Unsystematic Risk Factors and Mortgage Non- Performing Loans in Kenya: Evidence from Commercial Banks

Commercial banks face severe challenges relating to their processes due to variations in the financial system. Identifying methods for reducing mortgage defaults and reducing the level of nonperforming loans is very important. Mortgage defaults occur because of complex factors. The amounts of mortgage non-performing loans depend on unsystematic risk factors which have an effect on mortgage loans of commercial banks. The stronger the effect of such factors, the less useful is diversification across a large number of borrowers and the stronger are the fluctuations in portfolio losses over time. The study looked at unsystematic factors and mortgage non-performing loans in Kenya’s commercial banks. Annual panel secondary data spanning from 2014 to 2019 was obtained from the Central bank of Kenya, Banking Supervision report and Kenya National Bureau of Statistics. The six year period was chosen because of availability of Mortgage secondary data. A panel fixed effects regression model was employed to address the objective of this study. The fixed effects panel regression model results indicated that capital asset ratio and lending rate had negative and statistically insignificant effect on Mortgage non-performing. Loans to deposit ratio and bank size results indicated a positive and statistically significant effect on mortgage non-performing loans implying that loans to deposit ratio and bank size affects mortgage non-performing loans in Kenya’s commercial banks. ROA results indicated a negative but statistically significant effect on mortgage non-performing loans. The study recommended enactment of internal policies by banks in regard to unsystematic factors in order to minimize the surge in mortgage non-performing loans especially in Kenya.

Default Option Exercise over the Financial Crisis and beyond*

We document changes in borrowers’ sensitivity to negative equity and show heightened borrower default propensity as a fundamental driver of crisis period mortgage defaults. Estimates of a time-varying coefficient competing risk hazard model reveal a marked run-up in the default option beta from 0.2 during 2003–06 to about 1.5 during 2012–13. Simulation of 2006 vintage loan performance shows that the marked upturn in the default option beta resulted in a doubling of mortgage default incidence. Panel data analysis indicates that much of the variation in default option exercise is associated with the local business cycle and consumer distress. Results also indicate elevated default propensities in sand states and among borrowers seeking a crisis-period Home Affordable Modification Program loan modification.

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.

Markov-switching impacts of housing-market expectations on credit markets

Purpose The purpose of this paper is to investigate linkages between households’ expectations and credit markets in the housing crisis. Design/methodology/approach In the Markov-switching framework, the sample period is classified into high- and low-impact regimes based on impacts of expectations on default rates, and the good-time-to-buy (GTTB) index is chosen to proxy for expectations toward the housing-market dynamics. Findings The results suggest that in high-impact regimes, optimistic expectations are substantially associated with lower defaults for all default rates analyzed, and second mortgage defaults are more sensitive to households’ expectations than first mortgage defaults. In low-impact regimes, the GTTB index significantly influences composite and first-mortgage default rates, but its impact is insignificant for second mortgage and bankcard default rates. Originality/value The results provide compelling evidence that households’ expectations play more important roles in credit markets in turmoil periods.