Using Constrained Optimization for the Identification of Convergence Clubs

Postiglione, Paolo; Andreano, M. Simona; Benedetti, Roberto

doi:10.1007/s10614-012-9325-z

Cited by 41 publications

(28 citation statements)

References 44 publications

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“…They identify five convergence clubs across 191 NUTS-2 data over the period 1980-2002. More recently, Postiglione et al (2013) have employed a spatial Durbin model as an objective function of two cluster algorithms. In a panel of 187 NUTS-2 regions from 1981 to 2004, they find four convergence clubs.…”

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confidence: 99%

Regional club convergence in the EU: evidence from a panel data analysis

Lyncker¹,

Thoennessen²

2016

Empir Econ

116

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We investigate club convergence in income per capita in 194 European NUTS-2 regions using a nonlinear, time-varying factor model that allows for individual and transitional heterogeneity. Moreover, we extend an existing club clustering algorithm with two post-clustering merging algorithms that finalize club formation. We also apply an ordered response model to assess the role of initial and structural conditions, as well as geographic factors. Our results indicate the presence of four convergence clubs in the EU-15 countries. In support of the club convergence hypothesis, we find that initial conditions matter for the resulting income distribution. Geographic clustering is quite pronounced; besides a north-to-south division, we detect highincome clusters for capital cities. We conclude that the main supranational policy challenge is the politically sensitive handling of a multi-speed Europe.

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confidence: 99%

Regional club convergence in the EU: evidence from a panel data analysis

Lyncker¹,

Thoennessen²

2016

Empir Econ

116

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“…The analysis and the assessment of heterogeneity for geographically distributed data is one of the main challenges for the spatial analysts. In this paper, we use a modified version of SA introduced by Postiglione, Andreano, and Benedetti () to identify convergence clubs in a Neoclassical framework.…”

Section: The Methodologymentioning

confidence: 99%

“…The determination of these heterogeneous zones can be obtained by solving a not easy combinatorial optimization problem. This problem will be faced by using a modified simulated annealing (SA) algorithm recently introduced by Postiglione, Andreano, and Benedetti (). SA ensures the reaching of the global optimum, differently from other search algorithms (Geman and Geman ).…”

Section: Introductionmentioning

confidence: 99%

“…However, in particular, the main aim of this paper is to apply our algorithm for the identification of heterogeneous zones in the analysis of Verdoorn's law of EU NUTS 2 regions. This type of spatial heterogeneity could be interpreted as the presence of multiple spatial equilibria or spatial convergence clubs (Postiglione, Andreano, and Benedetti ; Postiglione, Benedetti, and Lafratta ) in the distribution of productivity growth. Furthermore, these partitions can be viewed as groups of regions where the local parameters of Verdoorn's model are stationary or as clusters of regions sharing a common productivity growth path.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Clusters in EU Productivity Growth

Postiglione¹,

Andreano²,

Benedetti³

2016

Growth and Change

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In the last year, a central issue in regional economic growth debate has been represented by the empirical analysis of Verdoorn's law related to the long‐term dynamic relationship between the rate of growth in output and the productivity growth due to increasing returns. Several papers have tested Verdoorn's law on European countries as well as many other world economies. Recently, attempts have been made to provide foundations for a spatial version of the original law specification. The main contributions were dedicated to the inclusion of spatial dependence in the economic model. Surprisingly, in the literature on Verdoom's law the analysis of the spatial heterogeneity is not often considered. The aim of this paper is the regional analysis of the spatial dependence and heterogeneity in Verdoorn's law, identifying spatial regimes that can be interpreted as clusters of productivity growth in European regions at NUTS 2 level. To pursue this objective, an optimization algorithm for the identification of groups is used. This constitutes a modified version of Simulated Annealing.

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“…The club convergence concept has been widely applied to the analysis of regional economic growth [1][2][3][4][5]. With the development of spatial econometrics, the spatiality of club convergence has received growing attention [6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Spatial Club Convergence of Regional Economic Growth in Inland China

Cheng-lin

Liu

2017

Sustainability

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Spatial club convergence is a group of regions which are adjacent to each other in space and have similar initial conditions and structural features while converging towards the same steady state in the economic development. Based on the Solow model, this paper builds a theoretical model to prove the mechanism of spatial club convergence. The spatial club convergence process is explored in inland China, using the case of the Zhongyuan urban agglomeration during the years of 1993-2009. This region has been experiencing a dramatic economic development and serves as an ideal test bed of the theory of spatial club convergence. The results show that in the two periods of 1993-1999, and 1993-2009, there was spatial club convergence in the 56 regions of Zhongyuan urban agglomeration of China. The respective convergence rates were 2.0% and 1.0%. Hence, both theoretical deduction and empirical studies verify the hypothesis of spatial club convergence.

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Using Constrained Optimization for the Identification of Convergence Clubs

Cited by 41 publications

References 44 publications

Regional club convergence in the EU: evidence from a panel data analysis

Regional club convergence in the EU: evidence from a panel data analysis

Spatial Clusters in EU Productivity Growth

Spatial Club Convergence of Regional Economic Growth in Inland China

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