Non-linear relationship between energy consumption transition and Green Total Factor Productivity: A perspective on different technology paths

2021 ◽  
Author(s):  
Fangming Xie ◽  
Bing Zhang ◽  
Ning Wang
Keyword(s):  
Energy Consumption ◽  
Linear Relationship ◽  
Total Factor Productivity ◽  
Factor Productivity ◽  
Non Linear

scholarly journals Industry Efficiency and Total Factor Productivity Growth under Resources and Environmental Constraint in China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Feng Tao ◽  
Ling Li ◽  
X. H. Xia
Keyword(s):  
Energy Consumption ◽  
Total Factor Productivity ◽  
Environmental Efficiency ◽  
Pollutant Emissions ◽  
Productivity Index ◽  
Productivity Change ◽  
Factor Productivity ◽  
Energy And Environment ◽  
Capital Labor Ratio ◽  
Investment Capital

The growth of China's industry has been seriously depending on energy and environment. This paper attempts to apply the directional distance function and the Luenberger productivity index to measure the environmental efficiency, environmental total factor productivity, and its components at the level of subindustry in China over the period from 1999 to 2009 while considering energy consumption and emission of pollutants. This paper also empirically examines the determinants of efficiency and productivity change. The major findings are as follows. Firstly, the main sources of environmental inefficiency of China's industry are the inefficiency of gross industrial output value, the excessive energy consumption, and pollutant emissions. Secondly, the highest growth rate of environmental total factor productivity among the three industrial categories is manufacturing, followed by mining, and production and supply of electricity, gas, and water. Thirdly, foreign direct investment, capital-labor ratio, ownership structure, energy consumption structure, and environmental regulation have varying degrees of effects on the environmental efficiency and environmental total factor productivity.

The impact of external debt on total factor productivity and growth in HIPCs: non-linear regression approaches

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sisay Demissew Beyene ◽  
Balázs Kotosz
Keyword(s):  
Total Factor Productivity ◽  
Threshold Model ◽  
External Debt ◽  
Seemingly Unrelated Regression ◽  
Complete Analysis ◽  
Threshold Values ◽  
Factor Productivity ◽  
Content Type ◽  
Non Linear ◽  
The Impact

Purpose The purpose of this study is to provide an empirical analysis of the impact of external debt on total factor productivity (TFP) and growth along with the TFP channel through which external debt affects the growth of heavily indebted poor countries (HIPCs). Design/methodology/approach This study uses panel data econometrics; basically, the seemingly unrelated regression (SUR) and alternative non-linear (panel threshold) models. For robustness check, it also uses panel-corrected standard errors, feasible generalized least squares and SUR (using alternative variables). Findings External debt significantly reduces both TFP and growth. Besides, it confirms that the relationship between external debt and TFP and gross domestic product growth is non-linear. Further external debt can affect the growth of HIPCs through the TFP channel. However, the threshold model result reveals weak evidence of threshold values although there are some threshold values of 67 and 54 for TFP and growth models, respectively. Originality/value To the best of the authors’ knowledge, this is the first study on most concerned countries (HIPCs) that shows a detailed and complete analysis of the TFP channel and the impact of external debt on growth. Thus, it provides appropriate and sound policies that consider the unique characteristics of the countries. Unlike most previous findings, this study does not support an inverted U-shape relationship between external debt and growth. Further, it provides insights into the relationships among TFP, external debt and growth. Moreover, it considers basic panel econometric tests like cross-sectional dependence, uses a non-linear simultaneous equations model along with the alternative non-linear model and is supported by different robustness checks.

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