Mortgage Refinancing Research Articles

The Impact of Mortgage Rates on Mortgage Refinancing

Mortgages loans are vital for the acquisition of housing property and mortgage lending rates play an important role in mortgage market trends, borrowers, and lenders’ decisions. Objective: the aim of this paper is to evaluate the combined effect of current and previous mortgage rates on mortgage refinancing. Prior work: the paper inclines on the ontology of a single reality of the interaction between mortgage rates and mortgage refinancing with attendant epistemology that their interaction is measurable. Method: the paper adopts the positivist paradigm and a quantitative technique. It used data on the U.S. Mortgage Bankers Association (MBA) retrieved from the economic and financial database of Fusion Media. Data were analysed using the OLS technique. Novel Findings show that current-actual and previous mortgage rates have a significant positive effect on mortgage refinancing at p=0.05 and p=0.04 respectively. Significance: the findings have implication for mortgage lending and refinancing decisions for mortgage bankers (lenders), mortgage borrowers and policy makers. It also provides current academic study material for university business schools and for future researchers to apply the model used in this research for related expanded research. Value: The paper contributes a new model with two genres of mortgage rate (current mortgage rate and previous mortgage rate) and how these two types of mortgage rates influence mortgage refinancing.

The Effects of TV Advertising and Ad Content on Consumer Financial Decisions: Evidence from Mortgage Refinancing

The Effects of TV Advertising and Ad Content on Consumer Financial Decisions: Evidence from Mortgage Refinancing

How Do Households Respond to Job Loss? Lessons from Multiple High-Frequency Datasets

How much and through which channels do households self-insure against job loss? Combining data from a large bank and from government sources, we quantify a broad range of responses to job loss in a unified empirical framework. Cumulated over a two-year period, households reduce spending by 30 percent of their income loss. They mainly self-insure through adjustments of liquid balances, which account for 50 percent of the income loss. Other channels—spousal labor supply, private transfers, home equity extraction, mortgage refinancing, and consumer credit—contribute less to self-insurance. Both overall self-insurance and the channels vary with household characteristics in intuitive ways. (JEL D12, G21, G51, J64, J65)

Is There Crowd Out in Mortgage Refinance?

Is There Crowd Out in Mortgage Refinance?

3.1 BILLION PKR PAKISTAN MORTGAGE REFINANCE COMPANY SUKUK: A FIRST OF ITS KIND FOR HOUSING FINANCE

The following presents a case study pertaining to innovation in the Sukuk industry in the Islamic capital market of Pakistan which has gained momentum over the last five years. The purpose of this case is to describe a recent Sukuk issued by Pakistan Mortgage Refinance Company (PMRC), a Mortgage Liquidity facility that issued Musharka Sukuk based on Shirkat-ul Aqd, aimed at developing housing finance market in Pakistan. Given the acute shortage of houses and reluctance amongst banks to grant consumers housing loans for a longer-term duration, this facility will enable affordable house financing through a Shariah-compliant mode, while offering a new avenue of investment for capital market participants. This paper describes the key features of the Sukuk, outlines its Shariah structure, and elaborates upon the mechanism of the transaction. A graphical illustration of the Sukuk structure is made to facilitate the reader’s understanding of each step of the transaction. The PKR 3.1billion PMRC Sukuk with the fixed-rate offering of 8.25% for 3 years is expected to be a landmark for the development of the housing sector of the country. It supplements the idea of how the issuance of Sukuk can play a vital role in addressing real economic needs.

Real Estate-Backed Mortgages and Alternative Recovery Techniques: Evidence from Selected Banks in Tanzania

Inefficiencies accompanying foreclosures in recovering outstanding debts of real estate-backed mortgages have necessitated banks and other mortgage lenders to opt for alternative recovery techniques. Extant studies have focused much on the application of workouts mainly in developed economies (which are characterized by well-established real estate and financial markets) with less attention from emerging economies. This study aimed at exploring how banks in Tanzania apply alternative recovery techniques in real estate-backed mortgages. A qualitative approach was used to collect the data from multiple commercial banks in Tanzania. Interviews, annual reports, and government documents were used to triangulate the information. Findings revealed that different forms of workouts are preferred. The most preferred technique was mortgage modification, followed by mortgage refinancing. Other workout techniques such as forbearance, transfer of debt to a new borrower and short sale are minimally applied. Likewise, the banks were found applying the scare-tactics to enforce the customers do all they can to clear their debts before considering the use of the workouts. The study recommends that to facilitate optimal workouts, all stakeholders including the government, the bank systems, borrowers, and real property professionals must jointly cooperate for mutual benefits. The study proposed that further research could explore the fraudulent practice of borrowers that limit operationalization of workouts. Moreover, an investigation on whether borrowers’ benefit by changing terms of their repayment could be made. Finally, further studies are needed to investigate whether there is heterogeneity in the application of workouts between commercial and residential mortgage with a view to establishing whether borrowers’ default intentionally or not.

