Averaging estimators for autoregressions with a near unit root (Q736566)

scientific article; zbMATH DE number 6609184

Language	Label	Description	Also known as
English	Averaging estimators for autoregressions with a near unit root	scientific article; zbMATH DE number 6609184

Statements

instance of

scholarly article

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title

Averaging estimators for autoregressions with a near unit root (English)

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author

Bruce E. Hansen

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published in

Journal of Econometrics

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publication date

4 August 2016

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MaRDI profile type

Publication

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full work available at URL

https://doi.org/10.1016/j.jeconom.2010.03.022

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cites work

Statistical predictor identification

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Maximum likelihood identification of Gaussian autoregressive moving average models

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SELECTING THE RANK OF THE COINTEGRATION SPACE AND THE FORM OF THE INTERCEPT USING AN INFORMATION CRITERION

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Asymptotically efficient autoregressive model selection for multistep prediction

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Asymptotic inference for nearly nonstationary AR(1) processes

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Model selection in partially nonstationary vector autoregressive processes with reduced rank structure

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Forecasting with difference-stationary and trend-stationary models

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Distribution of the Estimators for Autoregressive Time Series With a Unit Root

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Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root

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Efficient Tests for an Autoregressive Unit Root

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Co-Integration and Error Correction: Representation, Estimation, and Testing

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Specification via model selection in vector error correction models

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Least Squares Model Averaging

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Least-squares forecast averaging

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AVERAGING ESTIMATORS FOR REGRESSIONS WITH A POSSIBLE STRUCTURAL BREAK

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Jackknife model averaging

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Pooling of forecasts

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Frequentist Model Average Estimators

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MULTISTEP PREDICTION IN AUTOREGRESSIVE PROCESSES

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Selecting optimal multistep predictors for autoregressive processes of unknown order.

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On same-realization prediction in an infinite-order autoregressive process.

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Order selection for same-realization predictions in autoregressive processes

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On the selection of forecasting models

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THE ASYMPTOTIC DISTRIBUTION OF THE COINTEGRATION RANK ESTIMATOR UNDER THE AKAIKE INFORMATION CRITERION

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THE BEHAVIOR OF FORECAST ERRORS FROM A NEARLY INTEGRATED AR(1) MODEL AS BOTH SAMPLE SIZE AND FORECAST HORIZON BECOME LARGE

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Asymptotic mean‐squared forecast error when an autoregression with linear trend is fitted to data generated by an I(0) or I(1) process

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An asymptotically optimal selection of the order of a linear process

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Some Comments on C P

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Selection of estimation window in the presence of breaks

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Regression Theory for Near-Integrated Time Series

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Towards a unified asymptotic theory for autoregression

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Stochastic complexity and modeling

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Estimating the dimension of a model

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Asymptotically efficient selection of the order of the model for estimating parameters of a linear process

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Optimal forecast combinations under general loss functions and forecast error distributions

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On predictive least squares principles

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Identifiers

zbMATH Open document ID

1431.62382

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Mathematics Subject Classification ID

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10.1016/J.JECONOM.2010.03.022

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Sitelinks

Mathematics(1 entry)

mardi Publication:736566