Arbeitspapier

Integrated modified OLS estimation and fixed-b inference for cointegrating regressions

This paper is concerned with parameter estimation and inference in a cointegrating regression, where as usual endogenous regressors as well as serially correlated errors are considered. We propose a simple, new estimation method based on an augmented partial sum (integration) transformation of the regression model. The new estimator is labeled Integrated Modified Ordinary Least Squares (IM-OLS). IM-OLS is similar in spirit to the fully modified approach of Phillips and Hansen (1990) with the key difference that IM-OLS does not require estimation of long run variance matrices and avoids the need to choose tuning parameters (kernels, bandwidths, lags). Inference does require that a long run variance be scaled out, and we propose traditional and fixed-b methods for obtaining critical values for test statistics. The properties of IM-OLS are analyzed using asymptotic theory and finite sample simulations. IM-OLS performs well relative to other approaches in the literature.

Sprache
Englisch

Erschienen in
Series: Reihe Ökonomie / Economics Series ; No. 263

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Thema
bandwidth
cointegration
fixed-b asymptotics
fully modified OLS
IM-OLS
kernel

Ereignis
Geistige Schöpfung
(wer)
Vogelsang, Timothy J.
Wagner, Martin
Ereignis
Veröffentlichung
(wer)
Institute for Advanced Studies (IHS)
(wo)
Vienna
(wann)
2011

Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Vogelsang, Timothy J.
  • Wagner, Martin
  • Institute for Advanced Studies (IHS)

Entstanden

  • 2011

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