Abstract
A new point estimator for the AR(1) coefficient in the linear regression model with arbitrary exogenous regressors and stationary AR(1) disturbances is developed. Its construction parallels that of the median‐unbiased estimator, but uses the mode as a measure of central tendency. The mean‐adjusted estimator is also considered, and saddlepoint approximations are used to lower the computational burden of all the estimators. Large‐scale simulation studies for assessing their small‐sample properties are conducted. Their relative performance depends almost exclusively on the value of the autoregressive parameter, with the new estimator dominating over a large part of the parameter space.
| Item Type: | Journal article |
|---|---|
| Faculties: | Economics Economics > Chairs > CESifo-Professorship for Business Cycle Analysis and Surveys (closed) |
| Subjects: | 300 Social sciences > 330 Economics |
| Language: | English |
| Item ID: | 19992 |
| Date Deposited: | 15. Apr 2014 08:55 |
| Last Modified: | 04. Nov 2020 13:01 |
