scholarly journals Productivity Changes in the Chinese Provincial Governments

2016 ◽  
Vol 4 (1/2) ◽  
pp. 73
Author(s):  
Guangqiong Yang
Keyword(s):  
Total Factor Productivity ◽  
Economic Reforms ◽  
Factor Productivity ◽  
Envelope Analysis ◽  
Dea Method ◽  
Data Envelope Analysis ◽  
The Government ◽  
The Relationship ◽  
Inputs And Outputs

This paper applies a Data Envelope Analysis (DEA) method to the measurements and evaluations of Chinese provincial governmental productivity. It defines operationally the inputs and outputs of the government and governmental productivity in terms of eight indicators, and calculates the changes in governmental productivity with the DEA method for the period of 1985 to 2003. It decomposes the total factor productivity (TFP) into efficient changes and technical changes, and illustrates the characteristics of the changes in governmental productivity from periods to periods, and analyzes theoretically the characteristic patterns. It compares the differences in changes of governmental productivity among the different regions. In the processes of analysis, we emphasize the effects of administrative and economic reforms on governmental productivity, and the relationship between governmental productivity and administrative and economic reforms.

scholarly journals Environmental Regulation, Enterprises' Bargaining Power, and Enterprises' Total Factor Productivity: Evidence from China

2021 ◽  
Author(s):  
Shuwang Yang ◽  
Chao Wang ◽  
Hao Zhang ◽  
Tingshuai Lu ◽  
Yang Yi
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Environmental Economics ◽  
Bargaining Power ◽  
Factor Productivity ◽  
Firm Level ◽  
Capital Cities ◽  
Provincial Capital ◽  
The Government ◽  
The Relationship

Abstract The relationship between environmental regulation and enterprises' total factor productivity (TFP) has been a hot topic in the field of environmental economics, but the conclusions are still mixed. Employing a sample of 14,110 firm-year observations in China from 2010 to 2018, our research explores whether and when environmental regulation could trigger firms, to enhance TFP. The available evidence leads us to cautiously conclude that: 1) Environmental regulation notably improves enterprises' TFP, the conclusion still holds after a series of robustness tests. 2) Enterprises' bargaining power significantly weakens the influence of environmental regulation on enterprises' TFP. 3) Compared with non-state-owned enterprises and non-heavy-polluting industries, environmental regulation has a greater impact on state-owned enterprises and heavy-polluting industries; higher executive compensation does not motivate firms to improve TFP; compared with enterprises headquartered in non-provincial capital cities, environmental regulation has a greater impact on enterprises' TFP in provincial capital cities. Overall, the findings of our research are extremely relevant for the government, investor, and enterprise's manager, this paper provides micro-firm-level evidence for the Porter hypothesis in practice in China.

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.

scholarly journals Research on Green Total Factor Productivity of Logistics Industry and its threshold effect of Environmental Regulation

2021 ◽  
Vol 235 ◽  
pp. 02022
Author(s):  
Wanchun Li
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Threshold Model ◽  
Intermediate Stage ◽  
Threshold Effect ◽  
Inhibitory Effect ◽  
Regulation System ◽  
Factor Productivity ◽  
Logistics Industry ◽  
The Government

This paper is based on the input-output panel data of logistics industry in 30 provinces and regions in China from 2005 to 2017, using nonparametric DEA model to evaluate the green total factor productivity of logistics industry, and build a panel threshold model to empirically test the nonlinear impact of environmental egulation. It is found that environmental regulation has a double threshold effect on green total factor productivity of logistics industry, the estimated threshold values are 89.85 and 211.27 respectively; when environmental regulation is at a low level below 89.85, environmental regulation has a positive effect of 2.09% on green total factor productivity of logistics industry, when environmental regulation is in the intermediate stage of 89.85 to 211.27, environmental regulation has a positive improvement effect of 6.41% on green total factor productivity of logistics industry; when environmental regulation is at a higher level than 211.27, environmental regulation has a negative inhibitory effect of 1.57% on green total factor productivity of logistics industry. Based on the empirical conclusion, this paper puts forward: First, using the performance assessment as the baton to urge the local government to establish an effective environmental regulation system; second, the government should plan to guide the green transformation and upgrading of the logistics industry to avoid “one size fits all” environmental regulation.

scholarly journals The Relationship Between Public Expenditures, Total Factor Productivity and Economic Growth: A Panel Data Analysis

