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L-moments skewness and kurtosis as measures of regional convergence and cohesion

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  • Katarzyna Kopczewska

Abstract

type="main"> The paper deals with the statistical modeling of convergence and cohesion over time with the use of kurtosis, skewness and L-moments. Changes in the shape of the distribution related to the spatial allocation of socio-economic phenomena are considered as an evidence of global shift, divergence or convergence. Cross-sectional time-series statistical modeling of variables of interest is to overpass the minors of econometric theoretical models of convergence and cohesion determinants. L-moments perform much more stable and interpretable than classical measures. Empirical evidence of panel data proves that one pure pattern (global shift, polarization or cohesion) rarely exists and joint analysis is required.

Suggested Citation

  • Katarzyna Kopczewska, 2014. "L-moments skewness and kurtosis as measures of regional convergence and cohesion," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(4), pages 251-266, November.
    • Handle: RePEc:bla:stanee:v:68:y:2014:i:4:p:251-266
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    References listed on IDEAS

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    1. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.
    2. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
    3. Sergio J. Rey, 2001. "Spatial Dependence in the Evolution of Regional Income Distributions," Urban/Regional 0105001, University Library of Munich, Germany.
    4. Frank A. Cowell, 2008. "Income Distribution and Inequality," Chapters, in: John B. Davis & Wilfred Dolfsma (ed.), The Elgar Companion to Social Economics, chapter 13, Edward Elgar Publishing.
    5. Härdle, Wolfgang Karl & Blaskowitz, Oliver J. & Schmidt, Peter, 2004. "Skewness and Kurtosis Trades," Papers 2004,09, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
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    1. Kopczewska Katarzyna, 2019. "Can public intervention improve local public sector economic performance? The analysis of Special Economic Zones in Poland," Central European Economic Journal, Sciendo, vol. 6(53), pages 221-245, January.
    2. Milton Abdul Thorlie & Lixin Song & Muhammad Amin & Xiaoguang Wang, 2015. "Modeling and forecasting of stock index volatility with APARCH models under ordered restriction," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 329-356, August.
    3. Maria Mikos, 2019. "Zasięg dyfuzji bodźców gospodarczych– testowanie modelu rdzeń–peryferia w odniesieniu do kohezyjnej polityki regionalnej i lokalnej," Studia z Polityki Publicznej / Public Policy Studies, Warsaw School of Economics, vol. 6(2), pages 1-33.
    4. Tomasz Kopczewski & Łukasz Bil, 2024. "Exploring stock markets dynamics: a two-dimensional entropy approach in return/volume space," Bank i Kredyt, Narodowy Bank Polski, vol. 55(6), pages 731-758.

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