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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.

MSC:
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
91B84 Economic time series analysis
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References:
[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
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