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Sectoral Investigation of Asymmetries in the Conditional Mean Dynamics of the Real U.S. GDP Author info | Abstract | Publisher info | Download info | Related research | Statistics Prasad Bidarkota (Kansas State University)
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We investigate asymmetries in the conditional mean dynamics of four sectors of the U.S. GDP data. Since the statistical evidence on nonlinearities in the conditional mean could be influenced by the presence of outliers, or by a failure to model conditional heteroskedasticity, we explicitly account for outliers by assuming that the innovations are drawn from the stable family, and model time-varying volatility by a GARCH(1,1) process. We also allow for the possibility of long memory in the series with fractional differencing. Our results indicate only weak evidence of significant nonlinearities in the conditional mean in some sectors of the GDP.
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Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics .
Volume (Year): 3 (1999)
Issue (Month): 4 ()
Pages: 191-200
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Keywords: GDP symmetric stable distributions conditional heteroskedasticity long memory nonlinearity References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.:
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