000 02209cam  2200313za 4500
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008180705s2018    oncd    ob   f000 0 eng d
040 |aCaOODSP|beng
041 |aeng|bfre
043 |an-cn---
0861 |aFB3-5/2018-29E-PDF
1001 |aFelt, Marie-Hélène.
24512|aA look inside the box |h[electronic resource] : |bcombining aggregate and marginal distributions to identify joint distributions / |cby Marie-Hélène Felt.
24630|aCombining aggregate and marginal distributions to identify joint distributions
260 |a[Ottawa] : |bBank of Canada, |c2018.
300 |aiii, 49 p. : |bcol. charts.
4901 |aBank of Canada staff working paper, |x1701-9397 ; |v2018-29
500 |a"July 2018."
504 |aIncludes bibliographical references (p. 27-29).
5203 |a"This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure. Multiple examples are given of data settings where multivariate samples from the joint distribution of interest are not readily available, but some aggregate measures are observed. In the application, intra-household distributions are recovered by combining individual-level and household-level survey data. I show that, for individuals living in couple relationships, personal cash-management practices are significantly influenced by the partner's use of cash and stored-value cards. This finding implies that, for some methods of payment at least, ignoring the partner's impact might lead to spurious regression results due to an omitted variable bias"--Abstract, p. ii.
546 |aIncludes abstract in French.
693 4|aCash transactions
693 4|aEconometric models
7102 |aBank of Canada.
830#0|aStaff working paper (Bank of Canada)|x1701-9397 ; |v2018-29.|w(CaOODSP)9.806221
85640|qPDF|s2.08 MB|uhttps://publications.gc.ca/collections/collection_2018/banque-bank-canada/FB3-5-2018-29-eng.pdf