Migration decisions are complex, involving both economic and non-economic considerations, and are often made in conditions that depart significantly from the idealised information assumptions of many models. This paper uses a three-stage experimental research design to analyse migrant decision making in the face of complexity and varying information conditions (complete, imperfect, and overloading). It pays particular attention to differences based on previous migration experiences. It focuses on four main issues: (a) the balance between monetary and non-monetary factors; (b) the computation, via a range of methods, of relative decision weights attached to different factors; (c) the impact of country image in relation to information; and (d) the role of preferences in dealing with missing information. The research examines the decision weights for eight attributes of potential destination countries for a sample of 157 young, educated individuals in Slovakia. The relative advantages and challenges of utilising experimental methods in migration research are illustrated.3
There is no way to adequately evaluate the economic development of the V4 countries over recent decades without taking into account the role played in it by foreign direct investment (FDI
The objective of the paper is to give a picture of the sources of economic growth in the V4 countries during the decade following their EU entry and to crosscheck the results obtained by parametric and non-parametric approaches. Growth accounting technique is used to depict dynamics of the V4 countries evolution since 1995 up to 2013. The poor post-crisis performance reflected in TFP indicator is in line with the result of the absence of technological progress obtained by data envelopment analysis. Research Design & Methods: Sources of the economic growth are identified by growth accounting based on Solow-Swan model. Non-parametrical part employs an SBM measure of efficiency in Data envelopment analysis as an application of linear programming optimization. Findings: Main findings include determining faster-than-average economic growth of the V4 followed by a considerable decline both in total factor productivity and in catching-up rate in the after-crisis period. DEA approach reveals excessive use of labor in all of the V4 countries and finds almost negligible technological change. Implications & Recommendations: The main concern for economic policy in the V4 as well as the entire EU continues to be tackling unemployment and facilitating factors´ productivity by structural reforms. Contribution & Value Added: The paper makes use of parametric and non-parametric approaches with a view to cross-checking the results obtained on the technological change within the EU at large and across the V4 countries in particular. Article type: original research paper
National (global) competitiveness became the central issue during the global crisis. Using the values of the three main subdimensions of the Global Competitiveness Index, we propose alternative DEA-based competitiveness indicators. In our approach, the index is nested in the more general measure of the competitiveness-given-performance indicator. We find that globally competitive European countries do not transform competitiveness into income per capita efficiently. Decomposition of the scores suggests that most of the relative inefficiency concentrates in innovation activity. The results proved robust against the CCR model used in previous research as well as principal component analysis.
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