Efficiency, total factor productivity and returns to scale in a sustainable perspective: An analysis in the European Union at farm and regional level

2017 ◽  
Vol 68 ◽  
pp. 232-245 ◽  
Author(s):  
Vítor João Pereira Domingues Martinho
Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3429
Author(s):  
Svetlana Balashova ◽  
Apostolos Serletis

This paper uncovers linkages between oil price uncertainty, total factor productivity (TFP) growth, and critical indicators of knowledge production and spillovers. It contributes to the literature by investigating the effects of oil price volatility on TFP growth, controlling for two different channels for TFP growth; benefits from the quality of the national innovation system and from adopting new technologies. We use an unbalanced panel for 28 European Union countries for the period from 1990 to 2018. We find that oil price uncertainty has a negative and statistically significant effect on TFP growth, even after we control for technological advancements and the effects of globalization. We also find that the scale of research and innovation and international trade are positive contributors to TFP growth.


2009 ◽  
Vol 41 (5) ◽  
pp. 1152-1170 ◽  
Author(s):  
Roberto Ezcurra ◽  
Belen Iraizoz ◽  
Pedro Pascual

This paper examines the global trend of total factor productivity, efficiency, and technological change in the European Union regions over the period 1986–2004, using the Malmquist index computed by data envelopment analysis. The results reveal the important role played by technical efficiency in explaining total factor productivity growth in the European Union. For this reason, in a second stage, we investigate existing regional disparities in efficiency levels across the European regions, using a nonparametric methodology that allows us to study the dynamics of the entire cross-sectional distribution. Estimates show the presence of a process of convergence in efficiency levels over the sample period, despite a relatively low degree of intradistribution mobility. In order to complete these results, factors such as the geographical location of the various regions, country-specific characteristics, or the sectoral composition of economic activity were examined for their role in explaining the observed disparities.


2020 ◽  
Vol 240 (5) ◽  
pp. 565-605
Author(s):  
Sebastian Breuer ◽  
Steffen Elstner

AbstractThis paper shows how the German Council of Economic Experts (GCEE) determines Germany’s potential output, and compares the results with those of the European Commission. The approach of the European Commission is a natural benchmark, as it provides the basis for the deficit and debt rules of the European Union. In comparison with the European Commission’s method, the GCEE’s method places greater emphasis on demographic factors in estimating labour input. Additionally, both approaches differ regarding how they estimate the structural unemployment rate and total factor productivity. Finally, this paper discusses the limitations of, and the different options for estimating potential output.


2015 ◽  
Vol 25 (4) ◽  
pp. 406-434 ◽  
Author(s):  
Agnieszka Gehringer ◽  
Inmaculada Martínez-Zarzoso ◽  
Felicitas Nowak-Lehmann Danzinger

