Spatial econometric analysis of health services in Turkey through the perspective of the health development indicator

Year 2021, Volume: 8 Issue: 4, 555 - 563, 31.10.2021

Suna Tatlı

Abstract

Health-related parameters are critical as indicators of development, and as a result, governments allocate a sizable portion of their budgets to the health sector. The most fundamental variable considered an indicator of health development is the infant mortality rate, which was used as the dependent variable in this study. The data utilized in the study were compiled from the TURKSTAT web page and the TR Ministry of Health's health annuals, with the year 2019 serving as the reference point for access to all data. In the study, econometric analyses were performed while keeping the notion of contiguity in mind to reveal the factors healthily affecting the infant mortality rate at the NUTS 3 level, which encompasses all provinces in the TURKSTAT regional categorization. The distribution of infant mortality rates by provinces in Turkey was analyzed in this context, and it was discovered that there was a high degree of clustering between provinces. This clustering structure indicated the presence of a spatial relationship between provinces, and it was from this point of view that spatial econometric analysis of health services in Turkey was conducted. Analyzes were carried out using STATA and GeoDa package programs.

The diagnostic tests revealed the presence of spatial autocorrelation, necessitating the employment of the spatial autoregressive model (SAR Model) to explain the relationship between the variables. As a result, it was concluded that both the variables included in the study and the infant mortality rate in nearby locations have an effect on the infant mortality rate for each province.

Keywords

Health Economics, Spatial Health Econometrics, Health Development, Infant Mortality, Spatial Autoregsessive Model

