Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis
نویسندگان
چکیده
منابع مشابه
An ARFIMA Model for Volatility Does Not Imply Long Memory
Jiang and and Tian (2010) have estimated an ARFIMA model for stock return volatility. We argue that this result does not imply actual 'long memory' in such time series -as any kind of instability in the population mean yields apparent fractional integration as a statistical artifact. Alternative high-pass filters for studying stock market volatility data are suggested.
متن کاملModeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach
This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH, or A-FIGARCH, which is designed to account for both long memory and structural change in the conditional variance process. Structural change is modeled by allowing the intercept to follow the smooth exible functional form due to Gallant (1984). A Monte Carlo study nds that the A-FIGARCH model outperforms ...
متن کاملForthcoming in the Journal of Econometrics Bayesian Analysis of Long Memory and Persistence using ARFIMA Models
This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty into account when making inferences on quantities of interest. Our methods are then used to investigat...
متن کاملUK and Twenty Comparable Countries GDP-Expenditure-on-Health 1980-2013: The Historic and Continued Low Priority of UK Health-Related Expenditure
It is well-established that for a considerable period the United Kingdom has spent proportionally less of its gross domestic product (GDP) on health-related services than almost any other comparable country. Average European spending on health (as a % of GDP) in the period 1980 to 2013 has been 19% higher than the United Kingdom, indicating that comparable countries give far greater fiscal prio...
متن کاملModelling long-term heart rate variability: an ARFIMA approach.
Long-term heart rate variability (HRV) series can be described by time-variant autoregressive modelling. HRV recordings show dependence between distant observations that is not negligible, suggesting the existence of long-range correlations. In this work, selective adaptive segmentation combined with fractionally integrated autoregressive moving-average models is used to capture long memory in ...
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: SSRN Electronic Journal
سال: 2014
ISSN: 1556-5068
DOI: 10.2139/ssrn.2459806