Estimating the Autocorrelated Error Model with Trended Data: Further Results,
Abstract
A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 1979
- Accession Number
- ADA095041
Entities
People
- Bridger M. Mitchell
- Rolla Edward Park
Organizations
- RAND Corporation