| Title |
The convergence characteristics of China's carbon intensity: Evidence from a dynamic spatial panel approach |
| ID_Doc |
17252 |
| Authors |
Huang, JB; Liu, CH; Chen, SX; Huang, X; Hao, Y |
| Title |
The convergence characteristics of China's carbon intensity: Evidence from a dynamic spatial panel approach |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.scitotenv.2019.02.413 |
| Abstract |
In recent years, China's CO2 emissions have surged as the country's economy has expanded rapidly. Faced with mounting international and domestic pressures, China has made great efforts to curb CO2 emissions. To formulate targeted regional reduction plans, the features and characters of provincial carbon intensity should be carefully evaluated. In this study, the existence of convergence in China's carbon intensity and possible technological factors that may influence the convergence, are carefully investigated by building a united framework and employing dynamic spatial panel approach. The estimation results verify that there is significant spatial correlation in China's provincial carbon intensity. There is also evidence that the three different types of convergence (i.e., stochastic convergence, sigma-convergence and beta-convergence) exist during the sample period of 2000-2016. Moreover, among the technological factors of conditional beta-convergence, indigenous innovation activity is most critical. Not all foreign innovations stem from the inflow of foreign direct investment and trade exert a positive effect on carbon intensity reduction. Besides, it is estimated that the spatial spillovers effects from neighboring provinces are important to carbon intensity. (C) 2019 Elsevier B.V. All rights reserved. |
| Author Keywords |
Convergence; Carbon intensity; Technological factors; Dynamic spatial panel approach |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000462776800063 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
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