@misc{Trzpiot_Grażyna_Modeling_2015,
 author={Trzpiot, Grażyna and Majewska, Justyna},
 identifier={DOI: 10.15611/ekt.2015.4.13},
 year={2015},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Ekonometria = Econometrics, 2015, Nr 4 (50), s. 196-213},
 language={eng},
 abstract={In this article we investigate the latest developments on life expectancy modeling. We review some mortality projection stochastic models and their assumptions, and assess their impact on projections of future life expectancy for selected countries in the EU. More specifically, using the age- and sex-specific data of 20 countries, we compare the point projection accuracy and bias of six principal component methods for the projection of mortality rates and life expectancy. The six methods are variants and extensions of the Lee-Carter method. Based on one-step projection errors, the Renshaw and Haberman method provides the most accurate point projections of male mortality rates and the method is the least biased. The Quadratic CBD model with the cohort effects method performs the best for female mortality. While all methods rather underestimate variability in mortality rates and life expectancy, the Renshaw and Haberman method is the most accurate.},
 title={Modeling and projection life expectancy. The case of the EU countries},
 type={artykuł},
 keywords={life expectancy, mortality, Lee-Carter models family, stochastic models, przeciętne trwanie życia, umieralność, rodzina modeli Lee-Cartera, modele stochastyczne},
}