scholarly journals Research on Total Factor Productivity and Influential Factors of the Regional Water–Energy–Food Nexus: A Case Study on Inner Mongolia, China

2019 ◽  
Vol 16 (17) ◽  
pp. 3051 ◽  
Author(s):  
Chen ◽  
Ding ◽  
Wang ◽  
Yu
Keyword(s):  
Total Factor Productivity ◽  
Inner Mongolia ◽  
Influential Factors ◽  
Government Support ◽  
Factor Productivity ◽  
Tobit Regression ◽  
Negative Effects ◽  
Lower Efficiency ◽  
Positive Effects ◽  
Regional Water

With the supply of water, energy and food facing severe challenges, there has been an increased recognition of the importance of studying the regional water–energy–food nexus. In this paper, Inner Mongolia, including 12 cities in China, was selected as a research case. A super-efficiency slack based measure (SBM) model that considered the undesirable outputs was adopted to calculate the regional total factor productivity (TFP) and the Malmquist–Luenberger index was used to investigate the change trend of the TFP from 2007 to 2016 based on understanding the water–energy–food nexus. Finally, influential factors of the TFP were explored by Tobit regression. The results show that the 12 Inner Mongolia cities are divided into higher, moderate and lower efficiency zones. The higher efficiency zone includes Ordos, Hohhot, Xing’an, and Tongliao, and the lower efficiency zone includes Chifeng, Xilin Gol, Baynnur, Wuhai and Alxa. There is a serious difference in TFP between Inner Mongolia cities. During the study period, the TFP of the water–energy–food nexus in Inner Mongolia cities shows a rising trend, which is mainly driven by the growth of technical progress change. However, the average ML values of the lower and moderate efficiency zones were inferior to the higher efficiency zone in six of the ten years, so the difference between Inner Mongolia cities is growing. According to the Tobit regression, the mechanization level and degree of opening up have positive effects on the TFP, while enterprise scale and the output of the third industry have negative effects on the TFP. Government support does not have any significant impact on the TFP. Finally, suggestions were put forward to improve the TFP of the water–energy–food nexus in Inner Mongolia cities.

scholarly journals The Heterogeneous Impacts of Human Capital on Green Total Factor Productivity: Regional Diversity Perspective

2021 ◽  
Vol 9 ◽  
Author(s):  
Hang Xiao ◽  
Jialu You
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Capital Accumulation ◽  
Positive Influence ◽  
Human Capital Accumulation ◽  
Factor Productivity ◽  
Tobit Regression ◽  
Positive Effects ◽  
Heterogeneous Effects ◽  
Fiscal Spending

That human capital improves the efficiency of Green Total Factor Productivity has been established in research fields, but the heterogeneous effects of human capital on GTFP and its sustainable mechanisms are unclear. This study examines the effects of human capital accumulation, fiscal spending on education, and innovation on GTFP efficiency under spatial and temporal diversity. Employing panel data from 30 provinces from 2001 to 2018 in China, we analyzed the dynamic and static efficiency of GTFP in different regions by three-stage data envelopment analysis (DEA). The heterogeneous effects of human capital on GTFP were explored through Tobit regression. Results reveal that the average value of GTFP efficiency is an inverted U-shape and the presence of significant t geography differences. Human capital accumulation and fiscal spending on education have positive effects on GTFP efficiency; however, innovation negatively affects it. At the same time, marketization growth decreases the positive influence of human capital and education on GTFP efficiency. While, this effect was not observed regarding innovation, the implication of these results concerning the human capital heterogeneous effects of GTFP efficiency in a different geographic context. Establishing a fair and transparent system can reduce the endowments gap and effectively promote GTFP efficiency in developing countries.

scholarly journals Does capital drain reduce total factor productivity growth in developing countries?

2020 ◽  
Vol 2020 (2) ◽  
pp. 53-75
Author(s):  
Halit Yanikkaya ◽  
Abdullah Altum
Keyword(s):  
Total Factor Productivity ◽  
Developing Nations ◽  
Factor Productivity ◽  
Outward Fdi ◽  
Negative Effects ◽  
Full Sample ◽  
Positive Effects ◽  
Tfp Growth ◽  
Business Environments ◽  
Developed Nations

This study investigates the effects of foreign direct investment (FDI) and royalties and licence fees (RLF) on total factor productivity (TFP) growth of about 90 countries for the period 2003-2011 for both inward and outward variables. The estimates for the full sample indicate that while inward FDI stocks have no significant impact, outward FDI stocks reduce TFP growth. While none of the RLF measures have any significant effects, imports and exports have significantly positive effects on TFP growth for the full sample. Outward FDI stocks and RLF payments are estimated to have negative effects on TFP growth for developing nations. Moreover, both RLF receipts and payments are found to have a positive effect on TFP growth in developed nations. To stimulate TFP growth further, developing nations should improve their domestic business environments and find ways to keep investments at home

scholarly journals Effects of Higher Education Levels on Total Factor Productivity Growth

