scholarly journals How Does Industrial Digitalization Affect Enterprise Environmental Performance?

2021 ◽  
Author(s):  
Huwei Wen ◽  
Chien-Chiang Lee ◽  
Ziyu Song
Keyword(s):  
Total Factor Productivity ◽  
Environmental Performance ◽  
Jel Classification ◽  
Factor Productivity ◽  
Production Scale ◽  
Manufacturing Enterprises ◽  
Treatment Facilities ◽  
Production Technologies ◽  
The Relationship ◽  
Technology Effects

Abstract Despite the increasing use of digital technology in industrial production, how industrial digitalization affects the environmental performance of production activities remains unclear. This research contributes to the literature on the relationship between industrial digitalization and enterprise environmental performance by employing a large sample of Chinese manufacturing enterprises. Results indicate that the environmental performance of manufacturing enterprises has been significantly improved in the process of industrial digital transformation. Structural and technology effects are the influencing mechanisms. Industrial digitalization reduces the production scale of heavy polluting enterprises and improves product innovation and green total factor productivity, but it has an insignificant effect on total factor productivity. Moreover, industrial digitalization improves enterprise environmental performance by introducing front-end cleaner production technologies, rather than by increasing pipe-end pollutant treatment facilities.JEL Classification: Q56, O13, L86

scholarly journals The impact of research and development activity on the TFP level in manufacturing in Poland

Equilibrium ◽  
2019 ◽  
Vol 14 (4) ◽  
pp. 711-737 ◽  
Author(s):  
Elżbieta Roszko-Wójtowicz ◽  
Maria M. Grzelak ◽  
Iwona Laskowska
Keyword(s):  
Research And Development ◽  
Total Factor Productivity ◽  
Manufacturing Industry ◽  
Value Added ◽  
High Tech ◽  
Factor Productivity ◽  
Development Activity ◽  
Manufacturing Enterprises ◽  
The Impact ◽  
The Relationship

Research background: The paper presents the issue of total factor productivity in the manufacturing industry in Poland. It has been assumed that total factor productivity (TFP) is a synthetic measure of efficiency of the production process and a measure of the impact of technical progress on the rate of economic growth. Purpose of the article: The main aim of the paper is to assess the differentiation in the level of total factor productivity (TFP) occurring among the Section C manufacturing divisions in Poland. In particular, the paper raises the issue of measuring and analysing the relationship between expenditure on research and development and the level of TFP in manufacturing divisions in Poland. Methods: In the presented research, the TFP level was determined by using the two-factor Cobb-Douglas production function, while econometric panel models were used to assess the studied relationship. Findings & Value added: The presented considerations show that manufacturing divisions in Poland are diversified in terms of total factor productivity. Generally, manufacturing divisions with high R&D intensity, i.e. divisions classified as so-called high-tech ones, are characterised by a high TFP level. The econometric analysis carried out allows us to conclude that expenditure on R&D incurred in manufacturing enterprises significantly affects the level of TFP.

Firm Characteristics and Total Factor Productivity: Evidence from Indian Manufacturing Firms

2017 ◽  
Vol 11 (1) ◽  
pp. 77-98 ◽  
Author(s):  
Lopamudra D. Satpathy ◽  
Bani Chatterjee ◽  
Jitendra Mahakud
Keyword(s):  
Total Factor Productivity ◽  
Ordinary Least Squares ◽  
Jel Classification ◽  
Raw Material ◽  
Firm Characteristics ◽  
Manufacturing Companies ◽  
Factor Productivity ◽  
Size Of Firms ◽  
Specific Factors

Measurement of the productivity of firms is an important research issue in productivity literature. Over the years, various methods have been developed to measure firm productivity across the globe. But there is no unanimity on the use of methods, and research on the identification of factors which determine productivity has been neglected. In view of these gaps, this study aims to measure total factor productivity (TFP) and tries to identify firm-specific factors which determine productivity of Indian manufacturing companies. The study is based on data of 616 firms from 1998–99 to 2012–13. To measure TFP, the Levinsohn–Petrin (L-P) method has been employed, and the fully modified ordinary least squares (FMOLS) method has been used to identify factors that affect TFP. The results reveal that embodied and disembodied technology plays a crucial role in the determination of productivity overall in manufacturing and other sub-industries. Similarly, the size of firms and intensity of raw material imports are also important for the determination of productivity across the sub-industries. JEL Classification: C14, C33, D24, L60

scholarly journals The Relationship Between Public Expenditures, Total Factor Productivity and Economic Growth: A Panel Data Analysis

