IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v16y2016i3p717-739.html
   My bibliography  Save this article

Implementing Rubin's alternative multiple-imputation method for statistical matching in Stata

Author

Listed:
  • Anil Alpman

    (Paris School of Economics)

Abstract

This article introduces two new commands, smpc and smmatch, that implement the statistical matching procedure proposed by Rubin (1986, Journal of Business and Economic Statistics 4: 87–94). The purpose of statistical matching in Rubin’s procedure is to generate a single dataset from various datasets, where each dataset contains a specific variable of interest and all contain some variables in common. For two variables of interest that are not observed jointly for any unit, smpc generates the predicted values of each as a function of the other vari- able of interest and a set of control variables by assuming a partial correlation value (defined by the user) between the two variables of interest (other statistical matching procedures assume that they are conditionally independent given the control variables). The smmatch command, on the other hand, matches observations of different datasets according to their predicted values (using a minimum distance criterion) conditional on a set of control variables, and it imputes the observed value of the match for the missing. Copyright 2016 by StataCorp LP.

Suggested Citation

  • Anil Alpman, 2016. "Implementing Rubin's alternative multiple-imputation method for statistical matching in Stata," Stata Journal, StataCorp LP, vol. 16(3), pages 717-739, September.
  • Handle: RePEc:tsj:stataj:v:16:y:2016:i:3:p:717-739
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj16-3/st0452/
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0452
    File Function: link to article purchase
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Rubin, Donald B, 1986. "Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 87-94, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. François Gardes, 2021. "On the value of time and human life," Documents de travail du Centre d'Economie de la Sorbonne 21023, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Okay Gunes, 2017. "Analysis of Households' Decision Using Full Demand Elasticity Estimates: an Estimation on Turkish Data," Post-Print halshs-01491970, HAL.
    3. François Gardes, 2021. "Endogenous Prices in a Riemannian Geometry Framework," Post-Print halshs-03325414, HAL.
    4. 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.
    5. 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.
    6. François Gardes, 2018. "On the value of time and human life," Post-Print halshs-01903596, HAL.
    7. 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.
    8. François Gardes, 2021. "An Austrian Trade Cycle model with an Endogenous Value of Time," Post-Print halshs-03325379, HAL.
    9. François Gardes, 2021. "On the value of time and human life," Post-Print halshs-03325332, HAL.
    10. Armagan Tuna Aktuna-Gunes & Okay Gunes, 2017. "Measuring the Relative Domestic Production Scarcity of Time Spent in Domestic Activities for Turkey," Documents de travail du Centre d'Economie de la Sorbonne 17018, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    11. François Gardes, 2021. "An Austrian Trade Cycle model with an Endogenous Value of Time," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03325379, HAL.
    12. Anil Alpman & François Gardes, 2016. "Welfare Analysis of the Allocation of Time During the Great Recession," Post-Print halshs-01159507, HAL.
    13. Di Cosmo, Valeria & Tiezzi, Silvia, 2023. "Let them Eat Cake? The Net Consumer Welfare Impact of Sin Taxes," MPRA Paper 116214, University Library of Munich, Germany.
    14. François Gardes, 2021. "Endogenous Prices in a Riemannian Geometry Framework," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03325414, HAL.
    15. Armagan Tuna Aktuna-Gunes & Okay Gunes, 2017. "Measuring the Relative Domestic Production Scarcity of Time Spent in Domestic Activities for Turkey," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01491982, HAL.
    16. François Gardes, 2021. "An Austrian Trade Cycle model with an Endogenous Value of Time," Documents de travail du Centre d'Economie de la Sorbonne 21025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. François Gardes, 2018. "On the value of time and human life," Documents de travail du Centre d'Economie de la Sorbonne 18028, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    18. Anil Alpman & François Gardes, 2016. "Welfare Analysis of the Allocation of Time During the Great Recession," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01159507, HAL.
    19. 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.
