Table 3

Endogeneity test results

VariableIVMultiple fixed effects
(1)(2)
Fned36.699***0.302*
(3.51)(1.72)
Size0.145−0.062**
(1.34)(−2.46)
Lev0.914−0.282*
(1.64)(−1.70)
Growth−0.407*0.038
(−1.78)(1.12)
Age−0.376*−0.020
(−1.88)(−0.19)
ROA3.240**−0.267
(2.10)(−0.97)
Board1.355**−0.056
(2.07)(−0.56)
Indep2.009−0.106
(1.07)(−0.32)
Dual2.656***0.024
(3.60)(0.83)
Mshare1.628***−0.070
(3.64)(−0.62)
FM−23.743***−0.132
(−3.26)(−0.67)
Child0.365**−0.034
(2.27)(−1.20)
HT−0.155−0.000
(−0.94)(−0.74)
Law−0.054*−0.010
(−1.70)(−1.04)
YearYY
IndustryYN
FirmNY
Year-IndustryNY
Cons−6.2214.138***
(−1.59)(7.20)
N1,1291,129
Kleibergen-Paap rk LM statistic16.947*** (0.000) 
Cragg-Donald Wald F statistic16.672 
R2/Pseudo R20.774

Note(s): This table reports the results of the endogeneity test. Column (1) shows the second stage of the IV regression results of the effect of family non-executive directors on robot adoption. Meanwhile, I show the Kleibergen-Paap rk LM statistic and Cragg–Donald Wald F statistic in this table. Column (2) shows the result of the multiple fixed effects. We report t-statistics in parentheses. All models include year and industry-fixed effects. *, ** and *** indicate two-tailed statistical significance at the 10%, 5% and 1% levels, respectively. All variables are defined in  Appendix

Source(s): Table by authors

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