TU Darmstadt / ULB / TUprints

Residual Log-Periodogram Inference for Long-Run-Relationships

Hassler, Uwe ; Marmol, Francesc ; Velasco, Carlos (2009)
Residual Log-Periodogram Inference for Long-Run-Relationships.
Report, Primary publication

[img]
Preview
Text
ddpie_115.pdf
Copyright Information: In Copyright.

Download (418kB) | Preview
Item Type: Report
Type of entry: Primary publication
Title: Residual Log-Periodogram Inference for Long-Run-Relationships
Language: English
Date: 4 November 2009
Place of Publication: Darmstadt
Series: Darmstadt Discussion Papers in Economics
Series Volume: 115
Abstract:

We assume that some consistent estimator of an equilibrium relation between non-stationary fractionally integrated series is used in a first step to compute residuals (or differences thereof). We propose to apply the semiparametric log-periodogram regression to the (differenced) residuals in order to estimate and test the degree of persistence of the equilibrium deviation. Provided the first step estimator converges fast enough, we describe simple semiparametric conditions around zero frequency that guarantee consistent estimation of persistence from residuals. At the same time limiting normality is derived, which allows to construct approximate confidence intervals to test hypotheses on the persistence. Our assumptions allow for stationary deviations with long memory as well as for non-stationary but transitory equilibrium errors. In particular, in case of several regressors we consider the joint estimation of the memory parameters of the observed series and of the equilibrium deviation. Wald statistics to test for parameter restrictions of the system have a limiting chi-squared distribution. We also analyze the benefits of a pooled version of the estimate. The empirical applicability of our general cointegration test is investigated by means of Monte Carlo experiments and illustrated with a study of exchange rate dynamics.

Uncontrolled Keywords: Fractional cointegration; semiparametric inference; limiting normality; long memory; non-stationarity; exchange rates.
URN: urn:nbn:de:tuda-tuprints-48149
Additional Information:

JEL Classification: C14, C22; Erstellt Juni 2002

Classification DDC: 300 Social sciences > 330 Economics
Divisions: 01 Department of Law and Economics
01 Department of Law and Economics > Volkswirtschaftliche Fachgebiete
Date Deposited: 04 Nov 2009 14:50
Last Modified: 25 Oct 2023 07:19
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/4814
PPN: 378484478
Export:
Actions (login required)
View Item View Item