The impact of external debt on total factor productivity and growth in HIPCs: non-linear regression approaches

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sisay Demissew Beyene ◽  
Balázs Kotosz
Keyword(s):  
Total Factor Productivity ◽  
Threshold Model ◽  
External Debt ◽  
Seemingly Unrelated Regression ◽  
Complete Analysis ◽  
Threshold Values ◽  
Factor Productivity ◽  
Content Type ◽  
Non Linear ◽  
The Impact

Purpose The purpose of this study is to provide an empirical analysis of the impact of external debt on total factor productivity (TFP) and growth along with the TFP channel through which external debt affects the growth of heavily indebted poor countries (HIPCs). Design/methodology/approach This study uses panel data econometrics; basically, the seemingly unrelated regression (SUR) and alternative non-linear (panel threshold) models. For robustness check, it also uses panel-corrected standard errors, feasible generalized least squares and SUR (using alternative variables). Findings External debt significantly reduces both TFP and growth. Besides, it confirms that the relationship between external debt and TFP and gross domestic product growth is non-linear. Further external debt can affect the growth of HIPCs through the TFP channel. However, the threshold model result reveals weak evidence of threshold values although there are some threshold values of 67 and 54 for TFP and growth models, respectively. Originality/value To the best of the authors’ knowledge, this is the first study on most concerned countries (HIPCs) that shows a detailed and complete analysis of the TFP channel and the impact of external debt on growth. Thus, it provides appropriate and sound policies that consider the unique characteristics of the countries. Unlike most previous findings, this study does not support an inverted U-shape relationship between external debt and growth. Further, it provides insights into the relationships among TFP, external debt and growth. Moreover, it considers basic panel econometric tests like cross-sectional dependence, uses a non-linear simultaneous equations model along with the alternative non-linear model and is supported by different robustness checks.

Assessing the impact of knowledge management on total factor productivity

2019 ◽  
Vol 11 (1) ◽  
pp. 134-146 ◽  
Author(s):  
Mina Sami ◽  
Randa El Bedawy
Keyword(s):  
Knowledge Management ◽  
Total Factor Productivity ◽  
Current Literature ◽  
Organizational Level ◽  
Factor Productivity ◽  
Data Set ◽  
Content Type ◽  
Financial Indicator ◽  
Percent Increase ◽  
The Impact

Purpose The purpose of this paper is to examine the impact of knowledge management (KM) on the total factor productivity (TFP) at the organizational level in Egypt. Design/methodology/approach Using the novel available EC 2013 data set, which includes approximately 60,000 private organizations in Egypt, the paper explores the relationship between KM and TFP. For the purpose of dealing with endogeneity, the two-stage least squares econometric model has been implemented. Findings The study reveals that KM impacts positively the TFP of the Egyptian organizations. Conspicuously, each 10 percent increase in KM is associated with 9.3 percent increase in TFP. Originality/value The role of KM in the organizations has been under-researched globally, especially in Africa. This study contributes to the current literature by assessing the impact of KM on TFP, which represents the most comprehensive measure of the firm productivity; by implementing a novel instrumental variable in order to deal with endogeneity between KM and TFP; and by generating a more nuanced measure for the knowledge intensity that is not based on any financial indicator as in the most of the previous studies. Original findings can be highlighted from the paper as it demonstrates that the impact of KM is more important than proposed by the current literature. Conspicuously, the KM does not merely impact the customer satisfaction, the quality improvement and the profit margin, but it also impacts the TFP of the organizations.

scholarly journals Research on the Impact of Green Technology Innovation on Energy Total Factor Productivity, Based on Provincial Data of China

2021 ◽  
Vol 9 ◽  
Author(s):  
Mengxin Wang ◽  
Yanling Li ◽  
Gaoke Liao
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Technology Innovation ◽  
Threshold Model ◽  
Threshold Effect ◽  
Green Technology ◽  
Mediating Effect ◽  
Factor Productivity ◽  
Influence Mechanism ◽  
The Impact

Against the background of carbon peaking and carbon neutralization, green technology innovation plays an important role in promoting the energy total factor productivity (TFP). This study verifies the impact of green technology innovation on energy TFP in a complete sample and the subsamples by region, by constructing a panel threshold model, and analyzes its influence mechanism on the basis of the mediating effect test based on annual provincial data of mainland China from 2005 to 2018. The empirical results reveal the following: first, with the level of economic development as the threshold variable, there is a threshold effect in the impact of green technology innovation on the energy TFP; second, green technology innovation has an impact on the energy TFP through industrial structure upgrading; that is, industrial structure has a mediating effect in the influence mechanism; and third, there is heterogeneity in the impact of green technology innovation on the energy TFP among different regions in China, and the threshold effect only exists in the western region, since the central and eastern regions have crossed a certain developmental stage.

