Total factor productivity, its components and drivers

Haider, Franz; Kunst, Robert M.; Wirl, Franz

doi:10.1007/s10663-020-09476-4

Cited by 24 publications

(21 citation statements)

References 53 publications

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“…This stability suggests that technical efficiency has made a significant contribution towards the capabilities of sustainable development of coal mining cities, which could be the hallmark for other mining cities to adopt, with respect to resource allocation and utilization. In line with endogenous growth theories, R&D is a source of (TFPCH) TFP growth [32]. The decomposition effect gives an indication of the role of technological efficiency as R&D influences EFFECH, which leads to a robust upward movement of the technological frontier (TECHCH) with a growth of about 43.7%.…”

Section: Conversional Decomposition Of Sustainable Development Capabilities Of Coal Mining Citiesmentioning

confidence: 73%

“…The various challenges of the coal mining industries for now and the future are strongly linked to better approaches towards sustainability and transformation with the proposed way forward being all-round change caused by innovation through R&D and an industrial structure upgrade. R&D is a major source of novelty and technological advancement, while enhancement in technological capabilities positively affect production [32], and efficiency, creating a link between R&D and output. Cameron, et al [33] found a direct influence of R&D on total factor productivity (TFP) and this builds the nexus between R&D and TFP.…”

Section: Coal Mining Sector Challenges and Innovation In Randdmentioning

confidence: 99%

“…, where y is the optimal value and x is the actual value. The final values attained were therefore multiplied by 100 to arrive at the percentage and we proceeded to analyze the supporting reasons suggested in other studies [9,32,41] for high inefficiencies which push the sustainable development capabilities of the various cities down. The most prominent observations from Figures 4-7 are that first, stability and constant improvement in R&D over the period and especially in the regeneration group of coal mining cities was observed as high as above the constant 40% growth to about 80% growth in 2014; second, there was parallel movement of both R&D and capabilities, which generally reveals an increase in R&D influences capabilities in almost equal measure; third, there were large differences in efficiency towards achieving sustainable development capabilities at some point over the period especially in the growing, maturity, and declining cities, which have no observable catch-up.…”

Section: Comparative Analysis Of Randd Influence and Effectiveness Appraisalmentioning

confidence: 99%

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The Influence of R&D in Mining on Sustainable Development in China

Dabuo

Madzikanda

et al. 2021

Sustainability

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Mining and the utilization of mineral resources, especially coal for energy consumption, are considered a major contributor to China’s total index of environmental pollution, but there is less focus on its sustainable development. This study focused on the influence of research and development (R&D) on the sustainable development capabilities of 45 coal mining cities in China from 2008 to 2017. These cities were grouped into growing, maturity, declining, and regeneration categories. A DEAP model together with the Malmquist productivity index were used in calculating their sustainable development capabilities. It emerged that the R&D inclination for the coal mining cities was low at an average of 0.3406 and its influence has not pushed enough to reach the production frontier. The overall sustainable development capabilities of the four categories of coal mining cities were 0.6918 and also proved to have an unstable trend. There was evidence of inefficiencies in some categories of resource input and output. Technological changes (TECHCH) that promote the sustainable development capabilities grew at 12.2% for the period, which is moderately significant but still needs improvement. Major factors hindering the sustainable development of coal mining cities were insufficient desired input indicators including decisional capabilities, recovery in the treatment of pollution, and effective utilization of resources.

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Section: Conversional Decomposition Of Sustainable Development Capabilities Of Coal Mining Citiesmentioning

confidence: 73%

Section: Coal Mining Sector Challenges and Innovation In Randdmentioning

confidence: 99%

Section: Comparative Analysis Of Randd Influence and Effectiveness Appraisalmentioning

confidence: 99%

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The Influence of R&D in Mining on Sustainable Development in China

Dabuo

Madzikanda

et al. 2021

Sustainability

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“…Implementation of policy might be, however, difficult in the less developed regions as they face significant structural obstacles in diminishing the productivity gap (see eg. Haider et al, 2020, Bednář & Halásková, 2018.…”

Section: Discussionmentioning

confidence: 99%

Technological convergence across European regions

Kijek

Matras-Bolibok

2020

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Research background: Given the pivotal role of innovations and technological progress in shaping the economic development of regions and the crucial significance of spatial dimension of innovation processes at the regional level, the assessment of technological convergence in the regional scope becomes an essential research problem. Technological convergence could be identified on the basis of the analysis of total factor productivity (TFP). The significance of the technological convergence analysis results from the fact that income convergence can be both accelerated or impeded, depending on whether the initial differences in the level of technology (TFP) decrease or increase over time. Purpose of the article: The aim of the paper is twofold. Firstly, we attempt to develop a theoretical framework for the analysis of the technological convergence. Secondly, we investigate the technological convergence (on the basis of the TFP analysis) across European regions. Methods: During the first stage of the research, we employ the multiplicatively-complete Färe-Primont index to calculate TFP. The second stage of the study includes estimation of spatial panel models applied to assess the level of technological convergence across European regions. The research sample consists of 273 NUTS 2 European Union (EU) regions over the period 2010– 2016. Findings & Value added: The results of the study confirm a clear division of Europe into the Western European regions with high TFP values and the Eastern European regions with low TFP level. The research also shows that in the Eastern European regions the process of reducing the differences in the productivity levels is faster than in Western European regions. Since the issue of technological convergence is still not sufficiently explored in the relevant literature our paper attempts to fill a cognitive and methodological gap in the investigation of the technological convergence in the European regional space.

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“…Furthermore, for the period 1990 to 2006, Haider et al (2021) looked at how R&D, trade, and ICT affected TFP growth in 25 European countries, Japan, and the United States. They broke down TFP growth into two components: catching up and innovation (frontier shifts).…”

Section: Introductionmentioning

confidence: 99%

A New Method for Measuring Total Factor Productivity Growth Based on the Full Industry Equilibrium Approach: The Case of the Greek Economy

Tsounis

Steedman

2021

Economies

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A new method of identifying the sources of output growth and measuring total factor productivity (TFP) is proposed, with an application to data from the Greek economy. The price accounting approach, based on the full industry equilibrium (FIE) framework introduced by Opocher and Steedman, where technical progress not only increases outputs relative to inputs but also reduces output prices relative to input rewards, is used. The contributions of this paper are that, first, it amends the FIE TFP measurement approach to account for heterogeneous labor inputs, imported inputs, and indirect taxes, and applies the method to real-world data from the Greek economy; second, it provides a comparison of the results with those found by the use of the neoclassical approach to TFP measurement arguing that the FIE approach measures better sectoral TFP change, and third, it provides an estimate of the effects of sectoral research and development (R&D) expenditures and R&D diffusion from other sectors on TFP change for the Greek economy.

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Total factor productivity, its components and drivers

Cited by 24 publications

References 53 publications

The Influence of R&D in Mining on Sustainable Development in China

The Influence of R&D in Mining on Sustainable Development in China

Technological convergence across European regions

A New Method for Measuring Total Factor Productivity Growth Based on the Full Industry Equilibrium Approach: The Case of the Greek Economy

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