive the market price of mortgage credit risk, that is, the implied guarantee fees (g‐fees). Market‐implied g‐fees in counties most exposed to hurricanes would be 70% higher than inland counties. [ABSTRACT FROM AUTHOR]

A farming household's decision to continue producing agricultural commodities within the United States is influenced by a multitude of factors. Thus, this study seeks to examine whether the outstanding student loan balance of any member within a farming household may explain why the total number of acres devoted to the production of agriculture in the United States continues to decline. Panel data from the 2007–2009 Survey of Consumer Finances are analyzed via a fixed effect model to estimate the effect of outstanding student loan balances on farmland acreage owned, controlling for other factors like farm income, debt, and land prices. The results suggest that for each additional dollar of outstanding student loan debt, there is an associated decrease of 0.0064 acres in total farmland ownership. This suggests that student loan debt may also be a factor in the decline in real estate devoted to agriculture production. The estimated effect is both economically and statistically significant. This study contributes to the literature on the risks and constraints associated with farming households that own or seek to procure additional acres of agricultural producing real estate. [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]

The article provides a comprehensive overview of the Federal Home Loan Banks (FHLBanks) in the United States. It discusses the historical context of their establishment during the Great Depression and their evolution over time. The article highlights key legislation and regulatory changes that have shaped the FHLBanks' mission and membership. It also addresses criticisms of the FHLBanks and suggests potential opportunities for improvement, such as clarifying their mission, expanding membership, and increasing support for affordable housing. The article emphasizes the importance of adaptability and evolution for the FHLBanks to remain relevant in the changing financial industry. [Extracted from the article]

The relevance of the study is that the pandemic has affected the financial stability of many businesses. The purpose of the study is to consider the features of bank lending to businesses in a pandemic. Providing credit in the era of the coronavirus is associated with increased risk. However, this does not mean that it is impossible to obtain new funding. Banks still offer a variety of credit products, including mortgages and cash or credit card loans. Changes in the level of debt mask the distinction between new borrowings and repayments of existing amounts. Business loans are mostly short-term, and their rates can be adjusted relatively easily. Historical data shows that on average, 90% of new business loans have a variable or fixed rate with a maturity of less than one year. The huge surge in loans to new businesses is primarily conditioned upon this short-term financing. The speed and scale of the return of the gap to the pandemic is unprecedented. The practical significance lies in the analysis of problems and obstacles to bank lending to businesses in a pandemic, and ways to solve them. [ABSTRACT FROM AUTHOR]

Green This article is aimed at investigating the determinants of mortgage loan approval in developing countries, employing the binary probit model. Loan approval was made the response variable while deposit, amount to borrow, lending rate, gratuity, capacity to pay the loan and character of the borrowers stood as the explanatory variables. Cross-sectional data were collected from the four top banks in Nigeria. The result showed that all the variables had the correct signs but only the capacity to pay the loan has a significant impact in determining the success of mortgage loan approval. Collectively, all the variables have significant power to determine mortgage loan approval. It is therefore suggested that prospective borrowers should ensure that they have all it takes to refund the loan they wish to obtain from commercial banks. [ABSTRACT FROM AUTHOR]

This study investigates the impact of macroeconomic factors on housing loan flows in the Baltic region post-2008 housing bubble. Using stepwise regression, Lasso regression, and pooled regression, data is analyzed from Estonia, Latvia, and Lithuania spanning 2014 to 2023. Results reveal the significant influence of borrowing costs, wages, unemployment, and inflation rates on loan flows. [ABSTRACT FROM AUTHOR]

The article discusses developments in fair lending enforcement activities in the U.S. Topics include the largest redlining settlement announced by the Department of Justice (DOJ) in January 2023, federal regulatory developments, and litigation brought by city and county governments seeking to recover damages allegedly due to discrimination by mortgage lenders in their communities.

We investigate whether European banks adjust their loan prices and volumes of new lending in the months running up to major national elections. Using a unique dataset that draws on data covering some 250 banks in 19 Eurozone countries from 2010 to 2020 at monthly frequency, and that includes lending amounts and interest rates on new lending, we find that European banks increase loan rates for corporate and housing loans ahead of elections. This supports the view that loan pricing changes of European banks are driven by the electoral uncertainty inherent to the democratic election process. We find that the impact of elections is more pronounced for small banks, as well as obtain some evidence that elections affect the credit supply of banks. Our findings suggest that the occurrence of elections is affecting the behavior of European banks. [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]

We examine how the cost of issuing equity affects bank lending. Using the SEC rule change that allowed exchange‐listed firms with public float less than $75 million to raise equity via shelf registrations as a quasi‐natural experiment, we show that the affected banks increase mortgage lending relative to control banks. Furthermore, the affected banks reduce demand for precautionary capital and become less likely to sell mortgages to third parties. [ABSTRACT FROM AUTHOR]

