A Unit Root Test Based on the Modified Least Squares Estimator

• Activity Number: 489
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Wararit Panichkitkosolkul*+
• Companies: Thammasat University
• Keywords: Unit root test ; First-order autoregressive ; Ordinary least squares estimator ; Weighted symmetric estimator

Abstract

A unit root test based on the modified least squares (MLS) estimator for first-order autoregressive process is proposed and compared with unit root tests based on the ordinary least squares (OLS), the weighted symmetric (WS) and the modified weighted symmetric (MWS) estimators. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results have shown that all unit root tests can control the probability of Type I error for all situations. The empirical power of the K_mws test is higher than the other unit root tests, K_ols, K_ws and K_mls. Apart from that, the T_ws and T_mws tests also provide the highest empirical power. As an illustration, a monthly series of U.S. nominal interest rates on three-month treasury bills is analyzed.