Advertisement

A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002

  • Michele Battisti
  • Gianfranco Di VaioEmail author
Part of the Studies in Empirical Economics book series (STUDEMP)

Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the β-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North—South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to the whole sample, might be restrictive assumptions. Excluding a small number of regions that behave as outliers, only a few regions show an appreciable rate of convergence. The majority of data show slow convergence, or no convergence at all. Furthermore, a dualistic phenomenon seems to be present inside some States, reinforcing the “diverging-convergence” paradox.

Keywords

Regional growth Convergence patterns Mixture regression Spatial effects 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abreu M, De Groot HLF, Florax RJGM (2005a) A meta-analysis of β-convergence: the legendary 2%. J Econ Surv 19:389–420Google Scholar
  2. Abreu M, De Groot HLF, Florax RJGM (2005b) Space and growth: a survey of empirical evidence and methods. Région et Développement 21:13–44Google Scholar
  3. Anselin L (1988) Spatial econometrics: methods and models. Kluwer, DordrechtGoogle Scholar
  4. Anselin L (2001) Spatial econometrics. In: Baltagi BH (ed) A companion to Theoretical econometrics. Blackwell, Oxford, pp 310–330Google Scholar
  5. Anselin L (2005) Exploring spatial data with GeoDa: a workbook. Center for spatial integrated social science, Santa BarbaraGoogle Scholar
  6. Anselin L, Bera AK (1998) Spatial dependence in linear regression models with an introduction to spatial econometrics. In: Ullah A, Giles DEA (eds) Handbook of applied economic statistics. Marcel Dekker, New York, pp 237–289Google Scholar
  7. Arbia G (2006) Spatial econometrics: statistical foundations and applications to regional convergence. Springer, BerlinGoogle Scholar
  8. Armstrong HW (1995) Convergence among regions of the European Union, 1950–1990. Pap Reg Sci 74:143–152CrossRefGoogle Scholar
  9. Azariadis C, Drazen A (1990) Threshold externalities in economic development. Q J Econ 105:501–526CrossRefGoogle Scholar
  10. Badinger H, Müller WG, Tondl G (2004) Regional convergence in the European Union, 1985–1999: a spatial dynamic panel analysis. Reg Stud 38:241–253CrossRefGoogle Scholar
  11. Barro RJ, Sala-i-Martin X (1991) Convergence across states and regions. Brookings Pap Econ Act 1:107–182CrossRefGoogle Scholar
  12. Barro RJ, Sala-i-Martin X (1992) Convergence. J Polit Econ 100:223–251CrossRefGoogle Scholar
  13. Barro RJ, Sala-i-Martin X (2004) Economic growth, 2nd edn. MIT, CambridgeGoogle Scholar
  14. Bernard AB, Durlauf SN (1996) Interpreting tests of the convergence hypothesis. J Econom 71:161–173CrossRefGoogle Scholar
  15. Bloom DE, Canning D, Sevilla J (2003) Geography and poverty traps. J Econ Growth 8:355–378CrossRefGoogle Scholar
  16. Boldrin M, Canova F (2001) Inequality and convergence in Europe's regions: reconsidering European regional policies. Econ policy 16:207–253CrossRefGoogle Scholar
  17. Canova F (2004) Testing for convergence clubs in income per capita: a predictive density approach. Int Econ Rev 45:49–77CrossRefGoogle Scholar
  18. Commission of the European Communities (2005) Communication from the Commission. Third progress report on cohesion: towards a new partnership for growth, jobs and cohesion. 17.5.2005 COM(2005) 192 final. BrusselsGoogle Scholar
  19. De Sarbo WS, Cron WL (1988) A maximum likelihood methodology for clusterwise linear regression. J Classif 5:249–282CrossRefGoogle Scholar
  20. Durlauf SN, Johnson PA (1995) Multiple regimes and cross-country growth behaviour. J Appl Econom 10:365–384CrossRefGoogle Scholar
  21. Durlauf SN, Quah DT (1999) The new empirics of economic growth. In: Taylor JB, Woodford M (eds) Handbook of macroeconomics, vol 1. North Holland, Amsterdam, pp 235–308Google Scholar
  22. Durlauf SN, Kourtellos A, Minkin A (2001) The local Solow growth model. Eur Econ Rev 45:928–940CrossRefGoogle Scholar
  23. Durlauf SN, Johnson PA, Temple JRW (2005) Growth econometrics. In: Durlauf SN, Aghion P (eds) Handbook of economic growth. North Holland, Amsterdam, pp 555–677Google Scholar
  24. Ertur C, Le Gallo J, Baumont C (2006) The European regional convergence process, 1980–1995: do spatial regimes and spatial dependence matter? Int Reg Sci Rev 29:3–24CrossRefGoogle Scholar
  25. European Commission (2001) Unity, solidarity, diversity for Europe, its people and its territory. Second report on economic and social cohesion. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  26. European Commission (2004) A new partnership for cohesion. Convergence competitiveness cooperation. Third report on economic and social cohesion. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  27. Funck B, Pizzati L (eds) (2003) European integration, regional policy, and growth. World Bank, Washington D.C.Google Scholar
