Temporal-Spatial Evolution and Driving Factors of the Green Total Factor Productivity of China’s Central Plains Urban Agglomeration

As China’s largest urban agglomeration with rapid growth of economy and population, the development of the Central Plains Urban Agglomeration (CPUA) has been severely restricted by environmental problems. Thus, the green development performance of the CPUA is worth studying. This study used the panel data of 29 cities in the CPUA from 2003 to 2018 based on the Slacks-based Measure and Global Malmquist–Luenberger index to measure the green total factor productivity (GTFP) and its decomposition index of each city. A spatial econometric model was developed to explore the factors affecting the GTFP of the CPUA. The results show that the GTFP of the CPUA had an upward trend in 2003–2018, but the productivity level was still low. There were significant spillover effect in the GTFP among different cities of the CPUA. The results of the spatial measurement model show that technological progress, industrial structure and solid waste environmental regulationhave a significant positive spillover effect on the GTFP. The, fiscal expenditure, and informatization level also have positive impacts on the GTFP. In the future, local government should provide technical and financial support for the development of green industries in the CPUA, and accelerate the construction of environmental protection infrastructures.

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The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

Scientific Reports ◽

10.1038/s41598-021-93770-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Shen Zhong ◽

Hongli Wang

Keyword(s):

Total Factor Productivity ◽

Industrial Structure ◽

Spillover Effect ◽

Factor Productivity ◽

Spatial Econometric ◽

Spatial Spillover ◽

Negative Case ◽

Forestry Industry ◽

The Impact ◽

Spatial Spillover Effect

AbstractForestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.

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Impact of Green Total Factor Productivity in Marine Economy Based on Entropy Method

Polish Maritime Research ◽

10.2478/pomr-2018-0123 ◽

2018 ◽

Vol 25 (s3) ◽

pp. 141-146

Author(s):

Danjie Wu

Keyword(s):

Total Factor Productivity ◽

Environmental Governance ◽

Production Efficiency ◽

Industrial Structure ◽

Entropy Method ◽

Factor Productivity ◽

Factors Affecting ◽

Green Production ◽

Model Coefficient ◽

Marine Economy

Abstract In order to improve the efficiency of marine economic production and realize the sustainable and healthy development of marine economy, the spatial-temporal and dynamic evolution trend of marine economic green production efficiency in coastal areas of China is analysed by means of SFA basic model, coefficient of variation, coefficient of Gini and entropy method. It mainly includes three aspects: the result analysis of marine economy green production efficiency; the dynamic trend analysis of marine economy green production efficiency; the analysis of factors affecting marine economy green production efficiency. The results show that the factors affecting the total factor productivity of the marine economy are: development level of marine economy, marine material capital, level of opening to the outside world, marine industrial structure, marine human capital and marine environmental governance.

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Does foreign direct investment spillover total factor productivity growth? A study of Indian drugs and pharmaceutical industry

Benchmarking An International Journal ◽

10.1108/bij-09-2016-0148 ◽

2017 ◽

Vol 24 (7) ◽

pp. 1937-1955 ◽

Cited By ~ 1

Author(s):

Nitin Arora ◽

Preeti Lohani

Keyword(s):

Foreign Direct Investment ◽

Pharmaceutical Industry ◽

Total Factor Productivity ◽

Direct Investment ◽

Spillover Effect ◽

Foreign Firms ◽

Factor Productivity ◽

Content Type ◽

Domestic Firms ◽

Tfp Growth

Purpose Foreign firms have certain advantages which may spillover to domestic firms in the form of improvements in total factor productivity (TFP) growth. The purpose of this paper is to empirically observe the presence of TFP spillovers of foreign direct investment (FDI) to domestic firms through analyzing source of TFP growth in Indian drugs and pharmaceutical industry. Design/methodology/approach This paper examines the sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry over the period 1999 to 2014. The data of 304 firms has been used for estimation of the growth rates of TFP and its sources under stochastic frontier analyses based Malmquist productivity index framework. For frontier estimation, the Wang and Ho (2010) model has been executed using translog form of production function. Findings The results show that there exists significant TFP spillover effect from the presence of foreign equity in drugs and pharmaceutical industry of India. The results also show that the major source of TFP fluctuations in the said industry is managerial efficiency that has been significantly affected by FDI spillover variables. In sum, the phenomenon of significant Intra-industry (horizontal) efficiency led productivity spillovers of FDI found valid in case of Indian drugs and pharmaceutical industry. Research limitations/implications The number of foreign firms is very less to imitate the significant impact of foreign investment on TFP growth of Indian pharmaceutical industry at aggregated level; and the Wang and Ho (2010) model is failing to capture direct impact of FDI on technological change under Malmquist framework. Practical implications Since, there exists dominance of domestic firms in Indian drugs and pharmaceutical industry, the planners should follow the policy which not only attract FDI but also benefit domestic firms; for example, developing modern infrastructure and institution which will further help domestic firms to absorb spillovers provided by the Multinational Corporations and also accelerate the growth and development of the economy. Social implications In no case, the foreign firms should dominate the market share otherwise the efficiency spillover effect will be negative and the domestic firms will be destroyed under the self-centric approach of foreign firms protected by the recent patent laws. Originality/value The study is a unique attempt to discuss the production structure and sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry with such a wide coverage of 304 firms over a period of 16 years under Wang and Ho (2010) model’s framework. The existing studies on TFP spillovers are using either a small sample size of firms or based upon traditional techniques of measuring spillover effects.

