Changes in the Dependence Structure of AROPE Components: Evidence from the Spanish Regions

• CÉSAR GARCÍA-GÓMEZ ^[1] ; ANA PÉREZ ^[1] ; MERCEDES PRIETO-ALAIZ ^[1]
  1. [1] Universidad de Valladolid

     Universidad de Valladolid

     Valladolid, España

     
• Localización: Hacienda Pública Española / Review of Public Economics, ISSN 0210-1173, Nº 248, 2024, págs. 21-52
• Idioma: inglés
• DOI: 10.7866/HPE-RPE.24.1.2
• Enlaces
  • Texto completo
• Resumen

  • The AROPE rate is a multidimensional indicator to monitor poverty in the European Union which combines income, work intensity and material deprivation. However, it misses the possible relationship between its components. To overcome this drawback, some authors proposed to complement the AROPE rate with measures of the dependence between its dimensions, since higher dependence can exacerbate poverty. In this paper, we follow this approach and measure such dependence in the Spanish regions over the period 2008-2018 using three multivariate versions of Spearman’s rank correlation coefficient. Our results reveal an asymmetric effect of the economic cycle on the dependence between poverty dimensions, as this dependence, in many Spanish regions, substantially increased during the Great Recession but dropped little during the economic recovery. Moreover, regions with higher AROPE rates also tend to experience more dependence between its dimensions.

