Spatial heterogeneity in Italian local growth: an analysis based on the construction of a composite indicator

Journal title RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO
Author/s M. Simona Andreano, Roberto Benedetti, Andrea Mazzitelli
Publishing Year 2017 Issue 2016/3
Language Italian Pages 19 P. 9-27 File size 361 KB
DOI 10.3280/REST2016-003002
DOI is like a bar code for intellectual property: to have more infomation click here

Below, you can see the article first page

If you want to buy this article in PDF format, you can do it, following the instructions to buy download credits

Article preview

FrancoAngeli is member of Publishers International Linking Association, Inc (PILA), a not-for-profit association which run the CrossRef service enabling links to and from online scholarly content.

Spatial heterogeneity in Italian local growth: an analysis based on the construction of a composite indicator. The aim of the paper is to build a composite indicator for the analysis of the local growth, following the Jevons methodology. This indicator is constructed starting from two elementary indicators: the first refers to the virtuous components of the development and the second is based on its critical factors. The proposed indicator is applied on Italian NUT3 data and its spatial heterogeneity is analyzed.
Methods and Results.
The proposed composite indicator, to analyze the multidimensional phenomenon of the local growth, is based on the Jevons methodology. This technique uses the geometric mean to summarize the individual component information. In this way, unbalanced values will be automatically penalized. The spatial distribution of the indicator shows the presence of heterogeneous behavior of the Italian local growth. This heterogeneity is confirmed by the application of standard spatial analysis on the proposed indicator. .
Conclusions.
Empirical results show that Italian Provinces are characterized by socio-economic growth very different locally. Therefore, this complexity should be appropriately considered in the definition of local growth policies. North provinces evidenced hot spots behaviors, instead the South cold spots, where provinces with low values of the indicators are clustered together.

Keywords: Local growth, composite indicator, spatial heterogeneity, spatial dependence, NUTS 3

Jel codes: C01; C14; C21; C36; C52; O47.

  1. Aiello F., Attanasio M. (2004), How to transform a Batch of Simple Indicators to make up a Unique One?, Atti della XLII Riunione scientifica della Società italiana di statistica. Padova: CLEUP.
  2. Anselin L. (1995), Local Indicators of Spatial Association – LISA, Geographical Analysis, 27, pp. 93-115.
  3. Banca d’Italia (2014), Base Dati Statistica, ex Base Informativa Pubblica online.
  4. Brunini C., Messina A., Paradisi F. (2002), L’infrastrutturazione delle province italiane: metodi e sperimentazione, VI Conferenza nazionale di statistica, Roma.
  5. Cartone A., Postiglione P. (2016), Le componenti principali pesate geograficamente per la definizione di indicatori compositi locali, Rivista di Economia e Statistica del Territorio, 1, pp. 33-52.
  6. Chiarvesio M., Micelli M. (2007), Oltre il distretto come sistema: le strategie delle imprese fra locale e globale, in F. Guelpa, S. Micelli S. (a cura di), I distretti industriali del terzo millennio. Bologna: il Mulino.
  7. Cortese P., Mazzitelli A., Dickson M.M., Espa G., Giusti G., Martone C. (2015), I fenomeni illegali e la sicurezza percepita all’interno del sistema economico italiano. Roma: Unioncamere.
  8. Diewert W.E. (1976), Exact and Superlative Index Numbers, Journal of Econometrics, 4, pp. 115-145.
  9. Diewert W.E. (1995), Axiomatic and Economic Approaches to Elementary Price Indexes, NBER Working Papers n. 5104, Cambridge.
  10. Diewert W.E. (2004), Elementary Indices, in Consumer Price Index Manual: Theory and Practice, Geneva: International Labour Organization, chap. 20.
  11. Durlauf S., Johnson P.A. (1995), Multiple Regimes and Cross-country Behaviour, Journal of Applied Econometrics, 10, pp. 365-384.
  12. Eichhorn W., Voeller J. (1976), Theory of Price Index: Fisher’s Test Approach and Generalizations, in Lectures Notes in Economics and Mathematical Systems. Berlin: Springer-Verlag.
  13. Foresti G., Trenti S. (2007), I distretti in trasformazione: nuovi mercati, internazionalizzazione e l’emergere di leadership, in F. Guelpa, S. Micelli S. (a cura di), I distretti industriali del terzo millennio. Bologna: il Mulino.
  14. Getis A., Ord J.K. (1992), The Analysis of Spatial Association by Use of Distance Statistics, Geographical Analysis, 24, pp. 189-206.
  15. ISTAT (2014), Delitti denunciati dalle forze di polizia all’autorità giudiziaria.
  16. ISTAT (2015), Rapporto BES 2015.
  17. Martini M. (1992), I numeri indice in un approccio assiomatico. Milano: Giuffrè.
  18. Martini M. (2001), I numeri indice nel tempo e nello spazio. Milano: CUSL.
  19. Massoli P., Mazziotta, M., Pareto, A., Rinaldelli, C. (2013), Metodologie di sintesi sperimentali per i domini del BES, XXXIV Conferenza italiana di Scienze regionali AISRE.
  20. Massoli P., Mazziotta, M., Pareto, A., Rinaldelli, C. (2014), Metodologie di sintesi e analisi del territorio, Giornate della ricerca in ISTAT, 10-11 novembre.
  21. Mazziotta M., Pareto A. (2012), Indici sintetici per confronti spazio-temporali: un’applicazione alla dotazione infrastrutturale, XXIII Conferenza italiana di Scienze regionali.
  22. Moran P. (1948), The Interpretation of Statistical Maps, Journal of Royal Statistical Society Series B, 37, pp. 243-251.
  23. Nardo M., Saisana M., Saltelli A., Hoffman A., Giovannini E. (2005), Handbook of Constructing Composite Indicators: Methodology and User Guide, OECD Statistics Working Papers JT00188147, Paris.
  24. OECD (2008), Handbook on Constructing Composite Indicators. Methodology and User Guide. Paris: OECD Publications.
  25. Panzera D., Postiglione P. (2014), Economic Growth in Italian NUTS 3 Provinces, The Annals of Regional Science, 53, pp. 273-293.
  26. Prasada Rao D. S. (2009), Generalized Eltetö-Köves-Szulc (EKS) and Country-Product-Dummy (CPD): Methods for International Comparisons, in D.S. Prasada Rao (eds.), Purchasing Power Parities of Currencies: Recent Advances in Methods and Applications. Chelthenam (UK): Edward Elgar, pp. 86-120.
  27. UNDP (2015), Technical Notes, Human Development Report.
  28. World Bank (2009), World Development Indicators. Washington DC: World Bank.
  29. Zani S. (1993), Metodi statistici per le analisi territoriali. Milano: FrancoAngeli.

M. Simona Andreano, Roberto Benedetti, Andrea Mazzitelli, L’eterogeneità spaziale nello sviluppo locale in Italia: un’analisi basata sulla costruzione di un indicatore sintetico in "RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO" 3/2016, pp 9-27, DOI: 10.3280/REST2016-003002