2019 | vol. 63, nr 2 | 65-80
Article title

The impact of regional diversification in the size of the general government sector on the economies of EU countries

Title variants
Wpływ regionalnego zróżnicowania rozmiaru sektora finansów publicznych na gospodarki państw Unii Europejskiej
Languages of publication
The main objective of this article is proving how the regional diversification in the size of general government sector influences the economies of EU countries. To achieve this, presenting both the size of the general government sector and of the economy, using variables which enable comparison in time and space, is essential. Bearing this in mind, the general government sector has been depicted by nine variables and the economy has been described by thirteen explanatory variables. The complexity of the phenomenon imposes the implementation of an unconventional approach in this field of exploration. Our approach is based on Intelligent Data Analysis (IDA) - a methodology that includes a set of techniques that can be applied for extracting useful knowledge from large amounts of data. In order to indicate the impact of regional diversification in the size of the general government sector on the EU countries’ economies, probabilistic techniques were applied – Bayesian Networks. Analysis made in the study showed that the largest impact of the GGS size on the economy was identified in Portugal and Slovakia. The results of the studies show that the most "responsive" to the size of the GGS variable describing the economy was gross domestic product per inhabitant. The research proved that the economies of some countries showed similarities in the effect of the size of the general government sector on the parameters of the economy. We have identified five groups of such countries.
Głównym celem artykułu jest ukazanie wpływu regionalnego zróżnicowania rozmiaru sektora finansów publicznych na gospodarki państw Unii Europejskiej. Do osiągnięcia tego celu konieczne jest zobrazowanie rozmiaru zarówno sektora finansów publicznych, jak i gospodarki – za pośrednictwem zmiennych umożliwiających ich porównanie w czasie i w przestrzeni. Mając to na uwadze, sektor finansów publicznych zobrazowano za pośrednictwem dziewięciu zmiennych, a gospodarka została opisana za pomocą trzynastu zmiennych wyjaśniających. Złożoność tego zjawiska wymaga realizacji niekonwencjonalnego podejścia w tej dziedzinie badań. Podejście autorów opiera się na inteligentnej analizie danych (IDA) – metodologii obejmującej zestaw technik, które można zastosować do wydobywania użytecznej wiedzy z dużej ilości danych. W celu wskazania opisanych związków w artykule zastosowało techniki probabilistyczne – sieci Bayesa.
  • Magazzino C., 2012, Wagner versus Keynes: Public spending and national income in Italy, Journal of Policy Modeling, 34(6), pp. 890-905.
  • Maku O.E., 2009, Does government spending spur economic growth in Nigeria?, (2018.10.10).
  • Marlow M.L., 1986, Private sector shrinkage and the growth of industrialized economies, Public Choice, 49(2), 143-154.
  • Martins S., Veiga F.J., 2014, Government size, composition of public expenditure, and economic development, International Tax and Public Finance, 21(4), pp. 578-597.
  • Mehrara M., Keshtgar N., 2016). Government expenditure and economic growth in MENA region, International Journal of Applied, 4(1).
  • Mose, N., Kalio A., Kiprop S. Kibet L., Babu J., 2015, Effect of Government Expenditure on Economic Growth in East Africa: Panel Data Analysis, Mose, Kalio2, Retrieved on Sept.
  • Murphy K., 1998, A Brief Introduction to Graphical Models and Bayesian Networks,
  • Odhiambo N.M., 2015, Government expenditure and economic growth in South Africa: An empirical investigation, Atlantic Economic Journal, 43(3), pp. 393-406.
  • Pearl J., 1988, Probabilistic Inference in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, San Mateo, CA.
  • Pearl J., 2009, Causality: Models, Reasoning and Inference, 2nd edition, Cambridge, Cambridge University Press.
  • Peden E.A., 1991, Productivity in the United States and its relationship to government activity: An analysis of 57 years, 1929-1986, Public Choice, 69(1), pp. 153-173.
  • Pevcin P., 2004, Does optimal size of government spending exist?, University of Ljubljana, 10(1), pp. 101-135.
  • Quang A.L., 2010, New Approaches Using Probabilistic Graphical Models in Health Economics and Outcomes Research. Dissertation, Faculty of the USC Graduate School, University of Southern California.
  • Rahn R., Fox H., 1996, What Is the Optimum Size of Government?, Vernon K. Krieble Foundation.
  • Ram R., 1986, Government size and economic growth: A new framework and some evidence from cross-section and time-series data, The American Economic Review, 76(1), pp. 191-203.
  • Romero-Avila D., Strauch, R., 2008, Public finances and long-term growth in Europe: Evidence from a panel data analysis, European Journal of Political Economy, 24(1), pp.172-191.
  • Sáez M.P., Álvarez-García S., Rodríguez D.C., 2017, Government expenditure and economic growth in the European Union countries: New evidence, Bulletin of Geography. Socio-Economic Series, 36(36), pp. 127-133.
  • Saunders P., 1988, Private sector shrinkage and the growth of industrialized economies: Comment, Public Choice, 58(3), pp. 277-284.
  • Scully G.W., 1994, What Is the Optimal Size of Government in the United States?, National Centre for Policy Analysis – Policy Report, p. 188.
  • Scully G.W., 1995, The “growth tax” in the United States, Public Choice, 85(1-2), pp.71-80.
  • Sesen M.B., Nicholson A.E., Banares-Alcantara R., Kadir T., Brady M., 2013, Bayesian networks for clinical decision support in lung cancer care, PLoS ONE, 8(12), e82349.
  • Skica T., Rodzinka J. Mroczek T., 2015a, Data mining approach to determine the relationships between the economy and the general government sector size, Finansowy Kwartalnik Internetowy e-Finanse, vol. 11, no. 3, pp. 1-21.
  • Skica T., Rodzinka J., Fryc B., 2015b, Application of LEM2 algorithm in identification of relationships between the size of general government sector and the economy, Hyperion International Journal of Econophysics and New Economy, volume 8, issue 2, pp. 361-401.
  • Spiegelhalter, D. J., 1998, Bayesian graphical modelling: A case – study in monitoring health outcomes, Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(1), pp. 115-133.
  • Sriyana J., 2016, Optimum size of government spending in Indonesia, Journal of Applied Economic Sciences, 11(3), pp. 441-449.
  • Summer R., Heston A.W., 1984, Improved international comparisons of real product and its comparisons 1950-1977, Review of Income and Wealth, 30.
  • Vedder R.K., Gallaway L.E., 1998, Government size and economic growth, The Joint Economic Committee.
  • Zhang N.L., Poole D., 1996, Exploiting causal independence in Bayesian network inference, Journal of Artificial Intelligence Research, 5, pp. 301-328.
Document Type
Publication order reference
YADDA identifier
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.