✦ LIBER ✦

Testing for Serial Correlation in Regression Models with Lagged Dependent Variables

✍ Scribed by Robert K. Rayner

Book ID: 125771600
Publisher: MIT Press
Year: 1993
Tongue: English
Weight: 229 KB
Volume: 75
Category: Article
ISSN: 0034-6535
DOI: 10.2307/2110028

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Heteroscedasticity in Models with Lagged

Heteroscedasticity in Models with Lagged Dependent Variables

✍ D. F. Nicholls and A. R. Pagan 📂 Article 📅 1983 🏛 John Wiley and Sons 🌐 English ⚖ 219 KB

Estimating the covariance matrix for reg

Estimating the covariance matrix for regression models with ar(1) errors and lagged dependent variables

✍ Russell Davidson; James G. MacKinnon 📂 Article 📅 1980 🏛 Elsevier Science 🌐 English ⚖ 226 KB

A modification of the CUSUM test in the

A modification of the CUSUM test in the linear regression model with lagged dependent variables

✍ W. Ploberger; W. Krämer; R. Alt 📂 Article 📅 1989 🏛 Springer-Verlag 🌐 English ⚖ 390 KB

Testing for Serial Correlation in Least

Testing for Serial Correlation in Least Squares Regression

✍ E. J. Hannan 📂 Article 📅 1957 🏛 Oxford University Press 🌐 English ⚖ 951 KB

Testing for contemporaneous correlation

Testing for contemporaneous correlation of disturbances in seemingly unrelated regressions with serial dependence

✍ Wen-Jen Tsay 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 124 KB

Bias correction of OLSE in the regressio

Bias correction of OLSE in the regression model with lagged dependent variables

✍ Hisashi Tanizaki 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 150 KB

It is well known that the ordinary least-squares estimates (OLSE) of autoregressive models are biased in small sample. In this paper, an attempt is made to obtain the unbiased estimates in the sense of median or mean. Using Monte Carlo simulation techniques, we extend the median-unbiased estimator p