The threshold effect test of human capital on the growth of agricultural green total factor productivity: Evidence from China

2021 ◽  
pp. 002072092110032
Author(s):  
Fang Liu ◽  
Ning Lv
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Threshold Effect ◽  
Factor Productivity ◽  
Coordinated Development ◽  
Green Production ◽  
Threshold Regression Model ◽  
The Relationship ◽  
Different Levels ◽  
Agricultural Material

This paper constructs a threshold regression model to empirically test the non-linear relationship between rural human capital and agricultural green total factor productivity (AGTFP) with provincial panel data during 1993–2018. The results show that there is a significant double threshold effect between rural human capital and AGTFP under different levels of agricultural material capital (AF)and agricultural economic development (AGDP). When AF and AGDP are at different levels, the relationship between rural human capital and AGTFP presents an inverse N-type trend or an inverted U-type trend. The nonlinear relationship between rural human capital and AGTFP has been verified. It is necessary to attach importance to the promotion of agricultural human capital to the growth of AGTFP. It is suggested to strengthen education on environmental protection and green production technology training for farmers, and urge them to widely adopt the production mode of mitigating climate warming. In addition, it is important to ensure the coordinated development of AF and rural human capital while enhancing the input of AF.

scholarly journals The Sources of Economic Growth in Nigeria: A Growth Accounting Approach

2019 ◽  
Vol 5 (1) ◽  
pp. 89
Author(s):  
Emeka Nkoro ◽  
Aham Kelvin Uko
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Total Factor Productivity ◽  
Technological Development ◽  
Correlation Coefficients ◽  
Physical Capital ◽  
Growth Accounting ◽  
Factor Productivity ◽  
Foreign Investments ◽  
The Relationship

The study investigated the sources of growth in Nigeria for the period 1960 to 2017 using the growth accounting framework of the standard neoclassical production function.Specifically, the study focused on evaluating the contribution of capital, labour and total factor productivity to economic growth in Nigeria. Additionally, in order to establish the relationship between capital, labour and total factor productivity, and economic growth, correlation coefficients between the variables were estimated. The results correlation analysis showed that the growths of capital, labour and total factor productivity were positively correlated with economic growth. Furthermore, the results from the growth accounting framework revealed that capital was found to be the major driver of economic growth in Nigeria during the entire period, 1961-2017. In the case of the sub-periods, capital was the major driver of economic growth in Nigeria during the first sub-period, 1961-1980. However, during the period, 1981-2000, labour was the major driver of economic growth, followed by capital while TFP growth contribution deteriorated as it was negative. Also, TFP was the major driver of economic growth during the period 2001-2017. Based on the foregoing, the study therefore recommends that, policies that encourage physical capital, human capital and technological development through domestic and foreign investments should be adopted, nurtured, sustained and intensified, noting that capital, human capital and technological development are key to economic growth and development.

Determinants of Total Factor Productivity in Mexico, Indonesia, Nigeria, and Turkey (1980–2014)

2018 ◽  
Vol 4 (2) ◽  
pp. 192-217 ◽  
Author(s):  
Phillip Akanni Olomola ◽  
Tolulope Temilola Osinubi
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Negative Relationship ◽  
Annual Data ◽  
Factor Productivity ◽  
Distributed Lag ◽  
Long Run ◽  
The World ◽  
Government Stability ◽  
Short Run

This study analyzed the macroeconomic and institutional determinants of total factor productivity (TFP) in the MINT (Mexico, Indonesia, Nigeria, and Turkey) countries during the period 1980–2014. Annual data covering the period between 1980 and 2014 were used. Data on real gross domestic product (real GDP), labor force, gross fixed capital formation, foreign direct investment (FDI), human capital, and inflation were sourced from the World Development Indicators published by the World Bank. Also, data on corruption, government stability, and law and order were obtained from the database of International Country Risk Guide. Panel autoregressive distributed lag (PARDL) regression technique was used to estimate the model. Results showed that TFP growth rate declined on average by 1.4 per cent and 1.8 per cent in Mexico and Turkey, respectively, while Indonesia and Nigeria did not experience productivity growth on the average. Results also showed that in the long run, human capital and government stability had positive and significant effects on TFP, while FDI and corruption had negative but significant effects on TFP. In the short run, there existed a significant negative relationship between TFP and inflation. However, the effects of human capital and corruption on TFP were positive and significant. The study concluded that human capital and corruption were key drivers of TFP in the MINT countries both in the long run and short run.

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.

The Dynamic Correlation Between Capital Deepening and Total Factor Productivity in China

2020 ◽  
Vol 24 (4) ◽  
pp. 524-531
Author(s):  
Wuliu Zhang ◽  
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Negative Impact ◽  
Positive Impact ◽  
Linear Structure ◽  
Physical Capital ◽  
Influence Coefficient ◽  
Factor Productivity ◽  
Capital Deepening ◽  
The Impact

The impact of capital deepening on total factor productivity (TFP) is a significant and controversial issue. Based on the calculation of relevant indicators, this study adopts a Bayesian time-varying parameter model, Bayesian quantile regression, and adaptive Bayesian quantile models for in-depth statistical analysis. TFP was found to have a complex non-linear structure, and physical and human capital deepening indicators show a significant upward trend. The deepening of physical capital has a negative impact on TFP, while the deepening of human capital has a positive impact. In the capital deepening structure, the level of TFP has been improved and its structure optimized. Primary human and non-production physical capital deepening has no significant effect on TFP, while secondary human capital deepening has some significant effects on TFP. Tertiary and productive human capital deepening of TFP present two different forms of significant effect: the influence coefficient of the former declines in the increasing quantile and the change is larger, while the latter has a stable negative impact. The results of this study provide insights in terms of the improvement of China’s productivity.

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