Please use this identifier to cite or link to this item:
Title: Properties of Census Dual System Population Size Estimators
Authors: Xi Chen, S.
Tang, C.Y. 
Keywords: Capture-recapture
Discrete covariate
Erroneous enumeration
Kernel smoothing
Model bias
Population size estimation
Issue Date: Dec-2011
Citation: Xi Chen, S., Tang, C.Y. (2011-12). Properties of Census Dual System Population Size Estimators. International Statistical Review 79 (3) : 336-361. ScholarBank@NUS Repository.
Abstract: We study parametric and non-parametric approaches for assessing the accuracy and coverage of a population census based on dual system surveys. The two parametric approaches being considered are post-stratification and logistic regression, which have been or will be implemented for the US Census dual system surveys. We show that the parametric model-based approaches are generally biased unless the model is correctly specified. We then study a local post-stratification approach based on a non-parametric kernel estimate of the Census enumeration functions. We illustrate that the non-parametric approach avoids the risk of model mis-specification and is consistent under relatively weak conditions. The performances of these estimators are evaluated numerically via simulation studies and an empirical analysis based on the 2000 US Census post-enumeration survey data. © 2011 The Authors. International Statistical Review © 2011 International Statistical Institute.
Source Title: International Statistical Review
ISSN: 03067734
DOI: 10.1111/j.1751-5823.2011.00150.x
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Feb 4, 2023


checked on Jan 26, 2023

Page view(s)

checked on Feb 2, 2023

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.