Analysis of green total factor productivity in OECD and BRICS countries: based on the Super-SBM model

Abstract

To address the conflict between environmental constraints and fast economic growth, as well as to coordinate green growth strategies between developing and developed countries, improving green total factor productivity (GTFP) is an important way to accelerate the green and low-carbon transformation and get rid of the problems of environment and resources. Therefore, it is significant to analyze and compare the GTFP of Organization for Economic Cooperation and Development (OECD) and BRICS (i.e. Brazil, Russia, India, China and South Africa) countries. By applying the Super-SBM model, our study analyzes the distribution characteristics and the evolving trend of GTFP. The empirical results indicate that: (1) The GTFP of BRICS countries has significantly improved, but there is still a significant gap compared with OECD countries. (2) Brazil, Luxembourg and Norway's GTFP values are higher than others. (3) Among the BRICS countries, Brazil exhibits the highest value and China has the minimum value, which was far ahead in energy consumption and PM2.5. (4) In the analysis of OECD countries, Hungary displays the lowest average value and Luxembourg has the highest average value. As such, some policy implications improve green and low-carbon development.

The heterogeneous impacts of environmental technologies and research and development spending on green growth in emerging economies: the moderating role of financial globalization

“…Finally, according to the current research, the labor force, capital stock, and energy consumption are frequently used as inputs, and real GDP is used as the desired output; CO 2 emissions, SO 2 emissions, and wastewater are used as proxies for undesirable outputs (Kumar, 2006;Li and Lin, 2016;Sun, 2022). Considering the availability of data, we use the labor force, capital stock, and energy consumption as the inputs, real GDP as the desirable output, and CO 2 emissions as the undesirable output.…”

Evaluation and Spatial Correlation Analysis of Green Economic Growth Efficiency in Yangtze River Delta Urban Agglomeration

“…Zhang et al used the SBM model to measure the GEGE of countries along the Belt and Road [33]. Sun used the super-efficiency SBM model to measure the green total factor productivity in OECD and BRICS countries [34]. With the increasing role of urban agglomerations [35], few studies have been conducted on the GEGE measurement at the city or urban agglomerations level.…”

Will “Dual Control of the Amount and Intensity of Energy Consumption (DCEC)” Policy Increase Urban Green Competitiveness?

“…Early studies often directly used TFP indicators to represent GC levels [18]. In recent years, relevant studies have gradually adopted green TFP indicators that consider unexpected outputs to measure GC levels [35,36]. Considering the calculation method comprehensively, this article uses a directional distance function based on a relaxation value calculation and the Luenberger productivity index to calculate urban green total factor productivity (TFP) and uses this index to represent urban GC.…”