Inference in dynamic models for panel data using the moving block bootstrap

Ayden Higgins and Koen Jochmans

Papers from arXiv.org

Abstract: Inference in linear panel data models is complicated by the presence of fixed effects when (some of) the regressors are not strictly exogenous. Under asymptotics where the number of cross-sectional observations and time periods grow at the same rate, the within-group estimator is consistent but its limit distribution features a bias term. In this paper we show that a panel version of the moving block bootstrap, where blocks of adjacent cross-sections are resampled with replacement, replicates the limit distribution of the within-group estimator. Confidence ellipsoids and hypothesis tests based on the reverse-percentile bootstrap are thus asymptotically valid without the need to take the presence of bias into account.

Date: 2025-02
New Economics Papers: this item is included in nep-inv
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2502.08311 Latest version (application/pdf)

Related works:
Working Paper: Inference in Dynamic Models for Panel Data Using The Moving Block Bootstrap (2025)
Working Paper: Inference in Dynamic Models for Panel Data Using The Moving Block Bootstrap (2025)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2502.08311

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().