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Seasonal Heteroskedasticity in Time Series Data: Modeling, Estimation, and Testing
Seasonal Heteroskedasticity in Time Series Data: Modeling, Estimation, and Testing
RRS2008-11
Abstract
Seasonal heteroskedasticity refers to regular changes in variability over the calendar year. Models for two different forms of seasonal heteroskedasticity were recently proposed by Proietti and by Bell. We examine use of likelihood ratio tests with the models to test for the presence of seasonal heteroskedasticity, and use of model comparison statistics (AIC) to compare the models and to search among alternative patterns of seasonal heteroskedasticity. We apply the models and tests to U.S. Census Bureau monthly time series of housing starts and building permits.
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