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This study aims to investigate the factors that drive housing loan default in India based on unique micro-level data drawn from a public sector bank's credit files with a national presence in India. The authors address endogeneity in the loan to value ratio (LTV) while deciphering the drivers of default.

The study uses a probit regression approach to analyze the relationship between the probability of default and the explanatory variables. The authors introduce two instrumental variables to address the issue of endogeneity. The authors also add state-level demographic and several other control variables, including an indicator variable that captures the recent regulatory change. The authors’ analysis is based on 102,327 housing loans originated by the bank between January 2001 and December 2017.

The authors find that addressing the endogeneity issue is essential to specify default drivers, especially LTV, correctly. The nature of employment, gender, socio-religious category and age have a distinct bearing on housing loan defaults. Apart from the LTV ratio, the other key determinants of default are the interest rate, frequency of repayment, prepayment options and the loan period. The findings suggest that the population classification of branch location plays a significant role in loan default. The authors find that an increase in per capita income and an increase in the number of employed people in the state, which reflects borrowers' ability to pay by borrowers, reduce the probability of default. The change in the regulatory classification of loan assets by the Reserve Bank of India did not bear the main results.

The non-availability of the house price index in analyzing the default dynamics in the Indian housing finance market for the period covered under the study has constrained our analysis. The applicability of the equity theory of default, strategic default, borrowers' characteristics and personality traits are potential research areas in the Indian housing finance market.

The study's findings are expected to provide valuable inputs to the banks and the housing finance companies to explore and formulate appropriate strategic options in lending to this sector. It has highlighted various vistas of tailor-making housing loan product offerings by the commercial banks to ensure and steady and healthy growth of their loan portfolio. It has also highlighted the regulatory and policy underpinnings to ensure the healthy growth of the Indian housing finance market.

The study provides a fresh perspective on the default drivers in the Indian housing finance market based on micro-level data. In our analysis, the authors find clear evidence of endogeneity in LTV and argue that any attempts to decipher the default drivers of housing loans without addressing the issue of endogeneity may lead to faulty interpretation. Therefore, this study is unique in recognizing endogeneity and has gone deeper in identifying the default drivers in the Indian housing market not addressed by earlier papers on the Indian housing market. The authors also control for the regulatory changes in the Indian housing finance market and include state-level control variables like per capita GDP and the number of workers per thousand to capture the borrowers' ability to pay characteristics.

This study aims to formulate a behavioural credit scoring models for Indian small and medium enterprises (SME) entrepreneurs using certain behavioural and psychological constructs. Two separate models are built which can predict the credit default and wilful default of the borrowers, respectively. This research was undertaken to understand whether certain psychological and behavioural factors can significantly predict the borrowers’ credit and wilful default.

A questionnaire survey was undertaken by SME entrepreneurs of two Indian states, i.e. Uttar Pradesh and Maharashtra. The questionnaire had two dependent variables: wilful default and credit default and nine independent variables. The questionnaire reliability and validity were ensured through confirmatory factor analysis (CFA) and further a model was built using logistic regression.

The results of this study have shown that certain behavioural and psychological traits of the borrowers can significantly predict borrowers’ default. These variables can be used to predict the overall creditworthiness of SME borrowers.

The findings of this research indicate that using behavioural and psychological constructs, lending institutions can easily evaluate the credit worthiness of those borrowers, who do not have any financial and credit history. This will enhance the capability of financial institutions to evaluate opaque SME borrowers.

There are very few numbers of studies which have considered predicting the credit default using certain psychological variables, but with respect to Asian market, and especially India, there does not exist a single significant study which has tried to fulfil such research gap. Also, this is the first study that has explored whether certain psychological factors can predict the wilful default of the borrowers. This is one of the most significant contributions of this research.

This paper aims to study the data on losses on mortgage insurance in the Dutch housing market to find the key drivers of the probability of loss. In 2013, 25 per cent of all Dutch homeowners were “under water”: selling the property will not cover the outstanding mortgage debt. The double-trigger theory predicts that being under water is a necessary but not sufficient condition to predict mortgage default. A loss for the mortgage insurer is the result of a default where the proceedings of sale and the accumulated savings for postponed repayment of the principal associated to the loan are not sufficient to repay the loan.

For this study, the authors use a data set on losses on mortgage insurance at a national aggregate level covering the period from 1976 to 2012. They apply a discrete time hazard model with calendar time- and duration-varying covariates to analyze the relationship between year of issue of the insurance, duration, equity, unfortunate events like unemployment and divorce and affordability measures to identify the main drivers of the probability of loss.

