Retirement Expectations and Satisfaction with Retirement Provisions

Abstract

This paper investigates the relationship between subjective expectations regarding the replacement rate of income at retirement and several measures of pension satisfaction. We use panel data on Dutch employees, analyzed with fixed effects models, allowing for correlation between unobserved heterogeneity in satisfaction and optimism or pessimism in expectations. The level of the expected replacement rate is found to be positively related to satisfaction: respondents who revise their expectations of the level of their replacement rate upwards tend to become more satisfied with their pension provisions, in particular with the level of the expected benefits. We do not find robust evidence for a relationship between uncertainty and pension satisfaction.JEL Codes: D84, H55, I31

Heterogeneity in consumers’ income and pension expectations

“…5 Retirement replacement rate expectations are measured using a set of subjective probability questions. Since this has been described extensively in Van Santen et al (2012) and De Bresser and van Soest (2013, 2015, we explain it only briefly here. Six survey questions on the retirement income replacement rates (RIRRs) were asked to all respondents who worked as employees.…”

“…The NPM consists of short monthly questionnaires including questions on expectations concerning pension reforms and on satisfaction with pension provisions and the pension system, which have been analyzed elsewhere (see, e.g., Bissonnette and van Soest, 2012; De Bresser and van Soest, 2015) and a longer annual survey (usually administered in June) including the questions on expected retirement and replacement rates, expected income changes, and, since 2009, the perceived importance of the crisis. The early waves of annual data on expected replacement rates have been analyzed in Van Santen et al (2012) and De Bresser and van Soest (2013, 2015). In the present paper, we reanalyze these data focusing on their relation to the perception on the crisis (the data on which have not been used in earlier studies).…”

“…The answers to these six questions for a given respondent in a given year provide six points on the graph of the respondent's subjective cumulative distribution function of their RIRR. Following Bellemare et al (2012) and De Bresser and van Soest (2015), these six points are used to nonparametrically estimate the complete subjective distribution of the future RIRR for each observation. The distribution function is obtained by linking the six points corresponding to the reported probabilities using splines, imposing monotonicity.…”

Pension Pessimism in the Young Generation: Basics or Instincts to Blame?

“…Many international studies investigate pension expectations in connection with the rising statutory retirement age (Coppola & Wilke, 2014), the replacement rates (de Bresser & van Soest, 2015) or the well-being in retirement ages (Lusardi & Mitchell, 2011). We find examples of expectation surveys in different countries (Greenwald et al, 2017;Sekita, 2011) or different age groups of individuals (Lusardi & Olivia, 2014).…”

Subjective Inheritance Expectations and Economic Outcomes

“…Indeed, analyzing the predictive power of expectations can provide insights into the validity of expectations data -even if it is not possible to verify whether reported probabilities reflect the actual beliefs held by respondents, it might be possible to assess the internal consistency and plausibility of responses: evidence suggests that responses have such "face validity" when the questions concern welldefined events that are relevant to respondents' lives (Manski (2004)). De Bresser & van Soest (2015) apply two different methods to construct subjective replacement rate distributions from the reported probabilities. The first, proposed in Dominitz & Manski (1997), fits an assumed underlying (log-normal) distribution for each observation by minimizing the squared difference between the probabilities implied by the assumed distribution and those reported in the data; the second approach, adapted from Bellemare et al (2012), uses spline interpolation to fit a subjective distribution that passes through the points corresponding to the probabilities reported by the respondents.…”