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A Note on Rubin's Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations

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  • Moriarity, Chris
  • Scheuren, Fritz

Abstract

Statistical matching has been used for more than 30 years to combine information contained in two sample survey files. Rubin (1986) outlined an imputation procedure for statistical matching that is different from almost all other work on this topic. Here we evaluate and extend Rubin's procedure.

Suggested Citation

  • Moriarity, Chris & Scheuren, Fritz, 2003. "A Note on Rubin's Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 65-73, January.
  • Handle: RePEc:bes:jnlbes:v:21:y:2003:i:1:p:65-73
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    Citations

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    Cited by:

    1. Clinton P. McCully, 2013. "Integration of Micro and Macro Data on Consumer Income and Expenditures," BEA Working Papers 0101, Bureau of Economic Analysis.
    2. Ahfock, Daniel & Pyne, Saumyadipta & Lee, Sharon X. & McLachlan, Geoffrey J., 2016. "Partial identification in the statistical matching problem," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 79-90.
    3. Tarr, David G., 2013. "Putting Services and Foreign Direct Investment with Endogenous Productivity Effects in Computable General Equilibrium Models," Handbook of Computable General Equilibrium Modeling, Elsevier.
    4. Kiesl, Hans & Rässler, Susanne, 2006. "How valid can data fusion be?," IAB Discussion Paper 200615, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Azizur Rahman & Ann Harding & Robert Tanton & Shuangzhe Liu, 2010. "Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation," International Journal of Microsimulation, International Microsimulation Association, vol. 3(2), pages 3-22.
    6. Okay Gunes, 2017. "Analysis of Households' Decision Using Full Demand Elasticity Estimates: an Estimation on Turkish Data," Documents de travail du Centre d'Economie de la Sorbonne 17017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    7. Thomas F. Rutherford & David G. Tarr, 2014. "Poverty effects of Russia's WTO accession: Modeling “real” households with endogenous productivity effects," World Scientific Book Chapters,in: APPLIED TRADE POLICY MODELING IN 16 COUNTRIES Insights and Impacts from World Bank CGE Based Projects, chapter 12, pages 287-306 World Scientific Publishing Co. Pte. Ltd..
    8. Rutherford, Thomas & Tarr, David & Shepotylo, Oleksandr, 2005. "Poverty effects of Russia's WTO accession : modeling"real"households and endogenous productivity effects," Policy Research Working Paper Series 3473, The World Bank.
    9. Michael S. Rendall & Bonnie Ghosh-Dastidar & Margaret Weden & Zafar Nazarov, 2011. "Multiple Imputation for Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys," Working Papers WR-887-1, RAND Corporation.
    10. Okay Gunes, 2017. "Analysis of Households' Decision Using Full Demand Elasticity Estimates: an Estimation on Turkish Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01491970, HAL.

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