Complete or Partial Inflation Convergence in the EU?

This paper has one primary aim: to analyze whether there exists evidence in favor of inflation convergence, complete convergence, or common trends, partial convergence, within the European Union (EU). The analysis is done in a bivariate and multivariate framework, for traded and non-traded inflation rates, using sequential unit root tests, common trends analysis, and cointegration tests that allow for structural breaks. The results suggest that there is a di¤erent behavior between traded and non-traded inflation rates. In the bivariate framework, there is much stronger evidence of complete convergence for traded inflation rates than for non-traded inflation rates. In the multivariate framework, the complete convergence is only presented in the most tradeable inflation rate and there is a small number of common trends for the rest of traded inflation rates that suggests evidence of partial convergence in terms of long-run relationships. Finally, neither complete nor partial convergence is presented in the non-traded inflation rates.convergence, common trends, structural breaks, traded and nontraded inflation rates, European Union.

Conditioning factors on regional European clubs - a distributional approach

Growth literature has considered the existence of groups of economies which have been termed convergence clubs. Literature confirms their existence for European regional case. This paper has focused on how conditioning factors are influencing European regional GDPpc distribution. The estimation of conditioned stochastic kernels is the optimum methodology to consider whole distribution or partial conditionings

The Rich North-west, The Poor Middle-east – Consumption In EU Households

The aim of paper is to analyze household consumption in EU countries in the 21st century. The two hypotheses posited have been confirmed. The start of the 21st century saw an increase in consumer spending in EU households and reduction in the disparities between households of different countries. At the end of the first decade there was a stabilization in consumer spending. The differences in consumption between households can be considered as a) the effect of freedom of choice, and b) a consequence of specific restrictions that do not allow for an appropriate level of funds to meet household needs. Households with the most favourable situation are located in the United Kingdom and Austria. The most unfavourable situation can be observed in the households of Estonia, Latvia, Poland, Romania and Bulgaria

Nonparametric approach to evaluation of economic and social development in the EU28 member states by DEA efficiency

Data envelopment analysis (DEA) methodology is used in this study for a comparison of the dynamic efficiency of European countries over the last decade. Moreover, efficiency analysis is used to determine where resources are distributed efficiently and/or were used efficiently/inefficiently under factors of competitiveness extracted from factor analysis. DEA measures numerical grades of the efficiency of economic processes within evaluated countries and, therefore, it becomes a suitable tool for setting an efficient/inefficient position of each country. Most importantly, the DEA technique is applied to all (28) European Union (EU) countries to evaluate their technical and technological efficiency within the selected factors of competitiveness based on country competitiveness index in the 2000-2017 reference period. The main aim of the paper is to measure efficiency changes over the reference period and to analyze the level of productivity in individual countries based on the Malmquist productivity index (MPI). Empirical results confirm significant disparities among European countries and selected periods 2000-2007, 2008-2011, and 2012-2017. Finally, the study offers a comprehensive comparison and discussion of results obtained by MPI that indicate the EU countries in which policy-making authorities should aim to stimulate national development and provide more quality of life to the EU citizens.Web of Science122art. no. 7

Inflation Differentials in the Euro Area and their Determinants – an empirical view

In this paper, we present evidence on the statistical features of observed dispersion in HICP inflation rates in the Euro area. Our descriptive exercise shows that there is still a remarkable dispersion of HICP inflation rates across the member countries. We find that most of dispersion originates in the non-traded categories of the HICP. This suggests that the main source of dispersion in countries' headline inflation rates is in those components of the HICP where non-traded goods (services, (public) goods with regulated and administered prices) are more intensely represented. We then examine the determinants of inflation differentials in a panel of the states of the Euro area in 1999–2007 using alternative classifications of this group and three different datasets. The evidence presented shows that output gaps and a proxy for price level convergence were statistically significant. On the other hand, some determinants that were found significant in previous studies (for example Honohan and Lane, 2003, 2004; ECB, 2003) has no impact on inflation in our expanded time span (e.g. exchange rate movements) The dispersion of HICP inflation is expected to increase in the coming years as the new EU member states will join the Euro area. There are some risks for these countries connected with the common monetary policy, which is adjusted more to the conditions of stabilized advanced economies forming the core of the Euro area. This creates potential problems for the EU common monetary policy (ECB), in particular negative (positive) interest rates, their repercussions on investment processes, consumption and the possibility of creating asset bubbles.http://deepblue.lib.umich.edu/bitstream/2027.42/64425/1/wp958.pd