2019 ◽  
Vol 11 (6) ◽  
pp. 1790 ◽  
Author(s):  
Jie Liu ◽  
Chao Bi
Keyword(s):  
Higher Education ◽  
Total Factor Productivity ◽  
Doctoral Education ◽  
Spillover Effect ◽  
Chinese Government ◽  
Economic Sustainability ◽  
Factor Productivity ◽  
Negative Effects ◽  
Positive Effects ◽  
Tfp Growth

China is facing challenges to sustainable economic growth. Higher education of Chinese residents can affect total factor productivity (TFP) growth and hence has an influence on economic sustainability. However, currently, there is limited literature on the nexus between higher education and TFP in China. Therefore, this paper empirically analyzes the heterogeneous and spatial effect of higher education on the regional TFP growth using a dynamic spatial econometric model with provincial panel data from 2003 to 2016. The results indicate that different levels of higher education have significant effects on TFP growth and are mainly reflected in the spatial spillover effect. Bachelor and doctoral education (particularly doctoral education) demonstrated significant positive effects, whereas the technical school and master education had significant negative effects. When decomposing this effect into technical efficiency and technical progress to explore the mechanism of influences, the latter plays the major role. Therefore, the Chinese government can promote TFP growth and economic sustainability by expanding the scale of bachelor and doctoral education and improving the quality of technical and master education.

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.

Comparative analysis of efficiency and productivity growth in Canadian regional boreal logging industries

2003 ◽  
Vol 33 (9) ◽  
pp. 1653-1660 ◽  
Author(s):  
Atakelty Hailu ◽  
Terrence S Veeman
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Productive Efficiency ◽  
Set Covering ◽  
Data Envelopment Analysis Model ◽  
Factor Productivity ◽  
Data Set ◽  
Term Survival ◽  
Positive Effects ◽  
Logging Industry

The Canadian boreal logging industry has attracted little or no attention from economic researchers in spite of its importance for the competitiveness and long-term survival of other forest-based industries. This article uses a panel data set covering the period from 1977 to 1995 to analyze technical efficiency, technical change, and total factor productivity growth in the logging industries for six boreal provinces. The production technology is represented using a data envelopment analysis model. A transitive measure of productivity change that combines technical progress and changes in the degree of productive efficiency is computed. The empirical investigation reveals that logging activities in the boreal region are characterized by substantial efficiency differentials among the regions. Results from a Tobit analysis of efficiency differentials indicate that forest resource characteristics such as forest density and proportion of hardwood production were found to have positive effects. There was also evidence of significant positive scale effects. Engineering construction per area seems to be negatively related to efficiency. Total factor productivity in the boreal logging industry progressed at an average annual rate of 1.56%.

scholarly journals Cost Efficiency and Total Factor Productivity: An Empirical Analysis of Pakistan’s Insurance Sector

2016 ◽  
Vol 21 (1) ◽  
pp. 123-150
Author(s):  
Uzma Noreen ◽  
Shabbir Ahmad
Keyword(s):  
Total Factor Productivity ◽  
Malmquist Index ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Innovative Technology ◽  
Average Score ◽  
Factor Productivity ◽  
Tobit Regression ◽  
Insurance Sector ◽  
The Impact

This study uses data envelopment analysis and the Malmquist index to examine the impact of financial sector reforms on the efficiency and productivity of Pakistan’s insurance sector over the period 2000–09. Our results indicate that the sector is cost-inefficient, with an average score of 58 percent – an outcome of the inappropriate use of inputs. The Malmquist productivity index performs better, indicating an improvement in total factor productivity of about 3 percent on average. The second-stage Tobit regression analysis shows that large firms are relatively inefficient from an allocative perspective as they are unable to equate the marginal product of inputs with their factor prices. Furthermore, the results demonstrate that private firms are more efficient than public firms in the nonlife insurance sector. The empirical findings suggest that a more competitive environment, diversified products and innovative technology could improve the productivity of insurance firms in Pakistan.

scholarly journals Effects of Smart City Policies on Green Total Factor Productivity: Evidence from a Quasi-Natural Experiment in China

2019 ◽  
Vol 16 (13) ◽  
pp. 2396 ◽  
Author(s):  
Xin ◽  
Qu
Keyword(s):  
Total Factor Productivity ◽  
Traffic Congestion ◽  
Smart City ◽  
Natural Experiment ◽  
Population Expansion ◽  
Factor Productivity ◽  
Negative Effects ◽  
Development Patterns ◽  
City Policy ◽  
The City

When cities develop rapidly, there are negative effects such as population expansion, traffic congestion, resource shortages, and pollution. It has become essential to explore new types of urban development patterns, and thus, the concept of the “smart city” has emerged. The purpose of this paper is to investigate the links between smart city policies and urban green total factor productivity (GTFP) in the context of China. Based on panel data of 200 cities in China from 2007–2016 and treating smart city policy as a quasi-natural experiment, the paper uses a difference-in-differences propensity score matching (PSM-DID) approach to prevent selection bias. The results show: (a) Smart city policies can significantly increase urban GTFP by 16% to 18%; (b) the larger the city, the stronger and more significant this promotion.