2017 ◽  
Vol 1 (4) ◽  
pp. 175
Author(s):  
Prosenjit Das

Aim: India has emerged as one of the most favoured destinations in the global Information Technology (IT) outsourcing market. On the other hand, the IT industry has been playing an instrumental role in transforming India’s image from a low income-backward nation to a knowledge-based economy.  Furthermore, the role of IT industry has been pivotal in putting India on a higher growth path. In addition, India’s IT industry has been showing robust performance in revenue earning, particularly in export revenue. However, the performance of this industry is likely affected by some recent global phenomena, such as 2008’s subprime crisis originated in the US, uncertainties in changes in H1-B visa rules, Britain’s exit from the EU, automation etc. There are other factors, like exchange rate volatility, emerging competition from other low-cost outsourcing destination countries, are also posing threat to India’s IT-outsourcing business. Against this backdrop, it is crucial to analyse the sustainability of performance of Indian IT industry. Thus, the present study aims at assessing the performance of Indian IT industry and evaluating the determinants of performance thereafter.Design / Research methods: To realize the objectives of the study, firm level data has been collected from the Centre for Monitoring Indian Economy (CMIE) Prowess database. For empirical analysis, we have applied a two-stage method. In the first-stage, we have used Data Envelopment Analysis (DEA) based Malmquist Productivity Index (MPI) to evaluate the Total Factor Productivity Growth (TFPG) of Indian IT industry during the period from 2004-05 to 2014-15. For this purpose, a balanced panel consists of 70 IT firms has been considered. Further, the TFPG has been decomposed into three components, viz. Catch-up, frontier-shift, and scale efficiency change (SEC). Consequently, in the second-stage, three random-effects panel regression models are considered to investigate the determinants of TFPG, catch-up, and frontier-shift separately. Conclusions / findings: During the study period, the average TFP and frontier-shift has been improved. On the other hand, catch up effect is found to have declined. The variables, such as export intensity, salaries and wages intensity have positive and statistically significant impact on the catch-up and frontier-shift. Export intensity has positive impact on TFPG. Age of the firms has positive impact on catch-up and TFPG. Salaries and wages intensity has positive impact on TFPG. On an average, the firms which spent on research and Development (R&D) have experienced improvement in TFPG and frontier-shift. The public limited firms performed better than their private counterparts in terms of catch-up, frontier-shift, and TFPG. The non-group firms have performed better than the group firms in case of catch-up. On the other hand, on an average, the firms exhibiting decreasing Returns to Scale (DRS) are found to have registered deterioration in catch-up and TFPG with respect to the benchmark firms which are exhibiting Constant Returns to Scale (CRS). The firms exhibiting Increasing Returns to Scale (IRS) have shown improvement in catch-up and TFPG over the benchmark CRS firms. The impact of the US subprime crisis has been negative on catch-up, frontier-shift, and TFPG. The firms, which have spent on royalty, have experienced improvement in catch-up and TFPG. Originality / value of the article: So far in our knowledge, not so many studies of this kind have been done in the arena of empirical research pertains to the IT industry, especially in a developing country like India. Moreover, we have not found any study that covers the span of the dataset considered in the present study. In addition to this, the present study has employed a random-effects panel model to accommodate a number of time-invariant dummy variables which would not be possible in case of a fixed-effects panel model incorporated by some previous studies of this genre.Implications of the research: The identification of the determinants of TFPG and its components would help the stakeholders and policy makers of the IT industry to formulate appropriate policies which could mitigate the risks faced by the industry on one hand, and stimulate the forces that would enhance the growth of this industry on the other. For instance, to mitigate future risks, Indian IT industry should reduce its dependence on the US and UK markets. Besides, it should explore new markets in the EU, and other emerging economies where opportunities are plenty. To maintain India’s robust global position in the long run, Government of India should play the key role in providing world class infrastructure and telecommunication facilities to its IT industry. In addition to this, Government needs to rationalise and simplify the existing Indian labour law to facilitate the business of IT industry. Various stakeholders along with the Government should put necessary efforts to develop the domestic IT market as there exists ample of opportunities in future. Keywords: information technology industry, data envelopment analysis, Malmquist productivity index, random-effects model, total factor productivity, catch-up, frontier-shift, India. JEL: C23, C61, L86, O47


2015 ◽  
Vol 3 (2) ◽  
pp. 90
Author(s):  
Zdzisław W. Puślecki

<em>The main aim of the paper is analysis of the innovation and knowledge in creation of European Union global competitiveness and social security from regional perspective. To the particular goals of the research belong the presentation of the knowledge-based-growth (KBG) theory, the concept of innovation system, the innovation system and innovation process, constructed advantage, the Triple Helix model, Europe 2020 strategy and Innovation Union and Horizon 2020 as the financial instrument implementing the Innovation Union. The important results of the research is the conclusion that in the innovation process also in the European Union very important are the connection between science (universities), market (industry) and government at the regional level. There is positive dependence between innovation activity and effectiveness of the innovation process. The more interaction and cooperation also the creation of enterpreunership it can observe on the regional level than on the state. The new programme of the scientific and innovation research Europe 2020 and Innovation Union are very important factors of the economic growth, social security and global competitiveness of the European Union. The new economic narrative of the European Union is built around three main strands–boosting investments, pursuing structural reforms and fiscal responsibility. </em>


2020 ◽  
Vol 159 ◽  
pp. 05002
Author(s):  
Aknur Zhidebekkyzy ◽  
Rimma Sagiyeva ◽  
Zhansaya Temerbulatova

Today there is no single universally accepted method for assessing the competitiveness of the country’s regions. For this reason, the research created a methodology for assessing competitiveness at the regional level for Kazakhstan. The three-factor model of Huggins for ranking the regions of Great Britain by the level of competitiveness was used as the basis, and then the model was expanded on the example of a study assessing the competitiveness of the regions of the European Union countries. All data for assessing the competitiveness of the regions of Kazakhstan were collected from the official website of the Committee on Statistics of the Ministry of National Economy of the Republic of Kazakhstan. In the article, 14 regions and 2 cities of republican significance were ranked in terms of competitiveness. As a result, the most competitive regions of Kazakhstan were Almaty city, Atyrau region and Nur-Sultan city, the worst indicator was found for the North Kazakhstan and Zhambyl regions.


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