Welfare Regimes in the UE 15 and in the Enlarged Europe - an Exploratory Analysis

The basic aim of this paper is to assess existing welfare regimes in the countries of European Union before and after the enlargement of May 2004 (EU 15 and EU 25) following a comprehensive approach that considers different dimensions of welfare through an extended set of variables. The paper starts with a brief presentation of current debates on welfare regimes and the new social policy agenda in the European Union. It proceeds with the selection of different dimensions of social welfare and social policy, and related key variables that constitute the database for the following statistical analysis. Correlations, factor analysis and cluster analysis are performed in order to produce the clustering of welfare regimes as well as a tentative interpretation of underlying characteristics and patterns of welfare mix and social policies in European Union.

Welfare Regimes in the UE 15 and in the Enlarged Europe: An exploratory analysis

The basic aim of this paper is to assess existing welfare regimes in the countries of European Union before and after the enlargement of May 2004 (EU 15 and EU 25) building on a comprehensive approach that considers different dimensions of welfare through an extended set of variables. The paper starts with a brief presentation of current debates on welfare regimes and the new social policy agenda in the European Union. It proceeds with the selection of different dimensions of social welfare and social policy and related key variables that make up the database for the following multivariate statistical analysis, used in order to produce a clustering of welfare regimes. The paper concludes with a tentative interpretation of the underlying characteristics and patterns of current welfare mix and social policies in European Union.Welfare Regimes; Social Policy; European Union; Enlargement; Cluster Analysis

Regional Measures of Human Capital in the European Union

The accumulation of the human capital stock plays a key role to explain the macroeconomic performance across regions. However, despite the strong theoretical support for this claim, empirical evidence has been not very convincing, probably because of the low quality of the data. This paper provides a robustness analysis of alternative measures of human capital available at the level of EU NUTS1 and NUTS2 regions. In addition to the univariate measures, composite indicators based on different construction principles are proposed. The analysis shows a significant impact of construction techniques on the quality of indicators. While composite indicators and labour income measures point to the same direction of impact, their correlation is not overwhelmingly high. Moreover, popular indicators should be applied with caution. Although schooling and human resources in science and technology explain some part of the regional human capital stock, they cannot explain the bulk of the experience.human capital indicators, regional growth

European cohesion policy after 2006:some comments about current proposals

EU regional policy is in a challenging and dynamic period of change. Not only are there significant administrative problems to overcome in both the current and the new Member States, but there is also a major ongoing debate about the reform of EU regional policy after 2006. Post 2006, the principal challenge concerns economic and social cohesion in an enlarged Union. Enlargement will lead to a severely unbalanced EU territory in terms of the widening disparities between Member States and regions. The degree to which EU regional policy can meet these challenges will be determined by budgetary constraints. The period of successive increases in EU regional policy ended at the Berlin Council in March 1999. Aspects of the current debate concern not only the EU regional policy budget for 2007-2013 but also the possible allocations. In this context, the paper has two main objectives: a) To identify regional disparities in the forthcoming enlarged Europe using multivariate statistical analysis techniques. b) To assess different proposals arising from the Commission open debate on future Cohesion Policy. The data used in the analysis is Newcronos-REGIO database elaborated by EUROSTAT. As a result, a classification of all regions (NUTsII) in the EU-25 is obtained through factor and cluster analysis techniques. Results obtained show that regional disparities cannot be exclusively explained by GDP per capita. Other factors linked to the behaviour of the labour market and to the demographic characteristics of the territories are also of a great importance Key words: Economic and Social Cohesion, Regional Policy, Cluster Analysis

Assessing potential output growth of the Maltese economy using a production function approach

After outlining the various methods used to estimate potential output, this article presents estim- ates for Malta, the smallest member of the euro area, de- rived from one of the most commonly used methods, the production function approach. Given the uncertainty surrounding these kinds of estimates, these estimates are compared with those made for Malta by other in- stitutions using di erent methods. Based on this ana- lysis and on a cross-country comparison with other euro area economies, a number of observations are made that would enable potential growth to accelerate and result in a faster economic convergence.peer-reviewe