Zhu, Ke (2015): Hausman tests for the error distribution in conditionally heteroskedastic models.

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Abstract
This paper proposes some novel Hausman tests to examine the error distribution in conditionally heteroskedastic models. Unlike the existing tests, all Hausman tests are easytoimplement with the limiting null distribution of $\chi^{2}$, and moreover, they are consistent and able to detect the local alternative of order n−1=2. The scope of the Hausman test covers all Generalized error distributions and Student’s t distributions. The performance of each Hausman test is assessed by simulated and real data sets.
Item Type:  MPRA Paper 

Original Title:  Hausman tests for the error distribution in conditionally heteroskedastic models 
Language:  English 
Keywords:  Conditionally heteroskedastic model; Consistent test; GARCH model; Goodnessoffit test; Hausman test; Nonlinear time series. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C12  Hypothesis Testing: General 
Item ID:  66991 
Depositing User:  Dr. Ke Zhu 
Date Deposited:  30 Sep 2015 05:00 
Last Modified:  26 Sep 2019 22:52 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/66991 