scholarly journals Corporate Carbon Disclosure, Financing Structure and Total Factor Productivity: Evidence from Chinese Heavy Polluting Listed Corporates

2021 ◽  
Author(s):  
Sai Yuan ◽  
Xiongfeng Pan
Keyword(s):  
Total Factor Productivity ◽  
Mediating Effect ◽  
External Financing ◽  
Low Carbon ◽  
Factor Productivity ◽  
Disclosure Quality ◽  
Financing Structure ◽  
Financing Costs ◽  
Internal Financing

Abstract Low-carbon economy has become the current global economic development trend, and Corporate carbon disclosure has attracted more and more attention from scholars and investors. This paper creatively explores the mechanism of corporate carbon disclosure quality on total factor productivity with financing structure as a mediating variable. The content analysis method is used to construct a carbon disclosure evaluation index system that is suitable for Chinese companies. Through the mediating effect model and Sobel test, the internal mechanism of carbon disclosure quality affecting total factor productivity is analyzed, with Chinese heavy polluting listed corporates from 2015 to 2018 as research samples. The empirical results show that, Firstly, the Quality of carbon disclosure has a positive effect on the improvement of total factor productivity. The effect of monetary carbon disclosure quality on the improvement of total factor productivity is higher than that of non-monetary carbon disclosure quality. Secondly, the financing structure has a mediating effect on the quality of carbon disclosure and total factor productivity, and the mediating effect of internal financing capabilities is better than those of external financing costs. Finally, external financing costs and internal financing capabilities have mediating effects in both heterogeneous carbon disclosure quality and total factor productivity. The mediating effect of internal financing capabilities is significantly higher than the mediating effect of external financing costs. Meanwhile, the effect of monetary carbon disclosure quality on total factor productivity indirectly through internal financing capabilities is higher than that of non-monetary carbon disclosure quality.

scholarly journals Industrial Structure, R&D Staff, and Green Total Factor Productivity of China: Evidence from the Low-Carbon Pilot Cities

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shengqian Guo ◽  
Xue Tang ◽  
Ting Meng ◽  
Jincan Chu ◽  
Han Tang
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Structure Optimization ◽  
Mediating Effect ◽  
Green Economy ◽  
Low Carbon ◽  
Factor Productivity ◽  
Local Conditions ◽  
Carbon Policy ◽  
Using Data

Using data of 26 cities in China from 2004 to 2017, the green total factor productivity is investigated by the SMM-GML method. The corresponding empirical analysis is conducted with the DID model. This paper investigates the relation between low-carbon pilot policy (LCC) and green total factor productivity and discusses the mediating effect of industrial structure and the number of R&D staff (RDS). First, we find that LCC has a significant effect on pilot cities’ GTFP. And, it also promotes GTFP via industrial structure. Second, LCC can improve industrial structure optimization and realization, and industrial structure realization affects GTFP significantly, while optimization cannot. Third, LCC cannot attract more RDS, and RDS harms local GDFP because of talent misallocation. At last, the rate of GTFP presented different upward trends in the order of non-eastern cities and eastern cities. The effect of LCC on GTFP is significant in non-eastern cities, but not eastern ones, which clearly demonstrates the imbalanced development of the green economy. Therefore, the governments of eastern and non-eastern regions should adopt different measures based on local conditions in industrial structure transformation and recruitment and strengthen environmental regulations to make the effect of the low-carbon policy lasting and promote GTFP growth balance in all regions.

EVALUATING THE CONTRIBUTION OF TOTAL FACTOR PRODUCTIVITY ON AGRICULTURAL GROWTH IN AN GIANG PROVINCE

2018 ◽  
Vol 1 (29) ◽  
pp. 29-37
Author(s):  
Tan Van Truong
Keyword(s):  
Total Factor Productivity ◽  
Agricultural Production ◽  
Science And Technology ◽  
Agricultural Labor ◽  
Factor Productivity ◽  
Agricultural Growth ◽  
Regression Approach ◽  
Investment Capital ◽  
Agricultural Demand

By the growth regression approach, the research has identified that the investment capital contributed 1,939 and agricultural labor contributed 1,291 to the agricultural growth of An Giang province. More specifically, the contribution of TFP (Total Factor Productivity) to the agricultural growth in the period 2000 - 2004 was averagely 0,11%, in 2005 - 2010 was -5,03%, and in period 2011 - 2016 was 0,81%. The total factor productivity contributed to the agricultural growth slowly. In order to raise the contribution of TFP, the research represents 05 solutions including the increase of the effectiveness of using the investment capital, the increase of the quality of labor, the application of the science and technology into agricultural production, agriculturalrestructuring, and the increase of  agricultural demand.

