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Refusal Bias In Hiv Data From The Demographic And Health Surveys: Evaluation, Critique And Recommendations, Oyelola A. Adegboye, Tomoki Fujii, Denis H. Y. Leung
Refusal Bias In Hiv Data From The Demographic And Health Surveys: Evaluation, Critique And Recommendations, Oyelola A. Adegboye, Tomoki Fujii, Denis H. Y. Leung
Research Collection School Of Economics
Non-response is a commonly encountered problem in many population-based surveys. Broadly speaking, non-response can be due to refusal or failure to contact the sample units. Although both types of non-response may lead to bias, there is much evidence to indicate that it is much easier to reduce the proportion of non-contacts than to do the same with refusals. In this article, we use data collected from a nationally representative survey under the Demographic and Health Surveys program to study non-response due to refusals to HIV testing in Malawi. We review existing estimation methods and propose novel approaches to the estimation …
Corrigendum To "On Time-Varying Factor Models: Estimation And Testing" [J. Econometrics 198 (2017) 84-101], Liangjun Su, Xia Wang
Corrigendum To "On Time-Varying Factor Models: Estimation And Testing" [J. Econometrics 198 (2017) 84-101], Liangjun Su, Xia Wang
Research Collection School Of Economics
We note that Su and Wang (2017, On Time-varying Factor Models: Estimation and Testing, Journal of Econometrics 198, 84-101) ignore the bias terms when estimating the time-varying factor models. In this note, we correct the theoretical results on the estimation of time-varying factor models. The asymptotic results for testing the correct specification of time invariant factor loadings are not affected.