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0019.868361
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008190214t20182018onc    #ot   f|0| 0 eng  
040 |aCaOODSP|beng
041 |aeng|bfre
043 |an-cn---
0861 |aFB3-1/114-2018E-PDF
1001 |aChen, Heng,|d1981- |eauthor.
24510|a2017 Methods-of-Payment Survey : |bsample calibration and variance estimation / |cby Heng Chen, Marie-Hélène Felt and Christopher S. Henry.
264 1|aOttawa, Ontario, Canada : |bBank of Canada, |c2018.
264 4|c©2018
300 |a1 online resource (ii, 54 pages)
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
4901 |aTechnical report = Rapport technique, |x1919-689X ; |vno. 114
500 |a"December 2018."
504 |aIncludes bibliographic references.
520 |a"This technical report describes sampling, weighting and variance estimation for the Bank of Canada's 2017 Methods-of-Payment Survey. Under quota sampling, a raking ratio method is implemented to generate weights with both post-stratification and nonparametric nonresponse weight adjustments. In the end, we estimate variances of weighted means and proportions using bootstrap replicate survey weights. Compared with probability sampling, we find that (i) strong assumptions are required to reduce bias when probabilities of selection are unknown, and (ii) multiple weight adjustments for bias reduction inflate variance. Therefore, it is important to focus more on bias than on variance in the context of nonprobability sampling"--Abstract, page ii.
546 |aIncludes abstract in French.
69207|2gccst|aCurrency
7001 |aFelt, Marie-Hélène, |eauthor.
7001 |aHenry, Christopher S., |eauthor.
7102 |aBank of Canada.
830#0|aTechnical report (Bank of Canada)|x1919-689X ; |vno. 114.|w(CaOODSP)9.505019
85640|qPDF|s4.45 MB|uhttps://publications.gc.ca/collections/collection_2019/banque-bank-canada/FB3-1-114-2018-eng.pdf