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Research on the Spatial Effect of Green Economic Efficiency in China from the Perspective of Informatization

10.21203/rs.3.rs-20207/v1 ◽

2020 ◽

Author(s):

Xinbao Tian ◽

Chuanhao Yu

Keyword(s):

Industrial Structure ◽

Spillover Effect ◽

Coordination Mechanism ◽

Green Economy ◽

Spatial Econometric ◽

Index Method ◽

Spatial Spillover ◽

Regional Coordination ◽

Comprehensive Index Method ◽

Spatial Spillover Effect

Abstract Background: Green economy has been paid more and more attention in the information age. Informatization plays an important role in the development of green economy by the transmission of industrial structure rationalization and upgrading. Because of the spatial mobility of information, it is necessary to study the spatial spillover effect of information on the efficiency of green economy. In this paper, the non-radial directional distance function and the comprehensive index method are used to evaluate the efficiency of green economy and informatization respectively. On this basis, the spatial characteristics of the two are analyzed. Finally, the spatial econometric model is used to analyze the spatial impact of informatization on the efficiency of green economy. Results: The following findings can be drawn: (i)The spatial distribution of the green economy efficiency and informatization are unbalanced; (ii) There is a significant spatial spillover effect in the efficiency of green economy; (iii) The development of informatization plays an important impact on the efficiency of green economy. Conclusions: It can be seen that informatization plays an important role in the development of green economy, so we can get the following suggestions: (i) Developing green economy according to different conditions of different places. (ii) Establishing regional coordination mechanism of green economic development. (iii) Using informatization to promote the development of green economy.

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Agricultural Growth Accounting and Total Factor Productivity in Jordan

Environmental and Agricultural Informatics ◽

10.4018/978-1-5225-9621-9.ch079 ◽

2020 ◽

pp. 1709-1723

Author(s):

Samia Nadeem Akroush ◽

Boubaker Dhehibi ◽

Aden Aw-Hassan

Keyword(s):

Total Factor Productivity ◽

Productivity Growth ◽

Agricultural Research ◽

Agricultural Productivity ◽

Primary Source ◽

Factor Productivity ◽

Factors Affecting ◽

Tfp Growth ◽

Food And Agriculture ◽

Food And Agriculture Organization

This article develops new estimates of historical agricultural productivity growth in Jordan. It investigates how public policies such as agricultural research, investment in irrigation capital, and water pricing have contributed to agricultural productivity growth. The Food and Agriculture Organization (FAO) annual time series from 1961 to 2011 of all crops and livestock productions are the primary source for agricultural outputs and inputs used to construct the Törnqvist Index for the case of Jordan. The log-linear form of regression equation was used to examine the relationship between Total Factor Productivity (TFP) growth and different factors affecting TFP growth. The results showed that human capital has positive and direct significant impact on TFP implying that people with longer life expectancy has a significant impact on TFP growth. This article concludes that despite some recent improvement, agricultural productivity growth in Jordan continues to lag behind just about every other region of the world.

