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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.
Tomislava Pavić Kramarić, Marko Miletić and Renata Kožul Blaževski
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
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.
Andriy Stavytskyy, Vincent Giedraitis, Darius Sakalauskas and Maik Huettinger
This paper investigates the historical trends in economic development through the impact of economic depressions and emissions of greenhouse gasses, namely carbon dioxide (CO2). The analysis includes four countries: the United States, the United Kingdom, Germany and Japan. The focus, therefore, will be on the impact of two economic crises and their effect on global warming. Temperature changes in the longer period are very often regarded as a result of human activity, which can be measured by the increase of GDP (per capita). The findings indicate that GDP (per capita) parameters cannot be considered as correct measures of human pollution activity. The results show that the long-run temperature can be evaluated with the help of annual average temperatures of the previous four years. The proposed model does not only provide quite satisfactory forecasts, but is very stable with coefficients variables that can make a model more reliable for practice.
The aim of this paper is to analyze the convergence process among former Socialist countries, the Central and Eastern European (CEE), Western Balkan and Eastern Partnership countries. The relationships between the selected macroeconomic variables and per capita GDP growth rate are econometrically tested to support this research. The analyzed period is 2004-2016, with two sub-periods; 2004-2008 and 2009-2013. The subdivision is made to test if the recent financial crisis affected the absolute and conditional convergence process. The empirical findings support the economic convergence hypothesis. The results show that the recent financial crisis negatively affected only the absolute convergence process. The negative effects of the crisis on conditional convergence are not identified. The poorer countries in the analyzed group should do more to attract investment, as gross fixed capital formation has a clear positive impact on per capita growth in the examined sample of countries.
Hlalefang Khobai, Nicolene Hamman, Thando Mkhombo, Simba Mhaka, Nomahlubi Mavikela and Andrew Phiri
This study sought to contribute to the growing empirical literature by investigating the effects of FDI on per capita GDP growth for South Africa using time series data collected between 1970 and 2016. Compared to the majority of previous studies, we use quantile regressions which investigates the effects of FDI on economic growth at different distributional quantiles. Puzzling enough, the empirical results show that FDI has a negative influence on welfare at extremely low quantiles whereas at other levels this effect turns insignificant. Contrary, the effects of domestic investment on welfare is positive and significant at all levels. Collectively, these results have important implications for policymakers in South Africa.
This paper presents an empirical investigation of a large number of potentially significant determinants of current account deficits in five EU candidate and potential candidate countries (Albania, Croatia, Macedonia, Serbia and Turkey) in the period 2005 Q1-2015 Q4. Using panel regression techniques we find that current account imbalances in the EU candidate and potential candidate countries are mainly determined by real GDP growth rate and the degree of trade integration. Other factors that have a significant impact on current account balances include relative per capita income, crude oil trade balance and level of financial development. Interestingly, the status of the observed country (an EU candidate or a potential candidate country) does not have any effect on the current account balance. It is expected that further economic and financial development of the EU candidate and pre-accession would encourage domestic saving and contribute to improvement of their current account positions.
The aim of this paper is to evaluate the individual- and country-level variations in unregistered employment. To analyse whether it is marginalised groups who are more likely to engage in unregistered employment and explain the country-level variations, a 2010 Life in Transition Survey (LiTS) involving 38,864 interviews in 35 Eurasian countries is reported. Multilevel logistic regression analysis reveals that younger age groups, the divorced, and those with fewer years in education, are more likely to be unregistered employed. On a country-level, meanwhile, the prevalence of unregistered employment is strongly associated with tax morale; the greater the asymmetry between informal and formal institutions, the greater is the prevalence of unregistered employment. It is also higher when GDP per capita as well as social distribution and state intervention (subsidies and transfers, social contribution expenditure, health expenditure) are lower. The paper concludes by discussing the theoretical and policy implications.