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Quantitative Assessment of the Dynamics of Changes in the GDP Per Capita Index in the Regions of Bulgaria and Slovakia

References/Literatura: 1. Lewandowski, K. (2011). Ocena polityki regionalnej Unii Europejskiej w świetle badań empirycznych. Gospodarka w teorii i praktyce, 2 (29), 53-64. 2. Łaźniewska, E., Górecki, T., Chmielewski, R. (2011). Konwergencja regionalna . Poznań: Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu. 3. Puga, D. (2001). European Regional Policies in Light of Recent Location Theories. CEPR Discussion Paper Series , 2767, 14-15. 4. Surówka, A., Prędka, P. (2016). PKB per capita jako wyznacznik rozwoju ekonomicznego regionów

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Exploring Economic Growth and Environment Nexus in Nine Southeastern European Countries

policy , 37 (1), 246-253. doi: 10.1016/j.enpol.2008.08.025 unctadstat.unctad.org. (2017). US Dollars at constant prices (2005) per capita . [online] Available at: http://unctadstat.unctad.org/ [Accessed 6 Sep. 2017]. unfccc.int. (2018). The Paris Agreement - main page . [online] Available at: http://unfccc.int/paris_agreement/items/9485.php [Accessed 8 June 2018].

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Growth Effects of Cross-border Mergers and Acquisitions in European Transition Countries

Abstract

This paper deals with the economic effect of cross-border mergers and acquisitions on GDP per capita in European transition countries for the 2000- 2014 period. Our analysis shows that cross-border mergers and acquisitions have a negative effect on GDP per capita in the current period, whereas their lagged level positively impacts output performance. We found that transition countries characterized by a higher quality of institutional setting have achieved a positive impact on GDP per capita.

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Economic Growth and Environmental Quality in the European Union Countries – Is there Evidence for the Environmental Kuznets Curve?

., Krueger, A. B. (1991), Environmental impacts of a North American free trade agreement, Working Paper, 3914, National Bureau of Economic Research. Grossman, G. M., Krueger, A. B. (1993), Environmental impacts of the North American free trade agreement, in Peter Garber (ed.), The U. S.‑Mexico Free Trade Agreement, MIT Press, Cambridge. Hannesson, R. (2009), Energy and GDP growth, International Journal of Energy Sector Management, 3 (2), pp. 157-170. Hausman, J. A. (1978), Specification tests in econometrics, Econometrica, 46

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Convergence in GDP per capita across the EU regions— spatial effects

Abstract

The aim of this paper is to offer an empirical insight into the spatial effects of growth of regional income and disparities across EU regions (NUTS 2). Since regions are spatial units and there are interrelated standard linear regression is not sufficient to evidence the convergence process. Two models (Spatial Lag Model – SLM and Spatial Error model – SEM), derived from spatial econometrics, have been used to identify and explain spatial effects in convergence clubs—all EU countries (EU-28), countries that entered the EU in 2004 (EU-13) and countries that were in EU prior to 2004 (EU-15). Unconditional and conditional β-convergence has been examined in the period 2000-2015 thus covering two financial perspectives (including n + 2 rule3). Dummy variables have been also applied to catch the country-specific effects, such as national policies, legislation, technology progress, etc.

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Country’s Development as a Determinant of Early-Stage Entrepreneurial Activity

: Blackwell. Thurik, A. R. (2003). Entrepreneurship and unemployment in the UK. Scottish Journal of Political Economy, 50 (3), 264-290, http://dx.doi.org/10.1111%2F1467-9485.5003001 Thurik, A. R., Carree, M. A., van Stel, A. & Audretsch, D. B. (2008). Does self-employment reduce unemployment? Journal of Business Venturing, 23 (6), 673-686, http://dx.doi.org/10.1016%2Fj.jbusvent.2008.01.007 Van den Bergh, J. C. J. M. (2009). The GDP paradox. Journal of Economic Psychology, 30 (2), 117-135, http://dx.doi.org/10.1016/j

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Financial Stability of Insurance Companies in Selected CEE Countries

at: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=HU (15 December 2018). 35. World Bank (N/Ab), “World Bank national accounts data and OECD National Accounts data files”, available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=PL (15 December 2018). 36. World Bank (N/Ac), “World Bank national accounts data and OECD National Accounts data files”, available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=HR (15 December 2018). 37. Yanase, N., Asai, Y., Lai, G. C. (2008

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Marketing for Science Based Organizations Perspectives and Questions

Bibliography 1. A merican Marketing Association (2018). https://www.ama.org/AboutAMA/Pages/Definition-of-Marketing.aspx 2. Data Market (December 5, 2018). DataMarket: https://datamarket.com/data/set/1xdu/gdp-per-capita-constant-us-millions#!ds=1xdu!208h=1g&display=line 3. Drucker, P. (2008). The Five Most Important Questions You Will Ever Ask about Your Organization . San Francisco, California: Jossey-Bass 4. Drucker, P. (1973 & 1985). Management: Revised Edition . New York: HarperCollins. 5. Dubinskas, F. (1988). Janus

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Macroprudential Policies and Economic Growth

xtabond2: An introduction to “Difference” and “System” GMM in Stata.” Center for Global Development Working Paper No. 103. 21. Sanchez, A., & Rohn, O. (2016). How do policies influence GDP tail risks? OECD Economics Department Working Paper, No. 1339. 22. Slovik, P., & Cournede, B. (2011). Macroeconomic impact of Basel III. OECD Working Papers No. 844.

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Determinants of FDI in BRICS Countries: Panel Data Approach

Abstract

We empirically investigates the factors that affect Foreign Direct Investment (FDI) inflows in five BRICS countries for the period 1990–2015. We address the selection bias and unobserved heterogeneity by estimating a panel Heckman selection method and attempts to account for both selection and endogeneity within the new two-stage method. After addressing the above mentioned econometric issues, the infrastructure and GDP per capita variables under the new two-stage method remain positive and significantly similar to the coefficient of infrastructure and GDP per capita under the panel Heckman selection model. In addition, the inverse Mills ratio maintain its level of statistical significance, confirming the presence of both sample selection bias and endogeneity.

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