Log in

Relevant bibliographies by topics / Industrial total factor productivity / Journal articles

Journal articles on the topic 'Industrial total factor productivity'

To see the other types of publications on this topic, follow the link: Industrial total factor productivity.

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Industrial total factor productivity.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Vagionis, N., and N. Spence. "Total Factor Regional Productivity in Greece." Environment and Planning C: Government and Policy 12, no. 4 (December 1994): 383–407. http://dx.doi.org/10.1068/c120383.

Full text

Abstract:

The components of productivity change in manufacturing industry over the regions of Greece in the 1980s are examined. Regional differences in productivity are significant in two respects. They reflect the outcomes of different production processes in space where labour is supplied and combined with various sorts of capital and where specific technologies are used. They also reflect opportunities for developing efficient business operations in space, in that they indicate one important aspect of a region's comparative advantage. Change in value added in manufacturing is represented by change in the factor inputs of capital, labour, and technology. Some of this change in output is accounted for by constant returns to scale. The rest is a result of variable returns to scale, such as produced by agglomeration economies or diseconomies, different levels of infrastructure provision, etc, and technological change. Total factor productivity represents these sources of nonconstant returns to scale. It is shown that for Greece the largest gains in total factor productivity are to be found in the noncentral regions, and especially in those having industrial area projects and industrial grants and incentives. These results are in line with research undertaken in other contexts. Those areas with the most significant productivity gains from the deployment of new technology tend to be the well-established centres housing medium-sized populations. There is some evidence to suggest that new employment opportunities are associated with increases in total factor productivity, although rarely with advances in the use of new technology.

APA, Harvard, Vancouver, ISO, and other styles

2

Konstantinova, S., and A. Konarev. "Corporate growth and total factor productivity In industrial companies." Trakia Journal of Science 15, Suppl.1 (2017): 191–94. http://dx.doi.org/10.15547/tjs.2017.s.01.035.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Konstantinova, Sn, A. Konarev, and G. V. Georgieva. "RETURN AND TOTAL FACTOR PRODUCTIVITY OF PUBLIC INDUSTRIAL COMPANIES." Trakia Journal of Sciences 17, Suppl.1 (2019): 361–64. http://dx.doi.org/10.15547/tjs.2019.s.01.059.

Full text

Abstract:

Total factor productivity is a complex factor that affects not only corporate growth but also other key parameters of industrial companies. This paper explores the impact of this factor on the return on capital invested in these companies. Based on the example of a group of public companies whose shares are traded on the main and alternative markets of the Bulgarian Stock Exchange – Sofia, the level and the dynamics of the return and the total factor productivity is analysed. Dependencies are identified and opportunities for intensifying corporate growth are revealed

APA, Harvard, Vancouver, ISO, and other styles

4

Covick, Owen. "Total Factor Productivity and Wages Policy." Journal of Industrial Relations 32, no. 4 (December 1990): 488–512. http://dx.doi.org/10.1177/002218569003200402.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Verma, Satish, and Gurinder Kaur. "Total Factor Productivity Growth of Manufacturing Sector in Punjab." Indian Economic Journal 65, no. 1-4 (March 2017): 91–106. http://dx.doi.org/10.1177/0019466217727848.

Full text

Abstract:

The present article is an attempt to analyse the performance of Punjab’s manufacturing sector. For this, data used is of 12 two-digit industrial groups from 1980–81 to 2007–08. Dividing the entire data into pre-reform and post-reform period, the results of total factor productivity (TFP) of Punjab’s manufacturing sector revealed that it experienced meagre improvement (1.6 per cent per annum) during the last 28 years. Technical efficiency change (TEC) contributed more than technical change (TC) to TFPG. Paper and paper products (28), followed by non-metallic mineral products (32) and cotton, wool, silk and jute products (23 + 24 + 25) are most productive industrial groups. Wood and wood products (27) and leather and leather products (29) are least productive industrial groups. Among all the industrial groups, chemical and chemical products (30) acted as an innovator for maximum number of years, that is, 13 years. Panel data results highlighted that output, labour skills, size of factory and good emoluments to employees have a positive significant influence on TFP of Punjab’s manufacturing sector. The study concludes by giving policy implications.

APA, Harvard, Vancouver, ISO, and other styles

6

Cui, Herui, Haoran Wang, and Qiaozhi Zhao. "Which factors stimulate industrial green total factor productivity growth rate in China? An industrial aspect." Greenhouse Gases: Science and Technology 9, no. 3 (May 10, 2019): 505–18. http://dx.doi.org/10.1002/ghg.1874.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Feng, Jian, Lingdi Zhao, Huanyu Jia, and Shuangyu Shao. "Silk Road Economic Belt strategy and industrial total-factor productivity." Management of Environmental Quality: An International Journal 30, no. 1 (January 14, 2019): 260–82. http://dx.doi.org/10.1108/meq-06-2018-0109.

