Kernels are typically justified as a smoothing device in nonparametric analysis. We provide alternative interpretations which could lead to the use of asymmetric kernels. We thus derive the class of optimal asymmetric kernels, and analyse its main properties. We illustrate numerically its...

Vector autoregressions (VARs) are important tools in time series analysis. However, relatively little is known about the nite-sample behaviour of parameter estimators. We address this issue, by investigating ordinary least squares (OLS) estimators given a data generating process that is a purely...

A frequently used test for unspeciÞed nonlinear omissions is the parametric RESET, which is based upon a Þnite polynomial. We follow Abadir (1999), who suggests that the generalized hypergeometric function may provide a more ßexible proxy for the omission; and propose a new approach,...

Vector autoregressions (VARs) are important tools in time series analysis. However, relatively little is known about the finite-sample behaviour of parameter estimators. We address this issue, by investigating ordinary least squares (OLS) estimators given a data generating process that is a...

Vector autoregressions (VARs) are an important tool in time series analysis. However, relatively little is known about the finite-sample behaviour of parameter estimators. We address this issue, by investigating ordinary least squares (OLS) estimators given a data generating process that is a...

Python is a powerful high level open source programming language, that is available for multiple platforms. It supports object oriented programming, and has recently become a serious alternative to low level compiled languages such as C. It is easy to learn and use, and is recognized for very...