Table 11
Instrumental variable method.
(1) |
(2) |
(3) |
(4) |
|
---|---|---|---|---|
carbon1 | carbon1 | carbon1 | carbon1 | |
AI | −0.0012*** | −0.0002*** | −0.0045*** | −0.0004*** |
(0.000) | (0.000) | (0.001) | (0.000) | |
constant | −7.6178*** | −8.4958*** | ||
(0.037) | (0.028) | |||
CV | YES | YES | YES | YES |
FE | NO | NO | YES | YES |
N | 30561 | 23896 | 30554 | 23525 |
R2 | 0.0429 | 0.1257 | −0.2540 | 0.0654 |
Note: *, **, and ***denote statistical significance at the 10%, 5%, and 1% levels, respectively. CV stands for “Control Variables.” Columns (1)–(2) present the regression results when the proportion of employees in the computer industry and the lagged two-period AI level are used as instrumental variables, with the estimation method being OLS. Columns (3)–(4) present the regression results when the proportion of employees in the computer industry and the lagged two-period AI level are used as instrumental variables, with the estimation method being the fixed effects model. From the results, after addressing the endogeneity issue, the negative impact of the AI level of enterprises on carbon emission intensity remains valid.
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