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dc.contributor.authorOrwat-Acedańska, Agnieszka
dc.date.accessioned2019-08-05T11:23:29Z
dc.date.available2019-08-05T11:23:29Z
dc.date.issued2019
dc.identifier.issn1231-1952
dc.identifier.urihttp://hdl.handle.net/11089/29899
dc.description.abstractThe aim of the paper is to investigate the relationship between socio-economic factors and the level of health of citizens of selected European countries. Disability-adjusted life years (DALYs) were used as the measure of health. The author applied dynamic spatial panel data models with fixed effects and spatial autocorrelation of the error term. The models were estimated using a novel, modified quasi maximum likelihood method based on M-estimators. The approach is resistant to deviations from the assumptions on the distribution of initial observations. The estimation of initial observations is a severe weakness of standard methods based on the maximization of the quasi-likelihood function in the case of short panels. M-estimators are consistent and asymptotically normally distributed. The empirical analysis covers the specification, estimation, and verification of the models.en_GB
dc.language.isoenen_GB
dc.publisherWydawnictwo Uniwersytetu Łódzkiegoen_GB
dc.relation.ispartofseriesEuropean Spatial Research and Policy; 1
dc.rightsThis work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.en_GB
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0en_GB
dc.subjectdynamic spatial panel data modelsen_GB
dc.subjectM-estimationen_GB
dc.subjectfixed effectsen_GB
dc.subjectshort panelsen_GB
dc.subjectDALYs – disability-adjusted life yearsen_GB
dc.subjectthe level of healthen_GB
dc.subjectsocio-economic factorsen_GB
dc.titleDynamic spatial panel data models in identifying socio-economic factors affecting the level of health in selected European countriesen_GB
dc.typeArticleen_GB
dc.page.number195-211
dc.contributor.authorAffiliationUniversity of Economics in Katowice, Department of Demography and Economic Statistics
dc.identifier.eissn1896-1525
dc.referencesANAND, S. and HANSON, K. (1997), ‘Disability-adjusted lost years – a critical review’, Journal of Health Economics, 16, pp. 685‒702.en_GB
dc.referencesANAND, S. and HANSON, K. (1998), ‘DALYs: efficiency versus equity’, World Development, 26 (2), pp. 307‒310.en_GB
dc.referencesANSELIN, L. (1988), Spatial Econometrics: Methods and Models, The Netherlands: Kluwer Academic Press.en_GB
dc.referencesANSELIN, L. (2001), ‘Spatial Econometrics’, [in:] BALTAGI, B. H. (eds.), A companion to theoretical econometrics, Massachusetts: Blackwell Publishers Ltd., pp. 310‒330.en_GB
dc.referencesANSELIN, L., LE GALLO, J. and JAYET, J. (2008), ‘Spatial panel econometrics’, [in:] MATYAS, L., SEVESTRE, P. (eds.), The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice, Berlin-Heidelberg: Springer-Verlag, pp. 625‒660.en_GB
dc.referencesBARKER, C. and GREEN, A. (1996), ‘Opening the Debate on DALYs’, Health Policy and Planning, 11, pp. 179‒183.en_GB
dc.referencesBERMAN, S. (1995), ‘Otitis media in developing countries’, Pediatrics, 96, pp. 126‒131.en_GB
dc.referencesBINDER, M., HSIAO, C. and PESARAN, M. H. (2005), ‘Estimation and inference in short panel vector autoregressions with unit roots and cointegration’, Econometric Theory, 21, pp. 795‒837.en_GB
dc.referencesBUN, M. J. and CARREE, M. A. (2005), ‘Bias-corrected estimation in dynamic panel data models’, Journal of Business and Economic Statistics, 23, pp. 200‒210.en_GB
dc.referencesDAŃSKA-BORSIAK, B. (2011), Dynamiczne modele panelowe w badaniach ekonomicznych, Łódź: Wydawnictwo Uniwersytetu Łódzkiego.en_GB
dc.referencesDESJARLAIS, R., EISENBERG, L., GOOD, B., and KLEINMAN, A. (1995), World mental health: problems and priorities in low income countries, New York: Oxford University Press.en_GB
dc.referencesDEVLEESSCHAUWER, B., HAVELAAR, A. H., MAERTENS DE NOORDHOUT, C., HAAGSMA J. A., PRAET, N., DORNY, P., DUCHATEAU, L., TORGERSON, P. R., VAN OYEN H. and SPEYBROECK, N. (2014), ‘DALY calculation in practice: a stepwise approach’, International Journal of Public Health, 59 (3), pp. 571‒574.en_GB
dc.referencesELHORST, J. P. (2005), ‘Unconditional maximum likelihood estimation of linear and loglinear dynamic models for spatial panels’, Geographical Analysis, 37, pp. 85‒106.en_GB
dc.referencesELHORST, J. P. (2010a), ‘Spatial Panel Data Models’, [in:] FISCHER, M. M., GETIS, A., (eds), Handbook of Applied Spatial Analysis, Springer, Berlin.en_GB
dc.referencesELHORST, J. P. (2010b), ‘Applied spatial econometric: raising the bar’, Spatial Economic Analysis, 5 (1), pp. 9‒28.en_GB
dc.referencesELHORST, J. P. (2010c), ‘Dynamic panels with endogenous interaction effects when T is small’, Regional Science and Urban Economics, 40, pp. 272‒282.en_GB
dc.referencesEUROSTAT’S REPORT FOR THE EUROPEAN COMMISSION (2017), ‘Global Europe 2050’.en_GB
dc.referencesGOURIEROUX, C. and PHILLIPS, P. C. B., YU, J. (2010), ‘Indirect inference for dynamic panel models’, Journal of Econometrics, 157, pp. 68‒77.en_GB