Although the number of losses increases over time, the number of losses relative to the active insurance is still low, despite the fact that the Dutch housing market is the world’s most strongly leveraged housing market. On average, the peak in loss probability lies around a duration of four years. The average loss probability is virtually zero for durations larger than 10 years. Mortgages initiated just prior to the beginning of the financial crisis have an increased loss probability. The most important drivers of the loss probability are home equity, unemployment and divorce. Affordability measures are less important.

Mortgage insurance is available for the lower end of the market only and is intended to decrease the impact of risk selection by banks. The analysis is based on aggregate data; no information on individual households, like initial loan-to-value and price-to-income ratios; current home equity; and unfortunate events, like unemployment and divorce, is available. The research uses averages of these variables per calendar year and/or duration. Information on repayments of insured mortgages is missing.

This paper is the first to describe the main drivers of losses on insured mortgages in The Netherlands by using loss data covering two housing market crises, one in the early 1980s and the current crisis that started in 2008. Much has changed between the two crises. For instance, prices have risen steeply as has household indebtedness. Furthermore, alternative mortgage products have increased in popularity. Focusing a study on the drivers of mortgage losses exclusively on the current crisis could therefore be biased, given the time-specific circumstances on the housing market.

The authors examine the optimal consumption decisions of households in a micro-founded framework that introduces endogenous default. They study default in the context of a two-period process, assuming three non-overlapping steps of non-payment: delinquency, non-performing loans and bankruptcy (default).

In their model, the authors extend the analysis of loan default to two periods and include agent heterogeneity by considering also saving households. In the optimization problem, the authors obtain first-order conditions for borrowers who do not repay all of their loans (comparing them to those who fully repay them) and also for savers. In addition, by using nonlinear Generalized Method of Moments (GMM), they obtain consistent estimates of the household preference parameters and present the impulse responses of borrowers' consumption to demand shocks.

The authors derive an augmented consumption Euler equation for borrowers, which is a function inter alia of an expected default factor. They estimate this equation and find non-negligible differences in preference parameters relative to values reported in the literature. Further, an ordering by size of the household discount factors is provided empirically. Finally, the impulse responses of borrowers' consumption to a demand shock are found to last more for borrowers who do not fully repay their debts.

This work represents a promising line of research by introducing default in one of the basic components of DSGE models, making the latter more appropriate for analyzing monetary and macro-prudential policies.

The primary purpose of this paper is to review and critique Taleb's notion of black swan blindness for a subset of the broader field of financial economics – the search for capital adequacy rules for financial institutions who invest in residential mortgages. This search entails the analysis and prediction of extreme events in housing and mortgage markets.

The focus of this paper concerns efforts to assess the likelihood and consequences of extreme and consequential economic events prior to their occurrence. The goal is to assess the criticism offered by Taleb that economists overstate the understanding of extreme events. One piece of evidence consists of a case study of the literature and policies regarding capital adequacy for financial institutions who invest in residential mortgages. The other is a review of recent literature about the crisis that offers similar conclusions.

The evidence suggests that the criticism is valid. The case study reviews a number of areas in which the search for capital adequacy reflected the traits of black swan blindness as described by Taleb. The review of the recent literature about the crisis highlights a number of papers that reach similar conclusions. These include high level overviews of the literature on the crisis, e.g. Lo, a number of papers that specifically focus on housing and mortgage markets, and some very recent work about agent based modeling and complexity theory presented at the 2012 ARES meetings.

The conclusion suggests a number of ways in which economists can combat the potential of black swan blindness is our search for extreme events. One suggestion is to combat the error of confirmation with ongoing testing. Combating overly simplistic narratives can also be addressed by listening more carefully to the criticisms by people outside the field. Pay more attention to silent evidence by having more substantial and ongoing consumer testing of new products, more work to identify best practices, and more resources to enforce lending laws. Finally, more attention needs to be focused upon assumptions in the models that are based upon limited empirical evidence and, if found later to be false, may lead to dire outcomes.

These include more and ongoing evaluation of stress tests. New rules to adjust capital requirements over the business cycle are consistent with the suggestions of the paper. Economists need to spend more time exploring and learning from outliers in the models.

The recent crisis has been driven by a wide variety of factors from within many sectors and agents. The outcome has been a major problem for people in many sectors and regions of the economy. The hope is that economists can do a better job in the future to help policymakers and others be more prepared for the potential of extreme events in the hopes of avoiding them in the future or at least reducing their likelihood and damage caused by them.

The paper draws upon a wide variety of literature to establish its main points. Central to it is a review of an issue on which the author had substantial experience – academic and professional – and that also played a major role in the crisis – inadequate capital for an extreme downturn in house prices.

