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

Anil Alpman (), François Gardes () and Noel Thiombiano ()
Additional contact information
Anil Alpman: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
François Gardes: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Noel Thiombiano: CEDRES - Université de Ouaga II

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

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; Appariement statistique; Fusion de données; Utilisation du temps (search for similar items in EconPapers)
Date: 2017-05
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01529699v1
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Published in 2017

Downloads: (external link)
https://shs.hal.science/halshs-01529699v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-01529699

Access Statistics for this paper

More papers in Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
Bibliographic data for series maintained by CCSD ().