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Author: Andrew C Harvey
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Fabio Busetti and Andrew C Harvey
The paper considers tests for the presence of a random walk component in a stationary or trend stationary time series and extends them to series which contain structural breaks. The locally best invariant (LBI) test is d...Read more...
Andrew C Harvey, Siem Jan Koopman and J Penzer
Many series are subject to data irregularities such as missing values, outliers, structural breaks and irregular spacing. Data can also be messy, and hence difficult to handle by standard procedures, when they are intrin...Read more...
Andrew C Harvey and Mariane Streibel
A test for the presence of a stationary first-order autoregressive process embedded in white noise is constructed so as to be relatively powerful when the autoregressive parameter is close to one. This is done by setting...Read more...
Andrew C Harvey and Siem Jan Koopman
Much of economic analysis presupposes that certain economic time series can be decomposed into trends and cycles. Structural time series models are explicitly set up in terms of such unobserved components. This paper set...Read more...
Andrew C Harvey, Siem Jan Koopman and Marco Riani
A number of important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recordi...Read more...
Andrew C Harvey and Andrew Scott
This paper examines the implications of treating seasonality as an unobserved component which changes slowly over time. This approach simplifies the specification of dynamic relationships by separating non-seasonal from ...Read more...
Andrew C Harvey and N.G. Shephard
A stochastic variance model may be estimated by quasi-maximum likelihood procedure by transforming to a linear state space form. The properties of observations corrected for heteroscedasticity can be derived. A model wit...Read more...
Andrew C Harvey and Albert Jaeger
The stylized facts of macroeconomic time series can be presented by fitting structural time series models. Within this framework, we analyze the consequences of the widely used detrending technique popularized by Hodrick...Read more...