A random coefficient autoregressive model RCAR(1)model
نویسندگان
چکیده
منابع مشابه
Least squares estimation in a simple random coefficient autoregressive model.∗
The question we discuss is whether a simple random coefficient autoregressive model with infinite variance can create the long swings, or persistence, which are observed in many macro economic variables. The model is defined by yt = stρyt−1 + εt, t = 1, . . . , n, where st is an i.i.d. binary variable with p = P (st = 1), independent of εt i.i.d. with mean zero and finite variance. We say that ...
متن کاملBayesian Analysis of Random Coefficient AutoRegressive Models
Random Coefficient AutoRegressive (RCAR) models are obtained by introducing random coefficients to an AR or more generally ARMA model. These models have second order properties similar to that of ARCH and GARCH models. In this article, a Bayesian approach to estimate the first order RCAR models is considered. A couple of Bayesian testing criteria for the unit-root hypothesis are proposed: one i...
متن کاملEstimation in nonstationary random coefficient autoregressive models
We investigate the estimation of parameters in the random coefficient autoregressive model Xk = (φ+ bk)Xk−1 + ek, where (φ,ω 2, σ2) is the parameter of the process, Eb0 = ω2, Ee0 = σ 2. We consider a nonstationary RCA process satisfying E log |φ + b0| ≥ 0 and show that σ2 cannot be estimated by the quasi-maximum likelihood method. The asymptotic normality of the quasi-maximum likelihood estimat...
متن کاملEstimation in Random Coefficient Autoregressive Models
We propose the quasi-maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.
متن کاملNear–Integrated Random Coefficient Autoregressive Time Series
We determine the limiting behavior of near–integrated first–order random coefficient autoregressive RCA(1) time series. It is shown that the asymptotics of the finite dimensional distributions crucially depends on how the critical value 1 is approached, which determines whether the process is near–stationary, has a unit–root or is mildly explosive. In a second part, we derive the limit distribu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Publikacije Elektrotehni?kog fakulteta - serija: matematika
سال: 2004
ISSN: 0353-8893
DOI: 10.2298/petf0415045c