Full text

Abstract:

Purpose The purpose of this paper is to assess the effectiveness of the Silk Road Economic Belt (SREB) strategy and its role of industrial productivity in China. Design/methodology/approach To identify the causal effect of this strategy on industrial sustainable development, the authors first use the slacks-based measure model to calculate industries’ total-factor productivity (TFP) considered with CO2 emissions as undesirable output on the provincial level. Then, the authors use the PSM-DID method to identify the difference of TFPs between provinces and industries before and after the implementation of SREB strategy. Findings However, the authors find that there is no difference or even a relative decrease in TFPs of industries in target provinces after the implementation of the strategy, which reveals that the SREB strategy does not play a positive role of the industries’ sustainable development in years of 2014 and 2015. Originality/value The value of this result is to identify the short-term impact of SREB strategy and to seek for probable causes and appropriate solutions.

APA, Harvard, Vancouver, ISO, and other styles

8

Zhang, Luan, Miao Wang, and Weidong Wang. "Does Eco-innovation Improve Green Total Factor Productivity of China’s Industry?" E3S Web of Conferences 236 (2021): 04003. http://dx.doi.org/10.1051/e3sconf/202123604003.

Full text

Abstract:

The improvement of industrial green TFP is crucial for the sustainability of economy and environment. And the eco-innovation directly improves the industrial green TFP. However, there are few studies on the relation between eco-innovation and industrial green TFP. Based on the relevant data from 2006-2015 of 30 provinces in China, using SBM model this study firstly evaluates the industrial green TFP of each province by measuring the desirable output and undesirable output. Then the eco-innovation is measured by patent application quantity and further divided into breakthrough and incremental innovation by patent quality. The results show that eco-innovation improves the development of green industry in China. The promotion from breakthrough innovation is prominent. However, the incremental innovation restrains the development of green industry in China.

APA, Harvard, Vancouver, ISO, and other styles

9

JIANLEI, ZHANG, AN NA, and CHENG LONGDI. "Agglomeration and total factor productivity of China’s textile industry." Industria Textila 72, no. 04 (September 1, 2021): 443–48. http://dx.doi.org/10.35530/it.072.04.202013.

Full text

Abstract:

Agglomeration is an important characteristic in China’s textile industry development. But regional textile industry isseriously unbalanced, only eastern location entropy (LQ) is greater than 1 and is the highest of all, followed by thecentral, western and north-eastern regions. Total factor productivity (TFP) is an important indicator to measure theeconomic growth efficiency. The average annual growth rate (AAGR) of eastern textile industry TFP is the least andcentral TFP growth rate is the fastest. In order to investigate the relationship between agglomeration and TFP of China’stextile industry, especially at region level, this paper applies panel model to study how agglomeration influences TFPduring 2005–2018. The results show that increasing agglomeration degree restrains the TFP growth of China’s textileindustry. The coefficients of LQ on textile industry in China and four regions are all negative. There exists crowded effectin eastern textile industry. It has not formed the significant agglomeration effect in western and north-eastern textileindustry for very low agglomeration degree. So it implies that eastern textile industry can accelerate the implementationof industrial transfer and structural adjustment to lower agglomeration and maintain sustained profitability of textileenterprises. Western textile industry can strengthen agglomeration by undertaking industrial transfer from eastern regionto form agglomeration effect to promote TFP growth.

APA, Harvard, Vancouver, ISO, and other styles

10

Han, Gwangho. "Industrial Agglomeration Economies and Total Factor Productivity of Korean Regional Manufacturing." Journal of Economic Studies 38, no. 1 (February 28, 2020): 55–74. http://dx.doi.org/10.30776/jes.38.1.3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Liu, Haiying, Jing Xiu, Chunhong Zhang, and Xiaoqiang Zang. "INDUSTRIAL ENERGY CONSERVATION AND EMISSION REDUCTION TOTAL FACTOR PRODUCTIVITY IN CHINA." Environmental Engineering and Management Journal 14, no. 8 (2015): 1837–48. http://dx.doi.org/10.30638/eemj.2015.196.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Zhang, Shaohua, Tzu-Pu Chang, and Li-Chuan Liao. "A Dual Challenge in China’s Sustainable Total Factor Productivity Growth." Sustainability 12, no. 13 (July 1, 2020): 5342. http://dx.doi.org/10.3390/su12135342.

Full text

Abstract:

Since total factor productivity growth plays an essential role in China’s economic growth, the source of this growth has been a critical issue over the past decades. Hence, this paper applies an input slack-based productivity (ISP) index to investigate the contributors (i.e., labor and capital inputs) to China’s total factor productivity growth. The ISP index, combining the features of the directional distance function and Luenberger productivity index, can calculate the productivity change of each input factor under the total factor framework. According to the decomposition analyses, we find that China is confronting a dual challenge in total factor productivity growth: first, capital productivity growth exhibits a remarkable slowdown after the mid-1990s; second, although labor productivity continually expands, the relative labor efficiency among provinces has deteriorated since the 2000s. The results imply that the government should not only advocate upgrading industrial structure, but also consider balanced regional development policies for China’s sustainable growth.

