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.

Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

2020 ◽  
pp. 18-30
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Firm Level ◽  
Employment Level ◽  
The Impact ◽  
Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

scholarly journals Exports, Misallocation, and Total Factor Productivity of Furniture Enterprises

2019 ◽  
Vol 11 (18) ◽  
pp. 4892
Author(s):  
Chang Xu ◽  
Jianbing Guo ◽  
Baodong Cheng ◽  
Yu Liu
Keyword(s):  
Total Factor Productivity ◽  
Value Chain ◽  
Fixed Effects ◽  
Negative Impact ◽  
Market Competition ◽  
Fixed Effects Model ◽  
Factor Productivity ◽  
Labor Costs ◽  
Negative Effect ◽  
The Impact

With the increase in labor costs in China and the tremendous changes in the international trade environment, upgrading the total factor productivity of Chinese furniture export enterprises faces a great challenge. Lots of studies have explored the interaction of exports or misallocation on the total factor productivity (TFP) of furniture enterprises, however, there is little knowledge on the impact and interaction of both exports and misallocation on the TFP. Based on panel data of Chinese furniture enterprises, this paper measures the TFP and the distortion of labor and capital resources in Chinese furniture enterprises. A two-way fixed-effects model is used to analyze the impact of exports and misallocation on the TFP of Chinese furniture enterprises. The paper reveals several important findings. First, the TFP of Chinese furniture export enterprises is lower than that of non-export enterprises, this phenomenon is called the “export–productivity paradox”. Chinese furniture export enterprises are processing trade-oriented and labor-intensive enterprises at the low end of the value chain, exports have a negative effect on improving the TFP of furniture enterprises in the short term. Second, the distortion of labor and capital resources in Chinese furniture enterprises promotes improvements to the TFP of furniture enterprises rather than reducing the TFP of furniture enterprises. Last but not the least, we find that misallocation has a positive moderating effect on exports and can weaken the negative impact of exports on TFP by the “forced mechanism”, which is that the higher the distortion of the misallocation, the higher the cost of acquiring capital and labor, and enterprises are forced to enhance their productivity when facing market competition, thus promoting improvements to the TFP of furniture enterprises.

Are human capital, intellectual property rights, and research and development expenditures really important for total factor productivity? An empirical analysis

2019 ◽  
Vol 46 (6) ◽  
pp. 756-774 ◽  
Author(s):  
Misbah Habib ◽  
Jawad Abbas ◽  
Rahat Noman
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Intellectual Property ◽  
Property Rights ◽  
Research And Development ◽  
Total Factor Productivity ◽  
Intellectual Property Rights ◽  
Factor Productivity ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to investigate the impact of human capital (HC), intellectual property rights (IPRs) and research and development (R&D) expenditures on total factor productivity (TFP), which leads to economic growth. Design/methodology/approach The panel data technique is used on a sample of 16 countries categorized into two groups, namely Brazil, Russia, India and China (BRIC) and Central and Eastern European (CEE) countries and, in order to make a comparison for the time period of 2007–2015, the researchers used a fixed effect model as an estimation method for regression. Findings The results indicate that HC, IPRs and R&D expenditures appear to be statistically significant and are strong factors in determining changes in TFP and exhibit positive results in all sample sets. Moreover, IPRs alone do not accelerate growth in an economy, especially taking the case of emerging nations. Originality/value Considering the importance of CEE and BRIC countries, and inadequate research on these regions with respect to current study’s variables and techniques, the present research provides valuable insights about the importance of HC, IPR and R&D activities and their impact on TFP, which leads to economic growth. IPRs create a fertile environment for R&D activities, knowledge creation and economic development. Distinct nations can attain better economic status via HC, R&D activities, innovation, trade and FDI, although the relative significance of these channels is likely to differ across countries depending on their developmental levels.