    20. 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.
    21. François Gardes, 2021. "On the value of time and human life," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03325332, HAL.
    22. Leif Jacobs & Lara Quack & Mario Mechtel, 2021. "Distributional Effects of Carbon Pricing by Transport Fuel Taxation," Working Paper Series in Economics 405, University of Lüneburg, Institute of Economics.
    23. François Gardes, 2018. "On the value of time and human life," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01903596, HAL.
    24. 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.
    25. Anil Alpman & François Gardes, 2015. "Welfare Analysis of the Allocation of Time During the Great Recession," Documents de travail du Centre d'Economie de la Sorbonne 15012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Mar 2016.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. François Gardes, 2021. "On the value of time and human life," Documents de travail du Centre d'Economie de la Sorbonne 21023, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. 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.
    3. Joost Ginkel & Pieter Kroonenberg, 2014. "Using Generalized Procrustes Analysis for Multiple Imputation in Principal Component Analysis," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 242-269, July.
    4. Peter ven de Ven & Anne Harrison & Barbara Fraumeni & Dennis Fixler & David Johnson & Andrew Craig & Kevin Furlong, 2017. "A Consistent Data Series to Evaluate Growth and Inequality in the National Accounts Note: The views expressed in this research, including those related to statistical, methodological, technical, or op," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63, pages 437-459, December.
    5. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    6. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.
    7. Michael S. Rendall & Bonnie Ghosh-Dastidar & Margaret M. 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.
    8. Joost R. Ginkel, 2020. "Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 185-205, March.
    9. Arif Mamun & Ankita Patnaik & Michael Levere & Gina Livermore & Todd Honeycutt & Jacqueline Kauff & Karen Katz & AnnaMaria McCutcheon & Joseph Mastrianni & Brittney Gionfriddo, "undated". "Promoting Readiness of Minors in Supplemental Security Income (PROMISE): Technical Appendix to the Interim Services and Impact Report," Mathematica Policy Research Reports 24c37444a21d4046abb21395a, Mathematica Policy Research.
    10. Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," JRFM, MDPI, vol. 13(11), pages 1-24, November.
    11. Anil Alpman, 2015. "Implementing Rubin's Alternative Multiple Imputation Method for Statistical Matching in Stata," Post-Print hal-01159191, HAL.
    12. Brownstone, David, 1997. "Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition," University of California Transportation Center, Working Papers qt2zd6w6hh, University of California Transportation Center.
    13. Lamarche, Pierre, 2017. "Estimating consumption in the HFCS: Experimental results on the first wave of the HFCS," Statistics Paper Series 22, European Central Bank.
    14. Keane, Michael & Stavrunova, Olena, 2016. "Adverse selection, moral hazard and the demand for Medigap insurance," Journal of Econometrics, Elsevier, vol. 190(1), pages 62-78.
    15. Gina Yannitell Reinhardt, 2009. "Matching Donors and Nonprofits," Journal of Theoretical Politics, , vol. 21(3), pages 283-309, July.
    16. Westermeier, Christian & Grabka, Markus M., 2016. "Longitudinal Wealth Data and Multiple Imputation: An Evaluation Study," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(3), pages 237-252.
    17. Lambert, Claudia & Larkou, Chloe & Pancaro, Cosimo & Pellicani, Antonella & Sintonen, Meri, 2024. "Digital euro demand: design, individuals’ payment preferences and socioeconomic factors," Working Paper Series 2980, European Central Bank.
    18. François Gardes, 2018. "On the value of time and human life," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01903596, HAL.
    19. Marcello D’Orazio, 2015. "Integration and imputation of survey data in R: the StatMatch package," Romanian Statistical Review, Romanian Statistical Review, vol. 63(2), pages 57-68, June.
    20. Mr. Michael Weber & Ms. Michaela Denk, 2011. "Avoid Filling Swiss Cheese with Whipped Cream: Imputation Techniques and Evaluation Procedures for Cross-Country Time Series," IMF Working Papers 2011/151, International Monetary Fund.

    More about this item

    Keywords

    smmatch; smpc; data combination; missing data; multiple imputation; statistical matching;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:16:y:2016:i:3:p:717-739. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.