On bootstrap validity for specification testing with many weak instruments

Maximilien Kaffo and Wenjie Wang

Economics Letters, 2017, vol. 157, issue C, 107-111

Abstract: This paper studies the asymptotic validity of bootstrapping the J test of over-identifying restrictions and the Anderson–Rubin (AR) test under many/many weak instrument sequences. We show that the (residual-based) bootstrap consistently estimates the limiting distributions of interest under these asymptotic frameworks. Interestingly, such bootstrap validity holds even if the bootstrap cannot mimic well certain important properties in the model. In addition, the studied bootstrap procedures are easy to implement in practice because they do not require an a priori choice between the conventional asymptotics and the many/many weak instrument asymptotics. Monte Carlo simulation shows that the bootstrap techniques provide a more reliable method to approximate the null distribution of the J and AR test statistics under many/many weak instruments.

Keywords: Bootstrap; J test; Anderson–Rubin test; Many instruments; Weak instruments (search for similar items in EconPapers)
JEL-codes: C12 C15 C26 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176517302318
Full text for ScienceDirect subscribers only

Related works:
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:eee:ecolet:v:157:y:2017:i:c:p:107-111

DOI: 10.1016/j.econlet.2017.06.004

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().