2021 ◽  
Author(s):  
Remzi Can Yılmaz ◽  
Ahmet Rutkay Ardoğan
Keyword(s):  
Economic Growth ◽  
Total Factor Productivity ◽  
Developing Economies ◽  
Panel Data Analysis ◽  
Statistical Significance ◽  
Data Availability ◽  
Public Expenditures ◽  
Annual Data ◽  
Factor Productivity ◽  
The Relationship

According to the economics literature, there are two main sources of economic growth. While the first of the resources is the accumulation of production factors, the other is the part of the output that cannot be explained by the amount of input used in production, in other words, the total factor productivity. The level of total factor productivity is measured according to how efficiently the inputs are used in the production process. In this study, the hypothesis that public spending affects real economic growth through total productivity is investigated. In the first stage, whether the changes in public expenditures affect the total factor productivity or not; if it does, to what extent and in what direction it has been tried to be revealed. In the second stage, the effect of total factor productivity on economic growth was examined and the statistical significance, direction and extent of the relationship between variables were investigated. Annual data were used in the study and the year range is 2000-2017. The sampling economies were selected according to data availability, and there are a total of 20 developed and developing economies. Research was conducted using multiple panel regression analysis. According to the findings, the relationship between public expenditures and total factor productivity is statistically significant. An increase in public expenditures reduces the total factor productivity. The relationship between total factor productivity and economic growth is statistically significant, and an increase in total factor productivity also increases economic growth. An increase in public expenditures affects economic growth negatively by reducing the total factor productivity.

scholarly journals The Relationship between Environmental Regulation and Green Total Factor Productivity in China: An Empirical Study Based on the Panel Data of 177 Cities

2020 ◽  
Vol 17 (15) ◽  
pp. 5287 ◽  
Author(s):  
Mingliang Zhao ◽  
Fangyi Liu ◽  
Wei Sun ◽  
Xin Tao
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Inflection Point ◽  
Factor Productivity ◽  
Positive Effects ◽  
Development Level ◽  
The Mean ◽  
The Relationship

Promoting the coordinated development of industrialization and the environment is a goal pursued by all of the countries of the world. Strengthening environmental regulation (ER) and improving green total factor productivity (GTFP) are important means to achieving this goal. However, the relationship between ER and GTFP has been debated in the academic circles, which reflects the complexity of this issue. This paper empirically tested the relationship between ER and GTFP in China by using panel data and a systematic Gaussian Mixed Model (GMM) of 177 cities at the prefecture level. The research shows that the relationship between ER and GTFP is complex, which is reflected in the differences and nonlinearity between cities with different monitoring levels and different economic development levels. (1) The relationship between ER and GTFP is linear and non-linear in different urban groups. A positive linear relationship was found in the urban group with high economic development level, while a U-shaped nonlinear relationship was found in other urban groups. (2) There are differences in the inflection point value and the variable mean of ER in different urban groups, which have different promoting effects on GTFP. In key monitoring cities and low economic development level cities, the mean value of ER had not passed the inflection point, and ER was negatively correlated with GTFP. The mean values of ER variables in the whole sample, the non-key monitoring and the middle economic development level cities had all passed the inflection point, which gradually promoted the improvement of GTFP. (3) Among the control variables of the different city groups, science and technology input and the financial development level mainly had positive effects on GTFP, while foreign direct investment (FDI) and fixed asset investment variables mainly had negative effects.

New Evidence on the Relationship Between Economic Freedom and Growth: A Panel Cointegration Analysis for The Case of OECD

2012 ◽  
Vol 12 (3) ◽  
pp. 1850263 ◽  
Author(s):  
Ekrem Erdem ◽  
Can Tansel Tugcu
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Total Factor Productivity ◽  
Economic Freedom ◽  
Global Financial Crisis ◽  
Oecd Countries ◽  
Cointegration Analysis ◽  
Factor Productivity ◽  
The Impact ◽  
The Relationship

