Table 5 Political uncertainty and...

Table 5

Political uncertainty and asymmetry of operating costs: a placebo test

	(1)	(2)	(3)
$Δ l n S A L E_{t}$	0.962*** (69.915)	0.964*** (70.168)	0.965*** (70.154)
$Δ l n S A L E_{t} \times D_{t}$	−0.145*** (−3.063)	−0.143*** (−3.013)	−0.153*** (−3.223)
$Δ l n S A L E_{t} \times T U R N O V E R 1_{t}$	0.017* (1.801)
$Δ lnSAL E_{t} \times D_{t} \times TURNOVER 1_{t}$	0.009 (0.443)
$Δ l n S A L E_{t} \times T U R N O V E R 2_{t}$		0.006 (0.373)
$Δ lnSAL E_{t} \times D_{t} \times TURNOVER 2_{t}$		−0.025 (−1.169)
$Δ l n S A L E_{t} \times T U R N O V E R 3_{t}$			0.008 (0.704)
$Δ lnSAL E_{t} \times D_{t} \times TURNOVER 3_{t}$			−0.037 (−1.063)
Control	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes
Observations	20,392	20,392	20,392
Adjusted $R^{2}$	0.777	0.777	0.777

	(1)	(2)	(3)
$Δ l n S A L E_{t}$	0.962*** (69.915)	0.964*** (70.168)	0.965*** (70.154)
$Δ l n S A L E_{t} \times D_{t}$	−0.145*** (−3.063)	−0.143*** (−3.013)	−0.153*** (−3.223)
$Δ l n S A L E_{t} \times T U R N O V E R 1_{t}$	0.017* (1.801)
$Δ lnSAL E_{t} \times D_{t} \times TURNOVER 1_{t}$	0.009 (0.443)
$Δ l n S A L E_{t} \times T U R N O V E R 2_{t}$		0.006 (0.373)
$Δ lnSAL E_{t} \times D_{t} \times TURNOVER 2_{t}$		−0.025 (−1.169)
$Δ l n S A L E_{t} \times T U R N O V E R 3_{t}$			0.008 (0.704)
$Δ lnSAL E_{t} \times D_{t} \times TURNOVER 3_{t}$			−0.037 (−1.063)
Control	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes
Firm fixed effect	Yes	Yes	Yes
Observations	20,392	20,392	20,392
Adjusted $R^{2}$	0.777	0.777	0.777

Note(s): This table presents the results of a placebo test. For each political uncertainty event, we assume that the event happens again in the next three years and set up a simulated dummy variable for each year. The three dummy variables are denoted as $T U R N O V E R 1$ ⁠, $T U R N O V E R 2$ ⁠, and $T U R N O V E R 3$ ⁠. The subscript $t$ denotes the time index, while prefecture-city and firm indices are omitted for brevity. The dependent variable is $Δ l n X O P R$ ⁠, the log-change in operating costs. $Δ l n S A L E$ is the log-change in sales. $D$ is a dummy variable that takes the value of one if sales decrease, and zero otherwise. $T U R N O V E R$ is a dummy variable that takes the value of one if either the city head or mayor is changed in year $t$ ⁠, and zero otherwise. All variables are defined in the Table A1. Regressions control for both firm and year fixed effects. Robust t-statistics reported in parentheses are based on standard errors clustered by firm. In this table, *, **, and *** denote statistical significance at the 10, 5, and 1% levels, respectively

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