The method of instrumental variables (IV) and the generalized method of moments (GMM), and their applications to the estimation of errors-in-variables and simultaneous equations models in econometrics, require data on a sufficient number of instrumental variables that are both exogenous and...

We estabilsh the relationships between certain Bayesian and classical approaches to instrumental variables regression. We determine the form of priors that lead to posteriors for structural paameters that have similar properties as classical 2SLS and LIML and in doing so provide some new insight...

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply...

We consider the situation when there is a large number of series, $N$, each with $T$ observations, and each series has some predictive ability for the variable of interest, $y$. A methodology of growing interest is to first estimate common factors from the panel of data by the method of...

We examine the ability of the simple linear-quadratic model under rational expectations to explain dynamic behaviour of aggregate Canadian imports. In contrast to authors of previous studies who examine dynamic behaviour using the LQ model, we estimate the structural parameters using the Euler...

Accurate estimation of the dominant root of a stationary but persistent time series are required to determine the speed at which economic time series, such as real exchange rates or interest rates, adjust towards their mean values. In practice, accuracy is hampered by downward small- sample...

An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production functions.

El presente trabajo plantea un modelo estadístico flexible que captura paramétricamente la compleja condicionalidad y desvíos de normalidad que caracteriza a la estructura intertemporal de tasas de interés en la economía chilena entre los años 1992 y 2003. El modelo general consiste en una...

According to the Mixture of Distributions Hypothesis (MDH), returns volatility and trading volume are driven by a common news arrival variable. Consequently, these two variables should be correlated. This paper extends, and to some extent, globalises the concept of a common information arrival...