In this paper we examine the forecasting performance of five nonlinear GARCH(1,1) models. Four of these have recently been proposed in literature, while the fifth model is a new one. All five models allow for switching persistence of shocks, depending on the value and/or sign of recent returns....

This paper suveys several recently proposed regression-based methods that can be used to evaluate the usefulness of seasonally adjusted data, with specific focus on Census X-12 adjustment. These methods examine whether seasonality has indeed been removed and whether key properties (like a trend...

To enable answering the question in the title, we introduce a bivariate censored latent effects autoregression, and discuss representation, parameter estimation, diagnostics and inference. We show that this bivariate nonlinear model is very useful for examining common nonlinearity. We apply the...

One of the stylized facts in financial and international economics is that of increasing predictability of variables such as exchange rates and stock returns at longer horizons. This fact is based upon applications of long horizon regressions, from which the typical findings are that the point...

Generalized Method of Moments (GMM) Estimators are derived for Reduced Rank Regression Models, the Error Corrections Cointegration Model (ECCM) and the Incomplete Simultaneous Equations Model (INSEM). The GMM (2SLS) estimators of the cointegrating vector in the ECCM are shown to have normal...

The Interest in business cycle asymmetry has been steadily increasing over the last fifteen years. Most research has focused on the different behaviour of macro-economic variables during expansions and contractions, which by now is well documented. Recent evidence suggests that such a two-phase...

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