The problem of weak instruments is due to a very small concentration parameter. To boost the concentration parameter, we propose to increase the number of instruments to a large number or even up to a continuum. However, in finite samples, the inclusion of an excessive number of moments may be...

The use of many moment conditions improves the asymptotic efficiency of the instrumental variables estimators. However, in finite samples, the inclusion of an excessive number of moments increases the bias. To solve this problem, we propose regularized versions of the limited information maximum...

Estimation by maximumlikelihood is burdensome for models such that convolutions and stable distributions. Alternatively, we propose to use moments based on the empirical characteristic function. The objective of this paper is to propose an asymptotically efficient estimator.

This paper first provides some useful results on a generalized random coefficient autoregressive model and a Markov plus i.i.d. noise model. These results simultaneously imply strict staionarity, existence of higher-order moments, goemetric ergodicity and b-mixing with exponential decay rates,...

Testing frequently involves nuisance parameters wich are identified only under the alternative. This article proposes a class of test statistics wich asymptotic distributions are standard, namely chi-squares. We estimate the parameter vector using the generalized method of moments applied to...

Recent Studies on general equilibrium models with transaction costs show that the dynamics of the real exchange rate are necessarily nonlinear. Our contribution to the literature on nonlinear price adjustment mechanisms is threefold. First, we model the real exchange rates by a Multi-Regime...

The method of moments is based on a relation E[superscript theta[subscript 0]](h(X[subscript t, theta)) = 0, from which an estimator of theta is deduced. In many econometric models, the moment restrictions can not be evaluated numerically due to, for instance, the presence of a latent variable....

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...

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...