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A review of ALEX POLLOCK & HOWARD ADLER, SURPRISED AGAIN! THE COVID CRISIS AND THE NEW MARKET BUBBLE (2022) I approach phenomena that I don't understand with good cheer and [...]

The mortgage industry is central to ethno-racial stratification in homeownership access. Ample research demonstrates that unequal treatment of minorities has created major differences in the access and exclusion of low-cost loan products in the housing market. While numerous studies have documented the disadvantages Black and Latino homebuyers face, these studies have been limited in their assessment of credit worthiness in accessing a mortgage. This study draws on the annual dataset from the Home Mortgage Disclosure Act from 2018 and 2019 to assess ethno-racial disparities in mortgage outcomes by debt-to-income (DTI) levels. I demonstrate that DTI levels vary tremendously by ethno-racial groups. In addition, I show that loan rejections and high-cost loan originations are highest among Blacks and Latinos across DTI levels compared to White applicants. Depending on the adverse loan outcome, Asians perform similarly or slightly underperform compared to Whites. These trends are particularly true when examining high-cost loan originations as Blacks and Latinos with excellent credit worthiness perform similarly as Whites and Asians with below-average credit worthiness. Implications for ethno-racial stratification are discussed. [ABSTRACT FROM AUTHOR]

In 2013, the Dutch government mandated that new conforming mortgages must fully amortize. Within a difference-in-differences design, we estimate that the marginal wealth accumulation from amortization is close to one, even five years later. Households purchasing after the reform primarily cut consumption and leisure over other savings, leading to a rise in wealth. This holds if we use life events to instrument for the timing of home purchase. Estimates are similar for seemingly unconstrained households and movers, suggesting a broad applicability of our results. Consistent with a simple model, we find lower estimates for households that appear less financially sophisticated or willing to adjust short-term consumption. Mortgage amortization schedules are among the largest savings plans in the world, and our results highlight their critical importance for household wealth building and macroprudential policies. [ABSTRACT FROM AUTHOR]

This paper analyzes empirically the existence of the credit channel of monetary policy in Mexico, that is, the relationship between changes in the target interest rate and variations in credit granted by commercial banks. The study combines aggregate information with data from the individual balance sheets of commercial banks and conducts a panel data regression analysis. The analysis is performed for total credit and its components (business, consumer, and mortgage). Additionally, by using banks' accounting information, it explores whether the transmission mechanism occurs on the supply side. It is found that there is a negative and economically significant relationship between interest rate and credit, and such a relationship is established for different types of credit. Furthermore, evidence suggests that the transmission mechanism operates on the supply side, as banks with more robust balance sheets exhibit greater resilience to changes in the interest rate. [ABSTRACT FROM AUTHOR]

We investigate the bank lending channel of negative nominal policy rates from an empirical and theoretical perspective. For the empirical results, we rely on Swedish data, including daily bank-level lending rates. We find that retail household deposit rates are subject to a lower bound (DLB). Empirically, once the DLB is met, the pass-through to mortgage lending rates and credit volumes is substantially lower and bank equity values decline in response to further policy rate cuts. We construct a banking sector model and use our estimate of the pass-through of negative policy rates to lending rates as an identified moment to parameterize the model and assess the impact of negative policy rates in general equilibrium. Using the theoretical framework, we derive a sufficient statistic for when negative policy rates are expansionary and when they are not. [ABSTRACT FROM AUTHOR]

The noterate is a tool for predicting home mortgage rates, it is often skewed and has missing information. The noterate could be affected by incomplete or inaccurate data, thus leading to inaccurate predictions. Financial organizations including mortgage companies or banks need to consider the risk of uncertainty carefully and make a more accurate prediction based on some suitable models. To deal with this situation, in this paper we compared six computational statistical methods, including the ordinary least square model, maximum likelihood estimation, maximum a posterior, bootstrapping, Metropolis-Hastings, and Gibbs sampling method on a mortgage dataset. Based on the k fold cross-validation technique and four metrics including mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and mean absolute percentage error (MAPE), the bootstrapping method outperforms other methods. In practice, this method is recommended for predicting noterate. [ABSTRACT FROM AUTHOR]

