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Regression Composite Estimation: An Alternative Approach for the Current Population Survey
| Content Provider | Semantic Scholar |
|---|---|
| Author | Bonn'ery, Daniel Cheng, Yang Lahiri, Partha |
| Copyright Year | 2014 |
| Abstract | The Current Population Survey (CPS), a household survey sponsored by the U.S. Bureau of Labor Statistics (BLS) and conducted by the U.S. Census Bureau, is the primary source of information on the U.S. employment and unemployment levels and rates. The Census Bureau has been using the AK estimation technique for generating employment and unemployment levels and rates for the last several decades. The development of a new composite estimation method by Fuller & Rao (2001) and its subsequent adaptation by Statistics Canada for its production of offcial labor force statistics encourage us to conduct additional research for evaluation of the Fuller-Rao regression composite method in estimating the U.S. employment and unemployment rates. To this end, we frst adapt the Fuller-Rao regression composite estimation method before applying to the CPS data. Using CPS data for the period 2005-2012, we device a Monte Carlo simulation experiment in order to compare the proposed, survey-weighted direct and the AK estimates with the simulated true employment rates. Our study also includes CPS data analysis that compares the AK estimates with different Fuller-Rao type composite estimates. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://nces.ed.gov/FCSM/pdf/G2_Bonnery_2013FCSM_AC.pdf |
| Alternate Webpage(s) | https://s3.amazonaws.com/sitesusa/wp-content/uploads/sites/242/2014/05/G2_Bonnery_2013FCSM.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
