Slow Debt, Deep Recessions

Business credit lags GDP growth by about one year. This contributes to high leverage during recessions and slow deleveraging. We show that a model in which firms use risky long-term debt replicates this slow adjustment of firm debt. In the model, slow-moving debt has important effects for real activity. High levels of firm debt issued during expansions are only gradually reduced during recessions. This generates an adverse feedback loop between high default rates and low investment and thereby amplifies the downturn. Sluggish deleveraging slows down the recovery. (JEL E23, E32, E44, G31, G32)

P2P Lending platforms in Malaysia: the awareness among young adults

Background - Since 2016, the Securities Commission (SC) in Malaysia has given licenses to only eleven P2P lending platforms. Such lending platforms are expected to disrupt the lending services of traditional lenders in the coming years. However, being still in their infant stages, it is essential to know the extent to which such platforms are made known to potential investors out there. This study examines the extent to which young adults are aware of Malaysia's eleven P2P lending platforms. Methods - A sample of 65 undergraduate students majoring in finance and accounting was used for this pilot study. An online questionnaire was designed with three main parts: demographic, financial literacy, and P2P lending awareness. Results - Findings show that more than half of respondents in the sample are not aware of P2P lending platforms in Malaysia. Most of the respondents are financially literate to certain degrees. Those aware of their presence underestimated the potentially high level of their default rates and misunderstood that investor would be fully protected by such platforms when a loan default. Conclusions -The study's findings have shed light on the current awareness of P2P lending platforms among Malaysian young adults, potential investors of such platforms in the coming years.

Social ties, access to loans, and loan repayments in savings and loan associations: evidence from rural Tanzania

PurposeInstitutional structures of rural savings and loan associations influence their performances. One of the guiding principles for defining clear group membership boundaries is by setting rules on who has access. Social ties is a prominent requirement for membership. The objective of the current study is to provide quantitative evidence on the role of social ties membership criteria for the performance of saving and loan associations.Design/methodology/approachA cross-sectional survey was conducted in July–August 2019 comprising 48 associations in 13 villages in the Iringa District of Tanzania. In the current study, the authors use two indicators to measure the social ties between members, namely social closed association (the association applies criteria to accept only members who are relatives, friends or from the same hamlet) and physical distance (the fraction of members from other villages).FindingsThe authors find that associations are diverse both in terms of social ties, physical distance and performance, even in a small homogeneous region like Iringa District. Providing loans more easily to members with social ties has a negative relationship with loan repayment rates. Associations applying the social closeness criteria experience higher default rates than those not applying. The default rates become even worse when the fraction of member members from other villages increases in the socially tied associations.Practical implicationsPhysically distant members are more likely to default as they perceive less social pressure in an association with socially tied members. Development practitioners and policy makers should integrate the potential implications.Originality/valueThe authors provide empirical evidence on the relevance of social ties on credit access and repayment in savings and loan associations, using a novel multi-level data on financial performance in the context of community-based finance organizations in rural areas.

Modelling Credit Risk: Evidence for EMV Methodology on Portuguese Mortgage Data

ABSTRACTTraditional credit risk models failed during the recent financial crisis and revealed weaknesses in forecasting and stress testing procedures. One of the reasons for this failure was the fact that they did not include lifecycle and macroeconomic adverse selection effects. In this article, we assess the applicability of the Exogenous-Maturity-Vintage (EMV) models to study the determinants of default rates. We obtain and examine the exogenous, maturity and vintage curves from a dataset of Portuguese mortgage data. We show that the exogenous, maturity and vintage curves follow the expected behavior, and, we identify and discuss a set of explanatory variables.

Stress tests in Hungarian banking after 2008

The 2008 crisis highlighted the importance of using stress tests in banking practice. The role of these stress tests is to identify and precisely estimate the effect of possible future changes in market conditions on capital adequacy and profitability. This paper seeks to show a possible methodology to calculate the stressed point-in-time probability of default (PD) parameter. The presented approach contains a linear autoregressive distributed lag model to determine the connection between the logit of default rates and the relevant macroeconomic factors, and uses migration matrices to calculate PDs from the forecasted default rates. The authors illustrate the applications of this methodology using the Hungarian real credit portfolio data.

