Optimizing Credit Gaps for Predicting Financial Crises: Modelling Choices and Tradeoffs

Credit gaps are good predictors for financial crises, and banking regulators recommend using them to inform countercyclical capital buffers for banks. Researchers typically create credit gap measures using trend-cycle decomposition methods, which require many modelling choices, such as the method used, and the smoothness of the underlying trend. Other choices hinge on the tradeoffs implicit in how gaps are used as early warning indicators (EWIs) for predicting crises, such as the preference over false positives and false negatives. We evaluate how the performance of credit-gap-based EWIs for predicting crises is influenced by these modelling choices. For the most common trend-cycle decomposition methods used to recover credit gaps, we find that optimally smoothing the trend enhances out-of-sample prediction. We also show that out-of sample performance improves further when we consider a preference for robustness of the credit gap estimates to the arrival of new information, which is important as any EWI should work in real-time. We offer several practical implications.

Bridging the Agriculture Credit Gap: A Case Study of the Farmer Entrepreneurship Program of Jollibee Group Foundation

Access to credit presents a distinct problem for smallholding farmers and lenders alike. As a consequence, in the Philippines—as in many other developing economies—a sizable “agriculture credit gap” exists. This paper explores whether it is possible to rethink existing credit arrangements to support inclusive development goals. Our observations are based on a unique in-depth case study of an interlinked financing arrangement in the Farmer Entrepreneurship Program (FEP). This program is managed by the corporate foundation of Asia’s biggest fast-food chain, Jollibee Foods Corporation (JFC). The lenders in this program are FEP partner-cooperatives that interlink credit, crop buying, and other interventions to enable smallholders to sell their products to JFC and other buyers. For inclusive interlinking to materialize, significant social investments are required from program partners. Using a progressive case study method, three subunits within the study explain how financing can be made available. We use these observations to draw out possible generalizations of financing mechanisms that may be used in other commodity chains. We identify partnerships, particularly long-term relationships, as indispensable requisites for institutional voids to be filled and financing to flow into rural areas. We recommend key government interventions, especially since some of the requisites are in the nature of collective or public goods.

Filling the Gap

Can fintech credit fill the credit gap in the consumer and business segments? There are few cross-country studies that explore this question. Focusing on marketplace lending, an important part of fintech credit, we use data for 109 countries from 2015 to 2017 to study the relationship between fintech credit to businesses and consumers and various aspects of financial development. Marketplace lending to consumers grows in countries where financial depth declines highlighting the role of fintech credit in filling the credit gap by traditional lenders. This result is particularly strong in low-income countries. In the business segment, marketplace lending expands where financial efficiency declines. Our findings show that low-income countries take advantage of the fintech credit opportunity in the consumer segment but face important challenges in the business segment.

An International Comparison on Excessive Credit Expansion, Credit Guarantee Programs and The Risks Arising

Crediting in the banking sector plays an important role in all developed and developing countries. For this reason, it is monitored continuously by public authorities and measures are taken to control credit supply in economic growth periods. On the other hand, in an economic slowdown, when banks are reluctant to increase their credit portfolio, public credit guarantee programs are put into use to increase the credit supply. In this study, a sample covering 26 advanced and emerging economies was analyzed, and the effects of credit gap, credit guarantees and economic growth on credits and arising credit risks were investigated. The findings show that both credits and non-performing loans, an important measure of credit risk, are affected by credit gap, credit guarantees, and economic growth. On the one hand, public credit guarantees positively affect economic growth. On the other hand, though they are widely used for supporting small and medium-sized enterprises, our findings suggest that such expansive credit policies might negatively affect the riskiness of the credit portfolios and soundness of the banking sector.

Empirical study of the relationship between credit cycles and changes in credit ratings

The purpose of this study is to identify relationships between changes in ratings and the impact of credit cycles on them. The following methodology was used: we built up an applied statistical probit-model of multiple-choice to determine ratings changes. Our model includes a credit gap indicator for assessing the impact of the credit cycle. Our empirical research also includes a review of the time changes in the ratings during a ten-year period for developed and developing countries. The results of our study show that credit ratings are not only affected by cyclical changes within the credit cycle, but also are delayed in its relation to the cycle. From a practical point of view, these results indicate the practical need to take into account various macroeconomic factors because of the impact of credit cycles for forecasting and risk management in financial markets. During the changes of credit cycles, the rating agencies consider the shifts in macrostructure and in valuation of parameters accordingly to the distribution and ratings proportion for investment and speculative ratings classes. The level of credit ratings and credit gap indicator are strongly influenced by two macroeconomic factors: GDP growth rates and credit spread, the last impact factor relates to the mechanism of monetary policy (as a narrow lending channel). In the end of the credit cycle and the stage of recession (downturn), which is marked by empirical evidence, large number of speculative credit ratings occur and the credit spread begins increase which leads to the rise of negative effects in financial markets.