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

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

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

scholarly journals Improvement of Different Types of Environmental Regulations on Total Factor Productivity: A Threshold Effect Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Xubin Lei ◽  
Shusheng Wu
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Environmental Regulations ◽  
Threshold Model ◽  
Threshold Effect ◽  
Impact Behavior ◽  
Factor Productivity ◽  
Data Set ◽  
Different Types ◽  
The Impact

Based on the distinction of different types of environmental regulations, this paper attempts to test the threshold effect of environmental regulation on the total factor productivity (TFP) by employing a panel threshold model and a province-level panel data set during 2006–2016. Research results show that the influence of command-and-control and market incentive environmental regulation on the total factor productivity has a single threshold conversion characteristic of foreign direct investment (FDI) and financial scale, but the impact behavior and influence degree around the threshold are inconsistent. The effect of voluntary conscious environmental regulation on the total factor productivity has a single threshold conversion feature of human capital, and moderately enhanced intensity of environmental regulation is conducive to promoting the total factor productivity after crossing the threshold. Finally, in order to enhance the regional total factor productivity, relevant policy recommendations are proposed.

What drives total factor productivity and its growth in post-communist countries? The case of the Czech food industry

2020 ◽  
Vol 10 (3) ◽  
pp. 285-305
Author(s):  
Ivana Blažková ◽  
Ondřej Dvouletý ◽  
Ondřej Machek
Keyword(s):  
Total Factor Productivity ◽  
Food Industry ◽  
Generalized Method Of Moments ◽  
Sustainable Growth ◽  
Factor Productivity ◽  
Firm Age ◽  
Firm Level ◽  
Data Set ◽  
Content Type ◽  
The Impact

PurposeThe paper aims to investigate factors that drive the total factor productivity (TFP) and its growth in the Czech food industry over 2003–2017. The authors’ analysis focuses on firm-level characteristics such as location choice, sub-sector affiliation, use of debt, liquidity, asset turnover, firm size and firm age.Design/methodology/approachThe determinants of productivity were tested econometrically by estimation of multivariate regression models. The firm-level panel data set consisted of 14,488 observations (data of 980 firms spanning 15 years). TFP was estimated by three regression-based techniques – ordinary least squares (OLS) regression, instrumental variables (IV) approach and two-way generalized method of moments (GMM) regression. All three measures of TFP were used as outcome variables to estimate the impact of firm-level determinants on both TFP level and growth.FindingsThe results have shown statistically significant and reversed U-shaped relationship between the firm age and the TFP level (with a turning point in the age of 12.5 years). However, the dynamic models investigating the TFP growth have found that younger firms achieve higher productivity growth in comparison with older ones. Higher market share and assets turnover were positively associated with both TFP level and its growth.Research limitations/implicationsThis study brings several relevant propositions for future research. First, the authors recommend future researchers to study not only differences in the levels of productivity but also determinants of its growth. Second, the authors believe that adding a non-linear component to age as a factor explaining changes in the levels of productivity might be a very relevant contribution to the literature.Originality/valueAlthough it is generally accepted that successful and sustainable growth of firms, regions and economies can be achieved particularly through viable companies with high productivity, there is still a limited number of firm-level studies explaining the determinants of productivity levels and growth in agribusiness sectors in transition economies. Therefore, this study is expected to contribute to a better understanding of this important topic.

scholarly journals Research on the Impact of Government Environmental Information Disclosure on Green Total Factor Productivity: Empirical Experience from Chinese Province

2022 ◽  
Vol 19 (2) ◽  
pp. 729
Author(s):  
Liang Zhao ◽  
Liangyu Chen
Keyword(s):  
Economic Development ◽  
Total Factor Productivity ◽  
Information Disclosure ◽  
Threshold Model ◽  
Environmental Information ◽  
Factor Productivity ◽  
Urban Economic ◽  
Urban Economic Development ◽  
Environmental Information Disclosure ◽  
The Impact

