Similar Search Results

A principal component simulation of age-specific fertility : impacts of family and social policy on reproductive behavior in Germany

Vanella, Patrizio; Deschermeier, Philipp - 2018

This contribution proposes a simulation approach for the indirect estimation of age-specific fertility rates (ASFRs …) and the total fertility rate (TFR) for Germany via time series modeling of the principal components of the ASFRs. The … probability of 75%. Based on this result, it is unlikely that the fertility level will fall back to its extremely low levels of …

Persistent link: https://www.econbiz.de/10011860247

The Impact of Pandemic on Fertility in Russia : A Few Assumptions for the Forecast

Kazenin, Konstantin - 2021

fertility in developed countries. The significance of the outcome of these studies is under consideration designed to forecast … changes in fertility resulted from the pandemic in Russia, as well as to plan state policies to support fertility under the …

Persistent link: https://www.econbiz.de/10013230257

Stochastic population analysis : a functional data approach

Fang, Lei; Härdle, Wolfgang - 2015

Based on the Lee-Carter (LC) model, the benchmark in population forecasting, a variety of extensions and modifications are proposed in this paper. We investigate one of the extensions, the Hyndman-Ullah (HU) method and apply it to Asian demographic data sets: China, Japan and Taiwan. It combines...

Persistent link: https://www.econbiz.de/10010477583

Age- and sex-specific fertility in Germany until the year 2040 : the impact of international migration

Vanella, Patrizio - 2017

Good forecasts for future fertility developments are of high importance in political planning, especially regarding … measures in social insurance. Fertility is the main driver of demographic change, since small fertility rates lead to a … on a quasi-three principal component model are fitted to the age- and sex-specific fertility rates (ASSFR). Age …

Persistent link: https://www.econbiz.de/10011722114

Machine learning and multiple abortions

Kumar, Pradeep; Nicodemo, Catia; Oreffice, Sonia; … - 2024

This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and assess monetary savings through targeted interventions. We...

Persistent link: https://www.econbiz.de/10014545133