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We propose a new sequential procedure for estimating multivariate distributions in cases when conventional maximum likelihood has too many parameters and is therefore inaccurate or non-operational. The procedure constructs a multivariate distribution and its pseudo-likelihood sequentially, in...
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Optimal GMM is known to dominate Gaussian QMLE in terms of asymptotic efficiency [Chamberlain, G., 1984. Panel data. In: Griliches, Z., Intriligator, M.D. (Eds.), Handbook of Econometrics, vol. II, pp. 1248-1313]. I derive a new condition under which QMLE is as efficient as GMM for a general...
Persistent link: https://www.econbiz.de/10005296315
For covariance structure models, the QMLE second-order bias is derived and compared with EL and GMM. Surprisingly, QMLE and EL have the same second-order bias if QMLE and GMM(EL) are equally first-order efficient. Other examples favoring QMLE are given.
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When there are more moment conditions than observations, the usual GMM weighting matrix is singular. We show that using the generalized inverse is not a good idea. With continuous updating, the criterion function equals one for every parameter value.
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