On the construction of confidence intervals for ratios of expectations

Alexis Derumigny (), Lucas Girard () and Yannick Guyonvarch ()
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Alexis Derumigny: CREST
Lucas Girard: CREST
Yannick Guyonvarch: CREST

No 2019-07, Working Papers from Center for Research in Economics and Statistics

Abstract: In econometrics, many parameters of interest can be written as ratios of expectations. The main approach to construct confidence intervals for such parameters is the delta method. However, this asymptotic procedure yields intervals that may not be relevant for small sample sizes or, more generally, in a sequence-of-model framework that allows the expectation in the denominator to decrease to 0 with the sample size. In this setting, we prove a generalization of the delta method for ratios of expectations and the consistency of the nonparametric percentile bootstrap. We also investigate finite-sample inference and show a partial impossibility result: nonasymptotic uniform confidence intervals can be built for ratios of expectations but not at every level. Based on this, we propose an easy-to-compute index to appraise the reliability of the intervals based on the delta method. Simulations and an application illustrate our results and the practical usefulness of our rule of thumb.

Keywords: delta method; confidence regions; uniformly valid inference; sequence of models; nonparametric percentile bootstrap. (search for similar items in EconPapers)
JEL-codes: C18 C19 (search for similar items in EconPapers)
Pages: 60 pages
Date: 2019-04-15
New Economics Papers: this item is included in nep-ore
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