Time Series Regression Forecasting with Measurement Errors

摘要：

Estimation methods can have dramatic impact on the outcome of empirical analysis. In this article, we quantify the effects of estimation on prediction generated from time series regression models with and without measurement errors. The estimators considered are unconditional least squares, maximum likelihood and conditional least squares. The results suggest that although these estimators are asymptotically equivalent, the finite sampling properties of predictors based on those estimators can differ substantially, because of differences in finite-sample estimation efficiencies, and more importantly in residual regeneration methods.

关键词： Autoregressive Moving-average Model Estimation Measurement Errors Prediction Time Series Regression

作者: FANG Yue

作者单位: Lundquist College of Business University of Oregon Eugene, OR 97403, USA, China Europe International Business School Pudong, Shanghai, P.R.China

会议类型: 国际会议

会议名称: 2008年国际应用统计学术研讨会(2008 International Institute of Applied Statistics Studies)

会议地点: 烟台

会议语种:英文

页码: 1-5

在线出版日期: 2008-08-14（万方平台首次上网日期，不代表论文的发表时间）