The aim of this paper is to find a new answer to an old question “Is economic freedom good or not for economies?” which was refreshed after the Global Financial Crisis of 2008. For this purpose, the relationship between economic freedom and economic growth, and the relationship between economic freedom and total factor productivity in OECD countries were investigated by using panel data for the period of 1995-2009. Study employed the recently developed cointegration test by Westerlund (2007) and the estimation technique by Bai and Kao (2006) which account for cross-sectional dependence that is an important problem in the panel data studies. Although no significant relationship found between economic freedom and total factor productivity, cointegration analysis revealed that economic freedom matters for economic growth in OECD countries in the long-run, and estimation results showed that direction of the impact is negative.

scholarly journals Finance and Development: A Tale of Two Sectors

2011 ◽  
Vol 101 (5) ◽  
pp. 1964-2002 ◽  
Author(s):  
Francisco J Buera ◽  
Joseph P Kaboski ◽  
Yongseok Shin
Keyword(s):  
Quantitative Analysis ◽  
Total Factor Productivity ◽  
Financial Frictions ◽  
Substantial Part ◽  
Factor Productivity ◽  
Country Differences ◽  
Cross Country ◽  
Relative Productivity ◽  
The Relationship ◽  
Two Sectors

We develop a quantitative framework to explain the relationship between aggregate/sector-level total factor productivity (TFP) and financial development across countries. Financial frictions distort the allocation of capital and entrepreneurial talent across production units, adversely affecting measured productivity. In our model, sectors with larger scales of operation (e.g., manufacturing) have more financing needs, and are hence disproportionately vulnerable to financial frictions. Our quantitative analysis shows that financial frictions account for a substantial part of the observed cross-country differences in output per worker, aggregate TFP, sector-level relative productivity, and capital-to-output ratios. (JEL E23, E44, O41, O47)

scholarly journals DINAMIKA TOTAL FACTOR PRODUCTIVITY INDUSTRI BESAR DAN SEDANG INDONESIA

2014 ◽  
Vol 16 (3) ◽  
pp. 277-308
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Manufacturing Sector ◽  
Jel Classification ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Catching Up ◽  
Using Data

This paper calculates and decomposes the Total Factor Productivity (TFP) for large and medium scale industry in Indonesia covering the period of 2000-2009. By using Data Envelopment Analysis (DEA)  method, the result shows there is a shift of the supporting factors on the growth of TFP on manufacturing sector within the 2 (two) sample period. In the period of 2000-2004, efficiency change becomes the main contributor on the growth of TFP. Whereas in the period of 2005-2009, technical change becomes the main supporting factor of TFP,however it goes along with the growth of negative efficiency change or the decline of the company’s catching-up effect ability to adapt with the more advance technology. The grouping of the sample across subsectors, technical change and also efficiency change shows the declining amount of manufacture industry with superior productivity. Furthermore, the number of low and weakening catching-up industry is increasing.  Keywords: Indonesian manufacturing, total factor productivity, technical change, efficiency change, economic scale change, Data Envelopment Analysis JEL Classification: L6, M11

scholarly journals Sustainable Green Growth in Developing Economies

2022 ◽  
Vol 30 (6) ◽  
pp. 1-15
Author(s):  
Ruoyu He ◽  
Tomas Baležentis ◽  
Dalia Štreimikienė ◽  
Zhiyang Shen
Keyword(s):  
Total Factor Productivity ◽  
Environmental Performance ◽  
Developing Economies ◽  
Chinese Government ◽  
Factor Productivity ◽  
Green Growth ◽  
Average Growth ◽  
Belt And Road ◽  
Desirable And Undesirable Outputs ◽  
The Belt And Road

The Belt and Road Initiative (BRI) initiated by Chinese government could be regarded as a systematic framework for promoting economic cooperation and development among the countries along the Belt and Road and China. This paper attempts to analyze economic and environmental performance in 61 developing countries along Belt and Road. An additive total factor productivity growth measure allows aggregating contributions of individual countries along the BRI to construct a reasonable measure. Both desirable and undesirable outputs are considered. The growth in the total factor productivity is decomposed with respect to the economic and environmental contributions. The annual average growth rate of green productivity is 3.1% and the disparity of economic and environmental performance could be observed among countries. Some countries show robust economic growths while environmental performance slows down green growth. This indicates that developing economies should pay attention to environmental impacts and promote sustainable development by sharing emission reduction technologies.

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