zbMATH — the first resource for mathematics

Autoregressive conditional heteroscedasticity: a comparison of ARCH and random coefficient models. (English) Zbl 1328.62540
Summary: In this paper it is shown that the popular Autoregressive Conditional Heteroscedasticity (ARCH) models are closely related to more traditional random coefficient models. It is demonstrated that for every ARCH model a simple random coefficient model can be formulated which implies exactly the same conditional variance pattern for the variable of interest.

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
91B84 Economic time series analysis
Full Text: DOI
[1] Engle, Robert F., Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation, Econometrica, 50, 987-1007, (1982) · Zbl 0491.62099
[2] Hildreth, Clifford; Houck, James P., Some estimators for a linear model with random coefficients, Journal of the American statistical association, 63, 584-595, (1968) · Zbl 0162.49804
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.