Analyzing the impact of local government competition on green total factor productivity from the factor market distortion perspective: based on the three stage DEA model

Abstract From the perspective of factor market distortion, this paper explores the effect and internal mechanism of local government competition on green total factor productivity (GTFP). A three-stage DEA model was applied to measure the GTFP of 30 provinces from 2008 to 2017. Furthermore, the article analyses local government competition and factor market distortions influence on GTFP using the Spatial SDM model and mediation effect model. The statistical results reveal that the spatial correlation of GTFP is significantly present across Chinese different provinces. The growth of GTFP will be significantly inhibited by local government competition. Local government competition can indirectly restrict the improvement of GTFP through factor market distortion. Regional heterogeneity indicates that, in the eastern and central regions, local government competition does not significantly inhibit the growth of GTFP. Moreover, local government competition failed to restrain the improvement of GTFP through factor market distortion. However, in the western region, local government competition not only inhibited the growth of GTFP, but also inhibited the growth of GTFP by causing factor market distortion.

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Construction of Spatiotemporal Difference Image of the Impact of Financial Structure on China’s Total Factor Productivity

Computational Intelligence and Neuroscience ◽

10.1155/2021/7468866 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Yong Yu

Keyword(s):

Total Factor Productivity ◽

Evaluation Method ◽

Financial Structure ◽

Model Verification ◽

Factor Productivity ◽

Analysis Model ◽

Dea Model ◽

Dea Analysis ◽

Low Efficiency ◽

The Impact

My country’s current research on the influencing factors of total factor productivity has problems such as single evaluation method, low efficiency, and poor overall level in terms of evaluation methods and evaluation efficiency. Based on this, this study divides the financial structure into three traditional sections, banking, securities, and insurance, and uses the DEA model to study the temporal and spatial differences of the financial structure’s influence on the total factor productivity of the four major political and economic regions of China’s eastern, western, central, and northeastern China. First, establish a DEA model based on data mining algorithms, combine financial data comparisons over the years, to achieve a quantitative analysis of the financial structure’s impact on China’s total factor productivity, calculate financial efficiency, and then combine the DEA analysis data model with the grey correlation method. Analyze its internal influence rules, and design experiments for model verification analysis. The results show that the DEA analysis model can realize 8 iterations of data on the impact of financial structure on China’s total factor productivity, and its evaluation accuracy can reach more than 96.2%.

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Examining the Impact and Influencing Channels of Emission Trading Pilot Markets in China

11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES - Global Conference on Business and Social Sciences Proceeding ◽

10.35609/gcbssproceeding.2020.11(136) ◽

2020 ◽

Vol 11 (1) ◽

pp. 136-136

Author(s):

Qiong Wu ◽

Kanittha Tambunlertchai ◽

Pongsa Pornchaiwiseskul

Keyword(s):

Total Factor Productivity ◽

Co2 Emission ◽

Carbon Emission ◽

Emission Trading ◽

Chinese Government ◽

Synergy Effect ◽

Factor Productivity ◽

Plan Period ◽

Carbon Emission Trading ◽

The Impact

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference

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Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

Indian Journal of Economics and Development ◽

10.35716/ijed/19053 ◽

2020 ◽

pp. 18-30

Keyword(s):

Technical Efficiency ◽

Total Factor Productivity ◽

Technical Change ◽

Positive Impact ◽

Manufacturing Sector ◽

Factor Productivity ◽

Firm Level ◽

Employment Level ◽

The Impact ◽

Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

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Impact of Nanotechnology Patents on Green Development of China's Building Industry

Recent Patents on Nanotechnology ◽

10.2174/1872210513666191205123449 ◽

2020 ◽

Vol 14 (2) ◽

pp. 141-152

Author(s):

Xialing Sun ◽

Rui Zhang ◽

Xue Chen ◽

Pengpeng Li ◽

Jin Guo

Keyword(s):

