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Measuring Conditional Persistence in Time Series

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Abstract

The 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.

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  • George Kapetanios, 2002. "Measuring Conditional Persistence in Time Series," Working Papers 474, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:wp474
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    File URL: http://www.econ.qmul.ac.uk/media/econ/research/workingpapers/archive/wp474.pdf
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    References listed on IDEAS

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    1. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643.
    2. Lavergne, Pascal & Vuong, Quang H, 1996. "Nonparametric Selection of Regressors: The Nonnested Case," Econometrica, Econometric Society, vol. 64(1), pages 207-219, January.
    3. Chortareas, Georgios E. & Kapetanios, George & Shin, Yongcheol, 2002. "Nonlinear mean reversion in real exchange rates," Economics Letters, Elsevier, vol. 77(3), pages 411-417, November.
    4. George Kapetanios & Yongcheol Shin, 2002. "GLS Detrending for Nonlinear Unit Root Tests," Working Papers 472, Queen Mary University of London, School of Economics and Finance.
    5. Kapetanios, G., 1999. "Threshold Models for Trended Time Series," Cambridge Working Papers in Economics 9905, Faculty of Economics, University of Cambridge.
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    1. repec:gam:jeners:v:8:y:2015:i:11:p:13162-13193:d:59081 is not listed on IDEAS
    2. Francisco Martínez-Álvarez & Alicia Troncoso & Gualberto Asencio-Cortés & José C. Riquelme, 2015. "A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting," Energies, MDPI, Open Access Journal, vol. 8(11), pages 1-32, November.

    More about this item

    Keywords

    Persistence; Nonparametric regression; Nonlinear models; Real exchange rates;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; 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

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