Steven Haider
Professor of Economics Michigan State University
Biography
Industry Expertise
Areas of Expertise
Accomplishments
Teacher-Scholar Award
2009
Michigan State University
Education
University of Michigan, Ann Arbor, MI
Ph.D.
Economics
1998
University of Michigan, Ann Arbor, MI
M.A
Economics
1995
Affiliations
- 2014 – present, Research Affiliate, Institute for Research on Poverty, University of Wisconsin, Madison, WI
News
Why do infant death rates vary by race?
Futurity: Research News
2013-12-20
“What’s surprising about our findings is that when we take out all the factors we can observe—including mother’s age, education level, marital status, and state of residence—the difference in the rate in which black and white infants die remained absolutely stable for two decades,” says Steven Haider, professor of economics at Michigan State University. “We made no progress in shrinking that part of the gap.”...
Studying the black-white infant mortality gap
MSU Today
2013-12-19
“What’s surprising about our findings is that when we take out all the factors we can observe – including mother’s age, education level, marital status and state of residence – the difference in the rate in which black and white infants die remained absolutely stable for two decades,” said Steven Haider, professor of economics. “We made no progress in shrinking that part of the gap.”...
The Mystery of Why More Black Babies Die in Infancy than White Babies
TIME
2013-12-19
There have been many explanations offered for the difference in survival rates, including discrepancies in education, access to prenatal care, fatherly engagement, local healthcare options and wealth. But by analyzing the birth certificate data, the researchers were able to rule most of those out. “When we take out the factors we can observe—including mother’s age, education level, marital status and state of residence—the difference in the rate in which black and white infants die remained absolutely stable for two decades,” says Steven Haider, professor of economics at Michigan State University and one of the authors of the study. “We’ve made no progress in shrinking that part of the gap.”...
Journal Articles
Elderly Labor Supply
Workplace flexibility: Realigning 20th-century jobs for a 21st-century workforceSteven J Haider, David S Loughran
2010
What are we weighting for?
Journal of Human ResourcesGary Solon, Steven J Haider, Jeffrey M Wooldridge
2015
When estimating population descriptive statistics, weighting is called for if needed to make the analysis sample representative of the target population. With regard to research directed instead at estimating causal effects, we discuss three distinct weighting motives:(1) to achieve precise estimates by correcting for heteroskedasticity;(2) to achieve consistent estimates by correcting for endogenous sampling; and (3) to identify average partial effects in the presence of unmodeled heterogeneity of effects. In each case, we find that the motive sometimes does not apply in situations where practitioners often assume it does.
RAND HRS data documentation-Version L
RAND Center for the Study of AgingPatricia St Clair, Delia Bugliari, Nancy Campbell, Sandy Chien, Orla Hayden, Michael Hurd, Regan Main, Angela Miu, Mike Moldoff, Constantijn Panis, Philip Pantoja, Afshin Rastegar, Susann Rohwedder, Marian Oshiro, Julie Zissimopoulos
2011
The Health and Retirement Study (HRS) is a longitudinal household survey data set for the study of retirement and health among the elderly in the United States. It is extraordinarily rich and complex. With the goal of making the data more accessible to researchers, the RAND Center for the Study of Aging, with funding and support from the National Institute on Aging (NIA) and the Social Security Administration (SSA), created the RAND HRS data files. This document describes the RAND HRS data. The RAND HRS is a user-friendly version of a subset of the HRS. It contains cleaned and processed variables with consistent and intuitive naming conventions, model-based imputations and imputation flags, and spousal counterparts of most individual-level variables. All is elaborately documented, with special attention to comparability of variables across survey waves.
