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Full-Text Articles in Social and Behavioral Sciences
Consistent Model And Moment Selection Criteria For Gmm Estimation With Application To Dynamic Panel Data Models, Donald W.K. Andrews, Biao Lu
Consistent Model And Moment Selection Criteria For Gmm Estimation With Application To Dynamic Panel Data Models, Donald W.K. Andrews, Biao Lu
Cowles Foundation Discussion Papers
This paper develops consistent model and moment selection criteria for GMM estimation. The criteria select the correct model specification and all correct moment conditions asymptotically. The selection criteria resemble the widely used likelihood-based selection criteria BIC, HQIC, and AIC. (The latter is not consistent.) The GMM selection criteria are based on the J statistic for testing over-identifying restrictions. Bonus terms reward the use of fewer parameters for a given number of moment conditions and the use of more moment conditions for a given number of parameters. The paper applies the model and moment selection criteria to dynamic panel data models …
Higher-Order Improvements Of A Computationally Attractive K-Step Bootstrap For Extremum Estimators, Donald W.K. Andrews
Higher-Order Improvements Of A Computationally Attractive K-Step Bootstrap For Extremum Estimators, Donald W.K. Andrews
Cowles Foundation Discussion Papers
This paper establishes the higher-order equivalence of the k -step bootstrap, introduced recently by Davidson and MacKinnon (1999a), and the standard bootstrap. The k -step bootstrap is a very attractive alternative computationally to the standard bootstrap for statistics based on nonlinear extremum estimators, such as generalized method of moment and maximum likelihood estimators. The paper also extends results of Hall and Horowitz (1996) to provide new results regarding the higher-order improvements of the standard bootstrap and the k -step bootstrap for extremum estimators (compared to procedures based on first-order asymptotics). The results of the paper apply to Newton-Raphson (NR), default …
Higher-Order Improvements Of A Computationally Attractive K-Step Bootstrap For Extremum Estimators, Donald W.K. Andrews
Higher-Order Improvements Of A Computationally Attractive K-Step Bootstrap For Extremum Estimators, Donald W.K. Andrews
Cowles Foundation Discussion Papers
This paper establishes the higher-order equivalence of the k -step bootstrap, introduced recently by Davidson and MacKinnon (1999a), and the standard bootstrap. The k -step bootstrap is a very attractive alternative computationally to the standard bootstrap for statistics based on nonlinear extremum estimators, such as generalized method of moment and maximum likelihood estimators. The paper also extends results of Hall and Horowitz (1996) to provide new results regarding the higher-order improvements of the standard bootstrap and the k -step bootstrap for extremum estimators (compared to procedures based on first-order asymptotics). The results of the paper apply to Newton-Raphson (NR), default …