COVID-19 pandemic risk and probability of loan default: evidence from marketplace lending market

Financial Innovation

Table 10 COVID-19 risk and the likelihood of loan default: Robustness tests for government intervention

Variables	DV = LOANSTATUS
Variables	(1)	(2)	(3)
Panel A: Ordered logit model
PANDEMIC_DUMMY	− 0.165*** (0.010)
DAILY_CASES		0.007*** (0.000)
DAILY_DEATHS			0.074*** (0.001)
Loan originator individual effects	Yes	Yes	Yes
Controls	Yes	Yes	Yes
LR chi2	90,191.487	60,621.580	59,476.467
Prob > chi2	0.000	0.000	0.000
Pseudo-R-squared	0.189	0.213	0.221
N	288,356	212,917	212,917

Variables	DV = ONLYDEFAULTS
Variables	(1)	(2)	(3)
Panel B: Only default loans as dependent variable
PANDEMIC_DUMMY	0.687*** (0.007)
DAILY_CASES		0.007*** (0.000)
DAILY_DEATHS			0.061*** (0.001)
Loan originator individual effects	Yes	Yes	Yes
Controls	Yes	Yes	Yes
LR chi2	54,149.904	39,331.896	37,516.142
Prob > chi2	0.000	0.000	0.000
Pseudo-R-squared	0.150	0.160	0.153
N	814,872	503,153	503,153

Table reports the results for two panels. Panel A reports the findings of ordered logit regression analysis for the loan status (LOANSTATUS) with the sample consisting of only unresolved loans. The dependent variable is an ordered dependent variable that takes one of the six values (current, in grace period, 1–15 days late, 16–30 days late, 31–60 days late and 60+ days late). Panel B reports the logit regression findings with only the default loans (ONLYDEFAULTS) as the dependent variable. The dependent variable takes the value of 1 if the loan is classified as default or buyback and 0 otherwise. All model specifications employ robust standard errors in parentheses (*p < 0.10, **p < 0.05, ***p < 0.01)