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Moment-based tests under parameter uncertainty

Bontemps, Christian (2019) Moment-based tests under parameter uncertainty. Review of Economics and Statistics, 101 (1). pp. 146-159.

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This paper considers moment-based tests applied to estimated quantities. We propose a general class of transforms of moments to handle the parameter uncertainty problem. The construction requires only a linear correction that can be implemented in-sample and remains valid for some extended families of non-smooth moments. We reemphasize the attractiveness of working with robust moments, which lead to testing procedures that do not depend on the estimator. Furthermore, no correction is needed when considering the implied test statistic in the out-of-sample case. We apply our methodology to various examples with an emphasis on the backtesting of value-at-risk forecasts.

Item Type: Article
Language: English
Date: March 2019
Refereed: Yes
Place of Publication: Cambridge
Uncontrolled Keywords: moment-based tests, parameter uncertainty, out-of-sample, discrete distributions, value-at-risk, backtesting
JEL Classification: C12 - Hypothesis Testing
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 30 May 2018 07:07
Last Modified: 23 May 2019 13:01
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