scholarly journals Development Accounting

2010 ◽  
Vol 2 (1) ◽  
pp. 207-223 ◽  
Author(s):  
Chang-Tai Hsieh ◽  
Peter J. Klenow
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Capital Accumulation ◽  
Physical Capital ◽  
Human Capital Accumulation ◽  
Factor Productivity ◽  
Income Levels ◽  
The Past ◽  
Development Accounting ◽  
Proximate Determinants

Researchers have made much progress in the past 25 years in accounting for the proximate determinants of income levels: physical capital, human capital, and Total Factor Productivity (TFP). But we still know little about why these factors vary. We argue that TFP exerts a powerful influence on output not only directly, but also indirectly, through its effect on physical and human capital accumulation. We discuss why TFP varies across countries, highlighting misallocation of inputs across firms and industries as a key determinant. (JEL E22, E23, F21, F35, O10, O40)

scholarly journals PENGARUH HUMAN CAPITAL, STRUCTURE CAPITAL, DAN PHYSICAL CAPITAL TERHADAP KINERJA PERUSAHAAN PERBANKAN DI INDONESIA

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Agustinus Jeneo
Keyword(s):  
Human Capital ◽  
Intellectual Capital ◽  
Negative Impact ◽  
Stock Exchange ◽  
Value Added ◽  
Physical Capital ◽  
Return On Equity ◽  
Result Show ◽  
Capital Efficiency ◽  
The Impact

The objective of this study are to analyze the impact of intellectual capital (HumanCapital, Structure Capital and Physical Capital) on company’s financial performance Return on Assets (ROA) dan Return On Equity (ROE). This research used banking company data that listed in Indonesia Stock Exchange (IDX) 2011-2012. The model that used to measure intellectual capital was Pulic model agregatly-using Value Added Intellectual Coefficient (VAIC™) or separately-using Human Capital Efficiency (HCE), Structure Capital Efficiency (SCE), and Physical Capital/ Capital Employed Efficiency (CEE). The result show: (1) Human Capital Efficiency (HCE) not significant  impact on ROA, (2) Human Capital Efficiency (HCE) not significant impact on ROE, (3) Structure Capital Efficiency (SCE) not significant impact on ROA, (4) Structure Capital Efficiency (SCE) negative impact on ROE (5) Physical Capital/Capital Employed Efficiency (CEE) has a positive significant impact on ROA, (6) Physical Capital/Capital Employed Efficiency (CEE) has a positive significant impact on ROE

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.

scholarly journals Total Factor Productivity Shock and Economic Growth in Selected Asean+3 Countries: A New Evidence Using a Panel Var

2021 ◽  
Vol 21 (3) ◽  
pp. 1366-1383
Author(s):  
Noorazeela Zainol Abidin ◽  
Ishak Yussof ◽  
Zulkefly Abdul Karim
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Positive Impact ◽  
Production Costs ◽  
Panel Var ◽  
Factor Productivity ◽  
Data Set ◽  
Tfp Growth ◽  
The Impact ◽  
Panel Vector Autoregression

A comparison between countries shows that there is a difference in terms of economic growth achievement across nations. This difference is due to the contribution of capital growth, labor, and total factor productivity (TFP). Although the use of capital and labor plays a vital role in the production, the contribution of TFP growth is also indispensable, as it saves production costs. Nevertheless, in 1995-2000, most countries have experienced a negative growth of TFP in which can affect its contribution to economic growth. Therefore, the focal point of this study is to analyze the impact of TFP growth shock on economic growth in selected ASEAN+3 countries (i.e., Malaysia, Singapore, Thailand, Indonesia, Philippines, Cambodia, Vietnam, China, South Korea, and Japan), using the data set from 1981 to 2014. The study employed the panel vector autoregression (PVAR) method in analyzing the propagation of the shocks through impulse response function and variance decomposition. The main findings revealed that TFP growth shocks have a positive impact on economic growth. Besides, the results also showed that over the next ten years, the proportion of human capital variation would be more dominant in contributing to the economic growth for the selected ASEAN+3 countries. As the surge in TFP growth had a positive impact on economic growth, this finding indicated that each country needs to allocate more expenditure in the Research and Development (R&D) activities.

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.

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