Optimal forecasts in the presence of discrete structural breaks under long memory
نویسندگان
چکیده
We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for observations. observe significant changes forecasts when long-range dependence is taken into account. Using Monte Carlo simulations, we confirm that our substantially improve forecasting performance memory. further present an empirical application inflation rates emphasizes importance methods.
منابع مشابه
Long-memory versus structural breaks: An overview
We discuss the increasing literature on misspecifying structural breaks or more general trends as long range dependence We consider tests on structural breaks in the long memory regression model as well as the behaviour of estimators of the memory parameter when structural breaks or trends are in the data but long memory is not It can be seen that it is hard to distinguish deterministic trends ...
متن کاملLong memory or structural breaks: Can either explain nonstationary real exchange rates under the current oat?
Long memory or structural breaks: Can either explain nonstationary real exchange rates under the current oat? Christopher F. Baum Boston College Chestnut Hill, MA 02467 USA John T. Barkoulas Louisiana Tech University Ruston, LA 71272 USA Mustafa Caglayan Koç University Istanbul, Turkey This paper considers two potential rationales for the apparent absence of mean reversion in real exchange rate...
متن کاملthe effects of keyword and context methods on pronunciation and receptive/ productive vocabulary of low-intermediate iranian efl learners: short-term and long-term memory in focus
از گذشته تا کنون، تحقیقات بسیاری صورت گرفته است که همگی به گونه ای بر مثمر ثمر بودن استفاده از استراتژی های یادگیری لغت در یک زبان بیگانه اذعان داشته اند. این تحقیق به بررسی تاثیر دو روش مختلف آموزش واژگان انگلیسی (کلیدی و بافتی) بر تلفظ و دانش لغوی فراگیران ایرانی زیر متوسط زبان انگلیسی و بر ماندگاری آن در حافظه می پردازد. به این منظور، تعداد شصت نفر از زبان آموزان ایرانی هشت تا چهارده ساله با...
15 صفحه اولForecasting Long Memory Processes Subject to Structural Breaks
We develop an easy-to-implement method for forecasting a stationary autoregressive fractionally integrated moving average (ARFIMA) process subject to structural breaks with unknown break dates. We show that an ARFIMA process subject to a mean shift and a change in the long memory parameter can be well approximated by an autoregressive (AR) model and suggest using an information criterion (AIC o...
متن کاملSmall Sample Properties of Forecasts from Autoregressive Models under Structural Breaks∗
This paper develops a theoretical framework for the analysis of smallsample properties of forecasts from general autoregressive models under structural breaks. Finite-sample results for the mean squared forecast error of one-step ahead forecasts are derived, both conditionally and unconditionally, and numerical results for different types of break specifications are presented. It is established...
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: Journal of Forecasting
سال: 2023
ISSN: ['0277-6693', '1099-131X']
DOI: https://doi.org/10.1002/for.2988