APA, Harvard, Vancouver, ISO, and other styles

13

Wu, Shusheng, Bin Li, Qiaoling Nie, and Chao Chen. "Government expenditure, corruption and total factor productivity." Journal of Cleaner Production 168 (December 2017): 279–89. http://dx.doi.org/10.1016/j.jclepro.2017.09.043.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Chen, Chaofan, Qingxin Lan, Ming Gao, and Yawen Sun. "Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy." Sustainability 10, no. 4 (April 2, 2018): 1052. http://dx.doi.org/10.3390/su10041052.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Chang, Chia-Lin, and Les Oxley. "Industrial agglomeration, geographic innovation and total factor productivity: The case of Taiwan." Mathematics and Computers in Simulation 79, no. 9 (May 2009): 2787–96. http://dx.doi.org/10.1016/j.matcom.2008.09.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Zheng, Shunhui. "Evolution characteristics of total factor productivity of industrial enterprises in Fujian Province." Journal of Physics: Conference Series 1629 (September 2020): 012036. http://dx.doi.org/10.1088/1742-6596/1629/1/012036.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Todd, Douglas. "Total factor productivity growth and the productivity slowdown in the west german industrial sector, 1970-1981." Weltwirtschaftliches Archiv 124, no. 1 (March 1988): 108–26. http://dx.doi.org/10.1007/bf02708622.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Haroon, Maryiam. "Productivity Dispersion across Districts in Punjab." LAHORE JOURNAL OF ECONOMICS 24, no. 2 (July 1, 2019): 25–48. http://dx.doi.org/10.35536/lje.2019.v24.i2.a2.

Full text

Abstract:

Industrial clusters and special economic zones are key areas of focus for industrial policy makers who are aiming to expand the industrial base and increase competitiveness. Thus, the role of development of industrial clusters in the productivity improvement of manufacturing firms merits attention. We use the firm-level Census of Manufacturing Industries (CMI) and Directory of Industries (DOI) datasets to empirically investigate the relationship between agglomeration and firm level total factor productivity for different sectors in Punjab, Pakistan. Our findings suggest that there is a correlation between localization, urbanization and total factor productivity of firms in the Punjab. However, the relationship varies by sectors, necessarily pointing industrial policy towards sector-specific recommendations.

APA, Harvard, Vancouver, ISO, and other styles

19

Tao, Feng, Ling Li, and X. H. Xia. "Industry Efficiency and Total Factor Productivity Growth under Resources and Environmental Constraint in China." Scientific World Journal 2012 (2012): 1–10. http://dx.doi.org/10.1100/2012/310407.

Full text

Abstract:

The growth of China's industry has been seriously depending on energy and environment. This paper attempts to apply the directional distance function and the Luenberger productivity index to measure the environmental efficiency, environmental total factor productivity, and its components at the level of subindustry in China over the period from 1999 to 2009 while considering energy consumption and emission of pollutants. This paper also empirically examines the determinants of efficiency and productivity change. The major findings are as follows. Firstly, the main sources of environmental inefficiency of China's industry are the inefficiency of gross industrial output value, the excessive energy consumption, and pollutant emissions. Secondly, the highest growth rate of environmental total factor productivity among the three industrial categories is manufacturing, followed by mining, and production and supply of electricity, gas, and water. Thirdly, foreign direct investment, capital-labor ratio, ownership structure, energy consumption structure, and environmental regulation have varying degrees of effects on the environmental efficiency and environmental total factor productivity.

APA, Harvard, Vancouver, ISO, and other styles

20

Adofu, Ilemona, and Innocent Okwanya. "Linkages between Trade Openness, Productivity and Industrialization in Nigeria: A Co-integration Test." Research in World Economy 8, no. 2 (November 16, 2017): 78. http://dx.doi.org/10.5430/rwe.v8n2p78.

Full text

Abstract:

This study examines the effect of trade openness and total factor productivity on industrial output in Nigeria. The data used for this analysis covers the period 1981-2015. The paper employs the VAR model in estimating the effect of trade openness on industrial output. The impulse response function and the variance decomposition are used to examine the response of industrial output to shocks in trade openness and total factor productivity. The results show that trade openness has a positive increasing effect on industrial output in Nigeria while the effect of total factor productivity on industrial output is found to be insignificant. The impulse response function shows over the long run period tfP negative effect on industrial output in Nigeria. The findings of this study certainly have important policy implications: it suggests that policies geared towards increasing trade openness should be encouraged as this tends to improve industrial output. This study contributes to economics literature by looking at the degree to which trade openness and total factor productivity influence industrial output in Nigeria.

APA, Harvard, Vancouver, ISO, and other styles

21

Liang, Gefu, Dajia Yu, and Lifei Ke. "An Empirical Study on Dynamic Evolution of Industrial Structure and Green Economic Growth—Based on Data from China’s Underdeveloped Areas." Sustainability 13, no. 15 (July 21, 2021): 8154. http://dx.doi.org/10.3390/su13158154.

