Economic determinants of total factor productivity growth: The Bayesian modelling averaging approach

Sobieraj, Janusz; Metelski, Dominik

doi:10.15678/eber.2021.090410

Cited by 6 publications

(4 citation statements)

References 51 publications

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“…Scientific research conducted in the twenty-first century has shown the possibility of applying production functions in the economic analysis of the activities of enterprises and entrepreneurs that operate in the agricultural sector. Production functions are economic and mathematical models of production processes and quantitatively express a stable natural relationship between factors describing capital and labor costs (Sobieraj and Metelski, 2021) and an indicator characterizing the volume of agricultural production (Parlńska and Dareev, 2011;Ahmetov et al, 2019;Petrick and Kloss, 2018). Most scientific publications considered data for a number of years (the so-called time series).…”

Section: Literature Reviewmentioning

confidence: 99%

Production Functions for Assessing the Volumes of Agricultural Production in the Regions of Russia

Pinkovetskaia¹,

Arbeláez-Campillo²,

Rojas-Bahamón³

2022

MNJE

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The study was based on the development of production functions that characterize the activities of agricultural enterprises in the regions of Russia. Official statistical information on 65 regions of Russia for 2017 and 2018 was used. The conducted research made it possible to identify factors (investments in fixed assets and wages of employees) that affect the volume of production in the agricultural sector in the regions of Russia and suggest using two-factor production functions of high quality to describe this influence. It is proved that the economy of the country's regions has not reached saturation with agricultural products and there are significant reserves for further development of this sector. The developed production functions are effective management tools that allow assessing the level of use of financial and labor resources. The acquired new knowledge and tools for assessing the activities of agriculture in the Russian regions are of scientific and practical importance. They can be used in research of the agricultural sector of the economy, monitoring of production volumes, in determining the needs for resources necessary for the development of agriculture, substantiating plans and programs for its development.

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Section: Literature Reviewmentioning

confidence: 99%

Production Functions for Assessing the Volumes of Agricultural Production in the Regions of Russia

Pinkovetskaia¹,

Arbeláez-Campillo²,

Rojas-Bahamón³

2022

MNJE

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“…The theoretical underpinnings of this investigation lie in the vast landscape of business cycle models and empirical considerations that contribute to our understanding of economic synchrony. Keynesian models [8,9], rooted in demand-side dynamics, neoclassical models emphasizing supply-side changes [8,10], and the Real Business Cycle (RBC) model [11], highlighting the impact of technological change on productivity [12], offer distinct perspectives [8, 10,12,13]. Structural vector autoregressions (SVARs) unravel the intricate dynamics between construction and business cycles [14], while dynamic stochastic general equilibrium (DSGE) models provide a robust framework for modeling the stickiness of wages and prices affecting the construction sector [9,15].…”

Section: Introductionmentioning

confidence: 99%

Unveiling Economic Synchrony: Analyzing Lag Dynamics between GDP Growth and Construction Activity in Poland and Other EU Countries

Sobieraj,

Metelski

2024

Buildings

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This study examines the dynamic relationship between the business cycle and the construction sector activity in 27 EU countries, focusing on Poland. Using the cross-correlation function (CCF) and a set of economic- and construction-related variables, including GDP growth, construction production, building permits, and construction operating time by backlog, quarterly data from 2000Q1 to 2023Q2 (94 quarters in total) are analyzed. Beyond the CCF analysis, causality is also examined using Toda–Yamamoto tests to explore the nuanced temporal relationships between GDP growth and construction activity proxies. The research uncovers synchronized positive lag max results for construction production, suggesting a harmonized response to broader economic changes, especially within 9 to 11 quarters. In contrast, building permits and construction time by backlog show divergent positive lag max values, suggesting the need for tailored, localized strategies. Negative lag max values emphasize the anticipatory role of the construction sector as an early indicator of economic change. Overcoming methodological challenges, this study provides insights critical for policymakers and researchers, promoting a nuanced understanding of economic synchrony and guiding informed strategies for sustainable development. Future recommendations include refining localized strategies based on lag patterns for optimal economic management.

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“…From the perspective of the digital economy, T. Zhao [10] demonstrates that enhancing entrepreneurial activity has positive impact on the high-quality development of urban economy. The digital economy also has the functional characteristics of spatial effect, regional link-age, and productivity improvement [11][12][13]. J.…”

Section: Introductionmentioning

confidence: 99%

A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022

Shao-lun

2023

Sustainability

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Digital economy is a vital driving force for countries to promote economic recovery, rebuild competitive advantages and enhance governance capacity. Extensive research has been conducted in this field. In this paper, the text analysis tool of Bicomb2.04 and the knowledge graph visualization tool of CiteSpace are applied to analyze the digital economy research from 1992 to 2022, and a total of 7874 articles retrieved from the SSCI and SCI of the WOS core database are collected as the research data. The analysis provides a comprehensive overview of the research status of the digital economy, including the distribution of literature, research institutions and regions, research funds and publications, research authors, and cooperation networks. The core progress and frontier of international research are further analyzed according to the evolution of hot keywords, core system clustering, and the hot emergent words frontier. The results show that (1) the academic circle has a good overall research trend on the digital economy, which can be divided into three steadily rising research stages. The researchers take digital innovation as the core and extend it to the application of digital innovation, which has made groundbreaking theoretical contributions, but has not yet formed a team with field influence. (2) The evolution of hot keywords can be divided into four stages. Through hot clustering analysis, a basic theoretical system is constructed with digital technology and innovation as the core and digital governance, digital application, and digital path as the means. (3) The analysis of frontier areas also identified the digital platform economy, big data technology innovation, digital economy statistics, and the gig economy as potential research directions for the future. This study provides a guide for researchers to promote further research on the digital economy and is of great significance for promoting digital development level and constructing global digital ecosystem.

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Economic determinants of total factor productivity growth: The Bayesian modelling averaging approach

Cited by 6 publications

References 51 publications

Production Functions for Assessing the Volumes of Agricultural Production in the Regions of Russia

Production Functions for Assessing the Volumes of Agricultural Production in the Regions of Russia

Unveiling Economic Synchrony: Analyzing Lag Dynamics between GDP Growth and Construction Activity in Poland and Other EU Countries

A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022

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