Projection of Denmark’s Population 2021-2050 with a focus on Mortality Trends, Longevity, and Multigenerational Workforce

Thesis title: Projection of Denmark’s Population 2021-2050 with a focus on Mortality Trends, Longevity, and Multigenerational Workforce
Author: Abid, Mansoor
Thesis type: Diploma thesis
Supervisor: Miskolczi, Martina
Opponents: Šimková, Martina
Thesis language: English
Abstract:
The research’s aim is to project the population of Denmark from 2021 to 2050 and see the trends in longevity, mortality in the older ages while comparing them side by side with the official projections for the same time period. The main questions revolve around confirming if longevity is on the rise and mortality on the decline regardless of modelled assumptions of different projections, what are the consequences for the labor force and if immigration or an older workforce can be the solution. We find that Denmark would experience a small change in total population however an increase in the share of older population. Immigration will be beneficial however to very small extent. On the other hand, older workforce has a good potential with their good health, education levels and non-monetary motivations to stay in the workforce. Key areas identified that, if improved, can assist in a better and more feasible multigenerational workforce would be the communication and trust between management and the older employees. Along with that continued education and reskilling for the older employees will also be of paramount importance to make sure that a multigenerational workforce model can work on an organizational level and thus assist in slowing down the effects of aging on the productive population of Denmark.
Keywords: Demography; Denmark’ population; older workforce; multigenerational workforce; population projection; cohort component method; immigration and labor market; stationary population, ; behavioral analysis
Thesis title: Projection of Denmark’s Population 2021-2050 with a focus on Mortality Trends, Longevity, and Multigenerational Workforce
Author: Abid, Mansoor
Thesis type: Diplomová práce
Supervisor: Miskolczi, Martina
Opponents: Šimková, Martina
Thesis language: English
Abstract:
The research’s aim is to project the population of Denmark from 2021 to 2050 and see the trends in longevity, mortality in the older ages while comparing them side by side with the official projections for the same time period. The main questions revolve around confirming if longevity is on the rise and mortality on the decline regardless of modelled assumptions of different projections, what are the consequences for the labor force and if immigration or an older workforce can be the solution. We find that Denmark would experience a small change in total population however an increase in the share of older population. Immigration will be beneficial however to very small extent. On the other hand, older workforce has a good potential with their good health, education levels and non-monetary motivations to stay in the workforce. Key areas identified that, if improved, can assist in a better and more feasible multigenerational workforce would be the communication and trust between management and the older employees. Along with that continued education and reskilling for the older employees will also be of paramount importance to make sure that a multigenerational workforce model can work on an organizational level and thus assist in slowing down the effects of aging on the productive population of Denmark.
Keywords: multigenerational workforce; population projection; cohort component method; older workforce; Demography; Denmark’ population; immigration and labor market; stationary population; behavioral analysis

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: 3. 11. 2021
Date of submission: 30. 6. 2022
Date of defense: 25. 8. 2022
Identifier in the InSIS system: https://insis.vse.cz/zp/78637/podrobnosti

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