The determinants of regional growth: An empirical analysis

The paper analyses the growth process at work in the European Union during the period 1979-1990. The first part of the paper describes a theoretical model that guides the empirical work. Particular emphasis is placed on the role played by human capital, research activities and spillovers of technological knowledge. The model is then tested using OLS on a database of 122 major European Functional Urban Regions (FURs)

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.Distribution Dynamics, Stochastic Kernel, Kernel Density Estimation, beta-convergence, Regions

Group versus individual discrimination among young workers: a distributional approach

We evaluate the gender wage gap and the unexplained gender wage differential for workers 15-29 year old during the period 1990-1997, using a particularly rich set of data from the Italian Social Security System covering all individuals in the labour markets of two Italian provinces. We estimate separate earnings functions for men and women correcting for endogeneity of education and we evaluate gender discrimination by studying the entire distribution of the unexplained wage gap as suggested by Jenkins (1994). We evaluate discrimination against females by means of bivariate density functions. This innovation makes it possible to condition the density distribution on the marginal distribution of any characteristic and to evaluate more precisely the existence of group and individual discrimination. Our analysis suggests that discrimination is not evenly distributed among women, in relation to their characteristics; in particular, there is evidence of lower discrimination against highly educated females. Moreover in 1997, compared to 1990, discrimination increased in a appreciable way, affecting human capital rich females more significantly. While our work is based in a very local context the richness of the data and the methodological innovation give the results a wider application.wage differentials, wage discrimination, gender

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.nonparametric smoothing, spatial dependence

Convergence analysis as distribution dynamics when data are spatially dependent

Conditional distributions for the analysis of convergence are usually estimated using a standard kernel smoother but this is known to be biased. Hyndman et al. (1996) thus suggest a conditional density estimator with a mean function specified by a local polynomial smoother, i.e. one with better bias properties. However, even in this case, the estimated conditional mean might be incorrect when observations are spatially dependent. Consequently, in this paper we study per capita income inequalities among European Functional Regions and U.S. Metropolitan Statistical Areas through a distribution dynamics approach in which the conditional mean is estimated via a procedure that allows for spatial dependence (Gerolimetto and Magrini, 2009).Regional convergence, Distribution dynamics, Nonparametric smoothing, Spatial dependence

Analysing Growth and Distribution Dynamics - Isolating Divergence Factors

This paper analyses the factors driving convergence and divergence processes in the growth dynamics of European urban regions over the period 1978 to 1994. To achieve this, we develop a two-stage procedure. First, viewing growth of real GDP per capita as a multivariate process, a fully specified growth model is estimated assessing growth dynamics and the role of a rich set of variables. In particular, as noted elsewhere (Cheshire and Magrini, 2005), evidence is found which is supportive of a spatial adaptation of the endogenous growth model, with human capital related variables having a highly significant role in explaining growth differences. The second stage then uses a ‘distribution dynamics’ approach to evaluate the contribution of individual growth factors to convergence dynamics. More specifically, regression results are used to simulate alternative end period incomes which, via the estimation of stochastic kernels, enable us to isolate the role of selected variables in shaping the dynamics of the cross-sectional distribution of per capita income. This analysis suggests that the most important factor determining the form of FUR growth and convergence dynamics observed from 1978 to 1994 was the differing distribution of human capital. These results are compared with the results using the Markov Chain approach and it is found both techniques lead to similar conclusions.

Population Growth in European Cities: weather matters – but only nationally

This paper investigates differences in the rate of growth of population across the large city-regions of the EU12 between 1980 and 2000. The US model which assumes perfect factor mobility does not seem well adapted to European conditions. There is evidence strongly suggesting that equilibrating migration flows between cities in different countries are highly constrained in the EU. However, quality of life motives do seem to be a significant and important feature of differential population growth rates if measured relative to national rather than EU12 values. Once other factors are allowed for, a systematic and highly significant factor determining rates of urban population growth is climatic variation. Cities with better weather than that of their countries have systematically tended to gain population over the past 20 years once other factors – including natural rates of increase in the areas of each country outside the major cities - are allowed for: there is no such effect for climate variables if expressed relative to the value of the EU12 as a whole. On the other hand, there is evidence that the systematic spatial gains from European integration are reflected in a city’s population growth. The results are tested for spatial dependence and remain robust.growth; cities; quality of life differences; mobility; migration

Raising Urban Productivity or Attracting People? Different Causes, Different Consequences

This paper investigates growth differences in the urban system of the EU12 over the last decades of the 20th Century. Models in which growth of real GDP p.c. and rates of population growth are the dependent variables are compared. This suggests that it makes sense to model GDP growth in a European context. The analysis supports the conclusion that systems of urban governance are significantly related to economic growth, as is the distribution of highly skilled human capital and R&D activity. In addition, evidence is found supporting the conclusion that integration shocks in the EU favour core areas but when all else is controlled for peripheral regions experienced a systematic positive growth differential. Careful testing for spatial dependence reveals that national borders are significant barriers to adjustment but we can resolve such problems by including a set of variables designed to reflect spatial economic adjustment mechanisms where cities are densely packed so their economies interact. Models of population growth show some similar results but interesting and revealing differences. Strong evidence is found that there are substantial national border effects impeding the emergence of a full spatial equilibrium across the EU’s urban system. Better climate is the single most significant variable but only when expressed relative to the national (not EU) mean. As with economic growth, there are significant national border effects in patterns of spatial dependence. Concentrations of human capital and R&D, however are if anything negatively associated with attracting population – a finding which parallels the finding that a better climate relative to the national mean is associated with slower rather than faster growth of real GDP per capita.growth; cities; local public goods; human capital; convergence; territorial competition

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.Growth, urban system, spatial equilibrium

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

This paper investigates growth differences in the urban system of the EU12 between the means of 1978/80 and 1992/94 for a data set relating to Functional Urban Regions rather than the more normal NUTS regions comparing the results of ‘artisanal’ methods of model selection with those generated using general to specific model selection (using 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 yields a model virtually identical to the artisanal approach if mechanisms of spatial interaction are ignored. Testing, however, reveals problems of spatial dependence. We interpret this as indicating that significant variables reflecting mechanisms of spatial economic adjustment have been omitted. Including such variables in the set available to PcGets leads to the inclusion of two measures of spatial adjustment. Further testing shows that problems of spatial dependence are now eliminated. We interpret this result as evidence 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. Not only do the final results provide consistent estimates of parameters but they also support relevant theoretical insights. Moreover careful testing for spatial dependence reveals that national borders are still significant barriers to adjustment within the EU.