Copyright of Religación: Revista de Ciencias Sociales y Humanidades is the property of Religacion: Revista de Ciencias Sociales y Humanidades and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Early contact with people who need financial help is key in preventing financial derailment. It can prevent avoidable debt accumulation and accompanying psychological problems. In this field experiment, we investigated whether a descriptive social norm message mentioning an absolute number of customers who had previously reached out for help motivates customers of a Dutch mortgage lender to get in contact when they expect financial problems in the near future. The descriptive social norm letter did not result in more contacts. The results of our research contribute to the literature on social norm communication and debt prevention. Moreover, we present insights into the challenges associated with experimental field research on social influence and provide recommendations for future field work. [ABSTRACT FROM AUTHOR]

This research studies the effects of mortgage subsidies and asymmetric information in the US mortgage market. I exploit discontinuities in interest rates generated by pricing rules and find patterns consistent with advantageous selection. I estimate an industry model that highlights the relationship between mortgage subsidies, intermediary lenders' incentives, and borrowers' advantageous selection. The model shows that mortgage subsidies enable advantageous selection, creating a deadweight loss of $7.90 billion. The counterfactual analysis reveals that pricing borrowers' private information eliminates advantageous selection only if mortgages are not subsidized. Without the mortgage subsidy, pricing borrowers' private information improves efficiency by $728.58 million. [ABSTRACT FROM AUTHOR]

Subprime lending is concentrated in minority neighborhoods. However, the literature provides little evidence for what led to this concentration. We use the endorsement of credit scores in mortgage underwriting by the Government Sponsored Enterprises (GSEs) in 1995 to answer this question. We show that prime lenders were substituted by subprime lenders in minority neighborhoods. As a result, the share of subprime lending increased by 5 percentage points in minority neighborhoods, relative to nonminority neighborhoods. Prime lenders with a stronger relationship with the GSEs reduced their lending in minority neighborhoods more, and the level of securitization by the GSEs in minority neighborhoods also decreased. [ABSTRACT FROM AUTHOR]

The occurrence of negative phenomena over the past two years: the Covid-19 pandemic, the temporary disruption of supply chains, the war in Ukraine and the energy crisis has affected many aspects of the global economy, including the rise in inflation and interest rates. All borrowers, including more than two million households in Poland repaying home loans, have been affected by these changes - most notably visible in the dynamic increase in lending rates. In order to help borrowers repay the instalments of such loans granted in zloty, the Legislator introduced legislation in July 2022 allowing for the use of „credit holidays”. The purpose of this article is to present the results of a study carried out on the basis of sample home loans - the impact of the introduction of „credit holidays” on the level of loan principal and instalments, assuming that all the money saved from the suspension of instalments is used to overpay the loan.

The authors also conducted structured interviews with PPP loan recipients and found that those businesses that received smaller-reported loan amounts had more difficulties and less knowledge about the loan application process than larger loan recipients. They compare PPP lending to existing residential and small business lending patterns to assess the disadvantage of Black and Latinx neighborhoods in receiving PPP loans. Keywords: inclusive economic development; paycheck protection program; PPP; inclusivity EN inclusive economic development paycheck protection program PPP inclusivity 207 210 4 09/20/23 20230801 NES 230801 In 2019, the Federal Reserve Bank of Boston, The Initiative for a Competitive Inner City, and the W.E. Upjohn Institute for Employment Research partnered to gain a better understanding of the mechanisms and contexts that promote inclusive economic growth and development. During the first two phases - when approximately 60% of loans and 70% of loan dollars were allocated - majority Black and Latinx neighborhoods received disproportionately fewer PPP loans and dollars. [Extracted from the article]

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]

Copyright of NovaRUA Revista Universitaria de Administracion is the property of NovaRUA Revista Universitaria de Administracion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Complex disclosures have long been a major source of borrowers' poor understanding of mortgages. We examine the effect of simplifying mortgage disclosures in a difference-in-differences design around a significant disclosure rule mandated by the Consumer Financial Protection Bureau in 2015. We find that inexperienced borrowers (first-time home buyers) pay significantly lower interest rates after the disclosure regulation than experienced borrowers (repeat buyers), suggesting that simplifying these disclosures reduces mortgage interest costs. Additional tests show that the reduction in interest costs is not accompanied with more upfront noninterest costs paid by borrowers. Our cross-sectional analyses reveal two mechanisms through which simplifying disclosures lowers interest costs: curbing predatory lending and facilitating borrower shopping. We further find that disadvantaged borrowers (Black, Hispanic, and single female) benefit more from simplified disclosures. Last, we do not find that simplifying disclosures affects mortgage loan performance. JEL Classifications: G21; G5; G18; M4. [ABSTRACT FROM AUTHOR]

