我想做2020年创业板注册制改革对个股定价有效性的影响,
被解释变量为个股定价模型回归的调整R2,解释变量是个股波动率、换手率、非系统性风险、当日成交量
为短面板数据,n=638,T=267
现在已经用了面板回归,上面的变量都显著,用个体固定效应模型。
但是我需要检验注册制改革是否有影响,设改革前为0,改革后为1的虚拟变量event,前后时间都为半年,以及交乘项
能否继续用面板回归来检验,或者应该用其他方法?
如果可以,那这样是否存在稳健性问题,因为可能在注册制改革的时间点上,存在其他政策也会影响,我该如何排除其他政策可能影响的干扰?
下面是加入虚拟变量后混合回归后的结果
. reg ARsq2 Volatility NonSysRisk2 Turnover LNA event eventT eventNSR eventV eventLN,vce(cluster stock)
Linear regression Number of obs = 175,686
F(9, 657) = 486.97
Prob > F = 0.0000
R-squared = 0.8900
Root MSE = .03654
(Std. Err. adjusted for 658 clusters in stock)
------------------------------------------------------------------------------
| Robust
ARsq2 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Volatility | -1.111156 .0357144 -31.11 0.000 -1.181285 -1.041028
NonSysRisk2 | 3.921211 .1006518 38.96 0.000 3.723573 4.11885
Turnover | .0675141 .0282109 2.39 0.017 .0121196 .1229085
LNA | -.0065812 .0013201 -4.99 0.000 -.0091734 -.003989
event | -.1260986 .0252331 -5.00 0.000 -.1756457 -.0765514
eventT | -.0174338 .0260367 -0.67 0.503 -.068559 .0336914
eventNSR | -.5640672 .092941 -6.07 0.000 -.7465644 -.3815699
eventV | .2345098 .0341438 6.87 0.000 .1674657 .301554
eventLN | .002466 .0011216 2.20 0.028 .0002637 .0046682
_cons | .6831676 .0280631 24.34 0.000 .6280635 .7382717
------------------------------------------------------------------------------
. estimates store OLS
. test eventT eventNSR eventV eventLN
( 1) eventT = 0
( 2) eventNSR = 0
( 3) eventV = 0
( 4) eventLN = 0
F( 4, 657) = 17.43
Prob > F = 0.0000