Generalized method of moments estimation for cointegrated vector autoregressive models |
| |
Authors: | Suk K. ParkSung K. Ahn Sinsup Cho |
| |
Affiliation: | a Korea Development Bank, Republic of Koreab Department of Finance and Management Science, Washington State University, USAc Department of Statistics, Seoul National University, (151-747) 599 Gwanak-ro Gwanak-gu, Seoul, Republic of Korea |
| |
Abstract: | In this study, a generalized method of moments (GMM) for the estimation of nonstationary vector autoregressive models with cointegration is considered. Two iterative methods are considered: a simultaneous estimation method and a switching estimation method. The asymptotic properties of the GMM estimators of these methods are found to be the same as those of the Gaussian reduced-rank estimator. Through Monte Carlo simulation, the small-sample properties of the GMM estimators are studied and compared with those of the Gaussian reduced-rank estimator and the maximum likelihood estimator considered by other researchers. In the case of small samples, the GMM estimators are more robust to deviations from normality assumptions, particularly to outliers. |
| |
Keywords: | Cointegration GMM estimation VAR model |
本文献已被 ScienceDirect 等数据库收录! |
|