In this paper we propose a method for determining the number of regimes in threshold autoregressive models using smooth transition autoregression as a tool. As the smooth transition model is just an approximation to the threshold autoregressive one, no asymptotic properties are claimed for the...

In this paper, we propose a sequential method for determining the number of regimes in threshold autoregressive models. The proposed method relies on the superconsistency of sequential threshold estimates and uses general linearity tests to determine the number of thresholds. A simulation study...

Changes in the seasonal patterns of macroeconomic time series may be due to the effects of business cycle fluctuations or to technological and institutional change or both. We examine the relative importance of these two sources of change in seasonality for quarterly industrial production series...

In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests...

In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in a sample space. We study the performance of our tests by...

Changes in the seasonal patterns of macroeconomic time series may be due to the effects of business cycle fluctuations or to technological and institutional change or both. We examine the relative importance of these two sources of change in seasonality for quarterly industrial production series...

In this paper we propose a sequential method for determining the number of breaks in piecewise linear structural break models. An advantage of the method is that it is based on standard statistical inference. Tests available for testing linearity against switching regression type nonlinearity...

The asymmetric power ARCH model is a recent addition to time series models that may be used for predicting volatility. Its performance is compared with that of standard models of conditional heteroskedasticity such as GARCH. This has previously been done empirically. In this paper the same issue...

In this paper we propose a Lagrange multiplier test for volatility interactions among markets or assets. The null hypothesis is the Constant Conditional Correlation GARCH model in which volatility of an asset is described only through lagged squared innovations and volatility of its own. The...

Starting from a linear error correction model the stability and linearity of a German M1 moneyt demand function are investigated, applying smooth transition regression techniques. Using seasonally unadjusted data from 1961 (1) to 1990 (2) it is found that the money demand equation is both linear...