Table 6

Instrumental variable analysis

First stageSecond stage
(1)(2)
Predicted_Divergence 5.109***
 (1.848)
IV_MCA0.324** 
(0.156) 
IV_RegionalESGcover0.008*** 
(0.002) 
Size0.0010.204***
(0.002)(0.013)
Lev−0.026***−0.382***
(0.008)(0.078)
ROE0.0000.009**
(0.000)(0.004)
Top10.020*−0.337***
(0.011)(0.087)
SOE0.0000.175***
(0.003)(0.026)
INST−0.020***−0.041
(0.007)(0.063)
Volatility−0.003−0.877***
(0.005)(0.051)
Volume−0.004**0.013
(0.002)(0.014)
HHI−0.001−0.477**
(0.029)(0.202)
Constant0.568***−5.801***
(0.041)(0.447)
Industry FEYesYes
Year FEYesYes
N20,92320,923
Adj. R20.0360.091
Under-identification test
Kleibergen–Paap rk LM statistic16.795 
p-value0.000*** 
Weak identification test
Cragg–Donald Wald F statistic15.652 
Over identification test
Sargan test (p-value)0.12 

Note(s): This table reports the instrument variable/2SLS regression results. Results for the first and second stage are reported in columns (1) and (2), respectively. The instrumental variables are IV_MCA, which is firm-level climate attention and IV_RegionalESGcover, which is the annual sample median number of rating agencies covering firms in the same city. The Kleibergen–Paap rk LM statistic, Cragg–Donald Wald F statistic and Sargan test also are shown. The control variables are the same as in our baseline model. See Appendix A for variable definitions. All continuous variables are winsorized at the 1% and 99% levels. Standard errors, clustered at the firm level, are reported in parentheses. ***, ** and * indicate significance at the 1%, 5% and 10% levels, respectively

Source(s): Authors’ own work

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