Estimating the Persistence and the Autocorrelation Function of a Time Series that is Measured with Error

Publikation: Working paperForskning

Dokumenter

  • Rp10 08

    Forlagets udgivne version, 392 KB, PDF-dokument

  • Institut for Økonomi
An economic time series can often be viewed as a noisy proxy for an underlying economic
variable. Measurement errors will influence the dynamic properties of the observed process
and may conceal the persistence of the underlying time series. In this paper we develop
instrumental variable (IV) methods for extracting information about the latent process.
Our framework can be used to estimate the autocorrelation function of the latent volatility
process and a key persistence parameter. Our analysis is motivated by the recent literature
on realized (volatility) measures, such as the realized variance, that are imperfect estimates
of actual volatility. In an empirical analysis using realized measures for the DJIA stocks
we find the underlying volatility to be near unit root in all cases. Although standard unit
root tests are asymptotically justified, we find them to be misleading in our application
despite the large sample. Unit root tests based on the IV estimator have better finite
sample properties in this context.
OriginalsprogEngelsk
UdgivelsesstedAarhus
UdgiverInstitut for Økonomi, Aarhus Universitet
Antal sider38
StatusUdgivet - 2010

Se relationer på Aarhus Universitet Citationsformater

Download-statistik

Ingen data tilgængelig

ID: 19334754