We develop a panel data model explaining answers to subjective probabilities about binary events and estimate it using data from the Health and Retirement Study on six such probabilities. The model explicitly accounts for several forms of 'reporting behavior': rounding, focal point '50%' answers and item nonresponse. We find observed and unobserved heterogeneity in the tendencies to report rounded values or a focal answer, explaining persistency in 50% answers over time. Focal 50% answers matter for some of the probabilities. Incorporating reporting behavior does not have a large effect on the estimated distribution of the genuine subjective probabilities.2 Our sample is too small to distinguish answers of 'don't know' and refusals. See Shoemaker et al. (2002) for the differences in determinants of these two types of nonresponse. 3 We thank an anonymous referee for this classification suggestion. 4 As in the standard ordered probit model, the distances between the cut-off points determine the frequencies of the categorical outcomes, but the parameters themselves do not have a clear interpretation. MODELING SUBJECTIVE PROBABILITIES 9 We thank Patty St Clair for bringing this pattern of the data to our attention. We used the HRS imputations for missing values and deleted observations with missing values for 2010 (101 person-wave observations) for which imputations were not yet available. 10 We use the RAND model-based imputations for missing observations of income and wealth. 11 This variable is set to zero if missing (between 172 and 286 observations per wave). 12 We also experimented with the number of children but this did not improve the results. When missing, the variable was imputed from the previous or consecutive wave, and set to 0 if those were also missing (between 0 and 160 observations per wave). 13 Estimation results for these specifications are available on request.MODELING SUBJECTIVE PROBABILITIES 575 17 Using the parameter estimates in Tables V and VI, the estimated marginal effect of changing from high school to college education, keeping other variables constant, is given by À0.533 P(50/50) (1 À P(50/50)) + 0.750 P(50/50) P(nonresponse). For the average probabilities of a focal 50/50 and item nonresponse in Table III, this gives À0.533 Â 0.220 Â (1-0.220) + 0.750 Â 0.220 Â 0.045 = À0.083. MODELING SUBJECTIVE PROBABILITIES 579

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in An Economic Analysis of Identity and Career ChoiceMaria Knoth Humlum Kristin J. Kleinjans Helena Skyt Nielsen The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit company supported by Deutsche Post World Net. The center is associated with the University of Bonn and offers a stimulating research environment through its research networks, research support, and visitors and doctoral programs. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. ABSTRACT An Economic Analysis of Identity and Career ChoiceStandard economic models which focus on pecuniary payoffs cannot explain why there are highly able individuals who choose careers with low pecuniary returns. Therefore, financial incentives are unlikely to be effective in influencing career choices of these individuals. Based on Akerlof and Kranton (2000), we consider a model of career choice and identity where individuals derive non-pecuniary identity payoffs. Using factor analysis on a range of attitude questions, we find two factors related to identity (career orientation and social orientation), which are important for educational choices. The implication is that policymakers and institutions of higher education need to focus on identity related issues rather than just improved financial incentives if they aim at attracting the high ability youth to occupations with excess demand for labor.JEL Classification: I21

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