As housing demand rose post-COVID-19, new mortgage buyers with distinct preferences are entering the market. Nevertheless, the mortgage purchasing process can prove intricate and precarious for individuals lacking familiarity. Customers leverage various online platforms and supplementary sources to augment their knowledge and mitigate perceived risks, enabling them to make well-informed decisions during the mortgage buying process. Despite exerting these efforts, customers continue to harbor unfavorable purchase intentions due to their subpar purchasing experience, leaving mortgage lenders grappling with retention issues. Research has highlighted that only 15% of mortgage transfer customers would buy a mortgage from the original provider. The present study examines mortgage purchase intention and risk reduction by integrating customer empowerment and uncertainty reduction theories to contribute to the existing literature on mortgage decision-making. A survey was conducted among 554 mortgage buyers, and PLS-SEM was used to test the hypotheses. Knowledge positively influenced satisfaction (β = 0.15, p= = 0.01), and satisfaction positively affected purchase intention (β = 0.75, p = 0.01). The mediating mechanism of risk reduction through involvement and information search is also established. The findings suggest that customers involved in decision-making and information search are more likely to be satisfied with their purchase and experience less risk. Mortgage companies should encourage customers to be more involved and provide complete information during buying. As involved customers experience less confusion; they will make sound financial decisions and remain satisfied and loyal to the mortgage company. Using behavioral finance, policymakers could provide customers necessary nudges to improve decision-making. [ABSTRACT FROM AUTHOR]

The recent real estate debt crisis in China has dealt a huge blow to the banking sector. To address this challenge, we construct a dynamic game model that considers the interaction of the government, banks and real estate companies. The model is used to analyze the default behavior of real estate companies and loan losses for banks when facing information asymmetry. In addition, we empirically demonstrate the contagion effect of debt risk of real estate companies to banks, using a sample of 119 listed real estate companies and 42 listed banks in China from 2001 to 2020. The results show the following. (1) The debt risk associated with non-state-owned real estate companies is more likely to be contagious to banks compared to state-owned real estate companies. (2) The contagion effect of debt risk of real estate companies to banks is more significant among small and medium-sized banks. (3) The debt risk of non-state-owned real estate companies is most contagious for rural banks, followed by urban banks. Further tests show that the rising debt risk of non-state-owned real estate companies significantly increases the asset risk of small and medium-sized banks. This effect is reinforced through the liquidity channel. This implies that controlling the contagion of debt risk of non-state-owned real estate companies to small and medium-sized banks is an effective way to prevent the occurrence of banking crises. [ABSTRACT FROM AUTHOR]

The Chinese government encourages rural economic entities to use farmland management rights as collateral for loans, which helps to alleviate multi-level financing needs in rural areas. Based on the panel data of counties in Hubei Province, this paper adopts the Difference-in-Differences (DID) and the intermediary effect model to evaluate the impact of farmland management rights mortgage loans (FMRML) on the agri-food industrial agglomeration (AIA) in China. The study found that the pilot policy has significantly promoted the AIA. Moreover, the regression results remain robust after conducting the placebo test and the Propensity Score Matching Difference-in-Differences (PSM-DID) model, which demonstrates that the improvement effect is stable and long-lasting. From the heterogeneity analysis, it can be seen that the policy of FMRML has a more significant effect on the AIA in mountainous and hilly areas. By further analysis of the mechanism of action, it can be concluded that the pilot policy promotes the AIA by enhancing agricultural specialized production. The main findings can provide information for policymakers in China. The recommendations we have summarized encompass gradually expanding the scope of the pilot policy of FMRML, advancing the institutionalization and legalization of the policy, and promoting agricultural production specialization. [ABSTRACT FROM AUTHOR]

Because India has one of the world's fastest-growing economies, the Indian banking sector is essential to the country's reform. The approval of home loans to customers is one of the crucial tasks carried out by Indian banks. The risk of loan repayment outside of the agreed-upon time frame can be reduced by accurately estimating the customer's loan need. The majority of earlier studies on the development of banking lacked a methodical approach to analyze qualitative data. Even though the traditional multivariate statistically based factor analysis approach is a great way to categories data in qualitative analysis, the technique cannot be used without any statistical presumptions and additional information about the data. This study handles the banking attributes related to home loans using the Dominance-based Rough Set Approach (D-RSA). In order to categorize the customer's attributes, this study suggests using a preference-based "if ... then" decision rule. This rule can aid decision makers in understanding the risk factors associated with loan factors for a financial organization. [ABSTRACT FROM AUTHOR]