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: Edward Elgar Publishing BLUNDELL, R. &. S. BOND (1998), ‘’Initial conditions and moment restrictions in dynamic panel data models’’. Journal of econometrics , 87(1), pp. 115-143 BRIDA, J. G. & M. PULINA (2010), ‘’A Literature review on the tourism-led-growth hypothesis. Cagliari’’. CRENoS-CUEC (Working Papers CRENoS, 2010, 17) CANDELA, G. & P. FIGINI (2012.), The Economics of Tourism Destinations . Berlin Heidelberg: Springler-Verlag CORTÉS-JIMÉNEZ, I. & M. PULINA (2010), “Inbound tourism and long-run economic growth”. Current Issues in Tourism , 13(1), pp. 61


Research background: Posner’s technology gap theories and Vernon’s product life cycle assume that differences in innovation and technology levels are the cause of foreign trade. These theories are subject to empirical verification. To date, however, the analysis of the impact of innovation distance on a country’s export competitiveness is omitted. This article tries to fill this research gap. The author attempts to examine the relationship between the innovation gap and export competitiveness in industries with varying levels of technological advancement.

Purpose: The aim of the article is to research the direction and strength of the impact of the innovation gap on export competitiveness in 10 different industries in Central and Eastern Europe countries (CEECs).

Research methodology: Dynamic panel models were used in the research, which describe the impact of the technological gap on the export competitiveness of countries. To measure innovation, the indicator of innovative comparative advantage was constructed and based on the number of patents used. The technological gap in individual countries was calculated as the Euclidean distance indicators of the innovative advantage in a given country from other countries.

Results: In light of the presented results of the study, it can be concluded that innovation generally has a significant and positive impact on the competitiveness of exports in the high and medium-high technology industries of the CEECs, while it does not significantly affect the competitiveness of trade in low technology industries. In addition, the Visegrad countries in the high and medium-high technology industries generally have a low technological gap and a smaller distance in export competitiveness using the dynamic panel data model.

Novelty: The added value of this article is an innovative study on the impact of the technological gap on export competitiveness with the example of the CEECs using the dynamic panel data model.

panel data Monte Carlo evidence and application to employment equation. Review of Economic Studies, 58,277,97. Becker, K. and S. Holmes (2006). Corporate Income Tax Reform and Foreign Direct Investment in Germany: Evidence from Firm-Level Data, Cesifo Working Paper No.177 Category 1: Public Blundell, R. and Bond S. (1998). Innitial conditions and moment restrictions in dynamic panel data models,’ Discussion Paper No. 97-07, University College London. Boadway, R. (1979). Investment Incentives, Corporate Taxation and Efficiency in the Allocation of Capital. http


This study aims to examine bilateral trade flows across ECOWAS-15 nations with the use of a panel and cross section for the period of 1981-2013. The methodology carried out to achieve this objective involves the use of various techniques of estimation for the gravity model (Static and dynamic). More specifically, this study aims to investigate the formational impact of regional trade integration agreements on trade flows within a group of countries using the same currencies and ECOWAS at large. The main use of regional variables into gravity models is intended to determine whether RTAs lead to trade creation, or diversion. The results show the presence of a strong relationship among the factors of both RIAs and trade flows.


This paper assesses the effects of agricultural payments on changes in farmland bird diversity in Slovenia. Diversity was measured by Shannon index, while the impacts were estimated with the first-difference estimator on panel data for municipalities with and without special protection areas for birds. The effects of agricultural payments on farmland biodiversity require that the balance of financial instruments be taken into account when the agricultural policy is being drafted. The effects of payments in municipalities with and without special protection areas indicate the need to consider the landscape perspective and adapt schemes to landscape type while preparing the national agricultural policy.


Non-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable decision-making process should be implemented, for minimizing the effects of credit risk. The current paper uses a dynamic panel regression model to present the determinants of NPLs for the largest five banks of the Romanian Banking System during 2007-2016. A Generalized Method of Moments (GMM) regression is used and defined under three different types of variables: bank specific indicators, macroeconomic indicators and qualitative variables. Other studies illustrated also the determinants of NPLs in various banking systems from all around the world, such as Japan, China or several CEE countries (especially the emergent ones). After an in-depth analysis of the literature and Romanian market, the following variables were found to be relevant and were introduced into a dynamic data panel model: unemployment rate, annual average growth rate of gross domestic product, return on equity (ROE), loan to deposit ratio (LTD). The existing literature presents ROE as having a negative impact on NPLs, unemployment rate being positive correlated with NPLs and a negative relationship between economic growth and such loans. Our contribution to the current literature is represented by the introduction of two additional qualitative variables (Board Risk Management Ratio (BRMR), as the proportion of risk managers within the Board of Directors of each bank in question and the Expert Aggregate Priority Vector (EAPV), as the aggregated perceived risk regarding the NPLs). The decision of introducing these variables relies on previous research made in this area, results being validated by experts from the Romanian Banking System, according to the BASEL III and NBR criteria. The results of the current paper are consistent with the existent literature, the correlations and impact of the variables being relevant for the subject matter.

Studies 59, 645, 61 56 Barth, J.R. and Bradley, M. (1988). The impact of government spending on economic activity, mimeo, The National Chamber Foundation, Washington D.C. Benos N. (2004). Fiscal Policy and Economic Growth: Empirical Evidence from OECD Countries. Bleany M., Gemmell N., and Kneller R. (1995). Economic growth (New York; McGraw-Hill) Blundell, R. and Bond S. (1998). Innitial conditions and moment restrictions in dynamic panel data models,’ Discussion Paper No. 97-07, University College London. Cashin, P

, European higher education policy logics and policy implications”, Higher Education, Vol. 61, No. 6, pp. 757–769. 12. Park, H. M. (2011), Practical Guides To Panel Data Modeling: A Step by Step Analysis Using Stata, PhD, International University of Japan, Japan. 13. Paulsen, M. B., Smart, J. C. (2001), The Finance of Higher Education: Theory, Research, Policy, and Practice, Algora Publishing, USA. 14. Psacharopoulos G., Patrinos, H. A. (2004), “Returns to investment in education: a further update”, Education Economics, Vol. 12, No. 2, pp. 111-134. 15. Santiago, R

Models With Varying Parameters as A Tool to Classify Polish Voivodships in 2002-2008

One of the often used measures of economic development is gross domestic product per capita. In Poland the Main Statistical Office collects the data on this variable on several levels of aggregation. The paper shows the application of panel data models in order to classify Polish voivodships according to the level of economic development. As explained variable the regional GDP per capita was used and such variables as structure of employees, unemployment rate or retail sales per capita were the explaining variables. As a result the groups of voivodships with similar pattern of economic development were distinguished.


Recently, there has been observed intensified research on the impact of income inequalities on aspects of socio-economic development in the European Union. However, there are no comprehensive analyses concerning the relationship between these phenomena. Therefore the subject of the paper is the influence of income inequalities on socio-economic development. The author would like to verify the hypothesis that the character of the impact of income inequalities on socio-economic development in the European Union is negative. Analysis was conducted for the European Union in 2004-2017 using the panel data model, also estimated was the synthetic indicator of socio-economic development. The research conducted in the paper leads to ambiguous conclusions. On the one hand, inequalities measured for the whole distribution of income have no influence on socio-economic development in the European Union. However, the income gap between the richest and the poorest hinders the mentioned phenomenon.