Stefano Magrini

The evolution of income disparities among the regions of the European Union

Abstract Per capita income disparities, particularly evident between developed and less developed countries, are of noticeable importance even amongst the regions of the European Union and do not seem to reduce their extent following the predictions of the neoclassical model, despite the high degree of openness typical of regional economies. The empirical analysis of convergence among regions confronts two problems that, if not correctly addressed, can reduce the validity of the results. The first concerns the definition of region. Very often, in fact, empirical analyses within a regional context make use of the available data for administrative regions without adequately considering the consequent results of this choice. The second problem is related to the nature of the growth process. The methodology followed by the vast majority of researchers, i.e., cross-sectional regression, is based on the hypothesis of a growth process characterised by a smooth path towards a steady-state. As some authors have demonstrated empirically that this underlying hypothesis is invalid, it is interesting to develop an alternative methodology the results of which are not subject to this restrictive hypothesis on the growth process. The methodology suggested in this study focuses directly on the cross-sectional distribution of per capita income, modelling the growth process as a time homogeneous Markov chain. The methodology is then applied to per capita income data for 122 EU functional regions over the period 1979–1990.

Regional (Di)Convergence

Do regions converge? This essay provides an overview of the key developments in the study of regional convergence, discussing the methodological issues that have arisen since the first attempts to analyse convergence and critically surveying the results that have been obtained for different regional systems. Two underlying arguments will guide the attempt to reach an answer: (i) not all empirical approaches to the analysis of convergence appear equally reliable and not all results equally convincing; (ii) although most regional convergence studies make use of empirical methods originally developed to analyse cross-country convergence, regions and countries are far from interchangeable concepts. The picture that emerges from this particular perspective is one in which convergence is often confined to groups of geographically contiguous regions.

Endogenous Processes in European Regional Growth: Convergence and Policy

The traditional empirical approaches to the analysis of economic growth,cross-section and panel data regressions are substantially uninformative withrespect to the issue of convergence. Whether national or regional economies appear to converge in terms of per capita income or productivity levels (the so-called b-convergence) critically depends on the way in which the empirical model is specified. Traditional specifications witness a disproportionate presence of proxies for forces leading towards divergence among the conditioning variables. It is therefore hardly surprising that these analyses find a positive and statistically significant value for the estimate of the speed of convergence. Copyright 2000 Gatton College of Business and Economics, University of Kentucky.

Analysing Convergence through the Distribution Dynamics Approach: Why and How?

The convergence hypothesis has stimulated a heated debate within the growth literature. The present paper compares the two most commonly adopted empirical approaches, the regression approach and the distribution dynamics approach, and argues that the former fails to uncover important features of the dynamics that might characterise the convergence process. Next, it provides an in depth description of the features and underlying assumptions of the distribution dynamics approach as well as a detailed discussion of some important aspects related to the estimate of stochastic kernels via kernel density estimators. Finally, the empirical section allows to emphasises the interpretational advantages stemming from the use of stochastic kernels to capture the evolution of the entire cross-sectional income distribution. Incidentally, through a comparison between the results obtained from alternative sets of Italian regions, it suggest that the use of administrative regions could lead to ambiguous results.

Urban Growth Drivers and Spatial Inequalities: Europe - a case with geographically sticky people

We try to combine theory with empirical analysis to investigate the drivers of spatial growth processes, welfare and disparities in a context in which people are markedly immobile. Drawing on two of our recent papers (Cheshire and Magrini, 2006 and 2008), we review the evidence on the drivers of differential urban growth in the EU both in terms of population and output growth. The main conclusion from our findings is that one cannot reasonably maintain the assumption of full spatial equilibrium in a European context. This has a number of wider implications. It suggests that i. differences in real incomes in Europe - and more generally where populations are relatively immobile - are likely to persist and indicate real differences in welfare; ii. there is no evidence of a unified European urban system but rather of a set of national systems; iii. there are significant but theoretically consistent, differences in the drivers of population compared to economic growth.

Business cycle dynamics across the US states

Abstract The analysis of synchronization among regional or national business cycles has recently been attracting a growing interest within the economic literature. Far less attention has instead been devoted to a closely related issue: given a certain level of synchronization, some economies might be systematically ahead of others along the swings of the business cycle. We analyze this issue within a system of economies and show that leading (or lagging behind) is a feature that does not occur at random across the economies. In addition, we investigate the economic drivers that could explain this behavior. To do so, we employ data for 48 conterminous US states between 1990 and 2009.

Nonparametric Regression with Spatially Dependent Data

In this paper we present a new procedure for nonparametric regression in case of spatially dependent data. In particular, we extend usual local linear regression (along the lines of Martins-Filho and Yao, 2009) and propose a two-step method where information on spatial dependence is incorporated in the error covariance matrix, estimated nonparametrically. The finite sample performance of our proposed procedure is then shown via Monte Carlo simulations for various data generating processes.

European Urban Growth: Now for Some Problems of Spaceless and Weightless Econometrics

This paper investigates growth differences in the urban system of the EU12 for a data set relating to Functional Urban Regions comparing the results of �artisanal� methods of model selection with those obtained using general to specific model selection with PcGets. The artisanal approach tests hypotheses relating to the role of human capital, EU integration and fragmentation of urban government. The paper also explores issues of spatial dependence and mechanisms of spatial interaction. Using PcGets as suggested by Hendry and Krolzig (2004) to optimise model selection we find that while PcGets provides a powerful tool for model selection when applied to cross sectional data, caution is necessary to ensure that variables relating to spatial adjustment processes are included and spatial dependence is avoided. More generally, not only do the results provide consistent estimates of parameters but they also support relevant theoretical insights. Finally careful testing for spatial dependence reveals that national borders are still significant barriers to adjustment within the EU.

Regional Convergence and Aggregate Business Cycle in the United States

Magrini S., Gerolimetto M. and Engin Duran H. Regional convergence and aggregate business cycle in the United States, Regional Studies. The existing literature on convergence largely ignores the effect of aggregate fluctuations on the evolution of income disparities. However, if regional disparities follow a distinct cyclical pattern in the short run, the period of analysis should be chosen with great care to avoid distortions in the results. By analysing convergence among forty-eight conterminous US states through the distribution dynamics approach, it is shown that these distortions could be quite sizeable. Moreover, when convergence is analysed over an appropriate period that includes only complete cycles (1989–2007), results show that regional disparities exhibit a pro-cyclical behaviour and that the underlying long-run tendency is towards divergence.

A Novel Look at Long-run Convergence Dynamics in the United States

When regional disparities follow a cyclical short-run pattern, convergence analysis results can be sizably distorted. To tackle this issue, we propose a method based on the extraction of the trend from regional income time series that eschews misleading results when the nature of the cyclical pattern changes over time. Using real per capita personal income data for forty-eight conterminous US states and the distribution dynamics approach, we identify the following three distinct consecutive phases: strong convergence (1930–1970), substantial persistence (1971–1980), and divergence (1981–2010).