Table 10.

Spline regression around the event day for North China Provinces.

	Main Board				SME/GEM
	Coef.	SE	t-Stat		Coef.	SE	t-Stat
	(×100)	(×100)			(×100)	(×100)
${\Phi }_{10}$	−0.09	0.59	−0.15		−0.30	0.94	−0.32
${\Phi }_9$	−0.14	0.53	−0.27		0.53	0.93	0.57
${\Phi }_8$	−0.22	0.81	−0.27		−0.99	0.81	−1.22
${\Phi }_7$	−0.28	0.32	−0.86		−0.12	0.94	−0.13
${\Phi }_6$	−1.62	0.62	−2.61		−3.27	0.38	−8.63
${\Phi }_5$	−0.06	0.40	−0.15		−0.04	0.27	−0.16
${\Phi }_4$	−0.77	0.35	−2.24		−0.87	0.26	−3.32
${\Phi }_3$	0.51	0.62	0.82		−0.56	0.17	−3.34
${\Phi }_2$	0.71	0.44	1.61		2.03	0.83	2.46
${\Phi }_1$	−1.20	0.50	−2.43		−2.42	0.24	−10.10
$\beta \left(COVI{D}_{it}\right)$	−1.60	0.41	−3.94		−3.27	0.69	−4.71
${\Psi }_1$	0.65	0.41	1.58		1.34	0.38	3.48
${\Psi }_2$	1.53	0.31	4.92		2.03	0.69	2.92
${\Psi }_3$	−0.33	0.41	−0.82		−0.61	0.59	−1.04
${\Psi }_4$	−0.33	0.26	−1.27		−0.93	0.27	−3.47
${\Psi }_5$	−0.10	0.54	−0.19		−1.58	0.46	−3.45
${\Psi }_6$	−1.26	0.77	−1.65		−1.71	0.27	−6.36
${\Psi }_7$	0.96	0.76	1.25		0.67	0.66	1.01
${\Psi }_8$	0.34	0.50	0.69		2.13	0.27	7.90
${\Psi }_9$	0.07	0.38	0.18		−0.81	0.38	−2.11
${\Psi }_{10}$	1.48	0.46	3.23		2.33	0.69	3.36
Industry Fixed Effect	Yes				Yes
Province Fixed Effect	Yes				Yes
Adj. R-square (%)	0.67				1.25

Note: This table reports the spline 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. (3). 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 between Dec. 2th, 2019 and Feb 23rd, 2020.