Table 9

Firm size: small firms vs large firms

Full sampleBy firm size
Small firmsLarge firms
(1)(2)(3)
ΔlnSALEt0.980*** (75.908)0.986*** (65.688)0.971*** (68.301)
ΔlnSALEt×Dt−0.133*** (−5.258)−0.120*** (−3.512)−0.128*** (−3.656)
ΔlnSALEt×TURNOVERt−0.014** (−2.184)−0.001 (−0.080)−0.013** (−2.113)
ΔlnSALEt×Dt×TURNOVERt0.013 (0.892)−0.059*** (−3.987)0.010 (0.699)
ΔlnSALEt×SMALLt0.009 (1.364)  
ΔlnSALEt×Dt×SMALLt0.051*** (3.647)  
ΔlnSALEt×TURNOVERt×SMALLt0.015* (1.643)  
ΔlnSALEt×Dt×TURNOVERt×SMALLt−0.077*** (−3.846)  
ControlYesYesYes
Year fixed effectYesYesYes
Firm fixed effectYesYesYes
Observations20,39210,20210,190
Adjusted R20.6770.6710.684

Note(s): This table presents the results of testing the impact of firm size on the relation between political uncertainty and asymmetric behavior of operating costs. The subscript t denotes the time index, while prefecture-city and firm indices are omitted for brevity. The dependent variable is ΔlnXOPR, the log-change in operating costs. Column (1) adds the key variable SMALL. SMALL is a dummy variable that takes the value of one for a small firm and zero otherwise. A firm is defined as small in year t if the total assets are below the median of all the firms in year t, and vice versa. Columns 2 and 3 report the results on the subsamples of small firms and large firms, respectively. ΔlnSALE is the log-change in sales. D is a dummy variable that takes the value of one if sales decrease, and zero otherwise. TURNOVER 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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