  28. Galor O (1996) Convergence? Inferences from theoretical models. Econ J 106:1056–1069CrossRefGoogle Scholar
  29. Getis A (1995) Spatial filtering in a regression framework: examples using data on urban crime, regional inequality, and government expenditures. In: Anselin L, Florax R (eds) New directions in spatial econometrics. Springer, Berlin, pp 172–88Google Scholar
  30. Getis A, Griffith DA (2002) Comparative spatial filtering in regression analysis. Geogr Anal 34:130–140CrossRefGoogle Scholar
  31. Hart PE (1995) Galtonian regression across countries and the convergence of productivity. Oxf Bull Econ Stat 57:287–293Google Scholar
  32. Hawkins DS, Allen DM, Stromberg AJ (2001) Determining the number of components in mixture of linear models. Comput Stat Data Anal 38:15–48CrossRefGoogle Scholar
  33. Le Gallo J, Ertur C (2003) Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe, 1980–1995. Pap Reg Sci 82:175–201CrossRefGoogle Scholar
  34. Le Gallo J, Dall'erba S (2006) Evaluating the temporal and spatial heterogeneity of the European convergence process, 1980–1999. J Reg Sci 46:269–288CrossRefGoogle Scholar
  35. Lopez-Bazo E, Vaya E, Mora AJ, Surinach J (1999) Regional economic dynamics and convergence in the European union. Ann Reg Sci 33:343–370CrossRefGoogle Scholar
  36. Louis TA (1982) Finding the observed information matrix when using the EM algorithm. J R Stat Soc B 44:226–233Google Scholar
  37. MacLachlan G, Peel D (2000) Finite mixture models. Wiley, New YorkGoogle Scholar
  38. Mankiw NG, Romer D, Weil DN (1992) A contribution to the empirics of economic growth. Q J Econ 107:407–437CrossRefGoogle Scholar
  39. Martin P (1998) Can regional policies affect growth and geography in Europe? World Econ 21:757–774CrossRefGoogle Scholar
  40. Meliciani V, Peracchi F (2006) Convergence in per-capita GDP across European regions: a reappraisal. Empir Econ 31:549–568CrossRefGoogle Scholar
  41. Neven D, Gouyette C (1995) Regional convergence in the European community. J Common Market Stud 33:47–65CrossRefGoogle Scholar
  42. Paap R, van Dijk HK (1998) Distribution and mobility of wealth of nations. Eur Econ Rev 42:1269–1293CrossRefGoogle Scholar
  43. Pagan A (1984) Econometric issues in the analysis of regressions with generated regressors. Int Econ Rev 25:221–247CrossRefGoogle Scholar
  44. Petrakos G, Rodríguez-Pose A, Rovolis A (2005) Growth, integration, and regional disparities in the European union. Environ Plann A 37:1837–1855CrossRefGoogle Scholar
  45. Quah DT (1993a) Empirical cross-section dynamics in economic growth. Eur Econ Rev 37:426–434CrossRefGoogle Scholar
  46. Quah DT (1993b) Galton's fallacy and tests of the convergence hypothesis. Scand J Econ 95:427–443CrossRefGoogle Scholar
  47. Quah DT (1996a) Empirics for economic growth and convergence. Eur Econ Rev 40:1353–1375CrossRefGoogle Scholar
  48. Quah DT (1996b) Twin peaks: growth and convergence in models of distribution dynamics. Econ J 106:1045–1055CrossRefGoogle Scholar
  49. Quah DT (1996c) Regional convergence clusters across Europe. Eur Econ Rev 40:951–958CrossRefGoogle Scholar
  50. Quah DT (1997) Empirics for growth and distribution: stratification, polarization, and convergence clubs. J Econ Growth 2:27–59CrossRefGoogle Scholar
  51. Rey SJ, Montouri BD (1999) US regional income convergence: a spatial econometric perspective. Reg Stud 33:143–156CrossRefGoogle Scholar
  52. Sala-i-Martin X (1996a) The classical approach to convergence analysis. Econ J 106:1019–1036CrossRefGoogle Scholar
  53. Sala-i-Martin X (1996b) Regional cohesion: evidence and theories of regional growth and convergence. Eur Econ Rev 40:1325–1352CrossRefGoogle Scholar
  54. Solow RM (1999) Neoclassical growth theory. In: Taylor JB, Woodford M (eds) Handbook of macroeconomics, vol 1. North Holland, Amsterdam, pp 637–667Google Scholar
  55. Temple JRW (1998) Robustness tests of the augmented Solow model. J Appl Econom 13:361–375CrossRefGoogle Scholar
  56. Temple JRW (2000) Growth regressions and what the textbooks don't tell you. Bull Econ Res 52:181–205CrossRefGoogle Scholar
  57. Titterington DM, Smith AFM, Makov UE (1985) Statistical analysis of finite mixture distributions. Wiley, ChichesterGoogle Scholar
  58. Tsionas EG (2000) Regional growth and convergence: evidence from the United States. Reg Stud 34:231–238CrossRefGoogle Scholar
  59. Turner RT (2000) Estimating the propagation rate of a viral infection of potato plants via mixtures of regressions. Appl Stat 49:371–384Google Scholar
  60. Wedel M, Kamakura WA (1998) Market segmentation: conceptual and methodological foundations. Kluwer, DordrechtGoogle Scholar

Copyright information

© Physica-Verlag Heidelberg 2009

Authors and Affiliations

  1. 1.Dipartimento di Scienze Economiche e AziendaliLUISS Guido CarliRomeItaly

Personalised recommendations