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Determinants of Total Factor Productivity in Visegrad Group Nuts-2 Regions

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  • Barbara Danska-Borsiak

    (Faculty of Economics and Sociology, University of Łódź, Łódź, Poland)

Abstract

This article attempts to estimate the total factor productivity (TFP) for 35 NUTS-2 regions of the Visegrad Group countries and to identify its determinants. The TFP values are estimated on the basis of the Cobb-Douglas production function, with the assumption of regional differences in productivity. The parameters of the productivity function were analysed with panel data, using a fixed effects model. There are many economic variables that influence the TFP level. Some of them are highly correlated, and therefore the factor analysis was applied to extract the common factors – the latent variables that capture the common variance among those observed variables that have similar patterns of responses. This statistical procedure uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. Each component is interpreted using the contributions of variables to the respective component. I estimated a dynamic panel data model describing TFP formation by regions. An attempt was made to incorporate the common factors among the model’s explanatory variables. One of them, representing the effects of research activity, proved to be significant.

Suggested Citation

  • Barbara Danska-Borsiak, 2018. "Determinants of Total Factor Productivity in Visegrad Group Nuts-2 Regions," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 68(1), pages 31-50, March.
    • Handle: RePEc:aka:aoecon:v:68:y:2018:i:1:p:31-50
    Note: We are especially grateful to the referees of Acta Oeconomica for their comments, as well as to Associate Professor George Filis (Bournemouth University, UK) for his continuous aid, support, and guidance during the completion of this research.
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    Citations

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    Cited by:

    1. Arkadiusz Kijek & Tomasz Kijek, 2020. "Nonlinear Effects of Human Capital and R&D on TFP: Evidence from European Regions," Sustainability, MDPI, vol. 12(5), pages 1-14, February.
    2. Nicholas Tsounis & Ian Steedman, 2021. "A New Method for Measuring Total Factor Productivity Growth Based on the Full Industry Equilibrium Approach: The Case of the Greek Economy," Economies, MDPI, vol. 9(3), pages 1-21, August.
    3. Junfei Chen & Tonghui Ding & Huimin Wang & Xiaoya Yu, 2019. "Research on Total Factor Productivity and Influential Factors of the Regional Water–Energy–Food Nexus: A Case Study on Inner Mongolia, China," IJERPH, MDPI, vol. 16(17), pages 1-21, August.

    More about this item

    Keywords

    Total Factor Productivity (TFP); Visegrad Group; regional analysis; dynamic panel data model; factor analysis;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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