Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, we compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional...

We evaluate some aspects of the finite sample distribution of an instrumental variables estimator of a first order condition of the Holt et al. (1960) linear quadratic inventory model. We find that for some but not all empirically relevant data generating processes and sample sizes, asymptotic...

This paper considers regression-based tests for encompassing, when none of the models under consideration encompasses all the other models. For both in- and out-of-sample applications, I derive asymptotic distributions and propose feasible procedures to construct confidence intervals and test...

In many time series models, an infinite number of moments can be used for estimation in a large sample. I supply a technically undemanding proof of a condition for optimal instrumental variables use of such moments in a parametric model. I also illustrate application of the condition in...

A þT consistent estimator of a heteroskedasticity and autocorrelation consistent covariance matrix estimator is proposed and evaluated. The relevant applications are ones in which the regression disturbance follows a moving average process of known order. In a system of þ equations, this...

Econometric aspects of recent research on inventory models are surveyed. The discussion emphasizes issues relevant to instrumental variables estimation of a first order condition of the Holt et al. (1960) linear quadratic inventory model, including choice of instruments, covariance matrix...

This paper compares numerically the asymptotic distributions of parameter estimates and test statistics associated with two estimation techniques: (a)a limited information one, which uses instrumental variables to estimate a single equation (Hansen and Singleton (1982)), and (b)a full...

This paper shows how to generate the joint distribution of correlated random variables with specified marginal distributions. For cases where the marginal distributions are either normal or lognormal, it shows how to calculate analytically the correlation of the underlying normal distributions...

We consider using out-of-sample mean squared prediction errors (MSPEs) to evaluate the null that a given series follows a zero mean martingale difference against the alternative that it is linearly predictable. Under the null of no predictability, the population MSPE of the null "no change"...

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...