scholarly journals Impact of collaborative innovation on green total factor productivity in Yangtze River Economic Belt: Analysis based on endogenous spatial-temporal weight matrix

2021 ◽  
Author(s):  
lei Wu ◽  
Xiaoyan Jia ◽  
Jie Lv ◽  
Li Gao
Keyword(s):  
Total Factor Productivity ◽  
Yangtze River ◽  
Negative Impact ◽  
Positive Impact ◽  
Spatial Interaction ◽  
Evaluation Index System ◽  
Weight Matrix ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Collaborative Innovation

Abstract Technological innovation can promote high-quality economic growth. This paper discusses the promotion of green total factor productivity from the perspective of collaborative innovation in the Yangtze River Economic Belt. Firstly, the evaluation index system of collaborative innovation level is constructed from two aspects of collaborative innovation elements and collaborative innovation environment. Then the entropy method is used to measure its development level. The results show that the collaborative innovation level of provinces in the Yangtze River Economic Belt presents an increasing trend year by year. Meanwhile, there are regional differences, which is characterized by 'high in the middle reaches, middle in the downstream and low in the upstream' Secondly, the SDM model based on endogenous spatio-temporal weight matrix is constructed to analyze the influencing factors of green total factor productivity. The results show that collaborative innovation in the Yangtze River Economic Belt has significant negative impact on green total factor productivity in terms of spatial interaction and fiscal expenditure also has a negative impact. The spatial interaction between environmental protection and opening up has a significant positive impact on green total factor productivity. However, the spatial interaction between industrial structure and human capital on green total factor productivity is not obvious. Finally, this paper puts forward some policy suggestions to improve green total factor productivity.

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.

scholarly journals KONSENTRASI SPASIAL, AGLOMERASI DAN PRODUKTIVITAS PERUSAHAAN INDUSTRI MANUFAKTUR INDONESIA

2021 ◽  
Vol 4 (2) ◽  
pp. 146-156
Author(s):  
Kusuma Wardani (Universitas Indonesia) ◽  
Muhammad Halley Yudhistira (Universitas Indonesia)
Keyword(s):  
Total Factor Productivity ◽  
Negative Impact ◽  
Positive Impact ◽  
High Tech ◽  
Factor Productivity ◽  
Localization Economies ◽  
Instrument Variable ◽  
Urbanization Economies ◽  
The Impact ◽  
The Relationship

AbstractThis study aims to analyze the impact of agglomeration in the form of localization economies and urbanization economies on the productivity of manufacturing industrial companies in Indonesia. Unlike previous studies, this study will look at the effect of technology level on the relationship between productivity and agglomeration by classifying research samples into low-tech and high-tech industries. In addition, this study also improves the estimation technique by addressing the endogeneity problem that has the potential to arise in estimating the relationship between productivity and agglomeration to be overcome by using instrument variable (IV). The study was conducted in two stages of estimation using company-level panel data from 2010 to 2014. First, productivity was measured at the company level using Total Factor Productivity (TFP). Then, the company productivity is estimated together with the company and industry characteristic variables, including the agglomeration measurement variable which represents localization economies and urbanization economies. The regression results show a positive impact from localization economies and a negative impact from urbanization economies.AbstrakPenelitian ini bertujuan menganalisis dampak aglomerasi berupa localization economies dan urbanization economies terhadap produktivitas perusahaan industri manufaktur di Indonesia. Berbeda dengan penelitian terdahulu yang juga meneliti dampak aglomerasi industri terhadap produktivitas perusahaan, pada penelitian ini akan melihat pengaruh tingkat teknologi terhadap hubungan produktivitas dan aglomerasi dengan mengklasifikasikan sampel penelitian ke dalam industri berteknologi rendah dan industri berteknologi tinggi. Selain itu, peneltian ini juga memperbaiki teknik estimasi dari penelitian sebelumnya dengan menangani masalah endogenitas yang berpotensi muncul dalam mengestimasi hubungan produktivitas dan aglomerasi akan diatasi dengan penggunaan instrument variable (IV). Penelitian dilakukan dalam dua tahap estimasi dengan menggunakan data panel level perusahaan dari tahun 2010 sampai 2014. Pertama, produktivitas diukur pada level perusahaan dengan menggunakan Total Factor Productivity (TFP). Kemudian, produktivitas perusahaan diestimasi bersama variabel karakteristik perusahaan dan industri, termasuk variabel pengukuran aglomerasi yang mewakili localization economies dan urbanization economies. Hasil regresi menunjukkan adanya dampak positif dari localization economies dan dampak negatif dari urbanization economies.