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Effect of Complex Road Networks on Intensive Land Use in China’s Beijing-Tianjin-Hebei Urban Agglomeration

Land ◽

10.3390/land9120532 ◽

2020 ◽

Vol 9 (12) ◽

pp. 532

Author(s):

Chen Zeng ◽

Zhe Zhao ◽

Cheng Wen ◽

Jing Yang ◽

Tianyu Lv

Keyword(s):

Land Use ◽

Road Network ◽

Spillover Effect ◽

Urban Agglomeration ◽

Land Use Intensity ◽

Spatial Econometric ◽

Spatial Spillover ◽

The Road ◽

Intensive Land Use ◽

Spatial Spillover Effect

Coupled with rapid urbanization and urban expansion, the spatial relationship between transportation development and land use has gained growing interest among researchers and policy makers. In this paper, a complex network model and land use intensity assessment were integrated into a spatial econometric model to explore the spatial spillover effect of the road network on intensive land use patterns in China’s Beijing–Tianjin–Hebei (BTH) urban agglomeration. First, population density, point of interest (POI) density, and aggregation index were selected to measure land use intensity from social, physical, and ecological aspects. Then, the indicator of average degree (i.e., connections between counties) was used to measure the characteristics of the road network. Under the hypothesis that the road network functions in shaping land use patterns, a spatial econometric model with the road network embedded spatial weight matrix was established. Our results revealed that, while the land use intensity in the BTH urban agglomeration increased from 2010 to 2015, the road network became increasingly complex with greater spatial heterogeneity. The spatial lag coefficients of land use intensity were positively significant in both years and showed a declining trend. The spatially lagged effects of sector structure, fixed asset investment, and consumption were also significant in most of our spatial econometric models, and their contributions to the total spillover effect increased from 2010 to 2015. This study contributes to the literature by providing an innovative quantitative method to analyze the spatial spillover effect of the road network on intensive land use. We suggest that the spatial spillover effect of the road network could be strengthened in the urban–rural interface areas by improving accessibility and promoting population, resource, and technology flows.

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Industrial structure and total factor productivity: the Tunisian manufacturing sector between 1998 and 2004

The Annals of Regional Science ◽

10.1007/s00168-015-0670-4 ◽

2015 ◽

Vol 54 (2) ◽

pp. 639-662 ◽

Cited By ~ 9

Author(s):

Khaled Thabet

Keyword(s):

Total Factor Productivity ◽

Industrial Structure ◽

Manufacturing Sector ◽

Factor Productivity

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ANALYSIS OF COMPETITIVENESS OF THE TOURISM SECTOR EAST JAVA PROVINCE (A TECHNICAL EFFICIENCY & CONVERGENCE APPROACH)

Archives of Business Research ◽

10.14738/abr.86.8585 ◽

2020 ◽

Vol 8 (6) ◽

pp. 294-304

Author(s):

Suparno Suparno

Keyword(s):

Technical Efficiency ◽

Total Factor Productivity ◽

High Efficiency ◽

Government Expenditure ◽

Spillover Effect ◽

Productive Efficiency ◽

Factor Productivity ◽

Significance Level ◽

Tourism Sector ◽

Low Efficiency

This research analysis of tourism competitiveness is based on the very high disparity problem in the condition of the tourism sector in East Java Province. With a sample of 10 districts / cities and using investment data, tourist visits, population, government spending and tourism sector PDRB, it is produced that investment and tourist visits have a positive but not significant effect on tourism sector PDRB because due to the probability > 0.05. While the population and government expenditure have a positive and significant effect on the tourism sector PDRB due to the probability < 0.05. Fixed effect models that are formed are:PSP = 39485712 + 0.018 INV + 0.389 TOURIST + 22.304 POP + 0.065 GEX + e To measure tourism competitiveness, it is used with technical efficiency and total factor productivity where it is produced: Sidoarjo Regency, Malang City and Surabaya City are regencies / cities that have the highest level of technical efficiency with a value of 100% technical efficiency. Whereas with the calculation of total factor productivity in Gresik Regency (21,350), Jember Regency (16,543) and Kediri Regency (15,650) are regencies / cities that have the highest productivity. Based on the calculation of technical efficiency and total factor productivity results are obtainedL1) High efficiency and productive, Jember Regency; (2) High efficiency and less productive, Sidoarjo Regency, Malang City and Surabaya City; (3) Low and productive efficiency, Kediri Regency, Lamongan Regency and Gresik Regency; and (4) Low efficiency and less productive, Banyuwangi Regency, Pasuruan Regency and Pasuruan City. The spillover effect occurs in Pasuruan City, where the economy of Pasuruan City is affected by investments from Sidoarjo Regency and Surabaya City as indicated by the significance level of 0.051 Surabaya City investment and 0.048 for Sidoarjo Regency investment which means smaller and equal to 0.05. The calculation of convergence shows that the average convergence of regencies / cities in East Java to leader regions over 15 years and 5 months means that districts / cities need an average of 15 years and 5 months to match the conditions of tourism in the city of Surabaya.

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