Government environmental information disclosure is an important means to promote environmental supervision and law enforcement, and improve the level of environmental management. In order to explore the impact of government environmental information disclosure on the sustainability of urban economic growth, this paper uses the Pollution Information Transparency Index (PITI) to measure the degree of government environmental information disclosure, studies its effect on green total factor productivity through two-way fixed effect model and systematic GMM estimation method, and further adopts threshold model to study whether there is heterogeneity in this effect. The results show that: (1) Each unit of government environmental information disclosure will increase green total factor productivity by 0.2 units. (2) Considering the endogeneity, the promotion of government environmental information disclosure to green total factor productivity has increased. (3) The degree of government environmental information disclosure plays a non-linear role in the path of green total factor productivity. The greater the degree of economic development, the more obvious the effect of government environmental information disclosure on green total factor productivity. Therefore, this paper believes that the government should strengthen the disclosure of environmental information based on the urban economic development to ensure the sustainability of urban economic development.

Examining the Impact and Influencing Channels of Emission Trading Pilot Markets in China

2020 ◽  
Vol 11 (1) ◽  
pp. 136-136
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul
Keyword(s):  
Total Factor Productivity ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Emission Trading ◽  
Chinese Government ◽  
Synergy Effect ◽  
Factor Productivity ◽  
Plan Period ◽  
Carbon Emission Trading ◽  
The Impact

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference

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

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

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

Impact of Nanotechnology Patents on Green Development of China's Building Industry

2020 ◽  
Vol 14 (2) ◽  
pp. 141-152
Author(s):  
Xialing Sun ◽  
Rui Zhang ◽  
Xue Chen ◽  
Pengpeng Li ◽  
Jin Guo
Keyword(s):  
Total Factor Productivity ◽  
Inhibitory Effect ◽  
Building Industry ◽  
Factor Productivity ◽  
The Sustainable Development ◽  
Technological Support ◽  
Green Development ◽  
Panel Data Regression ◽  
The Impact ◽  
Building Engineering

Background: The sustainable development of the building industry has drawn increasing attention around the world. Nanomaterials and nanotechnology play an important role in the processes of energy saving and reducing consumption in the building industry. Nanotechnology patents provide key technological support for the green development of the building industry. Based on patent data in China, this paper quantitatively analyzed the application of nanotechnology patents in the building industry and the time trend, regional differences, and evolution of China's nano-patent applications in the building field. Methods: In this study, the environmental total factor productivity of the building industry considering carbon constraints was determined and then used as the dependent variable to measure the green development of the building industry. On this basis, a panel data regression model was constructed to determine the impact of nano-patents on the green development of the building industry. Results: Nanotechnology patents in the building industry can significantly improve total factor productivity. From the perspective of patent composition, technology-based patents that focus on substantial innovation can significantly promote the green development of the building industry, whereas strategic patents show a significant inhibitory effect. Regionally, the western region of China has the advantage of being less developed and thus more efficient than the central and eastern regions in the application of new nano-products. Finally, the research also showed a significant lag in the application of China's nanotechnology patents and low implementation efficiency. Conclusion: Nano patents can promote green development in the building industry, but there is room for improvement in the speed with which laboratory inventions are transformed into building engineering applications.

scholarly journals Impact of Migrant Workers on Total Factor Productivity in Chinese Construction Industry

2019 ◽  
Vol 11 (3) ◽  
pp. 926 ◽  
Author(s):  
Gui Ye ◽  
Yuhe Wang ◽  
Yuxin Zhang ◽  
Liming Wang ◽  
Houli Xie ◽  
...  
Keyword(s):  
Construction Industry ◽  
Total Factor Productivity ◽  
Migrant Workers ◽  
Annual Report ◽  
Learning By Doing ◽  
Construction Sector ◽  
Factor Productivity ◽  
The Sustainable Development ◽  
Statistical Yearbook ◽  
The Impact

Total factor productivity (TFP) is of critical importance to the sustainable development of construction industry. This paper presents an analysis on the impact of migrant workers on TFP in Chinese construction sector. Interestingly, Solow Residual Approach is applied to conduct the analysis through comparing two scenarios, namely the scenario without considering migrant workers (Scenario A) and the scenario with including migrant workers (Scenario B). The data are collected from the China Statistical Yearbook on Construction and Chinese Annual Report on Migrant Workers for the period of 2008–2015. The results indicate that migrant workers have a significant impact on TFP, during the surveyed period they improved TFP by 10.42% in total and promoted the annual average TFP growth by 0.96%. Hence, it can be seen that the impact of migrant workers on TFP is very significant, whilst the main reason for such impact is believed to be the improvement of migrant workers’ quality obtained mainly throughout learning by doing.

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