Using ‘working’ assumptions on conditional third and fourth moments of errors, we propose a method of moments estimator that can have improved efficiency over the popular Gaussian quasi‐maximum likelihood estimator (GQMLE). Higher‐order moment assumptions are not needed for consistency...

Here we present an expository, general analysis of valid post-selection or post-regularization inference about a low-dimensional target parameter in the presence of a very high-dimensional nuisance parameter which is estimated using selection or regularization methods. Our analysis provides a...

Here we present an expository, general analysis of valid post-selection or post-regularization inference about a low-dimensional target parameter in the presence of a very high-dimensional nuisance parameter which is estimated using selection or regularization methods. Our analysis provides a...

In this paper, using an IS-LM model with reserve market, we examine weather the operating procedure actually adopted by many central banks in the world, i.e. targeting directly short run interest rates and hence indirectly market interest rates, is more efficient in stabilizing output than a...

In this paper, using an IS-LM model with reserve market, we examine weather the operating procedure actually adopted by many central banks in the world, i.e. targeting directly short run interest rates and hence indirectly market interest rates, is more efficient in stabilizing output than a...

In this paper, using an IS-LM model with reserve market, we examine weather the operating procedure actually adopted by many central banks in the world, i.e. targeting directly short run interest rates and hence indirectly market interest rates, is more efficient in stabilizing output than a...

This article surveys estimation in stationary time series models using the approach of optimal instrumentation. We review tools that allow construction and implementation of optimal instrumental variables estimators in various circumstances { in single- and multiperiod models, in the absence and...

We propose and evaluate a technique for instrumental variables estimation of linear models with conditional heteroskedasticity. The technique uses approximating parametric models for the projection of right-hand side variables onto the instrument space, and for conditional heteroskedasticity and...