Pena and Box [Journal of Americal Statistical Association (1987) Vol. 82, PP. 836-843] proposed a factor model which aimed to explore the possibility of using lower-dimensional series to represent or explain an observed higher-dimensional multiple time series. However, there were no statistics...

In recent years it has become apparent that many of the classical testing procedures used to select amongst alternative economic theories and economic models are not realistic. In particular, researchers have become more aware of the fact that parameter estimation error and data dependence play...

We analyse the case where a unit-root test is based on a Dickey-Fuller regression the only deterministic term of which is a fixed intercept. Suppose, however, as could well be the case, that the actual data-generating process includes a broken linear trend. It is shown theoretically, and...

This paper proposes a novel method to select an experimental design for interpolation in random simulation. (Though the paper focuses on Kriging, this method may also apply to other types of metamodels such as linear regression models). Assuming that simulation requires much computer time, it is...

This paper is concerned with issues of model specification, identification, and estimation in exchange rate models with unobservable fundamentals. We show that the model estimated by Gardeazabal, Regulez and Vazquez (International Economic Review, 1997) is not identified and demonstrate how to...

This paper proposes a novel method to select an experimental design for interpolation in simulation. Though the paper focuses on Kriging in deterministic simulation, the method also applies to other types of metamodels (besides Kriging), and to stochastic simulation. The paper focuses on...

Many improvements have been proposed for the basic gravity model specification, most of which are confirmed by standard statistical tests due to the large number of observations often used to estimate such models. We use Monte Carlo experiments to examine situations in which features of models...

Quantile regression (QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fit a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even...

A mixed, geographically weighted regression (GWR) model is useful in the situation where certain explanatory variables influencing the response are global while others are local. Undoubtedly, how to identify these two types of the explanatory variables is essential for building such a model....

Monte Carlo evidence has shown that simple, misspecified discrete choice models for referendum contingent valuation data can lead to good estimates of mean willingness to pay (WTP). Empirical studies have found that estimates of mean WTP derived from simple parametric models often differ little...