References

• AKMAN, E. & TARIM, M. (2020). Turkey and England Health Systems: Comparison of Primary Health Care. International Journal of Health Management and Strategies Research. 6(2), 303-316.
• ALOGLU, N. & TASLIYAN, M. (2016). Evaluation of Family Health Centers’ Employees in the Past (Health Centers) and the Present System (Family Doctor): A Field Study in Kahramanmaras. International Journal of Health Management and Strategies Research. 2(3), 1-14.
• ANSELIN, L. (1988a). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, Dordrecht, The Netherlands.
• ANSELIN, L. (1988b). Lagrange Multiplier Test Diagnostics for Spatial Dependence and Spatial Heterogeneity. Geographical Analysis. 20(1), 1-17.
• ANSELIN, L., GALLO, J.L. & JAYET, H. (2008) Spatial Panel Econometrics. The Econometrics of Panel Data. Advanced Studies in Theoretical and Applied Econometrics, In: Mátyás L., Sevestre P. (eds), Vol. 46. Springer, Berlin, Heidelberg. 625-660.
• BARLAS, E., SANTAS, F. & KAR, A. (2014). Comparative Analysis of the Inter-Regional Infant Mortality Rate from the Perspective of Health Economics in Turkey.International Conference on Eurasian Economies, 2014 July 1-3; Skopje, Macedonia, 1-10. https://www.avekon.org/papers/959.pdf
• BASU, A. & MULLAHY, J. (2014). Health Econometrics: Overview.Encyclopedia of Health Economics. 1, 355-356.
• DEMIRTAS, Z. & METINTAS, S. (2017). Evaluation of Mother and Child Health Indicators in terms of Economic and Fertility Charecteristics in Turkish Republics, ESTUDAM Public Health Journal. 2(1),17-25.
• DER H.H. & YESILYURT M. E. (2020). Socio-Economic Determinants of Infant Mortality Rates. Thesis (Ms), Pamukkale University.
• ELHORST, J.P. (2010). Applied Spatial Econometrics: Raising the Bar.Spatial Econometrics Analysis. 5(1), 9-28.
• ELHORST, J.P. (2014). Linear Spatial Dependence Models for Cross-Section Data, Spatial Econometrics (Chapter2). SpringerBerlin Heidelberg. 5-36.
• FISCHER, M.M. & WANG, J. (2011). Spatial Data Analysis: Models, Methods And Techniques. Springer Science & Business Media.
• FREXEDAS, O.V. & VAYA, E. (2005). Financial Contagion Between Economies: An Exploratory Spatial Analysis. Estudios De Economia Aplicada. 23(1), 151-165.
• FLORAX, R.J. & VAN DER VLIST, A.J. (2003). Spatial Econometric Data Analysis: Moving Beyond Traditional Models. International Regional Science Review. 26(3), 223-243.
• GETIS, A. & ORD, J.K. (1992). An Analysis of Spatial Association by use of Distance Statistic, Geographical Analysis. 24(3), 189-206.
• GIBBONS, S. & OVERMAN, H.G. (2012). Mostly Pointless Spatial Econometrics, Journal of Regional Science. 52(2), 172-191.
• GIDER, O. & GUZEL, I. (2018). Evaluation of Selected Health Indicators of Turkey and Other European Union Candidate Countries.2nd International 12th National Congress on Health and Hospital Administration. 2018 Oct 11-13, Muğla, Turkey, 1658-1664.
• GUMPRECHT, D. (2007). Spatial Method in Econometrics. Doctoral Dissertation, WU Vienna University of Economics and Business.
• HAMZAOGLU, O. (2017). Hidden Mortality Among The Infants and the Regional Inequalities In Turkey.Community and Physician | A Journal of Turkish Medical Association. 32(4), 288-294.
• HORDIJK, L. & NIJKAMP, P. (1977). Dynamic Models of Spatial Autocorrelation. Environment and Planning A. 9(5), 505-519.
• KALANLAR, B. (2018). Health Sector in Turkey's Centenary, Current Situation and Prospects, Hacettepe Journal of Health Administration. 21(3), 495-510.
• KURT, A.K., SET, T. & ATES, E. (2019). The Relationship Between Primary Health Care Services and Pregnancy Diagnosis and Follow-Up, Eurasian Journal of Family Medicine. 8(4), 175-181.
• MANAVGAT, G. & CELIK, N. (2017). A Spatial Analysis for the Determinants of Health Status: The Case of Turkey NUTS-3.Sosyoekonomi. 25(34), 53-67.
• MOSCONE, F. & TOSETTI, E. (2014). Spatial Econometrics: Theory and Applications in Health Economics.Encyclopedia of Health Economics. 3, 329-334.
• REPUBLIC OF TURKEY MINISTRY OF HEALTH. (2019). Annal of Health Statistics [online]. Turkey, https://sbsgm.saglik.gov.tr/Eklenti/40564/0/saglik-istatistikleri-yilligi-2019pdf.pdf , [Date Accessed: 26/05/ 2021.]
• THE INTERNATIONAL CONFEDERATION OF MIDWIVES.(2017). International Definition of the Midwife [online]. The Hague, The Netherlands, https://www.internationalmidwives.org/assets/files/definitions-files/2018/06/eng-definition_of_the_midwife-2017.pdf , [Date Accessed: 14/08/ 2021].
• TURKISH STATISTICAL INSTITUTE. (2019). Province Indicators [online]. Turkey, https://biruni.tuik.gov.tr/ilgosterge/?locale=tr, [Date Accessed: 26/05/ 2021].
• TURKISH STATISTICAL INSTITUTE. (2019). Death and Cause of Death Statistics [online]. Turkey, https://data.tuik.gov.tr/Bulten/Index?p=Olum-ve-Olum-Nedeni-Istatistikleri-2019-33710#:~:text=Bebek%20%C3%B6l%C3%BCm%20h%C4%B1z%C4%B1%20binde%209,y%C4%B1l%C4%B1nda%20binde%209%2C1%20oldu, [Date Accessed: 02/08/ 2021].
• TURKISH STATISTICAL INSTITUTE. (2020). Birth Statistics [online]. Turkey, https://data.tuik.gov.tr/Bulten/Index?p=Birth-Statistics-2020-37229, [Date Accessed: 02/08/ 2021].
• VITON, P.A. (2010). Notes on Spatial Econometric Models, City and Regional Planning. [online]. https://www.yumpu.com/en/document/view/3858779/notes-on-spatial-econometric-models-the-ohio-state-university, [Date Accessed: 01/09/ 2021].
• WANG, S. & WU, J. (2020). Spatial Heterogeneity of the Associations of Economic and Health Care Factors with Infant Mortality in China Using Geographically Weighted Regression and Spatial Clustering, Social Science & Medicine. 263, 1-9.
• YANKEY, O., AMEGBOR, P.M. & LEE, J. (2021). The Effect of Sociodemographic Factors on the Risk of Poor Mental Health in Akron (Ohio): A Bayesian Hierarchical Spatial Analysis, Spatial and Spatio-temporal Epidemiology. 38, 100438.
• YETIM, B., DEMIRCI, S., KONCA, M., ILGUN, G. & CILHOROZ, Y. (2021). Socio-Economic Determinants of Infant Mortality Rate in Turkey. Sosyoekonomi. 29(47), 367-381.