1 Million for New Pensions and Retirement Research
The Netspar board has honored four applications for theme projects and awarded € 250 per project. The award of the four projects is in line with the opinion of the Partner Research Council, after scientific review by the Scientific Council. Netspar wishes the researchers good luck with the implementation of these three-year projects. The intended start is in January 2018.
More information per project:
Johan Mackenbach & Wilma Nusselder (EUR): Longer life, longer in good health, working longer? Implications of educational differences for the pension system
Data from various countries show that people with a higher education level live longer and much longer in good health than people with a lower education level. This has important consequences for the pension system, for example for solidarity and costs for disability benefits when people need to work longer. This project aims at giving individual projections of future (healthy) life expectancy at the level of education and understanding of the consequences for the (new) Dutch pension system.
Antoon Pelsser (UM): Design of Pension Contracts in Incomplete Markets and under Uncertainty
In recent years there has been a development which shifts (investment) risks in pensions increasingly to participants and less to employers. Therefore, in the interest of the participant, risks that are difficult to predict and uncertainties with regard to share prices and interest rates should be taken into account. This project aims at developing strategies that perform adequately, also when assessment errors are made.
Marcel Lever (CPB): Choice architecture in pensions and retirement
This research project will analyze the impact of customization and freedom of choice in pensions and retirement on social welfare. Two aspects of choice architecture will be looked into: choice limitation and individualized defaults. The project focuses on the effect of choice architecture in pension plans on retirement and on pension saving and investment. The analysis also includes the impact on choice of personal characteristics such as life expectancy, health, risk attitudes, housing tenure, etc. This focus allows us to perform in-depth analysis.
Peter de Goeij & Eric Postma (TiU): Data Science Solutions to Enhance Pension Communication
The purpose of this project is to use the power of state-of-the-art data science methods to study and improve communications in the field of pensions and insurance. It also explores the possibilities of machine learning (algorithms) to facilitate communication in the area of pensions and insurance. The intended output consists of academic papers, reports on the results obtained and software tools for performing the necessary improvements.