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GMM versus GQL inferences in semiparametric linear dynamic mixed models. (English) Zbl 1235.62137

Summary: Linear dynamic mixed models are commonly used for continuous panel data analysis in economic statistics. There exists generalized method of moments (GMM) and generalized quasi-likelihood (GQL) inferences for binary and count panel data models, the GQL estimation approach being more efficient than the GMM approach. The GMM and GQL estimating equations for linear dynamic mixed models can not, however, be obtained from the respective estimating equations under the nonlinear models for binary and count data. We develop the GMM and GQL estimation approaches for linear dynamic mixed models and demonstrate that the GQL approach is more efficient than the GMM approach, also under such linear models. This makes the GQL approach uniformly more efficient than the GMM approach in estimating the parameters of both linear and nonlinear dynamic mixed models.

MSC:

62P20 Applications of statistics to economics
62G05 Nonparametric estimation
62H12 Estimation in multivariate analysis
65C60 Computational problems in statistics (MSC2010)
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References:

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