dc.referencesHSIAO, C., PESARAN, M. H. and TAHMISCIOGLU, A. K. (2002), ‘Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods’, Journal of Econometrics, 109, pp. 107‒150.en_GB
dc.referencesHUBER, P. J. (1981), Robust Statistics. New York: Wiley.en_GB
dc.referencesKORNIOTIS, G. M. (2010), ‘Estimating panel models with internal and external habit formation’, Journal of Business and Economic Statistics, 28, pp. 145‒158.en_GB
dc.referencesKRUINIGER, H. (2013), ‘Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions’, Journal of Econometrics, 173, pp. 175‒188.en_GB
dc.referencesLAURELL, A. C. and ARELLANO, L. O. (1996), ‘Market commodities and poor relief: The World Bank proposal for health’, Journal of Health Economics, 26 (1), pp. 1‒18.en_GB
dc.referencesLEE, L. F. and YU, J. (2010a), ‘Estimation of spatial autoregressive panel data model a with fixed effects’, Journal of Econometrics, 154(2), pp. 165‒185.en_GB
dc.referencesLEE, L. F. and YU, J. (2010b), Estimation of spatial panels: random components vs. fixed effects, Manuscript, Ohio State University.en_GB
dc.referencesLEE, L. F. and YU, J. (2010c), ‘Some recent developments in spatial panel data models’, Regional Science and Urban Economics, 40, pp. 255‒271.en_GB
dc.referencesLEE, L. F. and YU, J. (2010d), ‘A spatial dynamic panel data model with both time and individual fixed effects’, Econometric Theory, 26, pp. 564‒597.en_GB
dc.referencesLOZANO, R., MURRAY, C. J. L., FRENK, J. and BOBADILLA, J. L. (1995), ‘Burden of diseases assessment and health system reform: results of a study in Mexico’, Journal of International Development, 7 (3), pp. 555–564.en_GB
dc.referencesMARTENS, W. J., NIESSEN, L. W., ROTMANS, J., JETTEN, T. H. and McMICHAEL A.J. (1995), ‘Potential impact of global climate change on malaria risk’, Environmental Health Perspectives, 103 (5), pp. 458–64.en_GB
dc.referencesMURRAY, C. J. L. (1994), ‘Quantifying the burden of disease: the technical basis for disability-ad¬justed life years’, Bulletin of the World Health Organization, 72 (3), pp. 429–445.en_GB
dc.referencesMURRAY, C. J. L. (1996), ‘Rethinking DALYs’, [in:] MURRAY, C. J. L., LOPEZ, A. D., The Global Burden of Disease and Injury Series, Harvard School of Public Health, World Health Organization, World Bank, Boston, 1, pp. 1–98.en_GB
dc.referencesMURRAY, C. J. L. and LOPEZ, A. D. (1994), Global comparative assessments in the health sector: disease burden, expenditures and intervention packages., Geneva, World Health Organization.en_GB
dc.referencesMURRAY, C. J. L. and LOPEZ, A. D. (1996a), ‘A comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020’, The Global Burden of Disease and Injury Series. The Global Burden of Disease, 1, Harvard School of Public Health, World Bank, World Health Organization.en_GB
dc.referencesMURRAY, C. J. L. and LOPEZ, A. D. (1996a), ‘A compendium of incidence, prevalence and mortality estimates for over 200 conditions’, The Global Burden of Disease and Injury Series.The Global Burden of Disease, 2, Harvard School of Public Health, World Bank, World Health Organization.en_GB
dc.referencesMURRAY, C. J. L., SALOMON, J. A., MATHERS, C. D. and D. LOPEZ A. D. (2002), Summary measures of population health – concepts, ethics, measurement and applications. Geneva, World Health Organization.en_GB
dc.referencesROBINE, J. M. (2006), ‘Summarizing Health Status’ [in:] PENCHEON, D., GUEST, C., MELZER, D. and GRAY, J. A. M., Oxford Handbook of Public Health Practice, Oxford University Press.en_GB
dc.referencesSU, L. and YANG, Z. (2015), ‘QML estimation of dynamic panel data models with spatial errors’, Journal of Econometrics, 185, pp. 230‒258.en_GB
dc.referencesTRZPIOT, G. and ORWAT-ACEDAŃSKA, A. (2016), ‘Spatial quantile regression in analysis of healthy life years in the European Union countries’, Comparative Economic Research, 19 (5), pp. 179‒199.en_GB
dc.referencesVAN DER VAART, A. W. (1998), Asymptotic Statistics.Cambridge University Press.en_GB
dc.referencesWRÓBLEWSKA, W. (2008), ‘Sumaryczne miary stanu zdrowia populacji’, Studia Demograficzne, pp. 153‒154.en_GB
dc.referencesYANG, Z. (2018), ‘Unified M-Estimation of Fixed-Effects Spatial Dynamic Models with Short Panels’, Journal of Econometrics, 205, pp. 423‒447.en_GB
dc.referencesYANG, Z., LI, C. and TSE, Y. K. (2006), ‘Functional form and spatial dependence in dynamic panels’, Economics Letters, 91, pp. 138‒145.en_GB
dc.referencesYU, J., DE JONG, R. and LEE, L. F. (2008), ‘Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large’, Journal of Econometrics, 146, pp. 118‒134.en_GB
dc.referencesYU, J. and LEE, L. F. (2010), ‘Estimation of unit root spatial dynamic panel data models’, Econometric Theory, 26, pp. 1332‒1362.en_GB
dc.contributor.authorEmailagnieszka.orwat@ue.katowice.pl
dc.identifier.doi10.18778/1231-1952.26.1.10
dc.relation.volume26en_GB


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