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Implementing Rubin's Alternative Multiple Imputation Method for Statistical Matching in Stata

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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)

Abstract

This paper introduces two new commands, smpred and smmatch, that implement the statistical matching procedure proposed by Rubin (1986). 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, smpred generates the predicted values of each as a function of the other variable of interest and a set of control variables by assuming a partial correlation value (defined by the user) between the two variables of interest (while current programs 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.

Suggested Citation

  • Anil Alpman, 2015. "Implementing Rubin's Alternative Multiple Imputation Method for Statistical Matching in Stata," Post-Print hal-01159191, HAL.
    • Handle: RePEc:hal:journl:hal-01159191
    Note: View the original document on HAL open archive server: https://hal.science/hal-01159191
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    References listed on IDEAS

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    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.
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    Cited by:

    1. Anil Alpman & François Gardes, 2016. "Welfare Analysis of the Allocation of Time During the Great Recession," Post-Print halshs-01159507, HAL.

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