Human capital and "club convergence" in Italian regions

The aim of the study is to investigate the presence of “convergence clubs†among Italian regions applying the stochastic notion of convergence. Regions are sorted according to some human capital accumulation indicators using the Classification and Regression Tree Analysis (CART). The analysis evidences a strong stochastic convergence process which characterizes all the regions suggesting the presence of different growth patterns. Furthermore, results seem to highlight that human capital accumulation favours regional growth particularly in initially “backwards†regions.

L'ASIMMETRIA DEGLI SHOCKS MONETARI SULLA PRODUZIONE NELLE REGIONI DELL'UNIONE MONETARIA EUROPEA

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A new approach for β-convergence estimation in Italy

In this paper we test the presence of β-convergence among Italian regions, in the period 1980-2003, in presence of a trend break in the series following a new approach (Vogelsang and Tomljanovich, 2002). The break year is considered either known (1992) and endogenously estimated from the data. When we consider a known trend break date model the results evidence the presence of a convergence process for most of the Italian regions in the considered period. The outcome relative to the unknown break date model, on the contrary, strongly depend on the econometric model used to estimate the β-convergence.β-convergence regional convergence

Regional convergence in Italy: time series approaches

This paper investigates the evolution of the gap between Italian regions and Italy as a whole during the period 1980-2007. We tested for the presence of the stochastic and β-convergence hypotheses using different time series approaches. The former was studied, first, for all the sample period and then, with an exogenous instantaneous break in the series. The presence of β-convergence, instead, was estimated considering a known and an unknown trend break date model. Our results show that most of the regions does not converge in an “actual” way, since they do not present a stochastic and β convergence simultaneously.β-convergence; stochastic convergence; time series approach; regional convergence

Specialization and growth in Italy: what spatial econometric analysis tells us.

This paper investigates the determinants of Italian regional specialization in the period 1995-2006. In particular, it tests and evaluates the presence of spatial autocorrelation in sectoral specialization patterns by the use of spatial econometrics tools. Results show positive effects of neighbouring regions specialization for advanced industry and services sectors and hence a progressive synchronization of economic cycles. By contrast, sectors traditionally considered backward, evidence the presence of a core-periphery structure. The introduction of spatial effects in the general regression model increases the number of significant explicative variables. In accordance with the findings from New Economic Geography openness and market access positively affect regional specialization in most of the considered sectors.Specialization, Regional growth, Spatial Econometrics.

IS THERE A CLUB CONVERGENCE AMONG ITALIAN REGIONS?

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SPECIALIZZAZIONE E CRESCITA: UN'APPLICAZIONE ALLE REGIONI DELL'UNIONE MONETARIA EUROPEA

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HOW MUCH SPECIALIZATION MATTERS IN EUROPEAN GROWTH: AN APPLICATION OF CART ANALYSIS TO EMU REGIONS

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The heterogeneous thresholds ordered response model: identification and inference

Although surveys routinely ask respondents to evaluate various aspects of their life on an ordered scale, there is concern about interpersonal comparability of these self-assessments. Statistically, the problem is one of identification in ordered response models with heterogeneous thresholds. As a solution to the identification problem, King et al. (2004) proposed using anchoring vignettes, namely brief descriptions of hypothetical people or situations that survey respondents are asked to evaluate on the same scale they use to rate their own situation. While vignettes have been introduced in several social surveys and are increasingly employed in a variety of fields, reliability of this approach hinges crucially on the validity of the assumptions of response consistency and vignette equivalence. This paper proposes a joint test of these key assumptions based on the fact that the underlying statistical model is overidentified if the two assumptions hold. Monte Carlo results show that the proposed test has good size and power properties in finite samples. We apply our test to self-assessment of pain using data from the first wave of the Survey of Health, Ageing and Retirement in Europe. We find that, when using only one of the three available vignettes, or when the test is carried out separately by subgroups of respondents, the overidentifying restrictions are less likely to be rejected