Borrowing Behavior Research Articles

Financial Knowledge, Personality Traits, and Risky Borrowing Behaviors in Iranian Households

This article examines the influence of financial knowledge and personality traits on risky borrowing behaviors among Iranian respondents. A proprietary dataset was used in this study. Logistic regression results indicated that numeracy and knowledge of the time value of money were negatively associated with two of the three risky borrowing behaviors (borrowing more than $1500 USD and use of rent-to-own). Conscientiousness was negatively related to the same two borrowing behaviors. Neuroticism negatively influenced use of payday lending. The article concludes with financial education policy suggestions for Iran and directions for future research.

Deep Learning for Mortgage Risk*

AbstractWe examine the behavior of mortgage borrowers over several economic cycles using an unprecedented dataset of origination and monthly performance records for over 120 million mortgages originated across the United States between 1995 and 2014. Our deep learning model of multi-period mortgage delinquency, foreclosure, and prepayment risk uncovers the highly nonlinear influence on borrower behavior of an exceptionally broad range of loan-specific and macroeconomic variables down to the zip-code level. In particular, most variables strongly interact. Prepayments involve the greatest nonlinear effects among all events. We demonstrate the significant implications of the nonlinearities for risk management, investment management, and mortgage-backed securities.

International Real Estate Review

The global economy is in the midst of a recession triggered by the ongoing pandemic of a novel coronavirus disease (COVID-19). The shutdown of the economy and a surge in the unemployment rate also cause stress to the US housing and mortgage system and create significant impacts on the default behaviour of mortgage borrowers. The potential rise in mortgage defaults may renew the long-standing debate over the empirical observation of why some mortgage borrowers do not default as "ruthlessly¨ as the finance theory predicts. In this paper, we propose an alternative theory to explain for the different default behaviours among mortgage borrowers. We hypothesize that the difference among time preferences across mortgage choices is one of the underlying factors that causes the heterogeneity in default patterns. Borrowers can either have a present-biased preference (overvaluing immediate outcomes), or a time-consistent preference (with standard exponential discounting). Borrowers with a present-biased preference are more likely to accept back-loaded mortgages that minimize up-front costs, even though this increases their risk of going ¡§underwater¡¨ and entering default when an adverse shock, such as the one from the ongoing pandemic, occurs.

A DYNAMIC DISCRETE CHOICE MODEL OF REVERSE MORTGAGE BORROWER BEHAVIOR

AbstractUsing unique data on reverse mortgage borrowers in the Home Equity Conversion Mortgage (HECM) program, we semiparametrically estimate a dynamic discrete choice model of borrower behavior. Our estimator is based on a new identification result we develop for models with multiple terminating actions. We show that the per‐period utility functions and discount factor are identified without restrictive, ad hoc identifying restrictions that lead to incorrect counterfactual implications. Our estimates provide insights about factors that influence HECM refinance, default, and termination decisions and allow us to quantify the trade‐offs involved for proposed program modifications, such as income and credit requirements.

Can Readability of Loan Description Affect Loan Success Rate and Loan Cost?: A Textual Analysis of P2P Loan Description

Text is an important form of information transfer. In a P2P (Peer-to-Peer) loan market with severe information asymmetry, loan descriptive information voluntarily written by a borrower may generate significant influence on investors’ decision-making. As an important language feature, readability determines whether the audience can accurately identify textual contents. To discuss the influence of readability of loan description on borrowing behaviors, the data of a Chinese P2P lending platform Renrendai during 2013–2017 were used in this study. Readability index of loan description was constructed through the textual analysis method, followed by an empirical verification of the influences of readability of loan description on loan success rate and loan cost. Results indicate that the readability of loan description in China’s P2P loan market can generate incremental information, and the readability of loan description has evident nonlinear relations with loan success rate and loan interest rate. Moreover, the readability of loan description presents a “reverse U-shaped” relation with loan success rate and a “U-shaped” relation with loan interest rate. Demographic information (gender and educational background) of borrowers will not influence investors’ feedback behaviors toward the readability of loan description. Conclusions provide empirical evidence for standardizing loan descriptive information on P2P lending platforms.

Effect of the Socioeconomic Characteristics of Borrowers on Microcredit Repayment Behaviour: An Application to a Category II Microfinance Institution in Cameroon

The purpose of this study is to determine the influence of socioeconomic characteristics of borrowers on microcredit repayment behaviour. The results of Probit regression statistical analysis using a database of 1805 individual loan contracts, credit records and follow-up files from 2007 to 2014 period by Community Credit of Africa (CCA) in Cameroon, reveal that educational level, awareness about the location of business and/or home of borrowers by the lender, sector of activities, availability of collateral, income stability, and personal wealth of borrowers have a statistically significant influence on microcredit repayment behaviour of borrowers. The outcome of the results shows that microfinance institutions should not only rely on financial indicators to assess the creditworthiness of borrowers. Other factors belonging to the social and economic characteristics of the borrowers are supposed to be integrated in credit risk models. These factors are sought to influence significantly microcredit repayment behaviour of borrowers.

