I am following the work of Acemolug, Restrepo(2020). Trying to figure out the effect of adopting robot to labor market variables..
Main dependent variable is increase in real wage, and explanatory variable is index of adopting Robot called APR
I ran Panel IV with fixed effect(industry, time). I also added year dummy, and control variables like ratio of female workers
My problem is that when I include control variables like female rato, STATA shows me some unplausbly large Wald Chi2 Statistics...like 58903.17
Can this result simply be interpreted as the high goodness- of- fitness of this model? or is that related to lack of observations or so??
I attach the code i used and result of baseline Model and model of including control variable
Code:
xtivreg delta_wage (KoreanAPR = APR_WestEurope) i.year if year >= 2005, fe vce(robust)
xtivreg delta_wage (KoreanAPR = APR_WestEurope) i.year delta_female if year >= 2005, fe vce(robust) Array
Array
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