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Is there Convergence or Divergence in the International Competitiveness of the Eurozone Countries?
Abstract
The unexpected Eurozone Sovereign Debt Crisis (2010–2012) aroused different attempts of interpretation among analysts and practitioners. While some attributed the crisis to a “contagion” effect of the Subprime Mortgages Financial Crisis in the United States (2007–2009), others saw in it an expression of deeper fundamental economic imbalances.
This chapter presents an evaluation of whether there is convergence or divergence in the sectorial international competitiveness of the Eurozone area countries. A Dynamic Panel Data analysis on country-level exports for all Eurozone members for a period that goes from 1993 to 2014 finds significant evidence of international competitiveness convergence in four- out of 10-export sectors, and no significant evidence of divergence in the rest. While that evidence is not consistent with the high expectations generated by monetary integration more than 15 years ago, those four sectors correspond to high value-added economic activities and, in that sense, indicate a more homogeneous productive modernization process is taking place in the area.
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This paper reexamines the benefits of pooling and, in addition, contrasts the performance of newly proposed heterogeneous estimators. The analysis utilizes a panel data set from 46 American states over the period 1963 to 1992 and a dynamic demand specification for cigarettes. Also, the forecast performance of the various estimators is compared. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology
This paper examines whether the Solow growth model is consistent with the international variation in the standard of living.
It shows that an augmented Solow model that includes accumulation of human as well as physical capital provides an excellent
description of the cross-country data. The paper also examines the implications of the Solow model for convergence in standards
of living, that is, for whether poor countries tend to grow faster than rich countries. The evidence indicates that, holding
population growth and capital accumulation constant, countries converge at about the rate the augmented Solow model predicts.
This paper challenges the current belief that income inequality has a negative relationship with economic growth. It uses an improved data set on income inequality, which not only reduces measurement error, but also allows estimation via a panel technique. Panel estimation makes it possible to control for time-invariant country-specific effects, therefore eliminating a potential source of omitted-variable bias. Results suggest that in the short and medium term, an increase in a country's level of income inequality has a significant positive relationship with subsequent economic growth. This relationship is highly robust across samples, variable definitions, and model specifications.
I. Introduction, 65. — II. A model of long-run growth, 66. — III. Possible growth patterns, 68. — IV. Examples, 73. — V. Behavior
of interest and wage rates, 78. — VI. Extensions, 85. — VII. Qualifications, 91.
This paper assesses how income inequality influences economic growth by estimating a reduced form growth equation across the 32 Mexican States.
Using dynamic panel data analysis, with both urban personal income for
grouped data and household income from national surveys, it finds that
inequality and growth are positively related. This relationship is stable
across variable definitions and data sets, but varies across regions and
trade periods.
This paper presents specification tests that are applicable after estimating a dynamic model from panel data by the generalized
method of moments (GMM), and studies the practical performance of these procedures using both generated and real data. Our
GMM estimator optimally exploits all the linear moment restrictions that follow from the assumption of no serial correlation
in the errors, in an equation which contains individual effects, lagged dependent variables and no strictly exogenous variables.
We propose a test of serial correlation based on the GMM residuals and compare this with Sargan tests of over-identifying
restrictions and Hausman specification tests.
A key economic issue is whether poor countries or regions tend to grow faster than rich ones: are there automatic forces that lead to convergence over time in the levels of per capita income and product? The authors use the neoclassical growth model as a framework to study convergence across the forty-eight contiguous U.S. states. They exploit data on personal income since 1840 and on gross state product since 1963. The U.S. states provide clear evidence of convergence, but the findings can be reconciled quantitatively with the neoclassical model only if diminishing returns to capital set in very slowly. Copyright 1992 by University of Chicago Press.
Multivariate unobserved components (structural) time series models are fitted to annual post-war observations on real income per capita in countries in the Euro-zone. The aim is to establish stylized facts about convergence as it relates both to long-run and short-run movements. A new model, in which convergence components are combined with a common trend and similar cycles, is proposed. The convergence components are formulated as a second-order error correction mechanism; this ensures that the extracted components change smoothly, thereby enabling them to be separated from transitory cycles. Copyright © 2005 John Wiley & Sons, Ltd.
This paper extends the cross sectionally augmented panel unit root test proposed by Pesaran (2007) to the case of a multifactor error structure. The basic idea is to exploit information regarding the unobserved factors that are shared by other time series in addition to the variable under consideration. Importantly, our test procedure only requires specification of the maximum number of factors, in contrast to other panel unit root tests based on principal components that require in addition the estimation of the number of factors as well as the factors themselves. Small sample properties of the proposed test are investigated by Monte Carlo experiments, which suggest that it controls well for size in almost all cases, especially in the presence of serial correlation in the error term, contrary to alternative test statistics. Empirical applications to Fisher’s inflation parity and real equity prices across different markets illustrate how the proposed test works in practice.
The concepts of sigma-convergence, absolute beta-convergence and conditional beta-convergence are discussed in this paper. The concepts are applied to a variety of data sets that include a large cross-section of 110 countries, the subsample of OECD countries, the states within the United States, the prefectures of Japan, and regions within several European countries. Except for the large cross-section of countries, all data sets display strong evidence of sigma-convergence and absolute beta-convergence. The cross-section of countries exhibits sigma-divergence and conditional beta-convergence. The speed of conditional convergence, which is very similar across data sets, is close to 2 percent per year. Copyright 1996 by Royal Economic Society.