Academic journal article Global Economic Observer

Testing the Convergence Hypothesis in the European Union

Academic journal article Global Economic Observer

Testing the Convergence Hypothesis in the European Union

Article excerpt

(ProQuest: ... denotes formulae omitted.)

1. Introduction

There are many statistical indicators used to assess the degree of economic convergence for more regions or countries. In this article, we are not interested in the classical measures used to evaluate the convergence. We will use the catch-up rate, which is not actually a convergence indicator, but it provides us indirectly important information regarding the degree of convergence. Moreover, the classical statistical indicators coefficient of variation, variance or inequality indicators are not enough to catch the evolution of the convergence process. Therefore, we propose in this article the study of convergence process in European Union in different periods by using the statistical tests.

This paper has several parts. After a brief introduction, a short literature review is made, underlying the latest results regarding the convergence assessment.

The empirical application supposes the computation of catch-up rates for each state of the EU-28 in different periods and the statistical evaluation of convergence process using the tests recognised by literature. A section dedicated to main conclusions was presented in the end.

2. The economic convergence in literature

Sala-i-Martin (1996) presented two classical measures of convergence represented by beta and sigma indicators that can also be used in order to compute the speed for getting convergence. Sigma measure reflects the convergence or divergence tendency and it depends on the value of sample variance. Beta indicator computes the speed for getting the convergence when it has a negative value. Authors like Mankiw, Römer and Weil (1992) and Islam (1995) showed that the economies with a low initial income will grow faster than the economies with higher initial incomes, using control variables like population growth and saving rate. Quah (1996) and Durlauf (1996) concluded that the transversal growth model is incompatible with the convergence, but consistent with the multiple mechanisms of endogenous growth. Friendman (1992) and Quah (1996) claimed that the real convergence should not be measured using beta indicator. The beta and sigma measures are linked and reciprocal checked. The poor economies tend to have a high speed of increase compared to the rich countries. This observation implies the following facts: the coefficient of variation for GDP/capita decreases in a slow way and there is a negative relation between the rate of GDP/capita and the initial level of this variable.

Azomahou, El ouardighi, Nguyen-Van, and Cuong Pham (2011) proposed a semi-parametric partially linear model to assess the convergence between EU countries, showing that there is no convergence for members with high income. Beyaert and Garcia-Solanes (2014) measured the impact of economic conditions on long-term economic convergence. The convergence in terms of GDP/capita is different from that of the business cycle during 1953-2010. Cuaresma, Havettová and Lábaj (2013) evaluated the income convergence dynamics and they proposed some forecast models for European countries. The authors predicted that the human capital investment will determine income convergence.

Palan and Schmiedeberg (2010) tested the structural convergence in terms of unemployment rate for Western European countries, observing divergence for technology-intensive manufacturing industries. Le Pen (2011) utilized the pair-wise convergence of Pesaran (2007) for the GDP per capita of some European regions.

Crespo-Cuaresma and Fernández-Amador (2013) determined the convergence patterns for European area business cycles. In the middle of 80's there was an obvious business cycle divergence while in '90 the convergence was persistent.

Kutan and Yigit (2009) used a panel data approach for 8 new countries in the EU and they stated that the productivity growth was determined by human capital in the period from 1995 to 2006. Monfort, Cuestas, and Ordóñez (2013) observed two convergence clubs in EU-14 by applying a cluster analysis. …

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