Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/86393 
Authors: 
Year of Publication: 
2005
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 05-112/4
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
An attempt is made to set rules for a fair and fruitful competition between alternative inference methods based on their performance in simulation experiments. This leads to a list of eight methodologic aspirations. Against their background we criticize aspects of many simulation studies that have been used in the past to compare competing estimators for dynamic panel data models. To illustrate particular pitfalls some further Monte Carlo results are produced, obtained from a simulation design inspired by an analysis of the (non-)invariance properties of estimators and occasionally by available higher-order asymptotic results. We focus on the very specific case of alternative implementations of one and two step generalized method of moments (GMM) estimators in homoskedastic stable zero-mean panel AR(1) models with random individual specific effects. We compare a few implementations, including GMM sytem estimators with alternative weight matrices, and illu! strate that an impartial evaluation of the outcome of a Monte Carlo based contest requires evidence - both analytical and empirical - on the completeness, orthogonality and relevance of the simulation design.
Subjects: 
finite sample behavior
generalized method of moments
initial conditions
Monte Carlo methodology
orthogonal parametrizations
JEL: 
C13
C15
C23
Document Type: 
Working Paper

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