Testing for ARCH in the presence of additive outliers

✍ Scribed by Dick Van Dijk; Philip Hans Franses; André Lucas

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 279 KB
• Volume: 14
• Category: Article
• ISSN: 0883-7252
• DOI: 10.1002/(sici)1099-1255(199909/10)14:5<539::aid-jae526>3.0.co;2-w

✦ Synopsis

In this paper we investigate the properties of the Lagrange Multiplier [LM] test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AOs). We show analytically that both the asymptotic size and power are adversely aected if AOs are neglected: the test rejects the null hypothesis of homoscedasticity too often when it is in fact true, while the test has diculty detecting genuine GARCH eects. Several Monte Carlo experiments show that these phenomena occur in small samples as well. We design and implement a robust test, which has better size and power properties than the conventional test in the presence of AOs. We apply the tests to a number of US macroeconomic time series, which illustrates the dangers involved when nonrobust tests for ARCH are routinely applied as diagnostic tests for misspeci®cation.