Measuring Conditional Persistence in Time Series
AbstractThe persistence properties of economic time series has been a primary object of investigation in a variety of guises since the early days of econometrics. This paper suggests investigating the persistence of processes conditioning on their history. In particular we suggest that examining the derivatives of the conditional expectation of a variable with respect to its lags maybe a useful indicator of the variation in persistence with respect to its past history. We discuss in detail the implementation of the measure. We present a Monte Carlo investigation of the suggested measure. We further apply the persistence analysis to real exchange rates.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 474.
Date of creation: Nov 2002
Date of revision:
Persistence; Nonparametric regression; Nonlinear models; Real exchange rates;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- F31 - International Economics - - International Finance - - - Foreign Exchange
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-12-02 (All new papers)
- NEP-ECM-2002-12-10 (Econometrics)
- NEP-ETS-2002-12-02 (Econometric Time Series)
- NEP-IFN-2002-12-02 (International Finance)
- NEP-RMG-2002-12-02 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lavergne, Pascal & Vuong, Quang H, 1996.
"Nonparametric Selection of Regressors: The Nonnested Case,"
Econometric Society, vol. 64(1), pages 207-19, January.
- Lavergne, P. & Vuong, Q., 1992. "Nonparametric Selection of Regressors : the Nonnested Case," Papers 9204, Southern California - Department of Economics.
- Pagan,Adrian & Ullah,Aman, 1999.
Cambridge University Press, number 9780521355643, December.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nick Vriend).
If references are entirely missing, you can add them using this form.