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AbstractWe investigate the forecasting accuracy of several simple methods for predicting mortality in small regional areas in Poland. We focus on methods that scale country-level forecasts appropriately and, therefore, can be used by official statistical agencies to improve population projections. We examine data from 379 sub-NUTS-3 districts in Poland for the period 2006–2019, divided into three subperiods. The first period is treated as the training sample and the latter two the testing subperiods. The mortality surface method delivers the most accurate forecasts of the mortality profiles whereas using the district-level standardized mortality rates (SMR) calculated for several broad age groups to scale the country-level mortality forecasts gives the best life expectancy at birth predictions. The latter approach is far better than using the NUTS-2-based standardized mortality rate (SMR), as practiced by the Polish statistical agency. For single age-groups predictions, the SMR-based methods deliver relatively accurate forecasts for young cohorts, but their forecasting accuracy deteriorates significantly with age.

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.

The paper concerns mortality in Poland. The aim of the article is to identify factors determining average life length of men and women in 66 subregions of Poland. We use spatial quantile regression methodology which 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 multidimensional distribution of error term.

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. ; Celem pracy jest badanie wpływu wybranych czynników na średnią długość życia z zdrowiu kobiet i mężczyzn w krajach UE. Ze względu na fakt, że kraje Unii Europejskiej charakteryzuje silne zróżnicowanie pod względem średniej długości życia w zdrowiu oraz jakości życia obywateli, stosujemy w pracy modele wielorakiej kwantylowej autoregresji przestrzennej. Regresja kwantylowa umożliwia analizę zależności pomiędzy zmiennymi w różnych kwantylach rozkładu zmiennej niezależnej. Ponadto narzędzie to jest odporne na założenie klasycznej regresji dotyczące postaci wielowymiarowego rozkładu składnika losowego. Estymacji punktowej parametrów modeli dokonano przy użyciu zmiennych instrumentalnych (Kim, Muller 2004), natomiast do estymacji przedziałowej i weryfikacji hipotezy istotności parametrów wykorzystano metodę bootstrap.

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.