Statistical Matching for Combining Time-Use Surveys with Consumer Expenditure Surveys: An Evaluation on Real Data

Anil Alpman (), François Gardes () and Noël Thiombiano ()
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Anil Alpman: Centre d'Economie de la Sorbonne - Paris School of Economics, https://centredeconomiesorbonne.univ-paris1.fr
François Gardes: Centre d'Economie de la Sorbonne - Paris School of Economics, https://centredeconomiesorbonne.univ-paris1.fr
Noël Thiombiano: Université Ouaga II - Cèdres

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: Performing a statistical match to combine two surveys made over the same population by traditional methods is shown to give biased estimates and variance of the imputed values. A method proposed by Rubin (1986) allows imputing an unobserved variable using observations in another dataset by taking into account the partial correlation between the variables that are jointly unobserved for any unit. We use a dataset where households report their expenditures and time-uses to show that fusioning expenditure and time-use surveys by Rubin's procedure allows to recover the true distribution of the missing variables and to yield minimally biased estimates

Keywords: Data combination; Data fusion; Missing data; Statistical matching; Time-Use (search for similar items in EconPapers)
JEL-codes: C10 D13 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2017-05
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:17024

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