In this paper we derive tests for parameter constancy when the data generating process is non-stationary against the hypothesis that the parameters of the model change smoothly over time. To obtain the asymptotic distributions of the tests we generalize many theoretical results, as well as new...

In this paper we introduce several test statistics of testing the null hypotheses of a random walk (with or without drift) against models that accommodate a smooth nonlinear shift in the level, the dynamic structure, and the trend. We derive analytical limiting distributions for all tests....

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...

This study addresses some modeling questions related to the possibility of structural change in models with non-stationary variables. Focusing on cointegration issues, some methodological aspects ere discussed, attempting to integrate coherently the several steps of the modelling strategy. These...

This paper analyzes the relationship between the properties of the prediction errors of a predictor that assumes an autoregressive unit root and its optimal detection. According with this relationship, new autoregressive unit root tests are proposed based on multi-step prediction errors. It is...

This paper investigates the impact of the Australia-New Zealand Closer Economic Relations (CER) Trade Agreement on bilateral trade of each member country by using historical time series data before and after the implementation of the CER. We determined the existence of endogenously determined...

This paper examines the major determinants of GDP growth in Iran using annual time series data spanning from 1960 to 2003. The Iranian economy has been subject to a multitude of structural changes and regime shifts during the sample period. Thus, time series properties of the data are first...

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily and weekly data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a new LM test that is resistant to additive outliers. The data...

This paper proposes a method for comparing and combining conditional quantile forecasts based on the principle of 'encompassing'. Our test for conditional quantile forecast encompassing (CQFE) is a test of superior predictive ability, constructed as a Wald-type test on the coefficients of an...