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date: 26 June 2022

An Introduction to Bootstrap Theory in Time Series Econometricslocked

An Introduction to Bootstrap Theory in Time Series Econometricslocked

  • Giuseppe Cavaliere, Giuseppe CavaliereDepartment of Economics, University of Bologna; Department of Economics, University of Exeter
  • Heino Bohn NielsenHeino Bohn NielsenDepartment of Economics, University of Copenhagen
  •  and Anders RahbekAnders RahbekDepartment of Economics, University of Copenhagen

Summary

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.

Subjects

  • Econometrics, Experimental and Quantitative Methods

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