We examine a simple estimator for the multivariate moving average model based on vector autoregressive approximation. In finite samples the estimator has a bias which is low where roots of the determinantal equation are well away from the unit circle, and more substantial where one or more roots...

A model to investigate the relationship between one variable and another usually requires controls for numerous other effects which are not constant across the sample; where the model omits some elements of the true process, estimates of parameters of interest will typically be inconsistent. Here...

Results on nonparametric kernel estimators of density differ according to the assumed degree of density smoothness; it is often assumed that the density function is at least twice differentiable. However, there are cases where non-smooth density functions may be of interest. We provide...

Identification in errors-in-variables regression models was recently extended to wide models classes by S. Schennach (Econometrica, 2007) (S) via use of generalized functions. In this paper the problems of non- and semi- parametric identification in such models are re-examined. Nonparametric...

Many asymptotic results for kernel-based estimators were established under some smoothness assumption on density. For cases where smoothness assumptions that are used to derive unbiasedness or asymptotic rate may not hold we propose a combined estimator that could lead to the best available rate...

Many important models, such as index models widely used in limited dependent variables, partial linear models and nonparametric demand studies utilize estimation of average derivatives (sometimes weighted) of the conditional mean function. Asymptotic results in the literature focus on situations...

The new distribution class, Asymmetric Exponential Power Distribution (AEPD), proposed in this paper generalizes the class of Skewed Exponential Power Distributions (SEPD) in a way that in addition to skewness introduces di¤erent decay rates of density in the left and right tails. Our...

The difference in yields between long-term and short-term securities has been used both as a business cycle leading indicator and as an indicator of the current impact of monetary policy. This paper tests for an asymmetry, in the form of a threshold effect, such that the impact of the yield...

For quantities that are approximately stationary, the information content of statistical forecasts tends to decline as the forecast horizon increases, and there exists a maximum horizon beyond which forecasts cannot provide discernibly more information about the variable than is present in the...

We consider the problem of determining the horizon beyond which forecasts from time series models of stationary processes add nothing to the forecast implicit in the conditional mean. We refer to this as the content horizon for forecasts, and define a forecast content function at horizons s =...