In this paper, we investigate whether incorporating common factors of CPI sub-aggregates into forecasting models increases the accuracy of forecasts of inflation. We extract factors by both static and dynamic factor models and then embed them in ARMA and VAR models. Using quarterly data of Iran’s CPI and its sub-aggregates, the models are estimated over 1990:2 to 2008:2 and out of sample ...

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between 'input' and 'output' time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modelin...

We consider maximum likelihood estimation of a particular noninvertible ARMA model with autoregressive conditionally heteroskedastic (ARCH) errors. The model can be seen as an extension to so-called all-pass models in that it allows for autocorrelation and for more flexible forms of conditional heteroskedasticity. These features may be attractive especially in economic and financial application...