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Estimation of a two‐equation panel model with mixed continuous and ordered categorical outcomes and missing data

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  • Martin Spiess

Abstract

Summary. The paper proposes an estimation approach for panel models with mixed continuous and ordered categorical outcomes based on generalized estimating equations for the mean and pseudoscore equations for the covariance parameters. A numerical study suggests that efficiency can be gained in the mean parameter estimators by using individual covariance matrices in the estimating equations for the mean parameters. The approach is applied to estimate the returns to occupational qualification in terms of income and perceived job security in a 9‐year period based on the German Socio‐Economic Panel. To compensate for missing data, a combined multiple imputation–weighting approach is adopted.

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  • Martin Spiess, 2006. "Estimation of a two‐equation panel model with mixed continuous and ordered categorical outcomes and missing data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 525-538, August.
    • Handle: RePEc:bla:jorssc:v:55:y:2006:i:4:p:525-538
    DOI: 10.1111/j.1467-9876.2006.00551.x
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    Cited by:

    1. Zhang, Xiao & Boscardin, W. John & Belin, Thomas R. & Wan, Xiaohai & He, Yulei & Zhang, Kui, 2015. "A Bayesian method for analyzing combinations of continuous, ordinal, and nominal categorical data with missing values," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 43-58.
    2. Martin Spiess & Pascal Jordan & Mike Wendt, 2019. "Simplified Estimation and Testing in Unbalanced Repeated Measures Designs," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 212-235, March.

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