Arbeitspapier

Cointegrating polynomial regressions: Fully modified OLS estimation and inference

This paper develops a fully modified OLS estimator for cointegrating polynomial regressions, i.e. for regressions including deterministic variables, integrated processes and powers of integrated processes as explanatory variables and stationary errors. The errors are allowed to be serially correlated and the regressors are allowed to be endogenous. The paper thus extends the fully modified approach developed in Phillips and Hansen (1990). The FM-OLS estimator has a zero mean Gaussian mixture limiting distribution, which is the basis for standard asymptotic inference. In addition Wald and LM tests for specification as well as a KPSS-type test for cointegration are derived. The theoretical analysis is complemented by a simulation study which shows that the developed FM-OLS estimator and tests based upon it perform well in the sense that the performance advantages over OLS are by and large similar to the performance advantages of FM-OLS over OLS in cointegrating regressions.

Sprache
Englisch

Erschienen in
Series: Reihe Ökonomie / Economics Series ; No. 264

Klassifikation
Wirtschaft
Hypothesis Testing: General
Estimation: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Thema
cointegrating polynomial regression
fully modified OLS estimation
integrated process , testing

Ereignis
Geistige Schöpfung
(wer)
Hong, Seung Hyun
Wagner, Martin
Ereignis
Veröffentlichung
(wer)
Institute for Advanced Studies (IHS)
(wo)
Vienna
(wann)
2011

Handle
Letzte Aktualisierung
10.03.2025, 11:43 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

  • Hong, Seung Hyun
  • Wagner, Martin
  • Institute for Advanced Studies (IHS)

Entstanden

  • 2011

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