Rational Inattention and Oversensitivity of Retirement to the State Pension Age

By Jamie Hentall MacCuish


This paper presents evidence that incorporating costly thought, modelled with rational inattention, solves two well-established puzzles in the retirement literature. The first puzzle is that, given incentives, the extent of bunching of labour market exits at legislated state pension ages (SPA) seems incompatible with rational expectations (e.g. Cribb, Emmerson, and Tetlow, 2016). Adding to the evidence for this puzzle, this paper includes an empirical analysis focusing on whether liquidity constraints can account for this bunching and finds they cannot. The nature of this puzzle is clarified by exploring a life-cycle model with rational agents that does match aggregate profiles. This model succeeds in matching these aggregates only by overestimating the impact of the SPA on poorer individuals whilst underestimating its impact on wealthier people. The second puzzle is that people are often mistaken about their own pension provisions (e.g. Gustman and Steinmeier, 2001). Concerning this second puzzle, I incorporate rational inattention to the SPA into the aforementioned life-cycle model, thus allowing for mistaken beliefs. To the best of my knowledge, this paper is the first to incorporate rational inattention into a life-cycle model. Rational inattention not only improves the aggregate fit of the data but better matches the response of participation to the SPA across the wealth distribution, hence simultaneously offering a resolution to the first puzzle. This paper researches these puzzles in the context of the ongoing reform to the UK female state pension age

As the population ages and pension systems adapt, there will be more confusion about the “correct” age to retire. As the paper shows, there is in fact already quite a bit of confusion about this in the UK. It is important to understand this to see the consequences on retirement choices. Plus it is interesting to see the application of rational inattention in a life-cycle model.


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