Effects of inequality on total factor productivity : exploring the technical efficiency channel in South Africa

2020 ◽  
Vol 15 (4) ◽  
pp. 97-122
Author(s):  
Delphin Kamanda Espoir ◽  
Nicholas Ngepah
Keyword(s):  
South Africa ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Fixed Effects ◽  
Empirical Studies ◽  
Stochastic Frontier ◽  
Likelihood Estimation ◽  
Political Stability ◽  
Factor Productivity ◽  
Positive Effects

A number of empirical studies have attempted to understand the effects of inequality on productivity through various channels such as human capital and political stability but have overlooked the efficiency linkage. This study utilises a stochastic frontier approach and a single-stage maximum likelihood estimation of a true fixed effects and true random effects model to investigate the effects of inequality on total factor productivity across the 52 districts of South Africa. The results obtained from the baseline regressions indicate that inequality has positive effects on technical inefficiency. This implies that an increase in inequality would exerts a negative effect on technical efficiency and therefore total factor productivity. In order to mitigate the negative effects, the study suggests that a mixture of pro-poor policies should be accentuated, as they might positively increase the earnings of those who are at the bottom of the distribution.

scholarly journals Non-parametric decomposition of total factor productivity growth in yam production in North-Central Nigeria

2021 ◽  
pp. 91-98
Author(s):  
R.G. Isonguyo ◽  
M.A Ojo ◽  
A.J. Jirgi ◽  
E.S. Yisa
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Data Bank ◽  
Productivity Index ◽  
Productivity Change ◽  
Regression Result ◽  
Factor Productivity ◽  
Tobit Regression ◽  
North Central ◽  
Non Parametric

Abstract. Non-parametric analysis of total factor productivity change in yam production in North-Central Nigeria from 1992 to 2016 was carried out with the use of secondary data. The secondary production data of yam for that period were collected from Food and Agriculture Statistical (FAOSTAT) data bank. Malmquist Total Factor Productivity Index (MTFPI) based on Data Envelopment Analysis (DEA), was used to empirically analyse the total factor productivity of the yam, while Tobit regression was used to analyse the determinants of total factor productivity in the study area. The results of the MTFPI analysis reveal that yam contributed 1.4% of technical efficiency change to productivity growth over the period studied. The technological contributions to productivity growth regressed at 1.8%. The study revealed the productivity growth of yam to be 0.2%. Tobit regression result showed credit borrowed, government policy (Agricultural Transformation Agenda – ATA), capital, and labour to have significant and positive relationships with the productivity of the crop at either p≤0.05 or p≤0.001 level of probability, which implies that increase in them led to increase in the crop’s productivity. Capital-labour was statistically significant but negatively related to yam productivity at p≤0.01, which implied that utilization of labour in a greater proportion than capital led to reduction or regress in its productivity growth. The study recommends farmers’ training on farm practices and techniques to increase yam productivity. They should be encouraged to accept improved yam varieties from research institutes, properly allocate the production resources and adopt improved technology to achieve productivity growth in the study area.

scholarly journals The Impact of Foreign Direct Investment Spillover Effects on Total Factor Productivity in Sri Lanka

2020 ◽  
pp. 37-49
Author(s):  
Kalaichevi Ravinthirakumaran ◽  
Tarlok Singh ◽  
Eliyathamby Selvanathan ◽  
Saroja Selvanathan
Keyword(s):  
Human Capital ◽  
International Trade ◽  
Sri Lanka ◽  
Research And Development ◽  
Total Factor Productivity ◽  
Spillover Effects ◽  
Annual Data ◽  
Factor Productivity ◽  
Positive Effects ◽  
The Impact

This paper examines whether FDI generates productivity spillovers in Sri Lanka, using the annual data over the period from 1978 to 2015. The autoregressive distributed lag model has been estimated to investigate the effects of FDI, research and development, human capital, international trade, technological gap, rate of inflation, population growth and civil war on total factor productivity (TFP). The results reveal that FDI positively influences TFP. The results also confirm that research and development, human capital and international trade have positive effects. The findings suggest that Sri Lanka needs to increase investment in human capital and in research and development and needs to introduce policies to attract FDI inflows.

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