This note shows that a very simple model can generate returns that resemble most of the temporal and distributional behavior of long returns surprisingly well. The model is based on the stochastic unit root process introduced in Granger and Swanson (1997)

Nonlinear models, especially threshold autoregressive [TAR] and exponential smooth transition autoregressive [ESTAR] classes, are widely applied for modeling real exchange rates in order to examine the validity of purchasing power parity [PPP]. Even though the nonlinear models are theoretically...

The U.S. unemployment rate is generally regarded as nonlinear. In this study, we show that if there had been no miners' general strike in October of 1949, and if the aggregate unemployment rate had been 0.3% lower during that month, the 1948-2002 U.S. unemployment rate would have been linear....

Recent empirical findings show that post-war real interest rates are quite persistent and that they also contain a large number of structural changes in their means. In this study, we also find concurring results for real interest rates from thirteen industrialized countries. We show, however,...

Various unit roots tests are suggested over the years. However, many of them suffer severe size problems as well as low power. Recently, Ng and Perron (Econometrica, 69, 1519-1554, 2001) propose new modelling strategy that yields good power and reliable size. This letter applies their testing...

This note presents some properties of the stochastic unit-root processes developed in Granger and Swanson ["Journal of Econometrics" (1997) Vol. 80, pp. 35-62] and Leybourne, McCabe and Tremayne ["Journal of Business & Economic Statistics" (1996) Vol. 14, pp. 435-446] that have not been or only...

This paper extends the previous results in Bessler and Yu (1994) on the official and black market exchange rates in Brazil. Rather than taking instantaneous data transformations to produce a stable long-run equilibrium relationship as Bessler and Yu did, the possibility of structural changes in...

Possibly hitherto unnoticed cointegrating relationships among integrated components of data series are identified. If the components are cointegrated, the data are said to ahve hidden cointegration. The implication of hidden cointegration on modeling data series themselves is discussed...