title: Women's retirement expectations: how stable are they?
abstract: OBJECTIVE
  Using the National Longitudinal Survey of Mature Women, we examine between- and within-person differences in expected retirement age as a key element of the retirement planning process. The expectation typologies of 1,626 women born between 1923 and 1937 were classified jointly on the basis of specificity and consistency.
  
  
  METHODS
  Latent class analysis was used to determine retirement expectation patterns over a 7-year span. Multinomial logistic regression analyses were employed to estimate the effects of demographic and status characteristics on the likelihood of reporting 4 distinct longitudinal patterns of retirement expectations.
  
  
  RESULTS
  Substantial heterogeneity in reports of expected retirement age between and within individuals over the 7-year span was found. Demographic and status characteristics, specifically age, race, marital status, job tenure, and recent job change, sorted respondents into different retirement expectation patterns.
  
  
  CONCLUSIONS
  The frequent within-person fluctuations and substantial between-person heterogeneity in retirement expectations indicate uncertainty and variability in both expectations and process of expectation formation. Variability in respondents' reports suggests that studying retirement expectations at multiple time points better captures the dynamics of preretirement planning.
authors.affiliation: Department of Human Development and Family Studies, The Pennsylvania State University, University Park, 18602, USA. jdw276@psu.edu
authors.forename: Jen D
authors.initials: JD
authors.lastname: Wong
authors.forename: Melissa A
authors.initials: MA
authors.lastname: Hardy
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001290:Attitude; D003469:Culture; D003625:Data Collection; D003657:Decision Making; D005260:Female; D005783:Gender Identity; D006801:Humans; D007588:Job Satisfaction; D008137:Longitudinal Studies; D008875:Middle Aged; D011336:Probability; D012044:Regression Analysis; D012179:Retirement / Q000523:psychology*; D012943:Social Security; D012959:Socioeconomic Factors; D014481:United States