Sampling units for the 2013 Methods-of-Payment survey were selected through an approximate stratified two-stage sampling design. To compensate for nonresponse and noncoverage and ensure consistency with external population counts, the observations are weighted through a raking procedure. We apply bootstrap resampling methods to estimate the variance, allowing for randomness from both the sampling design and raking procedure. We find that the variance is smaller when estimated through the bootstrap resampling method than through the naive linearization method, where the latter does not take into account the correlation between the variables used for weighting and the outcome variable of interest.
We are grateful to the AiE Editors, Gautam Tripathi, Kim P. Huynh, David T. Jacho-Chavez and two anonymous referees for their insightful comments which have led to the current much improved paper. We thank Geoffrey Dunbar, Shelley Edwards, Ben Fung, Kim P. Huynh, May Liu, Sasha Rozhnov and Kyle Vincent for their useful comments and encouragement. Maren Hansen provided excellent writing assistance. We also thank Statistics Canada for providing access to the 2011 National Household Survey and the 2012 Canadian Internet Usage Survey. The views of this paper are those of the authors and do not represent the views of the Bank of Canada.
Chen, H. and Shen, Q.R. (2019), "Variance Estimation for Survey-Weighted Data Using Bootstrap Resampling Methods: 2013 Methods-of-Payment Survey Questionnaire", The Econometrics of Complex Survey Data (Advances in Econometrics, Vol. 39), Emerald Publishing Limited, Bingley, pp. 87-106. https://doi.org/10.1108/S0731-905320190000039004
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