Reinforcement learning and mortgage partial prepayment behavior

An agent can learn from previous experience to make decisions. Several important studies claim that reinforcement learning plays a key role in explaining the evolution of the individual learning process. This paper studies the likelihood of mortgage partial prepayments and the process through which mortgage borrowers learn from making partial prepayment decisions in the residential mortgage market in China. Learning dynamics are measured by studying the mortgage partial prepayment behavior of individual borrowers. A longitudinal discrete choice model of the choice of the mortgage payment is presented and estimated using a rich set of mortgage loan history data from a leading mortgage lender in China. The results indicate that path dependency and reinforcement learning arise whenever a borrower's “partial prepayment” decision depends not only on current-stage variables and his/her individual characteristics but also on the learning experience (both from himself/herself and others). Borrowers with more partial prepayment experience in previous stages have a higher probability of making the same decision in the future. Moreover, learning dynamics are not monotonic, and recent experience plays a larger role than distal experience in determining a partial prepayment decision.

SOVEREIGN DEFAULT CONTAGION AND MONETARY POLICY IN AN AGENT-BASED MODEL

Sovereign default contagion was one of the most debated topics during the Eurozone sovereign debt crisis. Despite all the improvements in the financial situation since 2010, namely after European Central Bank quantitative easing policies, the nature of the problem and the policy prescriptions are still under dispute today. Using an agent-based model, we simulate sovereign default contagion for different monetary policy options in a world where governments have random incomes, different heterogeneous borrowing behaviors and risk aversion levels and where countries can enter into ex-ante agreements to protect themselves against default. Our simulations showed that default contagion can be a very fast and “destructive” process, and that monetary policy can have a very important role in preventing sovereign defaults through zero interest rate and quantitative easing policies.

Taxes and Borrower Behavior: Evidence from the Mortgage Interest Deductibility Limit

This paper estimates the behavioral response to mortgage interest tax deductibility by studying the discrete change in the net-of-tax marginal interest rate that occurs at $1 million in mortgage debt. Using data on 2004-2016 mortgage originations, I estimate excess bunching in the loan distribution based on a counterfactual that accounts for bunching at salient loan amounts. Findings suggest excess of about 54,000 loans at the deductibility limit, or 4.5% of the sample. The level of bunching implies an average reduction in borrowing around the $1 million limit of 9.4 percent, and mortgage demand elasticities between − 0.132 to − 0.115 for home purchase loans. Estimated elasticities imply that from 2004-2016 the MID induced $49.52 billion in deadweight loss in the mortgage market.

Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?

There are a large amount of studies on the impact of individual experience on learning outcome, which ignore the conditioning and implicitly assume that the learning behaviors are bound to arise. This study develops a two-stage conceptual model for the interpretation of individual learning, and aims to explore how individual’s prior experience affects the initiating of subsequent learning behavior first and then impacts the success of subsequent learning behavior. Using a large sample of loan application data over a five-year period from a Chinese P2P lending platform Renrendai, we found strong evidence that both prior successes and prior failures can motivate borrowers to take subsequent borrowing behaviors again. However, in regard to the impact of individual experience on learning outcome, our finding in online environment is contrary to the prevalent view in organizational learning—“we learn more effectively in failure than in success”. Specifically, we found only successes can lead to desirable success whereas failures can’t, which indicates that borrowers with failure experience are willing to repeat borrowing but unable to learn from their failures. Further, we find a beneficial interaction effect between borrower’s prior successes and prior failures on subsequent borrowing success. These results are robust across a variety of settings. Our study enriches the understanding of individual learning by focusing not only on outcome improvement but also on conditioning. Moreover, we investigate learning process in an online environment which is anonymous and lack of peer communication that offline organizations have, we draw some different findings. Our findings also offer practical insights for borrowers under financial difficulties and platform managers to correctly interpret prior experience and enhance the probability of subsequent funding success in P2P lending.

