A look inside the box : combining aggregate and marginal distributions to identify joint distributions / by Marie-Hélène Felt.: FB3-5/2018-29E-PDF

"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.

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Publication information
Department/Agency Bank of Canada.
Title A look inside the box : combining aggregate and marginal distributions to identify joint distributions / by Marie-Hélène Felt.
Variant title Combining aggregate and marginal distributions to identify joint distributions
Series title Bank of Canada staff working paper, 1701-9397 ; 2018-29
Publication type Series - View Master Record
Language [English]
Format Electronic
Electronic document
Note(s) "July 2018."
Includes bibliographical references (p. 27-29).
Includes abstract in French.
Publishing information [Ottawa] : Bank of Canada, 2018.
Author / Contributor Felt, Marie-Hélène.
Description iii, 49 p. : col. charts.
Catalogue number
  • FB3-5/2018-29E-PDF
Subject terms Cash transactions
Econometric models
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