Estimation for random coefficient autoregressive 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 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 کاملUnified Interval Estimation for Random Coefficient Autoregressive Models
The consistency of the quasi maximum likelihood estimator for random coefficient autoregressive models requires that the coefficient be a non-degenerate random variable. In this paper we propose empirical likelihood methods based on weighted score equations to construct a confidence interval for the coefficient. We do not need to distinguish whether the coefficient is random or deterministic an...
متن کاملMinimum distance estimation for random coefficient autoregressive models
In this paper, we extend the minimum distance method of Beran (1993) to random coefficient autoregressive (RCA) models. After stating the necessary assumptions the asymptotic properties of the minimum distance estimator are derived. A M S classification: 62M05
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: Korean Journal of Applied Statistics
سال: 2016
ISSN: 1225-066X
DOI: 10.5351/kjas.2016.29.1.257