Arbeitspapier

Estimation of possibly non-stationary first-order auto-regressive processes

This paper inspects a grid search algorithm to estimate the AR(1) process, based on the joint estimation of the canonical AR(1) equation along with its reverse form. The method relies on the GLS principle, accounting for the covariance error structure of the special estimable system. Nevertheless, it stands as potentially improving to rely on across-equation-restricted system estimation with free covariance structure. The algorithm is (computationally) implemented and applied to inference of the AR(1) parameter of simulated - some stationary, others non-stationary - series. Additionally, it is argued - and illustrated by simulation - that non-stationary AR(1) processes appear to be consistently estimable by OLS. Also, it is suggested that the parameter of a stationary AR(1) process is estimable by OLS from the AR(2) representation of its non-stationary "first-integrated" series; or from the joint estimate of the canonical and reverse form of the AR(1) process by OLS. Importance of further study of differenced, D(p) - stationary after being integrated p times - processes is concluded.

Sprache
Englisch

Erschienen in
Series: EERI Research Paper Series ; No. 21/2016

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Estimation: General
Hypothesis Testing: General
Computational Techniques; Simulation Modeling
Thema
Nonlinear Estimation
Grid Search Methods
AR(1) Processes
Integrated Series
Differenced Processes
Factored AR(1) Processes
Unit Roots

Ereignis
Geistige Schöpfung
(wer)
Martins, Ana Paula
Ereignis
Veröffentlichung
(wer)
Economics and Econometrics Research Institute (EERI)
(wo)
Brussels
(wann)
2016

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Martins, Ana Paula
  • Economics and Econometrics Research Institute (EERI)

Entstanden

  • 2016

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