Page 264 - Ebook HTKH 2024

Table 5. Effect of public administration conditional on industry type
Variable TEC1 TEC1 TEC2 TEC2

Environmental
governance -4.951*** -5.162*** -0.002*** -0.002***
(-13.76) (-12.93) (-12.70) (-12.16)
Business_dum 11.139*** 30.666*** 0.014*** 0.024***
(4.65) (14.53) (13.58) (23.08)
Environmental
governance
#business_dum 0.890 -1.360** -0.002*** -0.004***
(1.21) (-2.10) (-7.89) (-12.42)
LEV -14.648*** -0.006***
(-6.93) (-5.49)
SIZE 12.658*** 0.005***
(242.19) (187.44)
ROA 51.872*** 0.017***
(5.23) (3.40)
ROE 0.126 0.004*
(0.03) (1.70)
CASH 3.472 0.000
(0.49) (0.02)
Constant -228.132*** -567.431*** -0.093*** -0.237***
(-173.82) (-389.85) (-157.79) (-321.35)

Obs. 1,886 1,868 1,886 1,886
Year FE Yes Yes Yes Yes
Pseudo R2 0.158 19.63 13.30 13.32
This table examines the effect of public administration conditioning on industry
type. The dependent variable of the regressions alternatively represents one of two
corporate technology investment measures, TEC1 and TEC2. The independent variable

is variable in year t. X is a vector of control variables,

including Size, Leverage, ROA, ROE and Cash. To account for the impact of a firm’s

industry type, we introduce the dummy variable that equals one if firms belong to stock,
insurance and bank sections. Variable definitions and data sources of these controls are
presented in Appendix A. The continuous variables are winsorized at the top and bottom
1% of the sample distribution. Year-fixed effects are included unless otherwise stated.
The symbols ***, **, and * denote the statistical significance at 1%, 5%, and 10%,
respectively. Obs is the number of observations.
5. Conclusion

This paper delves into the relationship between public administration reform,
specifically in environmental governance, and corporate technology investment in

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