Total Factor Productivity ◽

Inhibitory Effect ◽

Building Industry ◽

Factor Productivity ◽

The Sustainable Development ◽

Technological Support ◽

Green Development ◽

Panel Data Regression ◽

The Impact ◽

Building Engineering

Background: The sustainable development of the building industry has drawn increasing attention around the world. Nanomaterials and nanotechnology play an important role in the processes of energy saving and reducing consumption in the building industry. Nanotechnology patents provide key technological support for the green development of the building industry. Based on patent data in China, this paper quantitatively analyzed the application of nanotechnology patents in the building industry and the time trend, regional differences, and evolution of China's nano-patent applications in the building field. Methods: In this study, the environmental total factor productivity of the building industry considering carbon constraints was determined and then used as the dependent variable to measure the green development of the building industry. On this basis, a panel data regression model was constructed to determine the impact of nano-patents on the green development of the building industry. Results: Nanotechnology patents in the building industry can significantly improve total factor productivity. From the perspective of patent composition, technology-based patents that focus on substantial innovation can significantly promote the green development of the building industry, whereas strategic patents show a significant inhibitory effect. Regionally, the western region of China has the advantage of being less developed and thus more efficient than the central and eastern regions in the application of new nano-products. Finally, the research also showed a significant lag in the application of China's nanotechnology patents and low implementation efficiency. Conclusion: Nano patents can promote green development in the building industry, but there is room for improvement in the speed with which laboratory inventions are transformed into building engineering applications.

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Impact of Migrant Workers on Total Factor Productivity in Chinese Construction Industry

Sustainability ◽

10.3390/su11030926 ◽

2019 ◽

Vol 11 (3) ◽

pp. 926 ◽

Cited By ~ 5

Author(s):

Gui Ye ◽

Yuhe Wang ◽

Yuxin Zhang ◽

Liming Wang ◽

Houli Xie ◽

...

Keyword(s):

Construction Industry ◽

Total Factor Productivity ◽

Migrant Workers ◽

Annual Report ◽

Learning By Doing ◽

Construction Sector ◽

Factor Productivity ◽

The Sustainable Development ◽

Statistical Yearbook ◽

The Impact

Total factor productivity (TFP) is of critical importance to the sustainable development of construction industry. This paper presents an analysis on the impact of migrant workers on TFP in Chinese construction sector. Interestingly, Solow Residual Approach is applied to conduct the analysis through comparing two scenarios, namely the scenario without considering migrant workers (Scenario A) and the scenario with including migrant workers (Scenario B). The data are collected from the China Statistical Yearbook on Construction and Chinese Annual Report on Migrant Workers for the period of 2008–2015. The results indicate that migrant workers have a significant impact on TFP, during the surveyed period they improved TFP by 10.42% in total and promoted the annual average TFP growth by 0.96%. Hence, it can be seen that the impact of migrant workers on TFP is very significant, whilst the main reason for such impact is believed to be the improvement of migrant workers’ quality obtained mainly throughout learning by doing.

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The Impact of Participation in PPP Projects on Total Factor Productivity of Listed Companies in China

Sustainability ◽

10.3390/su13147603 ◽

2021 ◽

Vol 13 (14) ◽

pp. 7603

Author(s):

Xiangdong Liu ◽

Guangxi Cao

Keyword(s):

Total Factor Productivity ◽

High Speed ◽

Operation Mode ◽

Listed Companies ◽

Financing Constraints ◽

Eastern Region ◽

Time Varying ◽

Factor Productivity ◽

The Impact ◽

China’S Economy

The key to transforming China’s economy from high-speed growth to high-quality development is to improve total factor productivity (TFP). Based on the panel data of China’s listed companies participating in PPP (Public–Private Partnerships) projects from 2010 to 2019, this paper constructs the time-varying DID method to test the impact of participation in PPP projects on the company’s TFP empirically, explore the mechanism of the effect of participation in PPP projects on the company’s TFP, and then conduct heterogeneous analysis from four perspectives: region, industry, ownership form, and operation mode. The empirical results show that participation in PPP projects can significantly promote the growth of the company’s TFP, which mainly comes from the promotion of the innovation level of listed companies and the alleviation of financing constraints by participating in PPP projects. In addition, participation in PPP projects has a significant impact on TFP of listed companies in the eastern region, listed companies in the secondary and tertiary industries, state-owned listed companies, and listed companies participating in PPP projects under the BOT mode.

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