The potential impact of financial portability measures on mortgage refinancing: Evidence from Chile

This study estimates the potential impact of a recent Financial Portability Law in Chile on the households’ mortgage refinancing probability. I show that mortgage refinancing is positively associated with financial education, liquidity needs, plus the value and timing for optimal refinancing. A counterfactual exercise shows the new legislation can substantially increase the refinancing probability and bring welfare gains, especially if it lowers the cognitive costs of the process. The refinancing probability may increase from 18% to 21.1% and create a welfare gain of 202 USD per borrower if only the pecuniary cost channel of the law is accounted for. However, the refinancing probability and welfare gains may increase to 29.2% and 902 USD, respectively, if the law can also significantly reduce the cognitive-education costs of refinancing. Welfare gains are larger for higher income households and owners of top valued homes. The refinancing gains could also boost the potential impact of monetary policy on consumption.

To Sell or To Retain: Interest Rate Risk and Banks' Mortgage Securitization Decisions

This paper shows the importance of interest rate risk and prepayment risk in fixed-rate mortgages in influencing banks’ securitization of mortgages. Banks with longer-maturity liabilities are more capable of taking the interest rate risk and therefore securitize fewer mortgages. In contrast, banks with shorter-maturity liabilities securitize more mortgages and originate fewer jumbo mortgages, which can not be securitized through Fannie Mae and Freddie Mac. Moreover, household mortgage refinancing induces prepayment risk. The prepayment risk matters more for banks with longer-maturity liabilities, due to their high retention of mortgages on balance sheets. Ex ante, anticipating the prepayment risk, banks with longer-maturity liabilities securitize more mortgages. Ex post, banks with longer-maturity liabilities are less likely to help households refinance their existing mortgages.

Investing in Lending Technology: IT Spending in Banking

This paper investigates lending technologies in the banking sector after the arrival of the information age, by examining investment in information technologies (IT) by U.S. commercial banks. Given the distinctive nature of banks’ dealings with information as they engage in lending activities, we link banks’ IT spending in various categories to different aspects of their lending technologies. Investment in communication IT is shown to be associated more with improving banks’ ability of soft information production and transmission, while investment in software IT helps enhance banks’ hard information processing capacity. By exploiting polices that affect geographic regions differentially, we show that banks respond to an increased demand for small business credit (mortgage refinance) by increasing their spending on communication (software) IT spending. We also find an asymmetric impact of technological development on labor employment in the banking sector.

Refinancing Cross-Subsidies in the Mortgage Market

Evidence from a range of countries reveals that household inaction in mortgage refinancing can be pervasive despite financial incentives to take action. Inactive households may implicitly cross-subsidize active households, allowing competitive lenders to set lower average mortgage rates. To provide a money-metric assessment of cross-subsidies, we construct a model of household refinancing and structurally estimate it on rich administrative data on the stock of loans in the U.K. mortgage market in June 2015. We estimate sizeable cross-subsidies during this sample period, from relatively poorer households and those located in less-wealthy areas towards richer households and those located in wealthier areas. The findings over this sample period highlight how the design of household finance markets can contribute to wealth inequality. Estimated cross-subsidies may differ in more recent periods given changes in the UK mortgage market since 2015.

Racial Differences in Mortgage Refinancing, Distress, and Housing Wealth Accumulation during COVID-19

The COVID-19 pandemic exacerbated racial disparities in U.S. mortgage markets. Black, Hispanic, and Asian borrowers were significantly more likely than white borrowers to miss payments due to financial distress, and significantly less likely to refinance to take advantage of the large decline in interest rates spurred by the Federal Reserve’s large-scale mortgage-backed security (MBS) purchase program. The wide-scale forbearance program, introduced by the 2020 Coronavirus Aid, Relief, and Economic Security (CARES) Act, provided approximately equal payment relief to all distressed borrowers, as forbearance rates conditional on nonpayment status were roughly equal across racial/ethnic groups. However, Black and Hispanic borrowers were significantly less likely to exit forbearance and resume making payments relative to their Asian and white counterparts. Persistent differences in the ability to catch up on missed payments could worsen the already large disparity in home ownership rates across racial and ethnic groups. While the pandemic caused widespread distress in mortgage markets, strong house price appreciation in recent years, particularly in 2020, means that foreclosure risk is lower for past-due borrowers now as compared with the aftermath of the Global Financial Crisis and Great Recession. Furthermore, borrowers who have missed payments have significantly higher credit scores now than those who were distressed in the 2007–2010 period, largely due to the widespread availability of forbearance for federally backed mortgages.

Does Appraiser and Borrower Race Affect Valuation?

Following concerns about undervaluation of minority-owned homes, we examine the incidence of racial appraisal bias using a nationwide sample of refinanced mortgages from 2000 to 2007. A unique feature of our data is that they allow us to observe the race of the both the homeowner and the appraiser. We do not observe large, systematic differences in the ratio of appraised values to automated valuation model (AVM) estimates between Black- and White-owned homes. Moreover, the appraiser's race and its interaction with the owner's race are not related to valuations. Our findings suggest that racial appraisal bias is either uncommon in the mortgage refinance market or has a relatively minor effect on valuations, on average.

