Testing for ARCH in the Presence of a Possibly Misspecified Conditional Mean
AbstractEver since the development of the Autoregressive Conditional Heteroskedasticity (ARCH) model (Engle ), testing for the presence of ARCH has become a routine diagnostic. One popular method of testing for ARCH is T times the R^2 from a regression of squared residuals on p of its lags. This test has been shown to have a Lagrange multiplier interpretation and is asymptotically distributed as a Chi^2(p) random variable. Underlying this test is the assumption of a correctly specified conditional mean. In this paper, we consider the properties of the ARCH test when there is a possibly misspecified conditional mean. Examples of misspecification include omitted variables, structural change, and parameter instability. We show that misspecification will lead to overrejection of the null of conditional homoskedasticity. We demonstrate the use of recursive residuals to improve the fit of a first stage conditional mean regression. We illustrate these results via Monte Carlo simulation and consider two empirical examples.
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Bibliographic InfoPaper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 370.
Length: 24 pages
Date of creation: 27 Aug 1998
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ARCH; model misspecification; recursive residuals; Lagrange Multiplier test;
Other versions of this item:
- Lumsdaine, Robin L. & Ng, Serena, 1999. "Testing for ARCH in the presence of a possibly misspecified conditional mean," Journal of Econometrics, Elsevier, vol. 93(2), pages 257-279, December.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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