On Computing Maximum-Likelihood Estimates of the Unbalanced Two-Way Random-Effects Model

Phillips, Robert F.

doi:10.1080/03610918.2011.626546

Communications in Statistics - Simulation and Computation

2012

DOI: 10.1080/03610918.2011.626546

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On Computing Maximum-Likelihood Estimates of the Unbalanced Two-Way Random-Effects Model

Robert F. Phillips

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“…, z ′ N ) ′ are treated as fixed.4 Liu and Rubin (1994) describe the properties of the ECME algorithm. For applications of it to panel data seePhillips (2004Phillips ( , 2012.…”

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confidence: 99%

Quasi maximum likelihood estimation of dynamic panel data models

Phillips

2017

Communications in Statistics - Theory and Methods

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This paper establishes the almost sure convergence and asymptotic normality of levels and differenced quasi maximum-likelihood (QML) estimators of dynamic panel data models. The QML estimators are robust with respect to initial conditions, conditional and time-series heteroskedasticity, and misspecification of the log-likelihood. The paper also provides an ECME algorithm for calculating levels QML estimates. Finally, it uses Monte Carlo experiments to compare the finite sample performance of levels and differenced QML estimators, the differenced GMM estimator, and the system GMM estimator. In these experiments the QML estimators usually have smaller -typically substantially smaller -bias and root mean squared errors than the panel data GMM estimators.

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“…, z ′ N ) ′ are treated as fixed.4 Liu and Rubin (1994) describe the properties of the ECME algorithm. For applications of it to panel data seePhillips (2004Phillips ( , 2012.…”

mentioning

confidence: 99%

Quasi maximum likelihood estimation of dynamic panel data models

Phillips

2017

Communications in Statistics - Theory and Methods

Self Cite

View full text Add to dashboard Cite

show abstract

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On Computing Maximum-Likelihood Estimates of the Unbalanced Two-Way Random-Effects Model

Cited by 1 publication

References 9 publications

Quasi maximum likelihood estimation of dynamic panel data models

Quasi maximum likelihood estimation of dynamic panel data models

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