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稀疏高维结构向量自回归的结构推断AI 解读

We consider statistical inference for impulse responses and forecast error variance decompositions in sparse, structural high-dimensional vector autoregressive (SVAR) systems. We introduce consistent estimators of impulse responses in the high-dimensional setting and suggest valid inference procedures for the same parameters. Statistical inference in our setting is much more involved since standard procedures, like the delta-method, do not apply. By using local projection…

谱密度估计的同时置信带AI 解读

We propose a method for the construction of simultaneous confidence bands for a smoothed version of the spectral density of a Gaussian process based on nonparametric kernel estimators obtained by smoothing the periodogram. A studentized statistic is used to determine the width of the band at each frequency and a frequency-domain bootstrap approach is employed to estimate the distribution of the supremum of this statistic over all frequencies. We prove by means of strong…

渐消加权区块自助法AI 解读

We introduce and study tapered block bootstrap methodology that yields an improvement over the well‐known block bootstrap for time series of Künsch (1989). The asymptotic validity and the favourable bias properties of the tapered block bootstrap are shown. The important practical issues of optimally choosing the window shape and the block size are addressed in detail, while some finite‐sample simulations are presented validating the good performance of the tapered block…