Thesis_gd_final_vers.. - Vernimmen

crisis breaks out, are the exposure to construction and development loans and to commercial real
estate. Contrary to our hypotheses, the growth rate lagged by eight quarters is significant but a
higher growth rate decreases the level of non-performing loans, whereas we expected that higher
past growth would have been positively correlated to the level of non-performing loans. The R²,
which indicates the part of the variance of the dependent variable explained by the regression,
stands at 22.9%. It means that the bank strategic asset allocation explains 22.9% of the level of
non-performing loans. The rest could be explained by more precise indicators of asset quality. The
regression on net interest income, the profitability measure which is the most likely to be directly
impacted by the asset mix and the level of non-performing loans, is statistically significant. As for
Table 15: Dynamic regressions
Dynamic regression on non-performing loans
Variable Coefficient z-stat p-value
com_re_lo 1.21% 14.89 0.000
com_re_lo_cr 2.62% 49.35 0.000
res_re_lo 1.34% 17.79 0.000
res_re_lo_cr 0.60% 17.21 0.000
dvpt_re_lo -3.92% -39.97 0.000
dvpt_re_lo_cr 8.19% 95.93 0.000
cc_lo 2.73% 16.15 0.000
ci_lo 0.43% 4.36 0.000
agri_lo 1.37% 9.52 0.000
lag8_growth_cr -0.14% -5.12 0.000
intercept 0.90% 29.11 0.000
Dynamic regression on the net interest income
Variable Coefficient z-stat p-value
securities 0.23% 39.15 0.000
com_re_lo 0.76% 89.31 0.000
com_re_lo_cr -0.10% -21.34 0.000
res_re_lo 0.50% 62.11 0.000
res_re_lo_cr 0.04% 13.15 0.000
dvpt_re_lo 1.10% 111.71 0.000
dvpt_re_lo_cr -0.54% -68.96 0.000
cc_lo 1.55% 93.38 0.000
ci_lo 0.75% 75.15 0.000
agri_lo 1.11% 74.18 0.000
lag8_growth -0.03% -10.37 0.000
non_perf_lo -1.71% -79.86 0.000
intercept 0.44% 96.24 0.000
non-performing loans, the “crisis effect” variables for commercial real estate loans and
construction and development loans have a negative impact on the net interest income. On the
contrary, the crisis variable for residential mortgage has a very slightly positive coefficient which is
yet significant. The increasing level of non-performing loans is also a strong explanatory variable
to the fall of the net interest as bankruptcy approaches. The R² on this second regression is 26.1%.
As a conclusion, the two regressions support our hypothesis that a bank asset mix has an effect on
the failure likelihood as it has an impact on the asset quality (shown by our regression on the level
of non-performing loans) and on the level of the net interest income (shown by our second
regression on net interest income). Based on the regressions’ explanatory power we can also say
that other factors, measuring more precisely asset risk and asset quality, are likely to explain the
level of non-performing loans and the evolution of the net interest income.
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