Presented By: Michigan Program in Survey and Data Science
MPSDS JPSM Seminar Series - 2020 California Neighborhoods Count: A validation of U.S. Census Population Counts and Housing Characteristic Estimates within California
Lane Burgette - RAND Corporation
MPSDS JPSM Seminar Series
November 8, 2023
12:00 - 1:00 pm EST
The seminar will be locked 10 minutes after the start of the presentation.
2020 California Neighborhoods Count: A validation of U.S. Census Population Counts and Housing Characteristic Estimates within California
In response to long-standing concerns about the accuracy of census data and about a possible undercount, we conducted the California Neighborhoods Count (CNC) study — the first-ever independent, survey-based enumeration to directly evaluate the accuracy of the U.S. Census Bureau's population totals for a subset of California census blocks. This 2020 research was intended to produce parallel estimates of the 2020 Census population and housing unit totals at the census block level, employing the same survey items as the census and using enhanced data collection strategies and exploration of imputation methods. The CNC block-level population estimates were sensitive to the imputation method used to account for non-responding households, likely in part due to limited availability of administrative data to assist the imputations. CNC identified more housing units than Census (23,929 versus 22,668), which may be due to CNC’s in-person address canvassing. Despite advancements in geospatial imaging software, as well as many other approaches used by the U.S. Census Bureau to assess coverage and validate addresses, in-field address verification might yield a more complete accounting of inhabited housing units than partially conducting address canvassing with in-office approaches.
Lane Burgette is a Senior Statistician at the RAND Corporation. Dr. Burgette’s applied research is primarily focused on health policy, especially Medicare’s physician payment policies. Other recent research projects include an evaluation of the 2020 Census in California, gun policy research, and recidivism risk estimation for employer background checks. Dr. Burgette’s methodological research focuses on causal inference, methods for missing data, and Bayesian modeling. Prior to RAND, he earned his Ph.D. in Statistics at the University of Wisconsin, and was a post-doctoral researcher in the Department of Statistical Science at Duke University.
November 8, 2023
12:00 - 1:00 pm EST
The seminar will be locked 10 minutes after the start of the presentation.
2020 California Neighborhoods Count: A validation of U.S. Census Population Counts and Housing Characteristic Estimates within California
In response to long-standing concerns about the accuracy of census data and about a possible undercount, we conducted the California Neighborhoods Count (CNC) study — the first-ever independent, survey-based enumeration to directly evaluate the accuracy of the U.S. Census Bureau's population totals for a subset of California census blocks. This 2020 research was intended to produce parallel estimates of the 2020 Census population and housing unit totals at the census block level, employing the same survey items as the census and using enhanced data collection strategies and exploration of imputation methods. The CNC block-level population estimates were sensitive to the imputation method used to account for non-responding households, likely in part due to limited availability of administrative data to assist the imputations. CNC identified more housing units than Census (23,929 versus 22,668), which may be due to CNC’s in-person address canvassing. Despite advancements in geospatial imaging software, as well as many other approaches used by the U.S. Census Bureau to assess coverage and validate addresses, in-field address verification might yield a more complete accounting of inhabited housing units than partially conducting address canvassing with in-office approaches.
Lane Burgette is a Senior Statistician at the RAND Corporation. Dr. Burgette’s applied research is primarily focused on health policy, especially Medicare’s physician payment policies. Other recent research projects include an evaluation of the 2020 Census in California, gun policy research, and recidivism risk estimation for employer background checks. Dr. Burgette’s methodological research focuses on causal inference, methods for missing data, and Bayesian modeling. Prior to RAND, he earned his Ph.D. in Statistics at the University of Wisconsin, and was a post-doctoral researcher in the Department of Statistical Science at Duke University.
Livestream Information
ZoomNovember 8, 2023 (Wednesday) 12:00pm
Meeting ID: 97217806877
Meeting Password: 2324
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