Full text

Abstract:

From the experiences of developed countries or areas, advanced industrial structure is an effective way to promote economic transformation and high-quality growth. This paper uses the economic development data of seven underdeveloped provinces in China in 10 years to study the relationship between industrial structure upgrading, industrial structure rationalization and green economic growth. The result shows: (1) The relationship between the upgrading of industrial structure and green total factor productivity (GTFP) is a non-linear relationship that is difficult to fit. (2) There are two turning points in the relationship curve between industrial structure upgrading and green total factor productivity (these can be called “rationalization points”). (3) The “rationalization points” are affected by the rationalization of the industrial structure. (4) The “rationalization point” divides the relationship curve into three intervals. Within the threshold range [0.661, 0.673] of the rationalization of the industrial structure, the upgrading of the industrial structure promotes the increase of green total factor productivity, while outside the range, the upgrading of the industrial structure inhibits the increase of green total factor productivity. Therefore, industrial development in underdeveloped areas should first implement rationalization of industrial structure. After the rational adjustment of the industrial structure, we will then develop a high-level industrial structure to improve the green TFP.

APA, Harvard, Vancouver, ISO, and other styles

22

Ngu, Vu Quoc. "Total Factor Productivity Growth of Industrial State‑owned Enterprises in Vietnam, 1976–98." Asean Economic Bulletin 20, no. 2 (August 2003): 158–73. http://dx.doi.org/10.1355/ae20-2e.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Rusek, Antonin. "Industrial growth in Czechoslovakia 1971–1985: Total factor productivity and capital-labor substitution." Journal of Comparative Economics 13, no. 2 (June 1989): 301–13. http://dx.doi.org/10.1016/0147-5967(89)90006-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Zhang, Yijun, Xiaoping Li, Yi Song, and Feitao Jiang. "Can green industrial policy improve total factor productivity? Firm-level evidence from China." Structural Change and Economic Dynamics 59 (December 2021): 51–62. http://dx.doi.org/10.1016/j.strueco.2021.08.005.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Al-Ayouty, Iman, and Hoda Hassaballa. "Towards Sustainable Development: Measuring Environmental Total Factor Productivity in Egypt." European Journal of Sustainable Development 9, no. 2 (June 1, 2020): 55. http://dx.doi.org/10.14207/ejsd.2020.v9n2p55.

Full text

Abstract:

Egypt’s heavy reliance on energy- and capital-intensive industries currently hinders its drive towards achieving sustainable development goals. This paper studies environmental total factor productivity (ETFP) for ten energy-intensive industries using the Malmquist index and data envelopment analysis (DEA) for the period 2002-2014. Through incorporating CO2 emissions by energy intensive industries, DEA helps identify both environmentally-efficient and inefficient industries. Findings indicate that: i) ETFP has remained almost unchanged for the 10 industries, with ‘technical progress’ improvement almost fully outweighed by an efficiency deterioration, ii) excluding the environmental component indeed yields overestimated total factor productivity (TFP). In its estimation of ETFP, the paper adds to exiting empirical literature since no similar estimation has been done for Egypt. Results may be relevant to other countries with similar industrial structures. Policy implications include the reliance on renewable sources of energy, bearing directly on the achievement of the seventh, ninth and twelfth SDG goals. Keywords: environmental total factor productivity; energy intensive industries; data envelopment analysis; Egypt

APA, Harvard, Vancouver, ISO, and other styles

26

Peng, Yuanxin, Zhuo Chen, and Jay Lee. "Dynamic Convergence of Green Total Factor Productivity in Chinese Cities." Sustainability 12, no. 12 (June 15, 2020): 4883. http://dx.doi.org/10.3390/su12124883.

Full text

Abstract:

China’s energy consumption in urban areas accounts for a large proportion of total energy consumption, and many pollutants are emitted with the energy consumption. Considering the requirement for green development of economy, it is necessary to study the green total factor productivity (GTFP) in cities. In this study, the Malmquist index, spatial autocorrelation analysis and convergence analysis are used to analyze the GTFP for 263 prefectural or higher-level cities in China. The results show a growing trend of values measured by the GTFP in Chinese cities, indicating an increase in efficiency. In addition. the eastern region has the highest efficiency, followed by the central region while the lowest being the western region. The calculated values of GTFP show a relatively strong overall spatial clustering with some local high-high clusters of high index values. GTFP also shows relatively weak divergence and no sign of convergence. Thus, we propose that, to improve GTFP and narrow the gap between regions, it would be necessary to enhance technological progress and restructuring industrial productivity in cities.

APA, Harvard, Vancouver, ISO, and other styles

27

Haider, Salman, and Javed Ahmad Bhat. "Does total factor productivity affect the energy efficiency." International Journal of Energy Sector Management 14, no. 1 (January 6, 2020): 108–25. http://dx.doi.org/10.1108/ijesm-11-2018-0010.

Full text

Abstract:

Purpose Because of growing energy consumption and increasing absolute CO2 emissions, the recent calibrations about the environmental sustainability across the globe have mandated to achieve the minimal energy consumption through employing energy-efficient technology. This study aims to estimate linkage between simple measure of energy efficiency indicator that is reciprocal of energy intensity and total factor productivity (TFP) in case of Indian paper industry for 21 major states. In addition, the study incorporates the other control variables like labour productivity, capital utilization and structure of paper industry to scrutinize their likely impact on energy efficiency performance of the industry. Design/methodology/approach To derive the plausible estimates of TFP, the study applies the much celebrated Levinsohn and Petrin (2003) methodology. Using the regional level data for the period 2001-2013, the study employs instrumental variable-generalized method of moments (GMM-IV) technique to examine the nature of relationship among the variables involved in the analysis. Findings An elementary examination of energy intensity shows that not all states are equally energy intensive. States like Goa, Rajasthan, Jharkhand and Tamil Nadu are less energy intensive, whereas Uttar Pradesh, Kerala, Chhattisgarh, Assam and Punjab are most energy-intensive states on the basis of their state averages over the whole study period. The results estimated through GMM-IV show that increasing level of TFP is associated with lower level of energy per unit of output. Along this better skills and capacity utilization are also found to have positive impact on energy efficiency performance of industry. However, the potential heterogeneity within the structure of industry itself is found responsible for its higher energy intensity. Practical implications States should ensure and undertake substantial investment projects in the research and development of energy-efficient technology and that targeted allocations could be reinforced for more fruitful results. Factors aiming at improving the labour productivity should be given extra emphasis together with capital deepening and widening, needed for energy conservation and environmental sustainability. Given the dependence of structure of paper industry on the multitude of factors like regional inequality, economic growth, industrial structure and the resource endowment together with the issues of fragmented sizes, poor infrastructure and availability and affordability of raw materials etc., states should actively promote the coordination and cooperation among themselves to reap the benefits of technological advancements through technological spill overs. In addition, owing to their respective state autonomies, state governments should set their own energy saving targets by taking into account the respective potentials and opportunities for the different industries. Despite the requirement of energy-efficient innovations, however, the cons of technological advancements and the legal frameworks on the employment structure and distributional status should be taken care of before their adoption and execution. Originality/value To the best of our knowledge, this is the first study that empirically examines the linkage between energy efficiency and TFP in case of Indian paper industry. The application of improved methods like Levinsohn and Petrin (2003) to derive the TFP measure and the use of GMM-IV to account for potential econometric problems like that of endogeneity will again add to the novelty of study.

APA, Harvard, Vancouver, ISO, and other styles

28

Wang, Nan, Wei Liu, Shanwu Sun, and Qingjun Wang. "The Influence of Complexity of Imported Products on Total Factor Productivity." Mobile Information Systems 2021 (September 9, 2021): 1–7. http://dx.doi.org/10.1155/2021/3384068.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

29

Ding, Chaoxun, and Ruidan Zhang. "The Measurement and Influencing Factors of Total Factor Productivity in the Chinese Rural Distribution Industry." Sustainability 13, no. 15 (July 31, 2021): 8581. http://dx.doi.org/10.3390/su13158581.

Full text

Abstract:

Total factor productivity (TFP) is critical to the sustainable development of the rural distribution industry. Improvements in productivity of the rural distribution industry can promote the high-quality development of the Chinese distribution industry. Studying the characteristics and influencing factors of total factor productivity in regard to the rural distribution industry in China is significant for promoting the transformation and development of the rural distribution industry. This paper uses the DEA–Malmquist Index to measure the total factor productivity (TFP) of the Chinese rural distribution industry and its decomposition index, and uses a panel data model to empirically study its influencing factors. The results show that, from 2008 to 2018, the TFP of the Chinese rural distribution industry showed a trend of rising first and then fluctuating and declining, with an average annual growth rate of 2.93%; the fluctuation direction of the TFP of the rural distribution industry in the eastern and western regions of China is basically the same, which has had a reverse change relationship with the central and northeast regions for many years. The industrial structure, urbanization rate, rural informatization rate, and conditions of the transportation facilities have significant impacts on the TFP of the rural distribution industry, among which the informatization rate has the greatest positive impact.

APA, Harvard, Vancouver, ISO, and other styles

30

Zhang, Yining, and Zhong Wu. "Intelligence and Green Total Factor Productivity Based on China’s Province-Level Manufacturing Data." Sustainability 13, no. 9 (April 29, 2021): 4989. http://dx.doi.org/10.3390/su13094989.

Full text

Abstract:

The application of intelligent technology has an important impact on the green total factor productivity of China’s manufacturing industry. Based on the provincial panel data of China’s manufacturing industry from 2008 to 2017, this article uses the Malmquist–Luenburger (ML) model to measure the green total factor productivity of China’s manufacturing industry, and further constructs an empirical model to analyze the impact mechanism of intelligence on green total factor productivity. The results show that intelligence can increase the green total factor productivity of the manufacturing industry. At the same time, mechanism analysis shows that intelligence can affect manufacturing green total factor productivity by improving technical efficiency. However, the effect of intelligence on the technological progress of the manufacturing industry is not significant. In addition, the impact of intelligence has regional heterogeneity. It has significantly promoted the green total factor productivity in the eastern and central regions of China, while its role in the western region is not obvious. The research in this article confirms that intelligence has a significant positive impact on the green total factor productivity of the manufacturing industry, and can provide suggestion for the current further promotion of the deep integration of intelligence and the green development of the manufacturing industry to achieve the strategic goal of industrial upgrading.

APA, Harvard, Vancouver, ISO, and other styles

31

Ma, Junwei, Jianhua Wang, and Philip Szmedra. "Economic Efficiency and Its Influencing Factors on Urban Agglomeration—An Analysis Based on China’s Top 10 Urban Agglomerations." Sustainability 11, no. 19 (September 28, 2019): 5380. http://dx.doi.org/10.3390/su11195380.