• Referencias bibliográficas
  • Alkire, S. and Foster, J. E. (2011), “Counting and multidimensional poverty measurement”, Journal of Public Economics, 95(7-8): 476-487.
  • Almeida, V., De Poli, S. and Martín, A. H. (2022), “The effectiveness of minimum income schemes in the EU”, Working Papers 627, ECINEQ, Society...
  • Atkinson, A. B. and Bourguignon, F. (1982), “The comparison of multi-dimensioned distributions of economic status”, The Review of Economic...
  • Ayala, L. and Cantó, O. (2022), “Radiografía de medio siglo de desigualdad en España”, Palma: Observatorio Social de la Fundación La Caixa.
  • Ayala, L. and Jurado, A. (2020), “Diferencias de desigualdad y bienestar en las regiones españolas”, in 4.o Informe sobre la Desigualdad en...
  • Ayala, L., Jurado, A. and Pérez-Mayo, J. (2011), “Income poverty and multidimensional deprivation: Lessons from cross-regional analysis”,...
  • Ayala, L., Jurado, A. and Pérez Mayo, J. (2022), “El ingreso mínimo vital: adecuación y cobertura”, Papeles de Economía Española, 172: 155-172.
  • Bourguignon, F. and Chakravarty, S. (2003), “The measurement of multidimensional poverty”, The Journal of Economic Inequality, 1(1): 25-49.
  • Chakravarty, S. R. (2018), Analyzing multidimensional well-being: A quantitative approach, New York, Wiley.
  • D’Agostino, A., Deluca, G. and Guégan, D. (2023), “Estimating lower tail dependence between pairs of poverty dimensions in Europe”, Review...
  • Decancq, K. (2014), “Copula-based measurement of dependence between dimensions of well-being”, Oxford Economic Papers, 66(3): 681-701.
  • Decancq, K. (2020), “Measuring cumulative deprivation and affluence based on the diagonal dependence diagram”, Metron, (78): 103-117.
  • Decancq, K. (2022), “Cumulative deprivation: identification and aggregation”, Working Papers 604, ECINEQ, Society for the Study of Economic...
  • Dolati, A. and Úbeda-Flores, M. (2006), “On measures of multivariate concordance”, Journal of Probability and Statistical Science, 4(2): 147-163.
  • Duclos, J.-Y. and Tiberti, L. (2016), “Multidimensional poverty indices: A critical assessment”, in Adler, M. D. and Fleurbaey, M. (eds.),...
  • Durante, F., Nelsen, R. B., Quesada-Molina, J. J. and Úbeda-Flores, M. (2014), “Pairwise and global dependence in trivariate copula models”,...
  • Ferreira, F. H. G. and Lugo, M. A. (2013), “Multidimensional poverty analysis: Looking for a middle ground”, World Bank Research Observer,...
  • García, J. E., González-López, V. and Nelsen, R. B. (2013), “A new index to measure positive dependence in trivariate distributions”, Journal...
  • García-Gómez, C., Pérez, A. and Prieto-Alaiz, M. (2021), “Copula-based analysis of multivariate dependence patterns between dimensions of...
  • García-Gómez, C., Pérez, A. and Prieto-Alaiz, M. (2022), “The evolution of poverty in the EU-28: a further look based on multivariate tail...
  • Genest, C., NeÅ¡lehová, J. and Rémillard, B. (2013), “On the estimation of Spearman’s rho and related tests of independence for possibly discontinuous...
  • Goedemé, T. (2013), “How much confidence can we have in EU-SILC? Complex sample designs and the standard error of the Europe 2020 poverty...
  • Joe, H. (1990), “Multivariate concordance”, Journal of Multivariate Analysis, 35(1): 12-30.
  • Joe, H. (2014), Dependence Modeling with Copulas, London: Chapman and Hall.
  • Kleiber, C. and Kotz, S. (2003), Statistical size distributions in economics and actuarial sciences, Hoboken, NJ: John Wiley & Sons.
  • Mashreghi, Z., Haziza, D. and Léger, C. (2016), “A survey of bootstrap methods in finite population sampling”, Statistics Surveys, 10: 1-52.
  • Mesfioui, M. and Quessy, J.-F. (2010), “Concordance measures for multivariate non-continuous random vectors”, Journal of Multivariate Analysis,...
  • Nelsen, R. B. (1996), “Nonparametric measures of multivariate association”, in Rüschendorf, L., Schweizer, B, and Taylor, M. D. (eds.), Distributions...
  • Nelsen, R. B. (2002), “Concordance and copulas: A survey”, in Cuadras, C. M., Fortiana, J. and Rodríguez-Lallena, J. A., (eds.), Distributions...
  • Nelsen, R. B. (2006), An introduction to copulas, New York: Springer-Verlag.
  • Nelsen, R. B. and Úbeda-Flores, M. (2012), “Directional dependence in multivariate distributions”, Annals of the Institute of Statistical...
  • NeÅ¡lehová, J. (2007), “On rank correlation measures for non-continuous random variables”, Journal of Multivariate Analysis, 98(3): 544-567.
  • Osier, G., Berger, Y. G. and Goedeme, T. (2013), “Standard error estimation for the EU-SILC indicators of poverty and social exclusion”, in...
  • Pérez, A. and Prieto-Alaiz, M. (2016a), “Measuring the dependence among dimensions of welfare: A study based on Spearman’s footrule and Gini’s...
  • Pérez, A. and Prieto-Alaiz, M. (2016b), “A note on nonparametric estimation of copula-based multivariate extensions of Spearman’s rho”, Statistics...
  • Quessy, J.-F. (2009), “Tests of multivariate independence for ordinal data”, Communications in Statistics Theory and Methods, 38(19): 3510-3531.
  • Rao, J., Wu, C. and Yue, K. (1992), “Some recent work on resampling methods for complex surveys”, Survey Methodology, 18(2): 209-217.
  • Rust, K. F. and Rao, J. (1996), “Variance estimation for complex surveys using replication techniques”, Statistical Methods in Medical Research,...
  • Schweizer, B. and Wolff, E. F. (1981), “On nonparametric measures of dependence for random variables”, The Annals of Statistics, 9(4): 879-885.
  • Seth, S. (2013), “A class of distribution and association sensitive multidimensional welfare indices”, The Journal of Economic Inequality,...
  • Seth, S. and Santos, M. (2019), “On the interaction between focus and distributional properties in multidimensional poverty measurement”,...
  • Tkach, K. and Gigliarano, C. (2018), “Multidimensional poverty measurement: dependence between well-being dimensions using copula function”,...