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Heavy-Tail and Plug-In Robust Consistent Conditional Moment Tests of Functional Form


Jonathan B. Hill


University of North Carolina (UNC) at Chapel Hill – Department of Economics

May 17, 2012


Abstract:     
We present asymptotic power-one tests of regression model functional form for heavy tailed time series. Under the null hypothesis of correct specification the model errors must have a finite mean, and otherwise only need to have a fractional moment. If the errors have an infinite variance then in principle any consistent plug-in is allowed, depending on the model, including those with non-Gaussian limits and/or a sub-root(n)-convergence rate. One test statistic exploits an orthogonalized test equation that promotes plug-in robustness irrespective of tails. We derive chi-squared weak limits of the statistics, we characterize an empirical process method for smoothing over a trimming parameter, and we study the finite sample properties of the test statistics.

Number of Pages in PDF File: 36

Keywords: conditional moment test, tail trimming, heavy tails

JEL Classification: C13, C20, C22

working papers series


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Date posted: August 22, 2011 ; Last revised: May 18, 2012

Suggested Citation

Hill, Jonathan B., Heavy-Tail and Plug-In Robust Consistent Conditional Moment Tests of Functional Form (May 17, 2012). Available at SSRN: http://ssrn.com/abstract=1914104 or http://dx.doi.org/10.2139/ssrn.1914104

Contact Information

Jonathan B. Hill (Contact Author)
University of North Carolina (UNC) at Chapel Hill – Department of Economics ( email )
Chapel Hill, NC 27599
United States
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