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

Author

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  • 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 des Ponts ParisTech - 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 des Ponts ParisTech - 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)

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.

Suggested Citation

  • Anil Alpman & François Gardes & Noel Thiombiano, 2017. "Statistical Matching for Combining Time-Use Surveys with Consumer Expenditure Surveys: An Evaluation on Real Data," Post-Print halshs-01529699, HAL.
    • Handle: RePEc:hal:journl:halshs-01529699
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01529699
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    Cited by:

    1. François Gardes, 2021. "Endogenous Prices in a Riemannian Geometry Framework," Post-Print halshs-03325414, HAL.
    2. François Gardes, 2021. "A Solution to the Estimation of an Enlarged GDP Including Domestic Production: An Estimation on Micro Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03325362, HAL.
    3. François Gardes, 2021. "A Solution to the Estimation of an Enlarged GDP Including Domestic Production: An Estimation on Micro Data," Post-Print halshs-03325362, HAL.
    4. François Gardes, 2021. "A Solution to the estimation of an Enlarged GDP Including Domestic Production: An Estimation on Micro Data," Documents de travail du Centre d'Economie de la Sorbonne 21024, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    5. François Gardes, 2021. "Endogenous Prices in a Riemannian Geometry Framework," Documents de travail du Centre d'Economie de la Sorbonne 21026, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    6. François Gardes, 2021. "Endogenous Prices in a Riemannian Geometry Framework," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03325414, HAL.

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