scholarly journals Study on the Effect of Environmental Regulation on the Green Total Factor Productivity of Logistics Industry from the Perspective of Low Carbon

2019 ◽  
Vol 12 (1) ◽  
pp. 175 ◽  
Author(s):  
Zijing Liang ◽  
Yung-ho Chiu ◽  
Xinchun Li ◽  
Quan Guo ◽  
Yue Yun
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Jiangsu Province ◽  
Spatial Effects ◽  
Low Carbon ◽  
Method Of Moment ◽  
Factor Productivity ◽  
Logistics Industry ◽  
Forward Logistics ◽  
The Government

Under the low-carbon background, with the aid of the Malmquist–Luenberger SBM (Slack-based Measure) model of unexpected output, the green total factor productivity (GTFP) of the logistics industry in Jiangsu Province, China, was measured and decomposed in this study based on the reality and experience of logistics industry development in 13 cities in three regions of Jiangsu Province in the years 2006–2018 by taking resource consumption into the input system and discharged pollutants into the output system. It is concluded that the environmental regulation (ER) has a significant positive effect on the growth of the GTFP of the logistics industry, and technological progress has become an important endogenous force that promotes the GTFP of the logistics industry in Jiangsu Province. On this basis, a dynamic GMM (Generalized method of moment) model and a Tobit model were constructed to further study the possible temporal and spatial effects of ER on the GTFP of the logistics industry. The research results reveal that the ER can exert both promoting and inhibitory effects on the GTFP of the logistics industry, and there is a temporal turning point for the effects. Besides, the effects notably differ spatially and temporally. Finally, some policies and advice for the green sustainable development of the logistics industry were proposed. For example, the government and enterprises should pay attention to the green and efficient development of the logistics industry and dynamically adjust the ER methods. They should consider the greening of both forward logistics links and reverse logistics system in the supply chain.

Legal Capacity

2011 ◽  
Author(s):  
Timothy Besley ◽  
Torsten Persson
Keyword(s):  
Total Factor Productivity ◽  
Legal Capacity ◽  
Factor Productivity ◽  
Empirical Observation ◽  
Role Of Government ◽  
Doing Business ◽  
The Right ◽  
Productive Role

This chapter focuses on the productive role of government in improving the environment for doing business. Improvements in the performance of government are measured as total factor productivity and differences in income across countries can be explained by differences in the quality of their economic institutions. This makes it essential to understand why some countries make the right investments in legal institutions and deploy such legal capacity effectively. A running theme of the chapter is the possibility of a complementarity between the extractive (taxation) and the productive (supporting markets) roles of government. This is at the heart of the empirical observation that market development and state development move hand in hand. But the key insight from this is that we have to understand the incentives of a government to make investments to improve the workings of the economy.

Raising workers' quality is key to global productivity

2017 ◽  
Keyword(s):  
Total Factor Productivity ◽  
Computer Technology ◽  
Factor Productivity ◽  
Content Type ◽  
Information And Computer Technology ◽  
The 1960S ◽  
Investment Growth ◽  
Ageing Populations

Subject Total factor productivity. Significance The first estimates in the 1960s suggested that the growth of labour and capital inputs accounted for 20-30% of economic growth, implying that total factor productivity (TFP) improvements accounted for the remaining 70-80%. However, the skills embodied in labour and the technology embodied in capital can now be measured much more accurately. After these contributions are subtracted, the role of TFP in growth is reduced. Impacts Improvement in the quality of capital is closely tied to rising investment in capital, especially information and computer technology. If investment growth continues to slow, this will affect future output both through the volume of capital as well as its productive quality. Ageing populations and persistent ultra-low rates raise ‘secular stagnation’ fears; the future will depend on a better-educated workforce.

scholarly journals Corporate innovation and corporate governance: A study of US firms

2009 ◽  
Vol 6 (3) ◽  
pp. 342-359
Author(s):  
Saurav Roychoudhury ◽  
Alexei Egorov
Keyword(s):  
Corporate Governance ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Total Factor Productivity Growth ◽  
Shareholder Rights ◽  
Factor Productivity ◽  
Corporate Innovation ◽  
Governance Index ◽  
Technological Constraints

