Thesis title: |
Quantifying influence of pandemic, migration, fertility decline on population dynamics: sensitivity analysis approach |
Author: |
Vlassova, Polina |
Thesis type: |
Diploma thesis |
Supervisor: |
Miskolczi, Martina |
Opponents: |
Hon, Filip |
Thesis language: |
English |
Abstract: |
Given thesis examines behavior of Germany’s population in response to changes in three key demographic variables: mortality, fertility, and migration. The analysis is conducted through six distinct scenarios, each involving adjustments to one of these parameters. Using a cohort-component projection model, the study evaluates population behavior patterns, including variations in age and gender structure, over the period from 2023 to 2050. The analysis employs Python-based modelling techniques to simulate demographic dynamics. Results indicate that sudden, minor mortality shocks, such as pandemics, generate short-term demographic pressures, followed by a rebalancing in the Total Dependency Ratio. Migration contributes significantly to population stability by combatting natural decline and possesses producing effects comparable to those of fertility. However, unlike fertility, which has a gradual and cumulative influence, changes in migration cause an immediate demographic effect. Sensitivity analysis evaluates the responsiveness of the Total Dependency Ratio and quantifies changes in projected population to uncover underlying behavioral patterns. These findings provide valuable guidance for policymakers seeking to address demographic challenges and develop an integrated strategy to ensure a sustainable population structure in Germany. |
Keywords: |
Population projection; sensitivity analysis; Germany; migration |
Thesis title: |
Quantifying influence of pandemic, migration, fertility decline on population dynamics: sensitivity analysis approach |
Author: |
Vlassova, Polina |
Thesis type: |
Diplomová práce |
Supervisor: |
Miskolczi, Martina |
Opponents: |
Hon, Filip |
Thesis language: |
English |
Abstract: |
Given thesis examines behavior of Germany’s population in response to changes in three key demographic variables: mortality, fertility, and migration. The analysis is conducted through six distinct scenarios, each involving adjustments to one of these parameters. Using a cohort-component projection model, the study evaluates population behavior patterns, including variations in age and gender structure, over the period from 2023 to 2050. The analysis employs Python-based modelling techniques to simulate demographic dynamics. Results indicate that sudden, minor mortality shocks, such as pandemics, generate short-term demographic pressures, followed by a rebalancing in the Total Dependency Ratio. Migration contributes significantly to population stability by combatting natural decline and possesses producing effects comparable to those of fertility. However, unlike fertility, which has a gradual and cumulative influence, changes in migration cause an immediate demographic effect. Sensitivity analysis evaluates the responsiveness of the Total Dependency Ratio and quantifies changes in projected population to uncover underlying behavioral patterns. These findings provide valuable guidance for policymakers seeking to address demographic challenges and develop an integrated strategy to ensure a sustainable population structure in Germany. |
Keywords: |
migration; Population projection; sensitivity analysis; Germany |
Information about study
Study programme: |
Economic Data Analysis/Data Analysis and Modeling |
Type of study programme: |
Magisterský studijní program |
Assigned degree: |
Ing. |
Institutions assigning academic degree: |
Vysoká škola ekonomická v Praze |
Faculty: |
Faculty of Informatics and Statistics |
Department: |
Department of Demography |
Information on submission and defense
Date of assignment: |
24. 10. 2024 |
Date of submission: |
25. 6. 2025 |
Date of defense: |
2025 |
Files for download
The files will be available after the defense of the thesis.