TY - JOUR
T1 - Investigating the impact of agricultural informatization on the carbon shadow price
AU - Meng, Yuan
AU - Shen, Zhiyang
AU - Štreimikienė, Dalia
AU - Baležentis, Tomas
AU - Wang, Songkai
AU - Zhang, Yunlong
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/3/15
Y1 - 2024/3/15
N2 - The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China.
AB - The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China.
KW - Agricultural informatization
KW - Carbon shadow price
KW - Data envelopment analysis
KW - Sustainable agricultural development
UR - https://www.scopus.com/pages/publications/85187228790
U2 - 10.1016/j.jclepro.2024.141330
DO - 10.1016/j.jclepro.2024.141330
M3 - Article
AN - SCOPUS:85187228790
SN - 0959-6526
VL - 445
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 141330
ER -