The paper relates corporate governance to firm’s total factor productivity growth of U.S. firms from 1990 to 2004. Given technological constraints, some firms are very efficient whereas others are not and some firms have much faster rates of innovation and productivity growth than others. Are these differences due to chance or are there some factors contributing to higher total factor productivity growth? In this paper, we find evidence that firms with stronger shareholder rights have higher total factor productivity growth. By employing the governance index compiled by Gompers, Ishii, and Metrick (2003), we determine that the effect of governance on productivity varies positively with the quality of corporate governance. Furthermore, this relationship is strongest among firms which have the strongest shareholder rights.

scholarly journals The Drivers of the Total Factor Productivity

2019 ◽  
Vol 85 (2) ◽  
pp. 12-20
Author(s):  
T. K. Kvasha
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Intangible Assets ◽  
Significant Proportion ◽  
High Tech ◽  
Factor Productivity ◽  
Patent Activity ◽  
Solow Model

The Total Factor Productivity (TFP) is now widely recognized as an important factor in both long-term economic growth and short-term growth fluctuations. Researchers of the International Monetary Fund came to the conclusion that the growth of the TFP was the most important long-term factor in raising the living standards. Therefore, the IMF and academics from different countries has been scrutinizing the reasons for the slowdown in TFP and investigating the underlying factors. The low rates of GDP grow in Ukraine call for finding the drivers, one of which is TFP growth. It raises the importance of analysis of the factors promoting this growth in Ukraine.  The purpose of this work is to define TFP drivers, which would be most effective for Ukraine. TFP drivers in foreign countries are analyzed, TFP dynamics for Ukraine is calculated by use of Solow model, and TFP drivers over 2000–2017 are determined.         The analysis of publications about TFP drivers at global level shows that they include: international transfer of knowledge and technologies, activities of small innovative fast-growing firms, the enhanced quality of quality of education, the increased expenditures on R&D and innovations, especially by business sector, the increased investments in intangible assets, the intensified patent activity, access of enterprises to lending. The TFP dynamics in Ukraine, calculated by the Solow model, is characterized by high growth rates by 2012, a sharp fall in 2013-2015, and a return to the growth path in 2016-2017, but, as in the whole world, by very moderate pace. The factors contributing to this return are capital investment in intangible assets, the increasing patent activity of Ukrainian researchers, the intensified innovation in the high-tech sector. Factors constraining the TFP and the contribution of innovation to economic growth are a significant proportion of technology transfer in the form of “know-how, agreements for the acquisition (transfer) of technologies”, which holds back the widespread introduction of cutting-edge technologies, and the reduction of funding for R&D and innovation. Further studies should be focused on searching for political decisions promoting implementation of structural reforms aimed to solve the existing problems and eliminate their consequences, especially in of the innovation and education field.

scholarly journals Does Low-Carbon City Construction Improve Total Factor Productivity? Evidence from a Quasi-Natural Experiment in China

2021 ◽  
Vol 18 (22) ◽  
pp. 11974
Author(s):  
Hongfeng Zhang ◽  
Lu Huang ◽  
Yan Zhu ◽  
Hongyun Si ◽  
Xu He
Keyword(s):  
Economic Development ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Progress ◽  
Scale Efficiency ◽  
Eastern Region ◽  
Low Carbon ◽  
Factor Productivity ◽  
City Construction ◽  
Low Carbon City

Low-carbon city construction (LCC) is an important strategy for countries desiring to improve environmental quality, realize cleaner production, and achieve sustainable development. Low-carbon cities have attracted widespread attention for their attempts to coordinate the relationship between environmental protection and economic development. Using the panel data from 2006 to 2017 of prefecture-level cities in China, this study applied the difference-in-differences (DID) method to analyze the effects of LCC on the total factor productivity (TFP) of the cities and its possible transmission mechanism. The results show significantly positive effects on TFP, but the effects on each component of TFP are different. Although the LCC has promoted technical progress and scale efficiency, it has inhibited technical efficiency. The accuracy of the results has been confirmed by several robustness tests. Mechanism analysis showed that the pilot policy of low-carbon cities has promoted technical progress and scale efficiency by technological innovation and the upgrading of industrial structure, but resource mismatches among enterprises have been the main reason for reduced technical efficiency. Regional heterogeneity analysis showed that the effects on TFP in the eastern region have been more significant than in the central and western regions. In the eastern region, they have promoted technical progress, while in the central and western regions, they have promoted technical progress and scale efficiency but hindered technical efficiency. This paper presents our findings for the effects of LCC on economic development and provides insightful policy implications for the improvement of technical efficiency in low-carbon cities.

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