Abstract
The double bootstrap is an important advance in confidence interval generation because it converges faster than the already popular single bootstrap. Yet the usual double bootstrap requires a stable pivot that is not always available, e.g., when estimating flexibilities or substitution elasticities. A recently developed double bootstrap does not require a pivot. A Monte Carlo analysis with the Waugh data finds the double bootstrap achieves nominal coverage whereas the single bootstrap does not. A useful artifice dramatically decreases the computational time of the double bootstrap.
Original language | English (US) |
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Pages (from-to) | 552-559 |
Number of pages | 8 |
Journal | American Journal of Agricultural Economics |
Volume | 80 |
Issue number | 3 |
DOIs | |
State | Published - Aug 1998 |
Externally published | Yes |
Keywords
- Confidence interval
- Convergence
- Elasticity
- Flexibility
- Iterated bootstrap
- Pivot
ASJC Scopus subject areas
- Agricultural and Biological Sciences (miscellaneous)
- Economics and Econometrics