Long memory and fractional cointegration with deterministic trends
We discuss the estimation of the order of integration of a fractional process that may be contaminated by a time-varying deterministic component, or subject to a break in the dynamics of the zero-mean stochastic component, and the estimation of the cointegrating parameter in a bivariate system gener...
Main Author: | |
---|---|
Published: |
London School of Economics and Political Science (University of London)
2006
|
Subjects: | |
Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428012 |
id |
ndltd-bl.uk-oai-ethos.bl.uk-428012 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-bl.uk-oai-ethos.bl.uk-4280122015-06-03T03:22:51ZLong memory and fractional cointegration with deterministic trendsIacone, Fabrizio2006We discuss the estimation of the order of integration of a fractional process that may be contaminated by a time-varying deterministic component, or subject to a break in the dynamics of the zero-mean stochastic component, and the estimation of the cointegrating parameter in a bivariate system generated by fractionally integrated processes and by additive polynomial trends. In Chapter 1 we review the theoretical literature on fractional integration and cointegration, and we analyse a situation in which a fractional model reconciles two apparently conflicting economic theories. In Chapter 2 we consider local Whittle estimation of the order of integration when the process is contaminated by a deterministic trend or by a break in the mean. We propose a simple condition to assess whether the asymptotic properties of the estimate are unaffected by the time-varying mean, and a test, with asymptotically normal test statistic under the null, to detect if that condition is met. In Chapter 3 we discuss local Whittle estimation when the zero-mean stochastic component is subject to a break: we show that the estimate is robust to instability in the short term dynamics, while in presence of a break in the long term dynamics only the highest order of integration is consistently estimated. We propose a test to detect that break: the limit distribution of the test statistic under the null is not standard, but it is well known in the literature. We also propose a procedure to estimate the location of a break when it is present. In Chapter 4 we consider a cointegrating relation in which a nonstationary, bivariate process is augmented by a deterministic trend. We derive the limit properties of the Ordinary Least Squares and Generalised Least Squares estimates: these depend on the comparison between the deterministic and the stochastic components.330.015195London School of Economics and Political Science (University of London)http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428012http://etheses.lse.ac.uk/1937/Electronic Thesis or Dissertation |
collection |
NDLTD |
sources |
NDLTD |
topic |
330.015195 |
spellingShingle |
330.015195 Iacone, Fabrizio Long memory and fractional cointegration with deterministic trends |
description |
We discuss the estimation of the order of integration of a fractional process that may be contaminated by a time-varying deterministic component, or subject to a break in the dynamics of the zero-mean stochastic component, and the estimation of the cointegrating parameter in a bivariate system generated by fractionally integrated processes and by additive polynomial trends. In Chapter 1 we review the theoretical literature on fractional integration and cointegration, and we analyse a situation in which a fractional model reconciles two apparently conflicting economic theories. In Chapter 2 we consider local Whittle estimation of the order of integration when the process is contaminated by a deterministic trend or by a break in the mean. We propose a simple condition to assess whether the asymptotic properties of the estimate are unaffected by the time-varying mean, and a test, with asymptotically normal test statistic under the null, to detect if that condition is met. In Chapter 3 we discuss local Whittle estimation when the zero-mean stochastic component is subject to a break: we show that the estimate is robust to instability in the short term dynamics, while in presence of a break in the long term dynamics only the highest order of integration is consistently estimated. We propose a test to detect that break: the limit distribution of the test statistic under the null is not standard, but it is well known in the literature. We also propose a procedure to estimate the location of a break when it is present. In Chapter 4 we consider a cointegrating relation in which a nonstationary, bivariate process is augmented by a deterministic trend. We derive the limit properties of the Ordinary Least Squares and Generalised Least Squares estimates: these depend on the comparison between the deterministic and the stochastic components. |
author |
Iacone, Fabrizio |
author_facet |
Iacone, Fabrizio |
author_sort |
Iacone, Fabrizio |
title |
Long memory and fractional cointegration with deterministic trends |
title_short |
Long memory and fractional cointegration with deterministic trends |
title_full |
Long memory and fractional cointegration with deterministic trends |
title_fullStr |
Long memory and fractional cointegration with deterministic trends |
title_full_unstemmed |
Long memory and fractional cointegration with deterministic trends |
title_sort |
long memory and fractional cointegration with deterministic trends |
publisher |
London School of Economics and Political Science (University of London) |
publishDate |
2006 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428012 |
work_keys_str_mv |
AT iaconefabrizio longmemoryandfractionalcointegrationwithdeterministictrends |
_version_ |
1716804812518981632 |