23rd Annual Morris Hansen Lecture

Title: Envisioning the 2030 U.S. Census

• Speaker:  Stephen E. Fienberg

• Discussants:  Ivan Fellegi, former Chief Statistician, Statistics Canada, and Robert Groves, Provost, Georgetown University

• Date/Time: Tuesday, January 7, 2013, 3:30 - 5:30 p.m.

• Location: Jefferson Auditorium, U.S. Department of Agriculture South Building Independence Ave. (between 12th and 14th Streets) Smithsonian Metro Station (Blue/Orange Lines)

• Reception: 5:30 p.m. in the Whitten Building Patio

• Registration: Please pre-register for this event at http://www.nass.usda.gov/morrishansen/ to help facilitate access to the building.

• Sponsors: the Washington Statistical Society, Westat, and the National Agricultural Statistics Service

• Download the Flyer


The level of the error in the U.S. decennial census as measured by gross error (the sum of the errors of omission and commission), has remained remarkably high at approximately 10% over the last three censuses. During the same period, the cost of the census has skyrocketed from $2.6 billion in 1990 to over $13 billion in 2010, even though the census long form was dropped in 2010 in favor of data collection over the decade via the American Community Survey. Without dramatic changes, the cost of a traditional census in 2020 will far outstrip the willingness of Congress to pay. Moreover, we predict that concerns about the confidentiality of census data will pose increasing problems despite the Census Bureau's constant vigilance. The Census Bureau clearly needs to become more nimble in testing new methodologies for census-taking without jettisoning the best of current approaches. In this presentation we will look beyond 2020 to 2030 and speculate on radical changes that could allow for greater census accuracy and lower costs. Methodologies we consider include: the use of aerial photography to supplement or even replace the master address file, the multiple roles for administrative records, and the widespread use of both individual and family-level online census forms. We discuss both obstacles and opportunities in addressing the challenge of placing everyone in the U.S. into appropriate household locations, and we reexamine the concept of counting everyone, “once, and only once, and in the right place.”

(This presentation is based on joint research with William F. Eddy)

Speaker Biography:

Stephen E. Fienberg is Maurice Falk University Professor of Statistics and Social Science at Carnegie Mellon University, holding appointments in the Department of Statistics, the Machine Learning Department, and the Heinz College. He has been on the faculty at Carnegie Mellon since 1980, except for a two-year appointment as vice president for academic affairs at York University, Toronto, and previously served on the faculty of the University of Chicago and the University of Minnesota. He was a member of the Committee on National Statistics from[masked] and chair from[masked] and again from[masked] following a sabbatical year at the Center for Advanced Study in the Behavioral Sciences. Dr. Fienberg received an honors B.Sc. in mathematics and statistics from the University of Toronto and an A.M. and Ph.D. in statistics from Harvard University. He is a member of the National Academy of Sciences, and an elected fellow of the American Academy of Arts and Sciences and the Royal Society of Canada, and a fellow of the American Statistical Association and the Institute of Mathematical Statistics, for which he served as president. Dr. Fienberg has chaired and served on numerous National Research Council panels on such topics as sharing research data, statistical assessments as evidence in the courts, decennial census methodology, evaluation of bilingual education studies, measuring racial discrimination, the polygraph and lie detection, and the technical and privacy dimensions of information on terrorism. Best known for his work on the analysis of categorical data, he is also co-author with Margo Anderson of Who Counts? The Politics of Census-Taking in Contemporary America.

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