<p><p><p>This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and Anderson, Ge, and Leo (2006) based on kernel estimation techniques. We give the asymptotic distribution theory of our estimator, which in some cases is nonstandard due to a boundary value problem. We also propose a method for conducting inference based on estimation of unknown quantities in the limiting distribution and show that our method yields consistent inference in all cases we consider. We investigate the finite sample properties of our methods by simulation methods. We give an application to the study of polarization within China in recent years.</p></p></p>
Authors
![Gordon Anderson](/sites/default/files/styles/square_desktop/public/2022-07/Gordon%20Anderson.png?itok=_2gdqYut)
Research Associate University of Toronto
Gordon is a Research Associate of the IFS and a Professor in the Department of Economics at the University of Toronto.
![Person graphic](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
Oliver Linton
![Person graphic](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
SNU
Working Paper details
- DOI
- 10.1920/wp.cem.2009.1409
- Publisher
- IFS
Suggested citation
G, Anderson and O, Linton and Y, Whang. (2009). Nonparametric estimation of a polarization measure. London: IFS. Available at: https://ifs.org.uk/publications/nonparametric-estimation-polarization-measure (accessed: 3 July 2024).
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