Building the business case for green affordable housing

The emerging business-driven case for green affordable housing reveals six drivers of profitability: 1) access to international green finance flows for better financing terms; 2) minimized incremental cost through early planning; 3) faster sales through market differentiation; 4) savings on utility bills for owners and renters; 5) lowered default rates and superior collateral value for green mortgages; and 6) fiscal and non-fiscal incentives from local or national governments. Additionally, fiscal and non-fiscal incentives from local or national governments can further catalyse the market. Case studies from several emerging markets show that the right combination of government incentives (including non-fiscal policies), education and technical assistance to developers (including a no-cost option), and green finance (including green bonds and green mortgages) can transform housing markets. In order to reflect the total life-time cost of ownership, the concept of affordability in housing should include the impact of resource-efficiency and resilience on the costs and risks of ownership.

The Impact of the Sharing Economy on Household Bankruptcy

Powered by digital technologies, many peer-to-peer platforms, or what is called the sharing economy, have emerged in the past decade. Although the impact of the sharing economy has received considerable attention over the past few years, extant research has not fully documented the impact of the sharing economy on consumers, workers, industry, or society as a whole. In this study, we exploit the geographical and temporal variation in Uber’s entry to examine its impact on the personal bankruptcy rate as well as on other consumer credit default rates. We empirically document the changes in personal bankruptcy filings after Uber’s entry, and show that personal bankruptcy filings under Chapter 7 experience a drop of 0.047 per 1,000 people after Uber enters a county, which translates to a 3.26% reduction in quarterly bankruptcy filings. Uber’s entry also leads to a reduction in Chapter 13 personal bankruptcy filings, but to a smaller degree (0.018 cases per 1,000 people per quarter). We check the validity of our estimates using business bankruptcy filings, which we find are uncorrelated with Uber’s entry.

Corporate stress and bank nonperforming loans: Evidence from Pakistan

Using detailed administrative Pakistani credit registry data, we show that banks with low leverage ratios are both significantly slower and less likely to recognize a loan as nonperforming than other banks that lend to the same firm. Moreover, we find suggestive evidence that this lack of recognition impedes loan curing, with banks with low leverage ratios reporting significantly higher final default rates than other banks for the same borrower (even after controlling for differences in loan terms). Our empirical findings are consistent with the theoretical prediction that classifying a nonperforming loan is more expensive for banks with less capital.

The Effects of the Brazilian Economic Recession of 2014-2016 on the Default Credit Card and in Private Label Card in the Food Retail

This study explores the effects of the Brazilian recession from 2014 to 2016 on the default of market credit cards and Private Label cards in food retail in a comparative way, through econometric analysis. The research evaluates the credit card default response in the market and, also, Private Label cards, after simulating shocks in macroeconomic variables such as Gross Domestic Product, wages, and unemployment rate, among others, through the application of an autoregressive vector model (VAR model). The data, on a monthly basis, were collected at the Central Bank of Brazil, the Brazilian Institute of Geography and Statistics and at a company in the private label card market. In addition, precedence tests are applied in order to check if there was any causality “in the sense of Granger” on the default of the market credit card and the Private Label card. Among the results found, it was possible to identify that the default rates of the credit card in the market and of the Private Label have different behaviors, from the simulations of the impulse response functions to the identification of the variables that precede them, being that the default of the Private Label card preceded a higher number of variables when compared to the default of credit cards in the market.

Promises and pitfalls of digital credit: Empirical evidence from Kenya

Digital credit is a recent innovation that raises hopes of improving credit access in developing countries. However, up until now, empirical research on the extent to which digital credit actually reaches people who are otherwise excluded from conventional credit markets and whether increased credit access is sustainable or threatened by high default and blacklisting rates is very scarce. Using representative data from Kenya, this article shows that digital credit increases borrowing opportunities, including for people less likely to otherwise have credit access in the conventional credit markets. However, we find that digital credit borrowing is also responsible for 90% of all blacklistings, which is partially driven by higher default rates in the digital credit market but also by a higher probability that digital credit defaults lead to blacklisting of the borrower, compared to defaults in other credit markets.