@misc{Rejda_Paulina_Trends_2022,
 author={Rejda, Paulina},
 contributor={Peternek, Piotr. Redakcja and Grześkowiak, Alicja. Redakcja},
 identifier={DOI: 10.15611/2022.17.6.06},
 year={2022},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={[w:] Zastosowanie metod ilościowych w ekonomii i finansach / pod red. Alicji Grześkowiak i Piotra Peterneka. - Wrocław: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu, 2022, s. 101-124},
 language={eng},
 abstract={The problem of child mortality in African countries is discussed in this article. The goal of this study was to examine the general situation in Africa in terms of economic and living conditions as well as their impact on child mortality in 2000 and 2019 and to select the most appropriate models to characterise this phenomenon. Cluster analysis was used to identify countries with similar socioeconomic characteristics and living conditions. Several regression models were estimated, analysed, and compared. Through the use of spatial models, the geographic context was incorporated into the statistical framework of the regression. The analysis demonstrated a significant improvement in economic and living conditions over the 19-year period. The Spatial Error Model turned out to be the best model for the 2000 data, however, OLS and Negative Binomial also performed well. There was no spatial autocorrelation in 2019 and none of the estimated models provided a good fit for the data. The 2000 models’ projections revealed unexpected outcomes. Despite the fact that a rise in life expectancy, access to drinking water, and GDP per capita was intended to result in a decrease in the dependent variable, the model estimates predicted that unemployment and the number of HIV-positive children would have the same effect on child mortality.},
 title={Trends and Causes of Child Mortality in African Countries},
 type={rozdział},
 keywords={child mortality, African countries, spatial analysis, cluster analysis, regression models, umieralność dzieci, kraje afrykańskie, analiza przestrzenna, analiza skupień, modele regresji},
}