Full text

Abstract:

Economic efficiency is the key issue of sustainable development in urban agglomerations. To date, more attention has been paid to the estimates of productivity gains from urban agglomerations. Differing from the previous studies, this paper focuses on the influencing factors and mechanisms of the economic efficiency of urban agglomerations, and check the effects of three different externalities (industrial specialization, industrial diversity and industrial competition) on the economic efficiency of urban agglomerations. The selected samples are multiple urban agglomerations, and the economic efficiency of urban agglomerations includes single factor productivity and total factor productivity. China’s top 10 urban agglomerations are selected as the case study and their differences in economic efficiency are portrayed comparatively. Firstly, a theoretical analysis framework for three different externalities effect mechanisms on the economic efficiency of urban agglomerations is incorporated. Secondly, economic efficiency measurement index system composes of labor productivity, capital productivity, land productivity and total factor productivity, and the impact of various factors on the economic efficiency of urban agglomerations is tested. The results confirm some phenomena (MAR externality, Jacobs externality and Porter externality) discussed or mentioned in the literature and some new findings regarding the urban agglomerations, derive policy implications for improving economic efficiency and enhancing the sustainability of urban agglomerations, and suggest some potentials for improving the limitations of the research.

APA, Harvard, Vancouver, ISO, and other styles

32

Yi, Fangqing, and Zenglian Zhang. "Energy Efficiency, Policy and GTFP." E3S Web of Conferences 53 (2018): 01033. http://dx.doi.org/10.1051/e3sconf/20185301033.

Full text

Abstract:

The environmental and resource constraints on economic growth are increasingly evident. China urgently needs to reshape its economic growth momentum. The increase in green total factor productivity is particularly necessary for the growth of the quantity and quality of the economy. This paper selects the provincial panel data of 30 provinces in China from 2001 to 2015, and establishes a panel exchangeable errors model to analyze the impact of eight indicators on green total factor productivity (GTFP) and verifies its effectiveness. Empirical analysis shows that inter-provincial government competition, environmental regulation, energy consumption, and capital stock have a significant impact on green total factor productivity. The influence of foreign direct investment, industrial structure, and industrialization level on the total factor productivity of green is not significant. Therefore, the government should adopt suitable, flexible and diverse environmental regulation policies, promote energy-saving emission reduction and technology innovations through policies such as taxes and subsidies, strengthen the linkage mechanism between industrial structure upgrading and energy efficiency, to increase green total factor productivity.

APA, Harvard, Vancouver, ISO, and other styles

33

Ghose, Arpita, and Paramita Roy Biswas. "Inter-Industrial Variation in Total Factor Productivity Growth of Manufacturing Sector of West Bengal." Indian Economic Journal 59, no. 2 (July 2011): 29–50. http://dx.doi.org/10.1177/0019466220110203.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Thabet, Khaled. "Industrial structure and total factor productivity: the Tunisian manufacturing sector between 1998 and 2004." Annals of Regional Science 54, no. 2 (March 2015): 639–62. http://dx.doi.org/10.1007/s00168-015-0670-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Wang, Qian, Shenggang Ren, and Ya Hou. "Atmospheric environmental regulation and industrial total factor productivity: the mediating effect of capital intensity." Environmental Science and Pollution Research 27, no. 26 (June 11, 2020): 33112–26. http://dx.doi.org/10.1007/s11356-020-09523-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Shen, Yongchang, Shujing Yue, Shiqian Sun, and Mengqi Guo. "Sustainable total factor productivity growth: The case of China." Journal of Cleaner Production 256 (May 2020): 120727. http://dx.doi.org/10.1016/j.jclepro.2020.120727.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Kemal, A. "Industrial Competitiveness of Pakistan (2000-10)." LAHORE JOURNAL OF ECONOMICS 12, Special Edition (September 1, 2007): 16–29. http://dx.doi.org/10.35536/lje.2007.v12.isp.a2.

Full text

Abstract:

Though Pakistan’s exports have increased significantly, analyses have shown that Pakistan’s industrial competitiveness is limited to a narrow range of products. This paper looks at the factors affecting Pakistan’s competitiveness ranking and relates these various factors to trends in Pakistan’s total factor productivity. In addition to looking at the components of Pakistan’s competitiveness ranking, this paper details the steps required for Pakistan to increase its global industrial competitiveness.

APA, Harvard, Vancouver, ISO, and other styles

38

Lin, Boqiang, and Ziyue Chen. "Does factor market distortion inhibit the green total factor productivity in China?" Journal of Cleaner Production 197 (October 2018): 25–33. http://dx.doi.org/10.1016/j.jclepro.2018.06.094.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Ramachandran, Renjith, Ketan Reddy, and Subash Sasidharan. "Agglomeration and Productivity: Evidence from Indian Manufactuaring." Studies in Microeconomics 8, no. 1 (June 2020): 75–94. http://dx.doi.org/10.1177/2321022220923211.

