The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

Abstract

Forestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.

Carbon Emission, Air Pollution, and Total Factor Productivity: Evidence from Prefecture-Level Cities in China

“…Current research on the relationship between carbon emission and production efficiency is inconclusive. Zhong and Wang (2021) find that the impact of forestry total factor productivity on carbon emissions presents an inverted U-shaped curve. Y.…”

“…(4) We adopt the 2SLS method to minimize the endogeneity problem of the measurement variables of environmental regulation intensity and explore the relationship between China’s environmental regulation and TFP. We contribute to the literature by showing that both carbon emission and air pollution-induced environmental regulations have a positive effect on TFP, implying synergistic effects of the two while existing research on the relationship between carbon emission and production efficiency is inconclusive (Xian & Zhou, 2021; Zhong & Wang, 2021). Furthermore, carbon emission has a greater impact on TFP, so enhancing environmental regulation on carbon emission can better improve TFP.…”

Impacts of forest plantation programs on sectoral CO2 emissions regionally in New Zealand

“…The literature on the impacts of forest areas on CO 2 emissions is strong. Many studies using different methodologies, such as autoregressive distribution lag (Solaymani et al 2023), Chi-square probability distribution (Iordan et al 2018), and Global DEA-Malmquist (Zhong and Wang 2021), argued that forests have negative and significant effects on CO 2 emissions and expanding forest areas can reduce CO 2 emissions. Xu et al (2023) conducted a study utilizing cointegration regression and revealed that China's forests are expected to sequester 531-645 Mt of carbon by 2050 across various scenarios.…”

The Panel Spatial Econometric Analysis for Development of Green Intensive Agriculture Based on Edge Computing and Internet of Things

“…The long response time of the system and the consumption of computing resources are also tough problems. To help the central server reduce the pressure, improve the data processing efficiency, and ensure the security and timeliness of data transmission, EC has become one of the important improvement methods [ 27 ]. EC refers to the centralized processing and analysis of data on the edge side away from the central server.…”