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Journal articles on the topic 'Industrial total factor productivity'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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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.

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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

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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.

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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.

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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

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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.

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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.

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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, wo

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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.

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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.

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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 impleme

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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.

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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 i

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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.

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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 indust

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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.

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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.

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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.

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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 correla

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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.

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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 inef

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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.

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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 indus

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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.

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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 turn

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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.

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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.

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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.

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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.

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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’ improveme

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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.

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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

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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.

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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

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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.

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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 o

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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.

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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 di

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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.

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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 indus

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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.

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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

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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.

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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 comp

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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 gr

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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.

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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

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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.

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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

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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.

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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.

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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.

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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.

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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.

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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 follo

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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.

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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 a

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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.

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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 an

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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.

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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 enviro

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