Macroeconomics and ARCH

James D. Hamilton

in Volatility and Time Series Econometrics

Published in print March 2010 | ISBN: 9780199549498
Published online May 2010 | e-ISBN: 9780191720567 | DOI:

Series: Advanced Texts in Econometrics

 Macroeconomics and ARCH

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Studying volatility has traditionally been a much lower priority for macroeconomists than for researchers in financial markets because the former's interest is primarily in describing the first moments. There seems to be an assumption among many macroeconomists that, if your primary interest is in the first moment, autoregressive conditional heteroskedasticity (ARCH) has little relevance apart from possible GARCH-M effects. This chapter suggests that even if our primary interest is in estimating the conditional mean, having a correct description of the conditional variance can still be quite important, for two reasons. First, hypothesis tests about the mean in a model in which the variance is mis-specified will be invalid. Second, by incorporating the observed features of the heteroskedasticity into the estimation of the conditional mean, substantially more efficient estimates of the conditional mean can be obtained.

Keywords: autoregressive conditional heteroskedasticity; GARCH-M effects; volatility; conditional variance; conditional mean

Chapter.  7265 words.  Illustrated.

Subjects: Econometrics and Mathematical Economics

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