Julius Goes

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Office: Feldkirchenstr. 21, Room: F21/00.82, 96052 Bamberg
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E-Mail: julius.goes(at)uni-bamberg.de
Phone: +49 (0) 951 863 2632
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Pillar 3: Changes in Human Capital, Labour Markets and Demographic Structures and their Relation to Social Inequalities in Modern Societies

Field: Statistics

Research Interests: Bayesian Statistics, Bayesian Demography, Ensemble Methods, Time Series, Spatial Statistics
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// DISSERTATION PROJECT

"Demographic Time Series Forecasting"

There has always been a demand for precise estimations and forecasts of demographic measures, such as mortality rates, migration flows, and population totals.

While much research has focused on obtaining these estimates at the national scale, there is a growing need for accurate subnational predictions. When data is disaggregated on a lower scale, observations become more noisy, and standard methods tend to perform poorly.

Bayesian hierarchical models offer a promising solution by pooling information across regions and time, making predictions more robust.

The dissertation aims to develop new methods within the Bayesian hierarchical framework to enhance the predictive performance of subnational demographic measures.

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// ACADEMIC BACKGROUND

2017 – 2020
M.Sc. in Survey Statistics, University of Bamberg

2012 – 2017
B.Sc. in International Business Administration, University of Bamberg

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// PUBLICATIONS

Goes (2024): Bayesian Forecasting of Mortality Rates for Small Areas Using Spatiotemporal Models, Demography 61(2): 439–462 (https://doi.org/10.1215/00703370-11212716)

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// CONFERENCES AND WORKSHOPS

Longevity 18: “Bayesian Mortality Modelling with Pandemics: a Vanishing Jump Approach”. London. 2023.

Statistische Woche: “Forecasting Mortality Rates for Small Areas using Spatial Bayesian Hierarchical Models”. Münster. 2022

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