Survey weighted estimating equation inference with nuisance functionals

Puying Zhao, David Haziza and Changbao Wu

Journal of Econometrics, 2020, vol. 216, issue 2, 516-536

Abstract: This paper provides a rigorous treatment on design-based estimating equation inference using complex survey data in the presence of nuisance functionals. The proposed design-based framework covers parameters from inequality measures and measures on performance evaluation in economic, business and financial studies but the scope of the paper is more broad. Unlike nuisance parameters in other settings where profile analysis is commonly used, the nuisance functionals are typically handled by using a “plug-in” estimator. We establish root-n consistency and asymptotic normality for parameters defined through survey weighted smooth or non-differentiable estimating functions even if the “plug-in” estimator for the nuisance functional has a convergence rate slower than root-n. A multiplier bootstrap procedure is proposed for three types of commonly used survey designs to tackle the challenge task of variance estimation. Results from a simulation study and an application to a real survey data set demonstrate the effectiveness of the proposed design-based inference on the Lorenz curve.

Keywords: Complex survey; Design-based inference; Empirical likelihood; Generalized method of moments; Inequality measure; Multiplier bootstrap; Non-smooth estimating function; Unequal probability sampling (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407619302404
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:econom:v:216:y:2020:i:2:p:516-536

DOI: 10.1016/j.jeconom.2019.11.003

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().