A higher-order correct fast moving-average bootstrap for dependent data

Davide La Vecchia, Alban Moor and Olivier Scaillet

Journal of Econometrics, 2023, vol. 235, issue 1, 65-81

Abstract: We develop the theory of a novel fast bootstrap for dependent data. Our scheme deploys i.i.d. resampling of smoothed moment indicators. We characterize the class of parametric and semiparametric estimation problems for which the method is valid. We show the asymptotic refinements of the new procedure, proving that it is higher-order correct under mild assumptions on the time series, the estimating functions, and the smoothing kernel. We illustrate the applicability and the advantages of our procedure for M-estimation, generalized method of moments, and generalized empirical likelihood estimation. In a Monte Carlo study, we consider an autoregressive conditional duration model and we compare our method with other extant, routinely-applied first- and higher-order correct methods. The results provide numerical evidence that the novel bootstrap yields higher-order accurate confidence intervals, while remaining computationally lighter than its higher-order correct competitors. A real-data example on dynamics of trading volume of US stocks illustrates the empirical relevance of our method.

Keywords: Fast bootstrap methods; Higher-order refinements; GeneraLized Empirical Likelihood; Confidence distributions; Mixing processes (search for similar items in EconPapers)
JEL-codes: C12 C15 C22 C52 C58 G12 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Working Paper: A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data (2022)
Working Paper: A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data (2020)
Working Paper: A higher-order correct fast moving-average bootstrap for dependent data (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:235:y:2023:i:1:p:65-81

DOI: 10.1016/j.jeconom.2022.01.008

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