Showing 1 - 9 of 9
Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data. While more data are better than less, diminishing returns suggest that we may not need terabytes of data to estimate a parameter or test a hypothesis. But which...
Persistent link: https://www.econbiz.de/10012216998
We study the asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games. We consider K-stage policy iteration (PI) estimators, where K denotes the number of policy iterations employed in the estimation. This class nests several estimators...
Persistent link: https://www.econbiz.de/10011797607
A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and autocorrelation in the data by using a nonparametric estimator of the optimal weighting matrix. This paper addresses the issue of choosing the corresponding smoothing parameter (or...
Persistent link: https://www.econbiz.de/10010336485
This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions …
Persistent link: https://www.econbiz.de/10011517194
This paper introduces measures for how each moment contributes to the precision of the parameter estimates in GMM …
Persistent link: https://www.econbiz.de/10012025702
function and that for generalised method of moments (GMM) with weight matrix equal to the inverse of the efficient GMM metric … for GMM for the non-diagonal GMM weight matrix setting. The paper demonstrates that GMM in such circumstances delivers a … GMM with a non-diagonal weight matrix and GEL. A simulation study examines the efficacy of the non-diagonal GMM and GEL …
Persistent link: https://www.econbiz.de/10011812336
This paper introduces measures for how each moment contributes to the precision of parameter estimates in GMM settings …
Persistent link: https://www.econbiz.de/10012152501
We give a general construction of debiased/locally robust/orthogonal (LR) moment functions for GMM, where the …
Persistent link: https://www.econbiz.de/10011824067
The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice. However, the estimator is severely biased when the data's time series dimension T is long due to the large degree of overidentification. We show that weak dependence along the panel's time...
Persistent link: https://www.econbiz.de/10014520814