Full text

Abstract:

This study analyses the impact of industrial agglomeration on the total factor productivity (TFP) of Indian manufacturing. We employ plant-level data from the Annual Survey of Industries (ASI) to measure TFP and industrial agglomeration. Our econometric analysis discerns a positive impact of industrial agglomeration on plant productivity. In addition, we find that the larger plants are the beneficiaries of productivity gains associated with agglomeration. Further, our findings are robust to alternate measures of TFP.

APA, Harvard, Vancouver, ISO, and other styles

40

Wu, Danjie. "Impact of Green Total Factor Productivity in Marine Economy Based on Entropy Method." Polish Maritime Research 25, s3 (December 1, 2018): 141–46. http://dx.doi.org/10.2478/pomr-2018-0123.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

41

Harris, Richard, and Shengyu Li. "Government assistance and total factor productivity: firm-level evidence from China." Journal of Productivity Analysis 52, no. 1-3 (November 1, 2019): 1–27. http://dx.doi.org/10.1007/s11123-019-00559-4.

Full text

Abstract:

Abstract Industrial policy, particularly through the provision of large-scale assistance to industry in the form of ‘tax holidays’ and subsidies to firms, is very important in China. A major contribution of this paper is to introduce firm-level measures of assistance directly into industry-level production functions determining firm output using Chinese firm-level panel data for 1998–2007 and analysing the impact of government assistance on TFP at the firm-level. Our results indicate inverted U-shaped gains from assistance: across the 26 industries considered, firms receiving assistance rates of 1–10, 10–19, 20–49 and 50+% experienced on average 4.5, 9.4, 9.2 and −3% gains in TFP level, respectively. We then decompose the growth of TFP and relate it to assistance and formal political connections between firms and the government. We find in general firms receiving assistance contributed relatively more to TFP growth than non-assisted firms. However, this was largely through new firms being ‘encouraged’ to start-up rather than through firms open throughout 1998 to 2007 improving. There is also evidence that closure rates were truncated as a result of assistance. Moreover, the better results for assisted firms was very much ‘driven’ by a sub-group that received assistance but had no formal political connections and were not State-owned.

APA, Harvard, Vancouver, ISO, and other styles

42

Feng, Xiwen, Mingshang Xin, and Xinghua Cui. "Impact of Global Value Chain Embedding on Total-Factor Energy Productivity of Chinese Industrial Sectors." Journal of Renewable Energy 2020 (July 15, 2020): 1–12. http://dx.doi.org/10.1155/2020/6239640.

Full text

Abstract:

In the four decades since China’s reform and opening up, China has been playing an active role in global value chain (GVC) due to its abundant resources. China has gained enormous benefits from opening up, but has also suffered huge energy costs in the process. In this study, we incorporated global value chains and energy consumption into a unified analysis framework and calculated the energy total-factor productivity (ETFP) of China’s industry and the degree of participation in GVC. In addition, in order to discover the contradictions and problems between China's participation in global value chains and the improvement of total energy factor productivity, the panel smooth transformation model (PSTR) was used to empirically test the nonlinear relationship between the ETFP and the degree of participation in GVC in China. From the analysis results, GVC participation, as well as the subdivided shallow GVC participation and deep GVC participation, first promoted the effect on ETFP and then suppressed it, showing an inverted U-shaped single threshold characteristic. The results indicated that in the progress of starting to participate in the GVC, the effect of technological progress of the GVC overweighed the scale effect of energy consumption, resulting in the growth of ETFP. However, due to the gradual reduction of technology dividends and the “low-end lock-in” situation, China was placed in the value chain by the developed countries, and the technological effect was gradually smaller than the scale effect of energy consumption. As a result, the increase in the total-factor productivity of energy was inhibited. At the same time, in the further examination of industry heterogeneity, the inverted U-shaped influence trend was more significant in high energy-consuming industries. The conclusions of this study can provide a new perspective and policy focus for China's participation in GVC to achieve the goal of increasing ETFP.

APA, Harvard, Vancouver, ISO, and other styles

43

Zhi, Mao, Goh Bee Hua, Shou Qing Wang, and George Ofori. "Total factor productivity growth accounting in the construction industry of Singapore." Construction Management and Economics 21, no. 7 (October 2003): 707–18. http://dx.doi.org/10.1080/0144619032000056126.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Sohag, Kazi, Kristina Chukavina, and Nahla Samargandi. "Renewable energy and total factor productivity in OECD member countries." Journal of Cleaner Production 296 (May 2021): 126499. http://dx.doi.org/10.1016/j.jclepro.2021.126499.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Sena, Vania. "Total factor productivity and the spillover hypothesis: Some new evidence." International Journal of Production Economics 92, no. 1 (November 2004): 31–42. http://dx.doi.org/10.1016/j.ijpe.2003.10.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Metcalfe, J. Stanley. "The Evolutionary Explanation of Total Factor Productivity Growth : Macro Measurement and Micro Process." Revue d’économie industrielle 80, no. 1 (1997): 93–114. http://dx.doi.org/10.3406/rei.1997.1670.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Wei, Xinyi, Qiuguang Hu, Weiteng Shen, and Jintao Ma. "Influence of the Evolution of Marine Industry Structure on the Green Total Factor Productivity of Marine Economy." Water 13, no. 8 (April 17, 2021): 1108. http://dx.doi.org/10.3390/w13081108.