The purpose of this article is to examine the effects that dynamic incentives and the borrowing histories of clients of informal lending institutions have on loan repayment performance, in particular, the extent to which multiple borrowing and progressive lending affect the repayment of loans.

The paper uses a data set of 835 borrowers drawn from an informal lending institution in Tanzania. Descriptive analysis and econometric models are used to test the developed hypotheses.

Whereas clients with multiple loans are associated with poor loan repayment, progressive lending contributes to positive repayment outcomes. Multiple borrowers face increased debt levels and thereby an increased inability to meet their repayment obligations; in contrast, progressive lending by building up a lender–client relationship helps clients to obtain higher loans with a minimum amount of screening.

This was a cross-sectional study based on a sample of individual clients drawn from a single institution. However, since the majority of clients had also taken out loans with other financial institutions, the sample is considered to be representative.

A client’s past repayment performance and multiple loan history must be assessed so that multiple borrowing can be prevented and credit absorption capacity can be gauged more accurately. The repeated nature of the interactions and the threat to cut off any future lending (if loans are not repaid) can be exploited to overcome any information deficit.

This study was conducted in a context in which the degree of information sharing was low and institutional access to clients’ credit histories was limited. It contributes knowledge on how lenders minimise the risk flowing from the ex ante information gap and moral hazards arising from the ex post information gap.

This study aims to investigate the determinants of homeowners’ planned holding periods. Real estate market is known for displaying buying and selling behavior that does not conform to traditional economic theories such as rational expectation or expected utility. Mounting evidence of anomalous observations appear to be supported by other theories, such as prospect theory, which in particular helps explain the disposition effect – sellers are too quick to sell when prices are climbing and hold on to properties longer when prices are plummeting. While this evidence is widely documented in housing studies based on data on realized holding periods (i.e. ex post), this study explores factors that may motivate homeowners to alter their expected holding horizons (i.e. ex ante) to form new preferred holding periods that may be shorter or longer than those planned during house search.

The empirical study uses data collected from two cross-section surveys of recent homebuyers in rising and declining housing markets in Southern California in 2004-2005 and 2007-2008, respectively.

The empirical results demonstrate that in addition to the financial characteristics of the recent homebuyer, the characteristics of the buying experience – non-monetary, such as the realized search duration, and monetary, such as perception of negative or positive premium paid for the house relative to its market value – have a statistically significant effect on the holding horizon revision. The data strongly indicate that the perception of having overpaid increases the likelihood of upward revision of the original holding horizon. This effect is stronger in the declining than in the rising market – a crucial finding that mirrors the disposition effect.

This study sheds new light on what may contribute to the disposition effect in housing markets that has not yet been investigated in past literature. The novel approach here is to look at how different house price environments may affect homeowners’ holding periods ex ante when they begin, rather than ex post when already realized.

The paper aims to explore the optimal strategies of inventory financing when the risk-averse retailer has different objectives, in the presence of multi-risk, i.e. demand risk, non-operational risk and retailer's strategic default risk.

This paper develops an inventory financing model consisting of a bank and a risk-averse retailer with strategic default. This paper considers two scenarios, i.e. the capital-constrained retailer cares about its profit or firm value. In the first scenario, the bank acts as a Stackelberg leader determining its interest rate, and the retailer acts as a follower determining its pledged quantity. In the second one, the bank capital market is perfectly competitive. Lagrange multiplier method is adopted to solve the optimization.

The optimal strategies in inventory financing scheme in two scenarios are derived. Only when the initial stock is relatively high, the retailer pledges part of the initial stock. Retailer's risk aversion reduces its pledged quantity and performance. The strategic default reduces its profit. When it is relatively high, the bank refuses to offer the loan.

Analytical inventory and financing strategies are specified to help retailers and banks to better understand the interaction of finance and operations management and to better respond to multi-risk.

New results and managerial insights are derived by incorporating partially endogenous strategic default and risk aversion into inventory financing, which enriches the interfaces of operations management and finance.

The chapter studies strategic default using an experimental approach.

The experiment considers a stochastic asset process and a loan with no down-payment. The treatments are two asset volatilities (high and low) and the absence and presence of social interactions via a direct effect on the subject's payoff.

I demonstrate that (i) people appear to follow the prediction of the strategic default model quite closely in the high asset volatility treatment, and that (ii) incorporating social interactions delays the strategic default beyond what is considered optimal.

The study tests adequately the strategic default using a novel experimental design and analyzes the neighbor's effect on that decision.