Showing 71 - 80 of 59,084
This paper proposes a GMM shrinkage method to efficiently estimate the unknown parameters identified by some moment restrictions, when there is another set of possibly misspecified moment conditions. We show that our method enjoys oracle-like properties, i.e. it consistently selects the correct...
Persistent link: https://www.econbiz.de/10014040004
We propose new generalized method of moments (GMM) estimators for the number of latent factors in linear factor models. The estimators are appropriate for data with a large (small) number of cross-sectional observations and a small (large) number of time series observations. The estimation...
Persistent link: https://www.econbiz.de/10014050472
The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error....
Persistent link: https://www.econbiz.de/10014051957
We consider a spatial econometric model containing a spatial lag in the dependent variable and the disturbance term with an unknown form of heteroskedasticity in innovations. We first prove that the maximum likelihood (ML) estimator for spatial autoregressive models is generally inconsistent...
Persistent link: https://www.econbiz.de/10014160295
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...
Persistent link: https://www.econbiz.de/10014164441
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....
Persistent link: https://www.econbiz.de/10014164952
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10014170199
The transition from economic theory to a testable form invariably involves the use of certain "simplifying assumptions". However, if these are not valid, misspecified model result. This paper considers consistent estimation of the dynamic panel model which often forms the basis of testable...
Persistent link: https://www.econbiz.de/10014139689
In this paper, we introduce the one-step generalized method of moments (GMM) estimation methods considered in Lee (2007a) and Liu, Lee, and Bollinger (2010) to spatial models that impose a spatial moving average process for the disturbance term. First, we determine the set of best linear and...
Persistent link: https://www.econbiz.de/10014145971
The finite sample behaviour is analysed of particular least squares (LS) and method of moments (MM) estimators in panel data models with individual effects and both a lagged dependent variable regressor and another explanatory variable which may be affected by lagged feedbacks from the dependent...
Persistent link: https://www.econbiz.de/10014104029