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

Table 5

Result of regression analysis of different estimation methods of the four groups.

	Group A		Group B		Group C
	(4) FE_Robust	(5) LSDV	(4) FE_Robust	(5) LSDV	(4) FE_Robust	(5) LSDV
lnRobot	0.108	0.108	0.194	−0.194	0.047	0.047
	(13.93)	(13.34)	(−20.59)	(−19.94)	(9.34)	(8.92)
lnFDI	−0.032	−0.032	0.021	0.021	−0.018	−0.018
	(−1.07)	(−1.03)	(0.29)	(0.28)	(−1.56)	(−1.49)
lnRD	0.029	0.029	0.172	0.172	0.018	0.018
	(0.76)	(0.73)	(4.18)	(4.04)	(1.06)	(1.01)
_Cons	2.717	3.082	1.401	1.166	2.592	3.237
	(12.01)	(13.82)	(2.51)	(1.84)	(31.15)	(40.29)
N	40	40	20	20	49	49
R^2	0.909	0.993	0.805	0.929	0.478	0.996
F	2.1e + 04	.	.	.	269.906	.

Notes. This table reports the results of the robustness test in Section 4.2. FE_Robust is FE using clustering robust standard and LSDV is least-squares dummy variables regression. The dependent variable is employment at the industrial level. 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.