FINITE-SAMPLE PROPERTIES OF FORECASTS FROM THE STATIONARY FIRST-ORDER AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION

DOI10.1017/S0266466607070338zbMath1237.62128OpenAlexW2144183724MaRDI QIDQ2886966

Yong Bao

Publication date: 14 May 2012

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

Full work available at URL: https://doi.org/10.1017/s0266466607070338

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Robustness and adaptive procedures (parametric inference) (62F35) Stationary stochastic processes (60G10)

Related Items (3)

Estimation bias and feasible conditional forecasts from the first-order moving average model ⋮ Multi‐step forecasting in the presence of breaks ⋮ Variable selection, estimation and inference for multi-period forecasting problems

Cites Work

• Predictors for the first-order autoregressive process
• The exact multi-period mean-square forecast error for the first-order autoregressive model
• The sampling distribution of forecasts from a first-order autoregression
• Unbiasedness of Predictions from Estimated Autoregressions when the True Order is Unknown
• The Bias and Moment Matrix of the General k-Class Estimators of the Parameters in Simultaneous Equations
• The prediction error of stationary Gaussian time series of unknown covariance

This page was built for publication: FINITE-SAMPLE PROPERTIES OF FORECASTS FROM THE STATIONARY FIRST-ORDER AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION