The overall goal of our program project and its individual research projects is to study decision-making and wellbeing using the Health and Retirement Study, exploring links between behavior on surveys and in the real world. Project 1 proposes to utilize the MRSdata about subjective probability beliefs on a wide variety of topics in conjunction with models of survey response and behavior under uncertainty to address four related questions. Project 2 proposes to use well-specified longitudinal economic models to analyze how health status and economic factors jointly affect labor force behavior as workers approach retirement age, with particular focus on the choices people make when their health declines. Project 3 proposes to bring to bear the concepts and methods of modern Economics on the traditional problem of well-being in Psychology, and the insights of modern Psychology about well-being in general and subjective well-being data in particular on the traditional problems in Economics of prediction of behavior, understanding expectation formation, and welfare analysis. Project 4 proposes to test theories about the mechanisms producing interviewer effects on self-report health data across different age groups; to invent and validate indicators of interviewer-related mechanisms producing measurement error; and to demonstrate improved statistical analyses about important age-related health phenomena by employing the measurement error indicators of those mechanisms. Project 5 proposes to analyze tendencies of respondents to the MRSfor nonresponse and response errors in answering related questions, as well as across the instrument as a whole. Project 6 proposes to identify what governs cross-sectional difference in portfolio choice with regard to risk preference, illiquid assets and behavioral finance. We propose three Cores designed to support this program of research - an Administrative Core, a Data Innovation Core and a Network core. These Cores provide an efficientway to maximize the scientific productivity of these six projects.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
3P01AG026571-02S1
Application #
7422527
Study Section
Special Emphasis Panel (ZAG1-ZIJ-1 (M1))
Program Officer
Phillips, John
Project Start
2005-09-30
Project End
2008-06-30
Budget Start
2007-05-15
Budget End
2007-06-30
Support Year
2
Fiscal Year
2007
Total Cost
$132,422
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Organized Research Units
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Bruine de Bruin, Wändi; Carman, Katherine G (2018) Measuring Subjective Probabilities: The Effect of Response Mode on the Use of Focal Responses, Validity, and Respondents' Evaluations. Risk Anal 38:2128-2143
Gideon, Michael; Helppie-McFall, Brooke; Hsu, Joanne W (2017) Heaping at Round Numbers on Financial Questions: The Role of Satisficing. Surv Res Methods 11:189-214
Helppie-McFall, Brooke; Hsu, Joanne W (2017) A Test of Web and Mail Mode Effects in a Financially Sensitive Survey of Older Americans. J Econ Soc Meas 42:151-169
Aufderheide, K J (2016) Refinements of and commentary on the silver staining techniques of Fernández-Galiano. Biotech Histochem 91:352-6
Hsu, Joanne W (2016) Aging and Strategic Learning: The Impact of Spousal Incentives on Financial Literacy. J Hum Resour 51:1036-1067
Delavande, Adeline; Manski, Charles F (2015) Using Elicited Choice Probabilities in Hypothetical Elections to Study Decisions to Vote. Elect Stud 38:28-37
Kimball, Miles (2015) COGNITIVE ECONOMICS. Jpn Econ Rev (Oxf) 66:167-181
Levy, Helen; Janke, Alexander T; Langa, Kenneth M (2015) Health literacy and the digital divide among older Americans. J Gen Intern Med 30:284-9
Benjamin, Daniel J (2015) Distributional Preferences, Reciprocity-Like Behavior, and Efficiency in Bilateral Exchange. Am Econ J Microecon 7:70-98
Delaney, Rebecca; Strough, JoNell; Parker, Andrew M et al. (2015) Variations in Decision-Making Profiles by Age and Gender: A Cluster-Analytic Approach. Pers Individ Dif 85:19-24

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