The concept of the autoregressive (AR) sieve bootstrap is investigated for the case of spatial processes in Z2. This … procedure fits AR models of increasing order to the given data and, via resampling of the residuals, generates bootstrap … criterion which allows to decide whether the AR sieve bootstrap asymptotically works for a specific statistic of interest or not …

The concept of the autoregressive (AR) sieve bootstrap is investigated for the case of spatial processes in Z2. This … procedure fits AR models of increasing order to the given data and, via resampling of the residuals, generates bootstrap … criterion which allows to decide whether the AR sieve bootstrap asymptotically works for a specific statistic of interest or not …

bootstrap inference about individual impulse responses and vectors of impulse responses when the horizon is fixed with respect … finite-sample accuracy is achieved when bootstrapping the lag-augmented autoregression using the bias adjustments of Kilian … (1999). The conventional bootstrap percentile interval for impulse responses based on this approach remains accurate even at …

The main contribution of this paper is a proof of the asymptotic validity of the application of the bootstrap to AR … establishing that a suitably constructed bootstrap estimator will have the same limit distribution as the least-squares estimator … robust standard errors or the bootstrap approximation of the distribution of autoregressive parameters. A simulation study …

bootstrap methods also fail to produce consistent estimators. To overcome these problems we develop percentile–t, subsample … bootstrap approximations to estimator distributions. Studentizing is employed to approximate scale, and the subsample bootstrap …

bootstrap techniques, applied to moving-maximum models, may be used to construct confidence and prediction intervals from …