DATA DEPENDENT RULES FOR SELECTION OF THE NUMBER OF LEADS AND LAGS IN THE DYNAMIC OLS COINTEGRATING REGRESSION

DOI10.1017/S0266466608080560zbMath1284.62421MaRDI QIDQ3632424

Mohitosh Kejriwal, Pierre Perron

Publication date: 11 June 2009

Published in: Econometric Theory (Search for Journal in Brave)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items (8)

The limit distribution of the estimates in cointegrated regression models with multiple structural changes ⋮ Asymptotic properties of the efficient estimators for cointegrating regression models with serially dependent errors ⋮ A two‐step procedure for testing partial parameter stability in cointegrated regression models ⋮ Model selection criteria for the leads-and-lags cointegrating regression ⋮ Integrated modified OLS estimation and fixed-\(b\) inference for cointegrating regressions ⋮ Quasi-likelihood ratio tests for cointegration, cobreaking, and cotrending ⋮ Parameter estimation and inference with spatial lags and cointegration ⋮ Inference on locally ordered breaks in multiple regressions

Cites Work

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• Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag
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