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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.