A curse of dimensionality arises when using the Continuum-GMM procedure to estimate large dimensional models. Two solutions are proposed, both of which convert the high di- mensional model into a continuum of reduced information sets. Under certain regularity conditions, each reduced information...

The method of moments proposed by Carrasco and Florens (2000) permits to fully exploit the information contained in the characteristic function and yields an estimator which is asymptotically as efficient as the maximum likelihood estimator. However, this estimation procedure depends on a...

A  curse of dimensionality  arises when using the Continuum-GMM procedure to estimate large dimensional models. Two solutions are proposed, both of which convert the high dimensional model into a continuum of reduced information sets. Under certain regularity conditions, each reduced...