scholarly journals The Influence of Complexity of Imported Products on Total Factor Productivity

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Nan Wang ◽  
Wei Liu ◽  
Shanwu Sun ◽  
Qingjun Wang
Keyword(s):  
Total Factor Productivity ◽  
Technological Progress ◽  
Negative Impact ◽  
Positive Impact ◽  
Factor Productivity ◽  
Product Complexity ◽  
Technological Efficiency ◽  
The World ◽  
Belt And Road ◽  
Import Trade

The research results show that, all over the world, the increase in complexity of China’s imported products has significantly promoted the growth of total factor productivity and technological progress but has no obvious impact on technological efficiency. In “Belt and Road” samples, the increase in import product complexity did not improve the total factor productivity and technological progress, which had a negative impact on technical efficiency. Whether it is anywhere in the world or in the scope of “Belt and Road” countries, the import product density has a significantly positive impact on total factor productivity but has no significant effect on the promotion of technological progress and efficiency. Therefore, it is necessary to focus on adjusting the import trade structure of “Belt and Road” countries. Relying on the domestic consumer market, the manufacturing imports from countries along the “Belt and Road” route should be expanded so as to stimulate the promotion of domestic industrial total factor productivity.

scholarly journals Carbon Sequestration Total Factor Productivity Growth and Decomposition: A Case of the Yangtze River Economic Belt of China

2019 ◽  
Vol 11 (23) ◽  
pp. 6809
Author(s):  
Guangming Rao ◽  
Bin Su ◽  
Jinlian Li ◽  
Yong Wang ◽  
Yanhua Zhou ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Total Factor Productivity ◽  
Yangtze River ◽  
Stochastic Frontier ◽  
Scale Efficiency ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Natural Ecosystems ◽  
Estimation Model

To find out whether carbon sequestration is both effective at mitigating climate change and promoting economic growth, in this paper, by adopting a stochastic frontier panel model with translog production function, carbon sequestration is incorporated into endogenous variables to establish estimation model of carbon sequestration total factor productivity (CSTFP) and examine CSTFP growth and its drivers decomposition of the Yangtze River Economic Belt (YREB) of China in three estimations. The result shows that, (1) compared to traditional TFP growth, CSTFP growth in YREB is improved by 26.74 percentages (from −26.55% to 0.20%), contributed by three positive drivers of technical efficiency change (28.59%), technological progress change (18.55%), and scale efficiency change (3.99%); (2) different CSTFP growth exists in three watershed segments of YREB, which firstly is the upper reaches (0.62%), then the lower reaches (0.11%) and the middle reaches (−0.14%). Improved CSTFP growth owes to carbon sequestration’s harmonious symbiosis where natural ecosystems and human activities are naturally blended while insufficient synergies are bottleneck for promotion of CSTFP growth in YREB. Related policy suggestions are provided in the end. The proposed analysis framework is efficient to disclose CSTFP growth in YREB, and can also be applied to similar analysis on CSTFP in regions and extended to multi-country/region analysis.

