This paper investigates the small sample size and power properties of the likelihood ratio test in the seasonal error correction model. Two specifications of the model at the annual frequency are analyzed. One is more restricted (RS), designed for the particular case of 'synchronous...

In this paper we propose an alternative method for investigating the sources behind the behavior of real wages and unemployment. The statistical model we study is a certain structural error correction model, a so called common trends model, which has become popular in the empirical...

In Bayesian analysis of VAR-models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior distributions provide better forecasts and are preferable from a theoretical standpoint. This paper considers the numerical procedures...

In this paper I present two new Lagrange multiplier test statistics designed for testing the null of GARCH (1,1), against the alternative of asymmetric GARCH. For one test the alternative is the generalized QARCH (1,1) model of Sentana [1995], and for the other the alternative is the logistic...

When testing for cointegration, the asymptotic inference typically in use can be plagued by size distortion due to an inadequate first order approximation. Hence, for practical purposes the inference can be completely misleading and result in false conclusions regarding the presence of long-run...

The detection of structural change and determination of lag lengths are long-standing issues in time series analysis. This paper demonstrates how these can be successfully married in a Bayesian analysis. By taking account of the inherent uncertainty about the lag length when deciding on the...

Since the true nature of a time series process is often unknown it is important to understand the effects of model choice. This paper examines how the choice between modelling stationary time series as ARMA or ARFIMA processes affects the accuracy of forecasts. This is done, for first-order...

In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...

The purpose of this paper is to use the bootstrap resampling technique to calculate confidence intervals for efficiency measures and Malmquist productivity indices. The efficiency and productivity measures are obtained from non-parametric linear programming models using primal production data....

In this paper we use Monte Carlo testing techniques for testing linearity against the smooth transition models. The Monte Carlo approach allows us to introduce a new test that differs from the tests existing in the literature in two respects. First, the test is exact in the sense that the...