1. Comments on “ Trajectories to Retirement: The Role of Personal Traits, Attitudes, and Expectations” by Hudomiet, Parker, & Rohwedder Gwenith G. Fisher SIEPR Conference on Working Longer and Retirement October 8, 2015

2. Summary Used longitudinal HRS data to group participants by work/retirement patterns (trajectories) Examined fluid cognitive ability and “Big 5” personality variables as psychological factors that may relate to work/retirement patterns Found that cognitive ability and some personality factors (extraversion, agreeableness) are related to retirement timing and patterns of work and retirement

3. Comments - Strengths Important to understand retirement timing and patterns as well as antecedents Examined psychological factors Used HRS data– longitudinal, nationally representative, heterogenous sample; broad array of variables Considered many different work/retirement patterns (“non- traditional” retirement) Thorough consideration of covariates/controls known to be related to the retirement process Interesting discussion of practical and policy implications

4. Comments HPR: Why might psychological factors affect work and retirement behavior? ◦Making certain workers WANT to work longer ◦Making employers want to KEEP certain workers ◦Making employers want to HIRE certain workers into bridge jobs Sound conceptual model but more integration of psychology literature would strengthen paper: ◦Retirement decision making (Feldman & Beehr, 2011; Wang & Shultz, 2010) ◦Person-environment fit theory ◦Work motivation (Kanfer, Beier, & Ackerman, 2013) ◦Prior research on personality and retirement ( Blekesaune & Skirbekk, 2012; Löckenhoff et al., 2009)

5. Comments Gc Gf Conceptualized fluid cognition as a stable characteristic Averaged cognition over time

6. Comments Possible selection bias Occupational choice: Workers with higher levels of cognitive ability may choose different jobs that facilitate working longer Control for job characteristics, such as job complexity (Willis et al., 2015; Fisher et al., 2014)

7. Comments HPR found a higher prevalence of part-time work in the service and transportation sectors Finding that extraversion is related to part-time bridge employment may be a function of labor demand and market opportunities Policy issue to establish more varied part-time work opportunities for older workers

8. Comments Other limitations worth noting in discussion: Small effect sizes – may limit practical implications Correlational research - cannot truly infer causality

9. Recommendations Clarify definition of working longer –Important to understand retirement ages given SSA policy changes Devote more attention to construct validity of cognitive measures –Episodic memory; fluid & crystallized abilities (McArdle, Fisher, & Kadlec, 2007) Model within and between-person changes in cognitive ability as predictors of retirement trajectory groups

10. Recommendations Further integrate with extant literature –More attention to psychological factors in relation to retirement timing than indicated (Fisher, Chaffee, & Sonnega, 2015) –How does this study extend prior research on personality and retirement? Address possible selection bias Control for job complexity

11. Future Research Examine additional personality variables –e.g., positive affectivity, negative affectivity (Watson, Clark, & Tellegen, 1988) Examine other psychological factors in relation to retirement timing Consider more specific types of bridge employment (Beehr & Bennet, 2015) –Career vs. non-career job –Self-employment

12. Model of Retirement Timing

13. Individual Factors Physical Health status Economic status Pensions Social Security eligibility Wealth and income Health insurance Demographic characteristics Psychological factors Cognitive functioning Mental health Motivation, needs and values Preferred-expected retirement age Attitudes toward aging & retirement Subjective life expectancy Role identity Personality Fisher, Chaffee, & Sonnega (2015)

14. Model of Retirement Timing Individual Factors Physical Health status Economic status Pensions Social Security eligibility Wealth and income Health insurance Demographic characteristics Psychological factors Cognitive functioning Mental health Motivation, needs and values Preferred-expected retirement age Attitudes toward aging & retirement Subjective life expectancy Role identity Personality Fisher, Chaffee, & Sonnega (2015)

15. References Beehr, T. A., & Bennett, M. M. (2015). Working after retirement: Features of bridge employment and research directions. Work, Aging and Retirement, 1(1), 112–128. Blekesaune, M., & Skirbekk, V. (2012). Can personality predict retirement behaviour? A longitudinal analysis combining survey and register data from Norway. European Journal of Ageing, 9(3), 199–206. Feldman, D. C., & Beehr, T. A. (2011). A three-phase model of retirement decision making. American Psychologist, 66(3), 193- 203. Fisher, G. G., Chaffee, D. S., & Sonnega, A. (2015). Retirement timing: A review and recommendations for future research. R&R - Work, Aging, and Retirement. Kanfer, R., Beier, M.E., & Ackerman, P.L. (2013). Goals and motivation related to work in later adulthood: An organizing framework. European Journal of Work and Organizational Psychology, 22(3), 253-264. Löckenhoff, C. E., Terracciano, A., & Costa, P. T.(2009). Five-factor model personality traits and the retirement transition: Longitudinal and cross-sectional associations. Psychology and Aging, 24(3), 722–728. McArdle, J. J., Fisher, G. G., & Kadlec, K. M. (2007). Latent variable analyses of age trends of cognition in the Health and Retirement Study, 1992 – 2004. Psychology and Aging, 22(3), 525‐545. Wang, M., & Shultz, K. S. (2010). Employee retirement: A review and recommendations for future investigation. Journal of Management, 36(1), 172-206. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070.

16. Work, Aging, and Retirement http://workar.oxfordjournals.org/ Editor-in-Chief: Mo Wang, University of Florida Warrington School of Business

17. Thank you! Gwen.Fisher@colostate.edu http://ohplab.colostate.edu Gwen.Fisher@colostate.edu http://ohplab.colostate.edu