Econometric Analysis of Total Factor Productivity in India

2021 ◽  
pp. 001946622098806
Author(s):  
Mushtaq Ahmad Malik ◽  
Tariq Masood ◽  
Mehraj Ahmad Sheikh
Keyword(s):  
Total Factor Productivity ◽  
Global Economy ◽  
Negative Impact ◽  
Positive Impact ◽  
New Technology ◽  
Factor Productivity ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Time Period ◽  
Two Stages

This article attempts to investigate the potential relationship and significance of various determinants of Total Factor Productivity (TFP) in India for the 1980–2016 time period. Specifically, this is achieved in two stages. In the first, the standard growth accounting approach is used to measure the changes in TFP. Then, the main model for establishing the determinants of TFP growth is estimated using the autoregressive distributed lag (ARDL) model. Our results suggest that inflation and financial development have a statistically positive impact on TFP. Foreign direct investment, imports, and capital formation are found to have a positive but insignificant impact on the TFP. On the other hand, exports, government size, and natural calamities have a statistically negative impact on TFP. Therefore, in order to accelerate the TFP, governments and policymakers need to design and implement policies to increase financial access to the private sector, while maintaining price stability; exports of high-value products; and increased economic integration in the global economy to benefit from foreign investment flows, which brings in new technology.

scholarly journals Impact of Regional Green Development Strategy on Environmental Total Factor Productivity: Evidence from the Yangtze River Economic Belt, China

2021 ◽  
Vol 18 (5) ◽  
pp. 2496
Author(s):  
Kailu Guo ◽  
Shixiang Li ◽  
Zhanqi Wang ◽  
Jianru Shi ◽  
Jun Bai ◽  
...  
Keyword(s):  
Total Factor Productivity ◽  
Development Strategy ◽  
Yangtze River ◽  
Evaluation Model ◽  
Chinese Government ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Industrial Transformation ◽  
Green Development ◽  
Negative Effect

Chinese government policy officially identify the Yangtze River Economic Belt (YREB) as one of regional green development strategies firstly in 2014. This strategy can be regarded as quasi-natural experiment, this paper aims to test its impact on regional environmental total factor productivity (TFP). First, slack-based measure model is used to calculate the environmental TFP from 2005 to 2017 at provincial level. Second, based on Chinese official statistics, differences-in-differences (DID) method is applied to construct an evaluation model of policy effect, combining with the kernel matching in propensity score matching (PSM) method. The results show that environmental TFP of YREB has significant spatial differences, with characteristic of high-east and low-west, its average level is 11.69 percentage points higher than the national average. YREB strategy promotes regional economic growth, but it does no effect on the regional environmental TFP yet. Modelling suggests that YREB strategy may play a role in the short term. From the significance of the control variables, infrastructure construction level is positively correlated with environmental TFP, while per capita GDP, financial development and energy consumption intensity have negative effect on environmental TFP. Based on this, policymakers should focus on green development, promoting industrial transformation, and enhancing environmental protection.

scholarly journals Research on Green Total Factor Productivity of Yangtze River Economic Belt Based on Environmental Regulation

2021 ◽  
Vol 18 (22) ◽  
pp. 12242
Author(s):  
Junxia He ◽  
Luxia Wang ◽  
Decai Tang
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Yangtze River ◽  
Environmental Governance ◽  
Efficiency Index ◽  
Scale Efficiency ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Input Output ◽  
Treatment Rate

With the acceleration of industrialization and urbanization, the Yangtze River Economic Belt (YREB) is facing many environmental problems that need to be solved in the process of development. This paper aims to analyze the environmental governance effects of nine provinces and two municipalities in the Yangtze River Economic Belt from 2009 to 2018. Firstly, based on the input-output index, the slacks-based measure (SBM) undesirable model and Malmquist (ML) index were used to measure the green total factor productivity (GTFP) of the YREB from 2009 to 2018. The results showed that the technological progress index contributed the most to the GTFP of the YREB, followed by the pure technical efficiency index and the scale efficiency index. Environmental regulation has no significant impact on the GTFP of the YREB. Secondly, by analyzing the effect of environmental governance in the YREB, the results show that the main reasons for the ineffective environmental governance in the YREB are the redundant input of environmental resources, excessive unwanted output, and low harmless treatment rate of municipal solid waste, rather than the low level of urban environmental management. Finally, this paper provides recommendations for the ineffective provinces and municipalities of the YREB to further optimize the input-output factors of environmental governance.

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