Modelling Global Burden of Disease Measures in Selected European Countries Using Robust Dynamic Spatial Panel Data Models

• Authors: Agnieszka Orwat-Acedańska

Title variants

Modelowanie wskaźników obciążenia chorobami w wybranych krajach Europy za pomocą odpornych dynamicznych przestrzennych modeli panelowych

• Languages of publication: EN

Abstracts

EN

The aim of the paper is to study relationships between selected socio‑economic factors and health of European citizens. The health level is measured by selected global burden of disease measures – DALYs (Disability Adjusted Life Years) and its two components: YLL (Years of Life Lost) and YLD (Years Lived with Disability). We identify which factors significantly affect these indicators of health. The empirical study uses a panel data comprising 16 countries mostly from the old‑EU in the period 2003–2013. Fixed‑effects dynamic spatial panel data (DSPD) models are used to account for autocorrelations of the dependent variables across time and space. The models are estimated with a novel, modified quasi maximum likelihood Yang method based on M‑estimators. The approach is robust on the distribution of the initial observations. The empirical analysis covers specification, estimation, and verification of the models. The results show that changes in YLD are significantly related to alcohol consumption, healthcare spending, social spending, GDP growth rate and years of education. Exactly the same set of factors is associated with variation in DALYs. Sensitivity of the YLL component to the socio‑economic factors is considerably weaker.

PL

Celem artykułu jest analiza powiązań między wybranymi czynnikami społeczno‑ekonomicznymi a stanem zdrowia mieszkańcow Europy. Stan zdrowia opisywany jest za pomocą wybranych wskaźnikow globalnego obciążenia chorobami – DALY (utracona długość życia korygowana niepełnosprawnością) oraz jego dwoma komponentami: YLL (lata życia z chorobą lub niepełnosprawnością) oraz YLD (lata życia utracone wskutek przedwczesnej śmierci). W opracowaniu zidentyfikowane zostały czynniki, ktore istotnie wpływają na kształtowanie się tych wskaźnikow braku zdrowia. W analizie empirycznej wykorzystano dane panelowe obejmujące 16 krajow, głownie ze „starej UE”, w latach 2003–2013. Do modelowania zależności wskaźnikow globalnego obciążenia chorobami od czynnikow społeczno‑ekonomicznych wykorzystane zostały dynamiczne przestrzenne modele panelowe z efektami ustalonymi (DSPD). Modele te estymowane są za pomocą nowego podejścia (Yanga), polegającego na modyfikacji metody największej wiarygodności i opartego na M‑estymacji tego typu modeli. Metoda ta jest odporna na założenia dotyczące rozkładu tzw. warunkow początkowych. Analiza empiryczna obejmuje specyfikację, estymację oraz statystyczną weryfikację modeli. Wyniki wskazują, że zmienność YLD jest w znacznym stopniu związana ze spożyciem alkoholu, wydatkami na opiekę zdrowotną, wydatkami socjalnymi, tempem wzrostu PKB oraz latami edukacji. Ta sama grupa czynnikow jest związana ze zmiennością DALY. Natomiast wrażliwość składowej YLL na czynniki społeczno‑ekonomiczne jest znacznie słabsza.

Keywords

EN

dynamic spatial panel data models (DSPD); M-estimation; fixed effects; short panels; disease burden measures; socio-economic factors

PL

dynamiczne przestrzenne modele danych panelowych; M-estymacja; efekty ustalone; krótkie panele; miary globalnego obciążenia chorobami; czynniki społeczno-ekonomiczne.; dynamiczne przestrzenne modele danych panelowych; M-estymacja; efekty ustalone; krótkie panele; miary globalnego obciążenia chorobami; czynniki społeczno-ekonomiczne.

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Acta Universitatis Lodziensis. Folia Oeconomica
• Year: 2020
• Volume: 2
• Issue: 347
• Pages: 109-127

Dates

published

2020-04-03

Contributors

author

Agnieszka Orwat-Acedańska

• University of Economics in Katowice, Faculty of Informatics and Communication Department of Demography and Economic Statistics

• https://orcid.org/0000-0003-4125-2995

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Identifiers

DOI

10.18778/0208-6018.347.07