2021 ◽  
Author(s):  
Remzi Can Yılmaz ◽  
Ahmet Rutkay Ardoğan
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Developing Economies ◽  
Panel Data Analysis ◽  
Statistical Significance ◽  
Data Availability ◽  
Public Expenditures ◽  
Annual Data ◽  
Factor Productivity ◽  
The Relationship

According to the economics literature, there are two main sources of economic growth. While the first of the resources is the accumulation of production factors, the other is the part of the output that cannot be explained by the amount of input used in production, in other words, the total factor productivity. The level of total factor productivity is measured according to how efficiently the inputs are used in the production process. In this study, the hypothesis that public spending affects real economic growth through total productivity is investigated. In the first stage, whether the changes in public expenditures affect the total factor productivity or not; if it does, to what extent and in what direction it has been tried to be revealed. In the second stage, the effect of total factor productivity on economic growth was examined and the statistical significance, direction and extent of the relationship between variables were investigated. Annual data were used in the study and the year range is 2000-2017. The sampling economies were selected according to data availability, and there are a total of 20 developed and developing economies. Research was conducted using multiple panel regression analysis. According to the findings, the relationship between public expenditures and total factor productivity is statistically significant. An increase in public expenditures reduces the total factor productivity. The relationship between total factor productivity and economic growth is statistically significant, and an increase in total factor productivity also increases economic growth. An increase in public expenditures affects economic growth negatively by reducing the total factor productivity.

scholarly journals The Relationship between Environmental Regulation and Green Total Factor Productivity in China: An Empirical Study Based on the Panel Data of 177 Cities

2020 ◽  
Vol 17 (15) ◽  
pp. 5287 ◽  
Author(s):  
Mingliang Zhao ◽  
Fangyi Liu ◽  
Wei Sun ◽  
Xin Tao
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Inflection Point ◽  
Factor Productivity ◽  
Positive Effects ◽  
Development Level ◽  
The Mean ◽  
The Relationship

Promoting the coordinated development of industrialization and the environment is a goal pursued by all of the countries of the world. Strengthening environmental regulation (ER) and improving green total factor productivity (GTFP) are important means to achieving this goal. However, the relationship between ER and GTFP has been debated in the academic circles, which reflects the complexity of this issue. This paper empirically tested the relationship between ER and GTFP in China by using panel data and a systematic Gaussian Mixed Model (GMM) of 177 cities at the prefecture level. The research shows that the relationship between ER and GTFP is complex, which is reflected in the differences and nonlinearity between cities with different monitoring levels and different economic development levels. (1) The relationship between ER and GTFP is linear and non-linear in different urban groups. A positive linear relationship was found in the urban group with high economic development level, while a U-shaped nonlinear relationship was found in other urban groups. (2) There are differences in the inflection point value and the variable mean of ER in different urban groups, which have different promoting effects on GTFP. In key monitoring cities and low economic development level cities, the mean value of ER had not passed the inflection point, and ER was negatively correlated with GTFP. The mean values of ER variables in the whole sample, the non-key monitoring and the middle economic development level cities had all passed the inflection point, which gradually promoted the improvement of GTFP. (3) Among the control variables of the different city groups, science and technology input and the financial development level mainly had positive effects on GTFP, while foreign direct investment (FDI) and fixed asset investment variables mainly had negative effects.

New Evidence on the Relationship Between Economic Freedom and Growth: A Panel Cointegration Analysis for The Case of OECD

2012 ◽  
Vol 12 (3) ◽  
pp. 1850263 ◽  
Author(s):  
Ekrem Erdem ◽  
Can Tansel Tugcu
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Total Factor Productivity ◽  
Economic Freedom ◽  
Global Financial Crisis ◽  
Oecd Countries ◽  
Cointegration Analysis ◽  
Factor Productivity ◽  
The Impact ◽  
The Relationship

The aim of this paper is to find a new answer to an old question “Is economic freedom good or not for economies?” which was refreshed after the Global Financial Crisis of 2008. For this purpose, the relationship between economic freedom and economic growth, and the relationship between economic freedom and total factor productivity in OECD countries were investigated by using panel data for the period of 1995-2009. Study employed the recently developed cointegration test by Westerlund (2007) and the estimation technique by Bai and Kao (2006) which account for cross-sectional dependence that is an important problem in the panel data studies. Although no significant relationship found between economic freedom and total factor productivity, cointegration analysis revealed that economic freedom matters for economic growth in OECD countries in the long-run, and estimation results showed that direction of the impact is negative.

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