Table 8.

COVID-19 and cross-sectional stock returns in North China.

	Main Board
	Mdl1				Mdl2
	Coef.	SE	t-Stat		Coef.	SE	t-Stat
	(×100)	(×100)			(×100)	(×100)
$\delta \left(PreCOVI{D}_{i,j}\right)$					−0.32	0.03	−9.90
$\beta \left(COVI{D}_{ijt}\right)$	−1.59	0.10	−5.69		−1.60	0.10	−5.81
$\gamma \left(PostCOVI{D}_{i,j}\right)$	0.33	0.03	10.10		0.32	0.03	9.75
Control Variables	Yes				Yes
Industry Fixed Effect	Yes				Yes
Province Fixed Effect	Yes				Yes
Adj. R-square (%)	0.17				0.21
	SME/GEM
	Mdl1				Mdl2
	Coef.	SE	t-Stat		Coef.	SE	t-Stat
	(×100)	(×100)			(×100)	(×100)
$\delta \left(PreCOVI{D}_{i,j}\right)$					−0.61	0.09	−6.93
$\beta \left(COVI{D}_{ijt}\right)$	−3.24	0.27	−11.99		−3.27	0.27	−12.07
$\gamma \left(PostCOVI{D}_{i,j}\right)$	0.33	0.09	3.76		0.31	0.09	3.52
Industry Fixed Effect	Yes				Yes
Province Fixed Effect	Yes				Yes
Adj. R-square (%)	0.37				0.42

Note: This table reports the baseline DID regression results of the coefficient estimates, standard errors (SE), $t$-statistics (t-stat) and adjusted R-square. Standard errors are grouped at the province level. The regression specification is shown in Eq. (1) and Eq. (2). We use the daily return series of Main Board firms and SME/GEM firms in the North China provinces as the dependent variable. The sample period is from Dec. 2nd, 2019 to Feb. 23rd, 2021.