Extending the Benefits of Mortgage Refinancing: the Case for the Auto-Refi Mortgage

Extending the Benefits of Mortgage Refinancing: the Case for the Auto-Refi Mortgage

Macroeconomic effects of the mortgage refinance and the home equity lines of credit

I examine how the mortgage refinance and the home equity lines of credit (HELOC) impact the increase in pre-crisis mortgage debt and post-crisis mortgage defaults. Financially constrained homeowners can cash out funds through refinancing mortgages or extract home equity through HELOC. My quantitative exercise shows that prevalent usage of refinancing increases pre-crisis mortgage debt, which amplifies the post-crisis foreclosure rate. HELOC also contributes to an increase in mortgage defaults, though it negligibly impacts pre-crisis mortgage debt.

Inequality During the COVID-19 Pandemic: The Case of Savings from Mortgage Refinancing

We study the distribution of savings from mortgage refinancing across income groups during the COVID-19 pandemic. Between February and June 2020, the difference in savings from refinancing between high- and low-income borrowers was ten times higher than before the pandemic. This was the result of two factors: individuals in the top quintile of the income distribution increased their refinancing activity more than comparable borrowers in the bottom quintile and, conditional on refinancing, they captured slightly larger improvements in interest rates. Exploiting idiosyncratic variation in COVID-19 case rates within zip codes over time, we find that changes in local economic conditions explain up to 74 percent of the increase in refinancing inequality tied to the pandemic. Using data on refinancing applications and funding rates we find that, conditional on applying, the funding rates and processing times for low-income borrowers were not differentially affected by the pandemic. Instead, low-income borrowers were underrepresented in the pool of applications. We estimate a difference of $5 billion in savings from refinancing between the top quintile of the income distribution and the rest of the market. This discrepancy has implications for the transmission of monetary policy and the evolution of wealth inequality.

How Do Households Respond to Job Loss? Lessons from Multiple High-Frequency Data Sets

How do households respond to job loss, and which self-insurance channels are most important? By linking high-frequency customer data from the largest bank in Denmark with government administrative registers, we quantify a broad range of responses to job loss in a unified empirical framework. Two responses stand out: during the first 24 months after job loss, reductions in household spending account for 30% of the income loss, while lower saving in liquid assets accounts for 50%. Other response margins highlighted in the literature - spousal labor supply, private transfers, home equity extraction, mortgage refinancing, and consumer credit - are less important.

Houses as ATMs: Mortgage Refinancing and Macroeconomic Uncertainty

ABSTRACTMortgage refinancing activity associated with extraction of home equity contains a strongly countercyclical component consistent with household demand for liquidity. We estimate a structural model of liquidity management featuring countercyclical idiosyncratic labor income uncertainty, long‐ and short‐term mortgages, and realistic borrowing constraints. We empirically evaluate its predictions for households' choices of leverage, liquid assets, and mortgage refinancing using microlevel data. Taking the observed historical paths of house prices, aggregate income, and interest rates as given, the model accounts for many salient features in the evolution of balance sheets and consumption in the cross‐section of households over 2001 to 2012.

Framing Bias in Mortgage Refinancing Decisions and Monetary Policy Pass-Through

This paper shows that households’ mortgage refinancing decisions suboptimally depend on uninformative reference points, imposing a friction to the refinancing channel of monetary policy. I study refinancing behavior in the UK, where on pre-determined dates initial fixed rates reset and mortgagors automatically move onto a reversion rate above market rates. A borrower’s expired fixed rate determines whether failing to refinance is perceived as a loss or as a gain, thus serving as a salient reference point. I find that borrowers for whom inaction implies a relative gain refinance on average 13.4% less than borrowers who face a loss. This evidence is at odds with optimal models of refinancing since future borrowing costs are unrelated to past rates.

Regional Heterogeneity and the Refinancing Channel of Monetary Policy*

We argue that the time-varying regional distribution of housing equity influences the aggregate consequences of monetary policy through its effects on mortgage refinancing. Using detailed loan-level data, we show that regional differences in housing equity affect refinancing and spending responses to interest rate cuts, but these effects vary over time with changes in the regional distribution of house price growth. We build a heterogeneous household model of refinancing with mortgage borrowers and lenders and use it to explore the monetary policy implications arising from our regional evidence. We find that the 2008 equity distribution made spending in depressed regions less responsive to interest rate cuts, thus dampening aggregate stimulus and increasing regional consumption inequality, whereas the opposite occurred in some earlier recessions. Taken together, our results strongly suggest that monetary policy makers should track the regional distribution of equity over time.

Extracting Features from Bank and Mortgage Company Commercials

Recent advances in machine learning have made it possible to extract rich data features from video. These techniques allow for a new understanding of the role of advertising in marketing products. I demonstrate how to extract text, image, and audio features from a novel dataset of over 20,000 bank and mortgage company commercials covering the years 2004 to 2015. I demonstrate that the extracted features display meaningful trends. I then apply these features to show how commercials impact mortgage and home equity loan origination and refinancing.