This paper reconsiders the conventional use of econometric models, especially identified vector autoregressive models, in guiding monetary policy. The main question I explore is whether these models are seriously flawed because they ignore asymmetries in the business cycles. Toward that end, models that allow for asymmetric business cycles—defined by the case where recessions and expansions are...

Normal residual is one of the usual assumptions of autoregressive models but in practice sometimes we are faced with non-negative residuals case. In this paper we consider some autoregressive models with non-negative residuals as competing models and we have derived the maximum likelihood estimators of parameters based on the modified approach and EM algorithm for the competing models. Also,...

Semiautogenous (SAG) mills for ore grinding are large energy consumption equipments. The SAG energy consumption is strongly related to the fill level of the mill. Hence, on-line information of the mill fill level is a relevant state variable to monitor and drive in SAG operations. Unfortunately, due to the prevailing conditions in a SAG mill, it is difficult to measure and represent from first ...

agriculture as one of the major economic sectors of iran, has an important role in gross domestic production by providing about 14% of gdp. this study attempts to forecast the value of the agriculture gdp using periodic autoregressive model (par), as the new seasonal time series techniques. to address this aim, the quarterly data were collected from march 1988 to july 1989. the collected data w...

In this paper, the effects of oil and gold prices on stock market index are investigated. We use a cointegrated vector autoregressive Markov-switching model to examine the nonlinear properties of these three variables during the period of January 2003 - December 2014. The Markov-switching vector-equilibrium-correction model with three regimes representing "deep recession", "mild recession" and ...

We study asymptotic properties of the local Whittle estimator of the long memory parameter for a wide class of fractionally integrated nonlinear time series models+ In particular, we solve the conjecture posed by Phillips and Shimotsu ~2004, Annals of Statistics 32, 656–692! for Type I processes under our framework, which requires a global smoothness condition on the spectral density of the sho...

0950-7051/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.knosys.2010.07.006 * Corresponding author. Tel.: +886 3 5712121x573 E-mail addresses: [email protected] (Y.-S (L.-I. Tong). The autoregressive integrated moving average (ARIMA), which is a conventional statistical method, is employed in many fields to construct models for forecasting time series. Although ARIMA can be adopte...

This paper studies the stability of nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Conditions under which the model is stable in the sense that its Markov chain repre...

Parametric copulae are shown to be an attractive device for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed estimators are established, leading to a general framework for inference and model specificat...