While often simple to implement in practice, application of the bootstrap in econometric modeling of economic and nancial 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 dier from standard asymptotic testing, which can be illustrated by simulations.

Cavaliere, G., Nielsen, H.B., Rahbek, A. (2021). An Introduction to Bootstrap Theory in Time Series Econometrics. Oxford : Oxford University Press [10.1093/acrefore/9780190625979.013.493].

An Introduction to Bootstrap Theory in Time Series Econometrics

Cavaliere, Giuseppe;
2021

Abstract

While often simple to implement in practice, application of the bootstrap in econometric modeling of economic and nancial 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 dier from standard asymptotic testing, which can be illustrated by simulations.
2021
Oxford Encyclopedia of Economics and Finance
1
43
Cavaliere, G., Nielsen, H.B., Rahbek, A. (2021). An Introduction to Bootstrap Theory in Time Series Econometrics. Oxford : Oxford University Press [10.1093/acrefore/9780190625979.013.493].
Cavaliere, Giuseppe; Nielsen, Heino Bohn; Rahbek, Anders
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/849287
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