Cauchy estimators for autoregressive processes with applications to unit root tests and confidence intervals

Beong Soo So, Dong Wan Shin

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

For autoregressive processes, we propose new estimators whose pivotal statistics have the standard normal limiting distribution for all ranges of the autoregressive parameters. The proposed estimators are approximately median unbiased. For seasonal time series, the new estimators give us unit root tests that have limiting normal distribution regardless of period of the seasonality. Using the estimators, confidence intervals of the autoregressive parameters are constructed. A Monte-Carlo simulation for first-order autoregressions shows that the proposed tests for unit roots are locally more powerful than the tests based on the ordinary least squares estimators. It also shows that the proposed confidence intervals have shorter average lengths than those of Andrews (1993, Econometrica 61, 139-165) based on the ordinary least squares estimators when the autoregressive coefficient is close to one.

Original languageEnglish
Pages (from-to)165-176
Number of pages12
JournalEconometric Theory
Volume15
Issue number2
DOIs
StatePublished - 1999

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