Publication Type
Working Paper
Version
publishedVersion
Publication Date
11-2018
Abstract
This paper considers the grid bootstrap for constructing confidence intervals for the persistence parameter in a class of continuous time models driven by a Levy process. Its asymptotic validity is established by assuming the sampling interval (h) shrinks to zero. Its improvement over the in-fill asymptotic theory is achieved by expanding the coefficient-based statistic around its in fill asymptotic distribution which is non-pivotal and depends on the initial condition. Monte Carlo studies show that the gird bootstrap method performs better than the in-fill asymptotic theory and much better than the long-span theory. Empirical applications to U.S. interest rate data highlight differences between the bootstrap confidence intervals and the confidence intervals obtained from the in- fill and long-span asymptotic distributions.
Keywords
Grid bootstrap, In-fill asymptotics, Continuous time models, Long-span asymptotics.
Discipline
Econometrics
Research Areas
Econometrics
First Page
1
Last Page
40
Publisher
SMU Economics and Statistics Working Paper Series, No. 20-2018
City or Country
Singapore
Citation
LUI, Yiu Lim; XIAO, Weilin; and YU, Jun.
The grid bootstrap for continuous time models. (2018). 1-40.
Available at: https://ink.library.smu.edu.sg/soe_research/2210
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.