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Fusion of data sets in multivariate linear regression with errors-in-variables

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Abstract

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regression models with errors--in--variables, in the case where various data sets are merged into a single analysis and the observable variables deviate possibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possible non--normality of the data, normal--theory methods yield correct inferences for the parameters of interest and for the goodness--of--fit test. The theory described encompasses both the functional and structural model cases, and can be implemented using standard software for structural equations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

Suggested Citation

  • Albert Satorra, 1996. "Fusion of data sets in multivariate linear regression with errors-in-variables," Economics Working Papers 183, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:183
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    1. Sik-Yum Lee & Kwok-Leung Tsui, 1982. "Covariance structure analysis in several populations," Psychometrika, Springer;The Psychometric Society, vol. 47(3), pages 297-308, September.
    2. Dahm, P. Fred & Fuller, Wayne A., 1986. "Generalized least squares estimation of the functional multivariate linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 19(1), pages 132-141, June.
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    More about this item

    Keywords

    Asymptotic robustness; multivariate regression; asymptotic efficiency; normal theory methods; multi--samples; errors--in--variables;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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