Full text

Abstract:

The 14th five-year plan emphasizes the importance of marine ecology and environmental protection, and the green concept is incorporated into the high-quality development system of the marine economy. This research used the data of 11 coastal provinces and cities in China from 2006 to 2016, based on the super-efficiency slack-based measure model and global Malmquist index model. The objective was to calculate the green total factor productivity (GTFP) of the marine economy, to study the impact of the evolution of the marine industrial structure on marine economic GTFP. The study found the following: (1) in general, the upgrade of marine industrial structure promoted the growth of marine economic GTFP and presented an inverted “U” trend of initially promoting and then suppressing. Spatially, only the advancement and rationalization of industrial structure in the Yellow and Bohai Sea regions inhibited the growth of marine economic GTFP. In terms of time, the advanced marine industrial structure promoted the growth of GTFP from 2006 to 2010, whereas that of industrial structure inhibited the growth of GTFP from 2011 to 2016. (2) The GTFP of the marine economy showed an increasing trend, but the conversion rate of production technology is low. Falling into the “efficiency trap” of highly advanced technology input and low-efficiency technology output should be avoided. (3) Affected by the mismatch of regional resources or industrial structure, government intervention showed an “opposite” mechanism in areas with different marine economic strengths. Government intervention in areas with higher marine economic strength was conducive to GTFP growth, whereas government intervention in areas with weaker marine economic strength would hinder GTFP growth.

APA, Harvard, Vancouver, ISO, and other styles

48

Ambashi, Masahito. "Competition Effects and Industrial Productivity: Lessons from Japanese Industry." Asian Economic Papers 16, no. 3 (November 2017): 214–49. http://dx.doi.org/10.1162/asep_a_00568.

Full text

Abstract:

This study mainly investigates the causal relation between the degree of competition, which is measured by the Lerner index, and the total factor productivity (TFP) growth rate on the basis of the Japanese industry-level panel data from 1980 to 2008. While the main finding uncovers a positive effect of competition on the TFP growth rate in manufacturing industries throughout the sample period, 1980–2008, the observed effect for non-manufacturing industries at this time is slightly negative. This unique finding of a negative competition effect suggests that the Schumpeterian hypothesis may be applicable in non-manufacturing industries.

APA, Harvard, Vancouver, ISO, and other styles

49

Cheng, Zhonghua, and Xiai Shi. "Can Industrial Structural Adjustment Improve the Total-Factor Carbon Emission Performance in China?" International Journal of Environmental Research and Public Health 15, no. 10 (October 18, 2018): 2291. http://dx.doi.org/10.3390/ijerph15102291.

Full text

Abstract:

How to improve the industrial total-factor carbon emission performance (TCPI), or total-factor carbon productivity, through industrial structural adjustment, is crucial to China’s energy conservation and emission reduction and sustainable growth. In this paper, we use a dynamic spatial panel model to empirically analyze the effect of industrial structural adjustment on TCPI of 30 provinces in China from 2000 to 2015. The results show that most of the provinces with high TCPI are located in the eastern coastal areas, while the provinces with relatively low TCPI are to be found in the central and western regions. The spatial auto-correlation tests show that there are significant global spatial auto-correlation and local spatial agglomeration characteristics in TCPI. The regression results of the dynamic spatial panel models show that at the national level, the structure of industrialization, the industrial structure of heavy industrialization, the coal-based energy consumption structure and the endowment structure have significant negative effects on the improvement of TCPI. The expansion of industrial enterprise scale, on the other hand, is conducive to an improvement in TCPI while the effects of foreign direct investment (FDI) structure and ownership structure on TCPI are not significant. At the regional level, there are certain differences in the effects of different types of industrial structural adjustment on TCPI.

APA, Harvard, Vancouver, ISO, and other styles

50

Dong, Xu, Yali Yang, Xiaomeng Zhao, Yingjie Feng, and Chenguang Liu. "Environmental Regulation, Resource Misallocation and Industrial Total Factor Productivity: A Spatial Empirical Study Based on China’s Provincial Panel Data." Sustainability 13, no. 4 (February 23, 2021): 2390. http://dx.doi.org/10.3390/su13042390.

Full text

Abstract:

A vast theoretical and empirical literature has been devoted to exploring the relationship between environmental regulation and total factor productivity (TFP), but no consensus has been reached and the reason may be attributed to the fact that the resource reallocation effect of environmental regulation is ignored. In this paper, we introduce resource misallocation in the process of discussing the impact of environmental regulation on TFP, taking China’s provincial industrial panel data from 1997 to 2017 as a sample, and the spatial econometric method is employed to investigate whether environmental regulation has a resource reallocation effect and affects TFP. The results indicate that there is a U-shaped relationship between environmental regulation and industrial TFP and a negative spatial spillover effect of environmental regulation on industrial TFP at the provincial level in China. Both capital misallocation and labor misallocation will lead to the loss of industrial TFP. Capital misallocation has a negative spatial spillover effect on industrial TFP, while labor misallocation is just the opposite. Environmental regulation can produce a positive resource reallocation effect, which in turn promotes the industrial TFP in the range of 28% to 33%, while capital misallocation and labor misallocation are only partial mediator.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!