Mortgage Experiences of Rural Borrowers in the United States: Insights from the National Survey of Mortgage Originations

Critchfield, Tim; Dey, Jaya; Mota, Nuno; Patrabansh, Saty

doi:10.2139/ssrn.3204477

Cited by 5 publications

(6 citation statements)

References 4 publications

(2 reference statements)

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“…In addition, while the COLI compares 30‐year mortgages, seven of the rural banks either only offered a 20‐year mortgage or, as in one case, only offered a 30‐year mortgage as a second mortgage. These results are in line with other research on the rural credit access, rural bank deserts, and rural borrowers (Critchfield et al 2019; MacTavish et al 2014; Roskey 2011; Singleton et al 2006).…”

Section: Resultssupporting

confidence: 91%

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The Enduring Price of Place: Revisiting the Rural Cost of Living^☆

2023

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Even as the 2016 elections brought increased public attention to rural life, stereotypes and misconceptions abound. One of these misperceptions is the generalization that prices are lower in rural areas. This article is a restudy of Zimmerman, Ham, and Frank (2008) research on geographic differences in the costs of living. Asking the same fundamental question—if someone bought the same thing in a rural and urban area, would they pay the same price?—and using the same methodology, the results 10 years later indicate that, contrary to popular perception, there was again no consistent pattern of lower prices in rural counties and no consistent pattern of a lower rural cost of living in all of the rural areas. While prices are only one piece of the larger picture of how rural households meet their needs, in addition to price differences, the results highlight how differences in rural life create additional costs that extend beyond prices.

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Section: Resultssupporting

confidence: 91%

“…a second mortgage. 19 These results are in line with other research on the rural credit access, rural bank deserts, and rural borrowers (Critchfield et al 2019;MacTavish et al 2014;Roskey 2011;Singleton et al 2006).…”

Section: Housingsupporting

confidence: 78%

The Enduring Price of Place: Revisiting the Rural Cost of Living^☆

2023

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“…This unique data set contains information from mortgage customers regarding the details from the shopping to loan closing process, including search efforts, familiarity, knowledge, satisfaction and information search. Many studies have used the NSMO data set, but none have attempted to model the consumer decision-making process using the SEM technique (Argento et al , 2019; Critchfield et al , 2019; Malliaris et al , 2019).…”

Section: Methodsmentioning

confidence: 99%

“…Customers overcome information asymmetry by increasing their familiarity with the product during purchase (Levy et al, 2020). Specifically, customer familiarity with mortgages varies considerably in the mortgage sector (Critchfield et al, 2019). Familiarity with mortgage terms such as interest rates or the loan application procedure enables clients to have a seamless shopping experience and satisfaction with loan terms by establishing a performance baseline before purchasing (Bhutta et al, 2020).…”

Section: Research Model and Hypothesis Developmentmentioning

confidence: 99%

“…Extant research in mortgages has concentrated on post-purchase consumer welfare indicators such as default (Agarwal et al, 2014(Agarwal et al, , 2017Bhutta et al, 2017), decision-making errors such as picking high-interest rate ARMs (Campbell et al, 2011;Agarwal et al, 2015;Agarwal et al, 2017;Argento et al, 2019;Critchfield et al, 2019;Malliaris et al, 2019), expectations of future housing price increases (Larson et al, 2021) and on the impact of mortgage purchase on future credit decisions (Fulford and Stavins, 2021). Only a few studies have scrutinised the mortgage decision-making process (Perry and Blumenthal, 2012;Perry and Lee, 2012;Grundl and Kim, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Antecedents of customer mortgage shopping satisfaction: the mediating role of search intensity, evidence from the NSMO survey

Reddy

Thanigan²

2022

IJHMA

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Purpose The purpose of this paper is to examine the antecedents of customer satisfaction during mortgage purchases. Mortgage demand in the USA has reached an all-time high because of an increase in housing demand after COVID-19. Nonetheless, several customers are dissatisfied with their service providers. Customers who actively search the market gain more information about mortgage providers and use this information to define expectations for lenders. The only way there will be customer satisfaction is if lenders meet these expectations. Therefore, it is economically significant for mortgage lenders to discover the antecedents of mortgage satisfaction. Design/methodology/approach In this study, the partial least squares approach was used to test the hypothesis that satisfaction was influenced by objective knowledge, familiarity and search intensity among a sample of customers (n = 4,512) from the National Survey of Mortgage Originations who had purchased a mortgage in the USA between 2019 and 2020. Findings The results of structural modelling showed that familiarity (β = 0.23 and p = 0.01) with and knowledge (β = 0.16 and p = 0.01) of mortgages significantly affected consumer satisfaction during mortgage purchase. Search intensity (p = 0.01) mediated the relationship between knowledge, familiarity and satisfaction. Research limitations/implications The primary implication is that mortgage service providers should prioritise educating customers about the mortgage buying process on their websites and in person. So managers must actively assist clients in having realistic expectations. Second, mortgage companies should establish a presence on third-party mortgage comparison websites to ensure that customers actively consider alternatives, thereby increasing customer satisfaction. Originality/value This study is unique in being an exploratory study to examine the antecedents of mortgage satisfaction using a public data set. This study uniquely examines the National Survey of Mortgage Originations data set with partial least squares approach to examine underlying customer attitudes.

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