An Introduction to Bootstrap Theory in Time Series Econometrics

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

While often simple to implement in practice, application of the bootstrap in econometric modeling of economic and financial time series requires establishing validity of the bootstrap. Establishing bootstrap asymptotic validity relies on verifying often nonstandard regularity conditions. In particular, bootstrap versions of classic convergence in probability and distribution, and hence of laws of large numbers and central limit theorems, are critical ingredients. Crucially, these depend on the type of bootstrap applied (e.g., wild or independently and identically distributed (i.i.d.) bootstrap) and on the underlying econometric model and data. Regularity conditions and their implications for possible improvements in terms of (empirical) size and power for bootstrap-based testing differ from standard asymptotic testing, which can be illustrated by simulations.
OriginalsprogEngelsk
TitelOxford Research Encyclopedia of Economics and Finance
RedaktørerJonathan H. Hamilton, Avinash Dixit, Sebastian Edwards, Kenneth Judd
ForlagOxford University Press
Publikationsdato2021
ISBN (Elektronisk)9780190625979
DOI
StatusUdgivet - 2021

ID: 248288328