3.4. Empirical Model
We describe the regression model for the main test of H1. The regression models for cross-sectional tests are described in Section 5. To test H1, we apply the multiple regression model as follows:CAR = β0 + β1CIPHT + β2PRO_CASE + β3SIZE + β4ROA + β5CURR + β6R&D + β7LOSS+ β8LEV + β9OPCF + β10TURN + β11CEO_AGE+ β12CEO_COM + β13CEO_TEN+ β14CEO_DUA + Week FE + Industry FE + Province FE + ε(2)  where CAR refers to our two types of accumulative abnormal return (CAR [−1, 1] and CAR [−2, 2]), CIPHT is an indicator variable that equals one if there have been provincial new COVID-19 cases for at least six consecutive days including the current day and zero otherwise. Based on H1, we suppose a negative coefficient of CIPHT.
Model (2) contains several determinants of accumulative abnormal return. Considering that provincial accumulated COVID-19 cases would affect the investors’ risk assessment, we add PRO_CASE into our model. PRO_CASE is the six-day mean value of the provincial ratio of the daily accumulated confirmed COVID-19 cases to the resident population. Moreover, along with prior studies, we control the firm attributes that will affect abnormal return [39,55,56]. SIZE is the natural logarithm of total assets; ROA is the return on assets; CURR is the current ratio; R&D is the ratio of R&D expenses to sales; LOSS is an indicator variable that equals one if the firm suffered a loss and zero otherwise; LEV is the leverage ratio of total liabilities to total assets; OPCF is the ratio of the firm’s operating cash flow to total assets; TURN is the asset turnover ratio. In addition, following prior studies [55,57,58,59], we add CEO attributes that will affect the market reaction. CEO_AGE is the age of the firm’s CEO; CEO_COM is the ratio of the firm’s CEO compensation to the net income; CEO_TEN is the tenure of the firm’s CEO that is defined as days of CEO’s tenure divided by 365; CEO_DUA is an indicator variable that equals one if the firm’s CEO holds a concurrent post in other work units and zero otherwise. Finally, we add week fixed effects, industry fixed effects, and province fixed effects. Appendix A presents detailed variable definitions.