ILR School

University of Michigan Node

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Recent Submissions

Now showing 1 - 4 of 4
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    NCRN Meeting Fall 2016: Scanner Data and Economic Statistics: A Unified Approach
    Redding, Stephen J.; Weinstein, David E. (2016-10)
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    NCRN Meeting Spring 2016: Developing job linkages for the Health and Retirement Study
    McCue, Kristin; Abowd, John; Levenstein, Margaret; Patki, Dhiren; Rodgers, Ann; Shapiro, Matthew; Wasi, Nada (2016-05-10)
    This paper documents work using probabilistic record linkage to create a crosswalk between jobs reported in the Health and Retirement Study (HRS) and the list of workplaces on Census Bureau’s Business Register. Matching job records provides an opportunity to join variables that occur uniquely in separate datasets, to validate responses, and to develop missing data imputation models. Identifying the respondent’s workplace (“establishment”) is valuable for HRS because it allows researchers to incorporate the effects of particular social, economic, and geospatial work environments in studies of respondent health and retirement behavior. The linkage makes use of name and address standardizing techniques tailored to business data that were recently developed in a collaboration between researchers at Census, Cornell, and the University of Michigan. The matching protocol makes no use of the identity of the HRS respondent and strictly protects the confidentiality of information about the respondent’s employer. The paper first describes the clerical review process used to create a set of human-reviewed candidate pairs, and use of that set to train matching models. It then describes and compares several linking strategies that make use of employer name, address, and phone number. Finally it discusses alternative ways of incorporating information on match uncertainty into estimates based on the linked data, and illustrates their use with a preliminary sample of matched HRS jobs.
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    Introduction to The Survey of Income and Program Participation (SIPP)
    Shaefer, H. Luke (2015-05-15)
    Goals for the SIPP Workshop Provide you with an introduction to the SIPP and get you up and running on the public-use SIPP files, offer some advanced tools for 2008 Panel SIPP data analysis, Get you some experience analyzing SIPP data, Introduce you to the SIPP EHC (SIPP Redesign), Introduce you to the SIPP Synthetic Beta (SSB)
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    Do Single Mothers in the United States use the Earned Income Tax Credit to Reduce Unsecured Debt?
    Shaefer, H. Luke; Song, Xiaoqing; Williams Shanks, Trina R. (National Poverty Center, 2011-10)
    The Earned Income Tax Credit (EITC) is a refundable credit for low-income workers that is mainly targeted at families with children. This study uses the Survey of Income and Program Participation’s (SIPP) topical modules on Assets & Liabilities to examine the effects of EITC expansions during the early 1990s on the unsecured debt of the households of single mothers. We use two difference-in-differences comparisons over the study period 1988 to 1999, first comparing single mothers to single childless women, and then comparing single mothers with two or more children to single mothers with exactly one child. In both cases we find that the EITC expansions are associated with a relative decline in the unsecured debt of affected households of single mothers. This suggests that single mothers may have used part of their EITC to limit the growth of their unsecured debt during this period.