Appraisal of the Nigerian Credit Reporting Act 2017

AbstractCredit reporting is the act of gathering information about the behaviour of borrowers and making such information available whenever a decision is to be made regarding a borrower's application for new credit. Following the introduction of credit bureaux in Nigeria in 2007, in 2017 the federal legislature enacted the Credit Reporting Act, creating a legal framework for the implementation of credit reporting and codifying global best practices adhered to in the practice and administration of credit reporting. This article examines the act in the light of its objectives and attempts to determine whether the legal framework it provides is conducive to the achievement of these objectives. It also considers the factors that might militate against the effective running of a credit reporting system in Nigeria and suggests measures to deal with these challenges.

Similarity Analysis of Learning Interests among Majors Using Complex Networks

At present, multi-specialization cross integration is the new trend for high-level personnel training and scientific and technological innovation. A similarity analysis of learning interests among specializations based on book borrowing behavior is proposed in this paper. Students of different majors that borrow the same book can be regarded as a way of measuring similar learning interests among majors. Considering the borrowing data of 75 majors, 14,600 undergraduates, and 280,000 books at the Northwest Normal University (NWNU), as an example, this study classified readers into majors depending on similarity among students. A complex network of similar learning interests among specializations was constructed using group behavior data. The characteristics of learning interests were revealed among majors through a network topology analysis, importance of network nodes, and calculation of the similarity among different majors by the Louvain algorithm. The study concluded that the major co-occurrence network was characterized as scale-free and small-world; most majors had mutual communication and an infiltrating relationship, and the 75 majors of NWNU may form six major interest groups. The conclusions of the study were related to the development of majors of the university, and a match between major learning communities was based on the borrowing interest in a similar network to reflect the relationship between the characteristics and internal operating rules of a major.

Monetary Policy and Borrowers’ Loan Defaults: Research Based on Data from Renrendai

AbstractThis paper uses Renrendai data to study the relationship between monetary policy and the default behavior of borrowers, and analyzes the transmission channels. The research shows that tight monetary policy will lead to a significant increase in a borrower's probability to default, and this effect will continue for several months. There may be two transmission channels: (i) monetary policy changes a debtor's liquidity through credit and balance sheet channels, which directly affects their current repayment behavior; and (ii) monetary policy may affect a borrower's investment, production and profitability, thus changing their long‐term solvency. The paper also finds that the repayment behavior of productive borrowers is more susceptible to monetary policy than consumptive borrowers, and that the default behavior of borrowers in coastal provinces is more susceptible to monetary policy than of borrowers in inland provinces. These findings provide new evidence for understanding how monetary policy affects individual behavior and its transmission mechanisms.

The Effects of Social Injustice Shocks on Borrower Behavior and Digital P2P Lending

The Effects of Social Injustice Shocks on Borrower Behavior and Digital P2P Lending

Covid-19 Economic Downturn - The Implication for Corporate Debts and Recovery Actions in Nigeria

The novel coronavirus disease (code-named ‘COVID-19’) has taken the world by storm, spreading like a wildfire. Major cities around the world are in a lockdown as a result of which businesses have closed down. This portends a great danger for borrowers and lenders as incidences of Non-Performing Loans are on the increase. It has therefore become necessary to interrogate and forecast what the behavior of lenders and borrowers would and should be in dealing with disputes and litigation that would attend the end of COVID-19. What are the available legal options for creditors whose depositors funds may become intractable due to the COVID-19 pandemic? What are the options for lenders whose businesses are in near comatose? Should the lenders hit the court immediately the pandemic subsides? Should the lenders wait a bit to let the dust settle? What is the probative value of pleading frustration or force majeure? These are some of the questions this article sets out to answer.

Analytical study of the repayment behavior of borrowers in Datia District of Madhya Pradesh

Analytical study of the repayment behavior of borrowers in Datia District of Madhya Pradesh

Government Debt Maturity and Term Structure of Credit Spreads

We investigate how government borrowing behaviors influence private sectors by exploring the relationship between government debt maturity and credit term structures. Using individual corporate bonds data between 1987 and 2015, we find that a longer government debt maturity is associated with a steeper credit term structure in both the primary and secondary corporate bond markets. An instrumental variable approach and an exogenous event study help us establish a causality. Our findings are more pronounced among riskier corporate bonds, and the influences of Treasury bond supply on credit term spreads are more pronounced near the maturity where this supply shock originates, suggesting that the credit risk and the maturity clientele channels together drive our findings.

