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2016 | 9 | nr 4 | 168--175
Tytuł artykułu

Bayesian Model Averaging in the Studies on Economic Growth in the EU Regions - Application of the gretl BMA package

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Economic growth is again one of the most important economic issues in literature since the 1980s. This paper falls into the mainstream of regional studies on economic growth and it tries to answer the recurring question: what are the determinants of economic growth at regional level. The objective of this article is to diagnose the determinants of economic growth among European regions on the basis of Bayesian methods applied to gretl software. (original abstract)
Rocznik
Tom
9
Numer
Strony
168--175
Opis fizyczny
Twórcy
  • Toruń School od Banking, Poland
autor
  • Poznań University of Economics and Business, Poland
  • Nicolaus Copernicus University in Toruń, Poland
Bibliografia
  • Albu, L. L. (2006), Trends in the interest rate-investment-GDP growth relationship, Journal for Economic Forecasting, 3(3), pp. 5-13.
  • Albu, L. L., & Roudoi, A. (2003), Factors and Mechanisms of Economic Growth in Transition Economies of Different Types (Case of Romania), Journal for Economic Forecasting, (4), pp. 50-64.
  • Albu, L. L. (2013), Foreign Trade and FDI as Main Factors of Growth in the EU, Journal for Economic Forecasting, (2), pp. 7-17.
  • Błażejowski, M., Kwiatkowski, J. (2013), Bayesian Model Averaging and Jointness Measures for gretl, MPRA Paper, 44322.
  • Cetin, M., & Dogan, I. (2015), The impact of education and health on economic growth: Evidence from Romania (1980-2011), Journal for Economic Forecasting, (2), pp. 133-147.
  • Fernandez, C, Ley, E, Steel, M. F. J. (2001), Benchmark Priors for Bayesian Model Averaging, Journal of Econometrics, 100(2), pp. 381-427.
  • Gazda, J., Puziak, M., (2013), The sources of economic growth in Polish regions, International Journal of Academic Research, 5, pp. 245-250.
  • Kilic, C., Arica, F. (2014), Economic Freedom, Inflation Rate and their Impact on Economic Growth: A Panel Data Analysis, Journal for Economic Forecasting, 17(1), pp. 160-176.
  • Koop, G. (2003), Bayesian Econometrics, John Wiley & Sons, New Jersey,USA.
  • Madigan, D., York, J., Allard, D. (1995), Bayesian Graphical Models forDiscrete Data, The International Statistical Review, 63(2), pp. 215-232.
  • Ruiz, V. R. L., Navarro, J. L. A., & Peña, D. N. (2016), Economic Growth and Intangible Capitals: An International Panel Data Model Applied in the 21st Century, Journal for Economic Forecasting, (2), pp. 102-113.
  • Simionescu, M. (2016a), Macroeconomic Determinants of Permanent Emigration from Romania: a Bayesian Approach, Journal of International Studies, 9(2), pp. 170-180.
  • Simionescu, M., & Albu, L. L. (2016), The impact of standard value added tax on economic growth in CEE-5 countries: econometric analysis and simulations, Technological and Economic Development of Economy, 22(6), pp. 850-866.
  • Simionescu, M., Ciuiu, D., Bilan, Y., Strielkowski, W. (2016), GDP and Net Migration in Some Eastern and South-Eastern Countries of Europe. A Panel Data and Bayesian Approach, Montenegrin Journal of Economics, 12(2), p. 161.
  • Simionescu, M. (2016b), The relation between economic growth and foreign direct investment during the economic crisis in the European Union, Zbornik radova Ekonomskog fakulteta u Rijeci: časopis za ekonomsku teoriju i praksu, 34(1), pp. 187-213.
  • Zellner, A. (1986), On Assessing Prior Distributions and Bayesian Regression Analysis with g-Prior Distributions, In: P. Goel and A. Zellner (ed.), Bayesian Inferenceand Decision Techniques: Essays in Honor of Bruno de Finetti, Amsterdam, Holland, Elsevier.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171449477

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