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

Tsounis, Nicholas; Steedman, Ian

doi:10.3390/economies9030114

Cited by 4 publications

(4 citation statements)

References 65 publications

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“…On one hand, total factor productivity (TFP) shows the part of the output that is not explained by the amount of inputs used in the production process, and on the other hand, TFP also shows how efficiently and intensively the inputs are used in this process. TFP is an important factor of long-term economic growth as well as short-term fluctuations in this growth (Tsounis and Steedman, 2021). TFP or the productivity of capital (including natural resources) and labor together change with economies of scale, improvements in productive factors allocation, and technological progress (Akkaya and Güvercin, 2018; Kim and Loayza, 2019).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Total Factor Productivity and the Significance of the Public Sector

Wostner¹,

Krizanic²,

Brezovnik³

et al. 2023

TRAS

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"It is typical in the modern world that most eco nomic growth is explained by an increase in total fac tor productivity, commonly accompanied by the rise of real capital. After the last financial crisis, Slovenia was specific in the growth of total factor productivity between 2009 and 2019 in that the 44 analyzed in dustries substituted the decline of net real values of fixed capital, associated with a large contraction in bank loans to non-financial corporations. During this period, Slovenia’s total factor productivity strength ened due to increases in innovative potential, human capital (employees with higher education), and the share of foreign trade in Slovenia’s GDP. The public sector played an important role in this, as the increase in innovation potential and human capital was the result of the increase in the real lev el of Slovenian Export and Development Bank loans to enterprises and from extensive EU Structural and Cohesion Funds placements. The growth of inno vation potential was influenced by the rise in the number of full-time researchers, and the increase in human capital was influenced by the economic cli mate in the EU"

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Section: Theoretical Frameworkmentioning

confidence: 99%

Total Factor Productivity and the Significance of the Public Sector

Wostner¹,

Krizanic²,

Brezovnik³

et al. 2023

TRAS

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“…Tsionas and Polemis (2019), Tsounis and Steedman (2021), Francis et al (2020), Whelan (2021), Dandan (2020), Harb and Bassil (2023).…”

Section: 4mentioning

confidence: 99%

Intelligent System of Estimation of Total Factor Productivity (TFP) and Investment Efficiency in the Economy with External Technology Gaps

Lopatin

2023

JCBAR

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This paper is the first to propose an aggregate S-trend factor production function to estimate total factor productivity (TFP) and investment efficiency in an economy. This function implements Charles R. Hulten's organizing principle: to what extent the growth of the economy is due to an increase in "productivity" (progress in technology and organization of production) and to what extent to "capital formation" (increased investment in human capital, knowledge and fixed capital). Estimation of future members of the series is usually done by a forecast model. It is a model that approximates a trend. The Verhulst's S-curve is used as the approximation function. Here A, B ,a are the parameters that change the shape of the S-curve, u, m are the parameters that change the position of the S-curve in the first quarter, t≥0. By aggregate S-trend production function we mean a two factor production function of the form z(t)= Here the function It represents the growth of the economy, which is by raw data and takes into account all influencing factors, and is certainly broader than the concept of " capital formation ", is a total factor productivity TFP. The error of approximation is quantitatively measured by the MAPE criterion.

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“…Research on factors and sources of productivity growth in the extractive sector are based on the reconstruction models of mining enterprises (Prokopenko et al, 2020;Tyurin and Stoianov, 2019;Bak, 2018), the efficiency of inter-sectoral and inter-sectoral interrelationships in the economy (Hyranek et al, 2021;Tsounis and Steedman, 2021;Jonek-Kowalska and Turek, 2017), determination of investment efficiency (Kim, Kim, and Yoo, 2020;Wellmer and Scholz, 2018), optimization of individual production processes (Gackowiec et al, 2019), effects of innovation on productivity (Woodhead and Berawi, 2020;Varlamova and Larionova, 2020;Wiratmadja, Govindaraju, and Handayani, 2016).…”

Section: Introductionmentioning

confidence: 99%

Convergent Technological and Hyperconvergent Forms of Productivity Improvement in the Extractive Sector of Economy

Ezdina,

Dotsenko,

Shavina

et al. 2024

IJTech

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The advancement of the extractive sector is affected by a combination of external and internal factors, such as the volatility of world prices with demand for raw materials and the peak of productivity due to technological limitations. In this context, the global demand for raw materials may lead to different issues and an increase in productivity is dependent on the widespread adoption of technologies, which form the essence of Industry 4.0. Therefore, this research aimed to identify the influence of convergent technologies on productivity in the extractive sector of the economy and determine the role of national technological platforms in facilitating the process. The research methodology was formed by the works of Russian and foreign economists in the field of raw materials markets analysis, mineral sector productivity, perspectives and conditions of Industry 4.0 development, technological convergence, as well as regulation of innovation interaction between science and production. The results showed that a recurring cycle of long-term developmental challenges, "productivity stagnation -slowdown of investments inflow -further productivity stagnation" was identified by analyzing prices in the global raw materials market, investment patterns, incomes, and productivity trends within the Russian extractive sector. In addition, this cycle was supported by reliance on equipment imports and the replication of outdated technologies. Due to the advancements of Industry 4.0, a convergent technological approach to modernization was proposed to increase productivity. In this context, a platform was developed for the diffusion of convergent technologies based on the analysis of international practices of using NBIC-convergence in the activities of mineral complex enterprises. Hyperconvergent technologies were particularly considered to mediate the transition from the "Internet of Things" to the "Internet of Everything", facilitating the evolution of automated to fully unmanned production processes. The results could be used in the formation of strategic programs for the modernization of the extractive sector.

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

Cited by 4 publications

References 65 publications

Total Factor Productivity and the Significance of the Public Sector

Total Factor Productivity and the Significance of the Public Sector

Intelligent System of Estimation of Total Factor Productivity (TFP) and Investment Efficiency in the Economy with External Technology Gaps

Convergent Technological and Hyperconvergent Forms of Productivity Improvement in the Extractive Sector of Economy

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