The Internal Logic of Poverty-Returning: Theory and Verification of Vulnerable Poverty Alleviation

Since the implementation of the accurate poverty alleviation policy, the number of poor people in China has been shrinking, but the phenomenon of returning to poverty also occurs from time to time. To ensure that everyone is out of poverty, preventing and eliminating poverty-returning after out of poverty must be the key work in the current stage of poverty alleviation. To this end, this paper discusses the reason why there is the phenomenon of poverty-returning after out of poverty as well as the temporary poverty reduction. This paper innovatively proposes the theory of vulnerable poverty alleviation to explain it, verifies the theory by empirical analysis, and further demonstrates how to prevent the problem of poverty-returning after out of poverty. This is not only a necessary measure to consolidate the existing achievements in poverty alleviation, and achieve the goal of building a well-off society in an all-round way, but also a practical problem that needs to be highly valued in consolidating the achievements in poverty alleviation after 2020.After the poor have been lifted out of poverty, when they are affected by other external events, they are likely to return to poverty again if lacking the buffering and protection of assets, vice versa. Therefore, the situation that the family transfers from poverty to non-poverty but with no assets or few assets is called vulnerable poverty alleviation in this paper. Then the paper uses the three rounds of micro-survey data from 2010 to 2014 provided by China Family Panel Survey（CFPS）to verify it. Firstly, the propensity score matching method is used to verify the effect of asset endowment on reducing the probability of returning to poverty. Then the conditional Markov model” is constructed to explore the impact of different types of asset endowment on the state of poverty alleviation—poverty-returning” under the general scenario and risk shock scenarios. Finally, the path that out of poverty but not return to poverty is discussed.The results indicate that there is a significant difference in the probability of returning to poverty among families with different asset endowment. The fewer assets a family owns, the more likely it is to return to poverty, so asset endowment can prevent the phenomenon of returning to poverty. Specifically, production assets, financial assets, self-use assets and human assets endowments can inhibit the occurrence of returning to poverty. Among them, the role of production assets is most significant, and asset endowment plays the most significant role in preventing families from returning from mild poverty alleviation to shallow poverty, and asset endowment will play a more important role in risk shock scenarios than the general scenario. The role of asset endowment will be weakened if there exists a perfect public service system and high welfare for a region or borrowing behavior for an individual. This shows that the perfect public service system and the higher transfer payment in the high welfare area also play the role of safety net”, replacing the role of assets in alleviating the phenomenon of returning to poverty.Therefore, this paper argues that the government should incorporate asset indicators into the dynamic adjustment system of poverty identification; meanwhile, it should further improve the public welfare system, fundamentally encourage poor families to engage in production and business activities, and implement skill training, which will help to consolidate the achievements of poverty alleviation.

How do macroprudential loan-to-value restrictions impact first time home buyers? A quasi-experimental approach

In this paper, we analyse the effect of the introduction of macroprudential limits on loan-to-value ratios on the borrowing behaviour of first-time-home-buyers in Ireland. Observing lending activity pre- and post- the unanticipated introduction of the regulations in 2015, we estimate the direct effect of the regulations on first-time-buyer leverage and house purchasing decisions. We exploit a unique provision in the macroprudential framework, that places different loan-to-value limits on properties above and below a fixed house price (€ 220,000), to determine the causal effect of the macroprudential measures on this group of borrowers. We find that LTVs fell by approximately 1.4 percentage points after the measures, with larger reductions recorded for high income borrowers. We also find that borrowers increased their downpayments in response to the regulations, with no change in the house price paid. However, findings differ across the income distribution, indicating the impact of wealth constraints on borrower behaviour. This research reinforces the importance of using granular data to understand the impact of loan-to-value regulations.

Is there the Pareto principle in public library circulation? A case study of one public library in Taiwan

The Pareto Principle, also known as the 80/20 rule is currently an important and popular management rule applied to marketing and customer relationship management (CRM). The rule indicates that the vital few causes inputs or efforts bringing the most results, outputs, or rewards. Analyzing circulation data to understand the usage status of library collections can help libraries comprehend their patrons’ behaviour. However, little research has been done to analyse circulation data of public libraries to reveal patrons’ usage behaviours. This paper aimed to analyse the circulation data generated by a municipality public library in Taiwan to gauge if the Pareto Principle manifested in this context. Subsequently, using bibliomining analysis, this research further identified vital patrons and their characteristics, as well as book-borrowed distributions to help analyse patrons' book borrowing behaviour to improve the efficiency of library management and library marketing as well as CRM. The circulation data of the public library follows the Pareto Principle, approximating to the 80/20 rule. Findings showed that when the accumulative percentage of patron is 24.7 percent, the accumulative percentage of borrowed books is 75.3 percent. The vital few patrons borrow the majority of the collections. This paper is the first study to reveal that the Pareto Principle could be found in circulation data of a public library in Taiwan. It could help libraries identify vital patrons and major collections, and improve the efficiency of their management and marketing activities in future. For other types of libraries, it would be interesting for us to explore the existence of the Pareto Principle further.