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Financial Innovation

Table 12 Two-stage least squares regression

From: Excess stock returns and corporate environmental performance in China

 

First stage

Second stage

(1)

(2)

EAVERAGE

0.009***

 

(28.95)

 

ERANK

0.073***

 

(62.26)

 

LOGGREEN

 

0.046***

 

(9.41)

BETA

0.005***

− 0.002***

(4.12)

(− 3.48)

LOGSIZE

0.076***

− 0.008***

(155.53)

(− 16.27)

BM

0.112***

− 0.004***

(63.54)

(− 3.56)

MOM

0.002

− 0.001

(1.46)

(− 1.29)

ROE

0.010***

− 0.002

(3.14)

(-0.96)

INV

− 0.022***

0.002*

(− 11.92)

(1.88)

TURNOVER

− 0.019***

− 0.021***

(− 15.13)

(− 32.92)

F-test of instruments

1305.79

 

(p-value)

(0.00)

 

Sargan overidentification test

 

0.136

(p-value)

 

(0.71)

Constant

1.350***

− 0.244***

(92.17)

(− 24.53)

Year/month fixed effects

Y

Y

Observations

221,500

221,500

Adjusted R2

0.3730

0.3571

  1. This table reports the results of a two-stage least squares regression of the excess stock returns (RET) on corporate environmental performance (LOGGREEN) and controls with robust standard errors clustered at the firm level. The sample period is March 2014 to November 2021, and the unit of observation is a month. EAVERAGE is the industry average E-score for the first year in the sample. ERANK is a dummy variable that takes the value of 1 if the industry average E-score is higher than the median and 0 otherwise. All other variables are defined in Table 2. All regressions include year-month fixed effects. We use F-tests and the Sargan overidentification test to confirm the robustness of our instruments. *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively
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