We use a DSGE model with financial frictions and with macroprudential limits on both banks and mortgage borrowers, in the form of capital requirements and maximum debt‐service ratios. We then examine: (i) the impact of different combinations of macroprudential limits on key macroeconomic aggregates; (ii) their interaction with each other and with monetary policy; and (iii) their effects on the volatility of key macroeconomic variables and on welfare. We find that capital requirements on banks are the optimal tool when faced with a financial shock, as they nullify the effects of financial frictions and reduce the effects of the shock on the real economy. Instead, limits on mortgage debt‐service ratios are optimal following a housing demand shock, as they disconnect the housing market from the real economy, reducing the volatility of inflation. Hence, no policy on its own is sufficient to deal with a wide range of shocks. [ABSTRACT FROM AUTHOR]

The ultimate goal of studying high-end customer loyalty is to identify their shortcomings in customer maintenance and provide appropriate service marketing guidelines for public and private banks. This study selected the high-end customer groups of Agricultural Bank of China and Hengfeng Bank as specific research objects and collected a total of 380 data for mean, standard deviation, and correlation analysis. Through statistical analysis of data, it was found that high-end customers have varying degrees of perception towards service quality, perceived value, and customer satisfaction. There is a positive correlation between potential factors of customer loyalty and various dimensions to varying degrees. In order to improve the correlation between variables, this study provides relevant suggestions for public and private banks from three aspects: service quality, perceived value, and customer satisfaction, guiding them to maintain and improve the loyalty of high-end customers to financial institutions. [ABSTRACT FROM AUTHOR]

All over the world, home loans and mortgages are part and parcel of the products and services being offered by the financial institutions-such as banks and homeowner mortgage institutions to their numerous customers. Prior, during and post home loan transactions, they owe their customers the duty to ensure full disclosure of all the terms and conditions in the mortgage agreements without withholding any information. This paper examines any act contrary to uberrimae fidei-utmost good faith in the transactions. Uberrimae fidei requires the highest standard of good faith on both the lender and borrower to disclose all material facts that could influence the decisions of the other party in seeking and granting home loans and mortgages. Failure might result in severe consequences by exploring both the civil and criminal responsibilities and liabilities of the party who acted mala fide-in bad faith. Against this backdrop, this paper examines the protection offered by the laws to ensure level playing field prior, during and after mortgage lending transactions. [ABSTRACT FROM AUTHOR]

The long-sought self-sufficiency goal of contemporary social welfare systems has been mostly elusive, even in developed countries. This paper presents a revised version of the Self-Sufficiency Framework as a pragmatic strategy for welfare reform, investigating how the current neoliberal approach centered on promoting employment (workfare) could be made more socially just and freedom-oriented. Thus, the framework proposed here accepts the central goal of promoting employment (self-sufficiency) at the core of current welfare systems, but complements that goal with a strong and non-stigmatizing welfare support package and with labor market reforms aimed at combating exploitative forms of employment. Furthermore, the proposed model emphasizes the need for financial inclusion, notably in the banking system and the mortgage industry. [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]

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]

We examine the economic consequences of a rule designed to improve consumers' understanding of mortgage information. The 2015 TILA‐RESPA Integrated Disclosures rule (TRID) simplifies the mortgage disclosures provided to consumers. As a consequence, TRID‐affected mortgages become a less attractive investment opportunity to banks. Our main results document that mortgage applications affected by TRID are less likely to be approved following the rule's effective date. We find evidence consistent with both a decrease in consumers' information processing costs and an increase in banks' secondary market frictions, providing insight into the potential channels through which this reduction in mortgage credit operates. We also find that banks partially compensate for reduced mortgage lending by increasing small business lending, and that fintechs absorb mortgage demand in areas with reduced mortgage lending by banks. Our study documents real actions that firms take in response to disclosure transparency regulation and contributes to the literature on the economic consequences of such regulation. [ABSTRACT FROM AUTHOR]

Nonbank mortgage originators, which operate through the originate‐to‐distribute (OTD) model, account for more than half of all the mortgage origination in the United States. However, less is known about which factors drive the quality of mortgage originations through nonbanks. I show that an exogenous shock that reduced collateral risk for funding intermediaries of nonbank mortgage originators led to a greater issuance of riskier mortgages that culminated in 10–30% higher ex post defaults. These results show how the quality of mortgage origination in the OTD model of nonbanks is affected by the collateral risk borne by their funding intermediaries. Overall, the results highlight funding intermediaries' monitoring incentives as one of the factors that drive the quality of mortgage originations through nonbanks. [ABSTRACT FROM AUTHOR]