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Spatial Quantile Regression In Analysis Of Healthy Life Years In The European Union Countries

Author

Listed:
  • Trzpiot Grażyna

    (Full Professor, Department of Demography and Economic Statistics, Faculty of Informatics and Communication, University of Economics in Katowice, Poland)

  • Orwat-Acedańska Agnieszka

    (Department of Demography and Economic Statistics, Faculty of Informatics and Communication, University of Economics in Katowice, Poland)

Abstract

The paper investigates the impact of the selected factors on the healthy life years of men and women in the EU countries. The multiple quantile spatial autoregression models are used in order to account for substantial differences in the healthy life years and life quality across the EU members. Quantile regression allows studying dependencies between variables in different quantiles of the response distribution. Moreover, this statistical tool is robust against violations of the classical regression assumption about the distribution of the error term. Parameters of the models were estimated using instrumental variable method (Kim, Muller 2004), whereas the confidence intervals and p-values were bootstrapped.

Suggested Citation

  • Trzpiot Grażyna & Orwat-Acedańska Agnieszka, 2016. "Spatial Quantile Regression In Analysis Of Healthy Life Years In The European Union Countries," Comparative Economic Research, Sciendo, vol. 19(5), pages 179-199, December.
    • Handle: RePEc:vrs:coecre:v:19:y:2016:i:5:p:179-199:n:10
    DOI: 10.1515/cer-2016-0044
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    References listed on IDEAS

    as
    1. Lee, Lung-fei, 2007. "The method of elimination and substitution in the GMM estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 140(1), pages 155-189, September.
    2. Tae-Hwan Kim & Christophe Muller, 2004. "Two-stage quantile regression when the first stage is based on quantile regression," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 218-231, June.
    3. James P. Lesage, 1997. "Bayesian Estimation of Spatial Autoregressive Models," International Regional Science Review, , vol. 20(1-2), pages 113-129, April.
    4. Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 252-277, April.
    5. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    6. Philip Kostov, 2009. "A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(1), pages 53-72.
    7. Lee, Lung-fei, 2007. "GMM and 2SLS estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 137(2), pages 489-514, April.
    8. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
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