CLUB CONVERGENCE & REGIONAL SPILLOVERS IN EAST JAVA

This study try to identify the â-convergence process among regions in East Java using panel data of 37 regencies & municipalities between 1983-2002, taking into account the presence of spatial heterogeneity and spillover effects. Detection of spatial regimes using G-I* statistics (Getis & Ord, 1995) on regional per capita GDP values in 1983 found cluster of high income regions (group of “rich”) in central & eastern part of East Java, and cluster of low income regions (group of “poor”) in western part. The result of OLS & GLS regression on absolute convergence model found the existence of â-divergence process of East Java in overall period (1983-2003), consistent with the ó convergence which showing upward trend (divergence). Meanwhile, the same divergence process is also found in absolute convergence equation estimated for each club, even though in slower rate than East Java divergence rate. Using the methodology proposed by Burn, Combes, & Renard (2002) this study founds the existence of negative spillover effects between regions in “rich” clubs and from “rich” clubs to the “poor” one, where the magnitude is greater in the latter case. The club of “poor” regions is diverging faster than the “rich”. This finding is robust in every convergence equation (with or without the spillover effects). The lack of diversity on East Java’s manufacturing industries (Santosa & Michael, 2005 and Landiyanto, 2005) seems contribute to its divergence process by engaging a competitive mode between regions.â-convergence, divergence, spatial regimes, spillover effects

[Review of] Joseph Hraba. American Ethnicity

Hraba uses the social science disciplines--i.e., sociology, history, and psychology--to set the scope of his research on American ethnicity. Hraba combines the theoretical premises of assimilation, pluralism, and ethnic conflict theory as methods for Viewing ethnic group convergence to and divergence from American society. Each theory is only a partial explanation of societal modernization and ethnic evolution . . . and together they offer a fuller understanding of ethnic evolution in the modernization process (p. 7). Societal modernization and ethnic evolution are keys for understanding the convergence (inclusion) and divergence (exclusion) process

Technological Capabilities Asymmetries in Latin American and the Caribbean

This paper analyzes the convergence process in Latin America and the Caribbean during the 1960-2005 period. The evidence is not favorable to clear convergence or divergence trends, but to a slight process of convergence until the 1970s, and then global divergence. In turn, the results suggest the existence of transitory clubs of convergence during the 1960-1974 and 1990-1994 periods. After that, the lower income economies showed convergence to the relative richer countries, but in a context of increasing dispersion of the per capita income. The development accounting and the decomposition of the total factor productivity (TFP) indicate that those results are mainly explained by relative differences in the technological capabilities, and that the existence of structural differences is a key factor to explain the nonconvergence in technological capabilities. The efforts to integrate the economies were not enough to reduce the gap but the divergence in technological capabilities would have been worst without the integration process.Convergence; Total Factor Productivity Decomposition; Technological Capabilities; Economic Integration; Latin American and the Caribbean

Educating 14- to 19-year olds in England: a UK lens on possible futures

Here we draw on recent research and on earlier contributions on convergence and divergence across Great Britain to consider possible future trajectories for 14-19 education and training in England. We use a UK-wide lens to reflect on 14-19 strategies in England by showing how common issues can be tackled in different ways in Scotland, Wales and Northern Ireland. The article identifies what could be seen as three models of upper secondary education - Type 1 (England); Type 2 (Scotland and Wales); and Type 3 (Northern Ireland) - that have been part of the picture of divergence. We conclude that the process of divergence is likely to continue in the short-term but, in the longer term, wider political factors could produce post-devolution convergence. © 2011 Institute of Education, University of London

Testing for convergence in stock markets: A non-linear factor approach

This paper applies the Phillips and Sul (2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US over the period 1973-2008. We carry out the analysis on both sectors and individual industries within sectors. As a first step, we use the Stock and Watson (1998) procedure to filter the data in order to extract the long-run component of the series; then, following Phillips and Sul (2007), we estimate the relative transition parameters. In the case of sectoral indices we find convergence in the middle of the sample period, followed by divergence, and detect four (two large and two small) clusters. The analysis at a disaggregate, industry level again points to convergence in the middle of the sample, and subsequent divergence, but a much larger number of clusters is now found. Splitting the cross-section into two subgroups including Euro area countries, the UK and the US respectively, provides evidence of a global convergence/divergence process not obviously influenced by EU policies

Information Theoretic Structure Learning with Confidence

Information theoretic measures (e.g. the Kullback Liebler divergence and Shannon mutual information) have been used for exploring possibly nonlinear multivariate dependencies in high dimension. If these dependencies are assumed to follow a Markov factor graph model, this exploration process is called structure discovery. For discrete-valued samples, estimates of the information divergence over the parametric class of multinomial models lead to structure discovery methods whose mean squared error achieves parametric convergence rates as the sample size grows. However, a naive application of this method to continuous nonparametric multivariate models converges much more slowly. In this paper we introduce a new method for nonparametric structure discovery that uses weighted ensemble divergence estimators that achieve parametric convergence rates and obey an asymptotic central limit theorem that facilitates hypothesis testing and other types of statistical validation.Comment: 10 pages, 3 figure

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether beta-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.Stochastic convergence, beta-convergence, non-stationarity panel data tests, cross-section dependence, multiple structural breaks.

Testing for Convergence in Stock Markets: A Non-Linear Factor Approach

This paper applies the Phillips and Sul (2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US over the period 1973-2008. We carry out the analysis on both sectors and individual industries within sectors. As a first step, we use the Stock and Watson (1998) procedure to filter the data in order to extract the long-run component of the series; then, following Phillips and Sul (2007), we estimate the relative transition parameters. In the case of sectoral indices we find convergence in the middle of the sample period, followed by divergence, and detect four (two large and two small) clusters. The analysis at a disaggregate, industry level again points to convergence in the middle of the sample, and subsequent divergence, but a much larger number of clusters is now found. Splitting the cross-section into two subgroups including Euro area countries, the UK and the US respectively, provides evidence of a global convergence/divergence process not obviously influenced by EU policies.stock market, financial integration, European Monetary Union convergence, factor model

Testing stock market convergence: a non-linear factor approach

This paper applies the Phillips and Sul (Econometrica 75(6):1771–1855, 2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US between 1973 and 2008. We carry out the analysis on both sectors and individual industries within sectors. As a first step, we use the Stock and Watson (J Am Stat Assoc 93(441):349–358, 1998) procedure to filter the data in order to extract the long-run component of the series; then, following Phillips and Sul (Econometrica 75(6):1771–1855, 2007), we estimate the relative transition parameters. In the case of sectoral indices we find convergence in the middle of the sample period, followed by divergence, and detect four (two large and two small) clusters. The analysis at a disaggregate, industry level again points to convergence in the middle of the sample, and subsequent divergence, but a much larger number of clusters is now found. Splitting the cross-section into two subgroups including euro area countries, the UK and the US respectively, provides evidence of a global convergence/divergence process not obviously influenced by EU policies