Effect of Industrial Robots on Employment in China: An Industry Level Analysis

Table 7

Result of FE model by adding control variables for intervention.

	Group A	Group B	Group C
	(7) lnL	(7) lnL	(7) lnL
lnRobot	0.0876	−0.160	0.035
	(8.00)	(−2.05)	(1.78)
lnFDI	−0.0306	0.040	−0.026
	(−1.37)	(0.69)	(−1.26)
lnRD	−0.00840	0.199	0.016
	(−0.26)	(2.00)	(1.06)
lnWage	−0.132	−0.142	0.531
	(−0.56)	(−0.36)	(2.68)
lnVA	0.204	−0.121	−0.409
	(1.29)	(−0.40)	(−2.08)
_Cons	2.766	2.399	1.858
	(5.14)	(1.21)	(3.92)
N	40	20	49
R^2	0.916	0.765	0.493
F	86.743	13.561	11.119

Notes. This table reports the results of the robustness test in Section 4.2. The dependent variable is employment at the industrial level. We add wage and value-added (VA) in our model as control variables. All other variables are defined in Section 3.2. t statistics are reported in parentheses. , , and indicate significance at the 1%, 5%, and 10% levels, respectively.