Table 4.

COVID-19 Case Origin Disclosure and Insurance Take-up Incorporating Demographic Differences

This table examines whether the impact of case origin disclosure on insurance take-up is due to the demographic differences of the user base of the social media app among prefectures. Ratio of New Users Above 60 and Ratio of New Female Users capture the proportion of daily newly registered users above 60 and the proportion of daily newly registered female users in a prefecture city. Disclose (t-1) continues to have a significant impact on insurance take-up when demographic differences are controlled for. Each observation refers to a prefecture-day combination. Robust standard errors in parentheses are clustered at prefecture cities. All regression models include a constant and its estimates are not tabulated for brevity. *** p < 0.01, ** p < 0.05, * p < 0.1.

	(1)	(2)	(3)
Y=	lnPolicies	lnPremiums	ln(Premium Per Policy)
Disclose (t-1)	0.043***	0.069***	−0.018
	(0.014)	(0.017)	(0.026)
lnConfirmed (t-1)	0.045***	−0.033***	−0.057***
	(0.010)	(0.010)	(0.015)
lnDead (t-1)	0.024	−0.019	0.087
	(0.042)	(0.034)	(0.054)
lnProvConfirmed (t-1)	−0.001	0.015	−0.073***
	(0.006)	(0.009)	(0.022)
Ratio of New Users Above 60	0.034	0.988***	1.141
	(0.025)	(0.283)	(1.137)
Ratio of New Female Users	0.086***	0.502***	−0.574**
	(0.015)	(0.075)	(0.246)
Prefecture FEs	Y	Y	Y
Day FEs	Y	Y	Y
Observations	9003	9003	8895
Adjusted R-squared	0.756	0.885	0.516