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Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

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Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Respondent Rules and the Quality of Net Worth Data in the HRS

Archived Abstract of Former PSC Researcher

Hill, Daniel H. "Respondent Rules and the Quality of Net Worth Data in the HRS." AHEAD/HRS Report No. 94-002. 12 1993.

The HRS uses an informed selection procedure in choosing with spouse to ask about the household's assets and debts. This is more expensive than presumptive selection which has been commonly employed in past surveys. This paper evaluates the quality of the resulting net worth data in terms of the exactness of the reports. A trivariate ordered probit model is developed and estimated. This model controls for the self-selectivity of both the gender and proxy interview status of the net-worth respondent. The results suggest that the informed selection procedure does indeed result in lower item non-response and less reliance on approximation strategies than would a presumptive "husband R1" respondent rule.

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