Practical Kolmogorov-Smirnov Testing by Minimum Distance Applied to Measure Top Income Shares in Korea
- Authors
- 박명호
- Issue Date
- 31-Jul-2018
- Publisher
- AMER STATISTICAL ASSOC
- Citation
- JOURNAL OF BUSINESS ECONOMIC STATISTICS, v.36, no.3, pp.523 - 537
- Journal Title
- JOURNAL OF BUSINESS ECONOMIC STATISTICS
- Volume
- 36
- Number
- 3
- Start Page
- 523
- End Page
- 537
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/3386
- ISSN
- 0735-0015
- Abstract
- We study Kolmogorov-Smirnov goodness-of-fit tests for evaluating distributional hypotheses where unknown parameters need to be fitted. Following the work of Pollard (1980), our approach uses a Cramer-von Mises minimum distance estimator for parameter estimation. The asymptotic null distribution of the resulting test statistic is represented by invariance principle arguments as a functional of a Brownian bridge in a simple regression format for which asymptotic critical values are readily delivered by simulations. Asymptotic power is examined under fixed and local alternatives and finite sample performance of the test is evaluated in simulations. The test is applied to measure top income shares using Korean income tax return data over 2007-2012. When the data relate to estimating the upper 0.1% or higher income shares, the conventional assumption of a Pareto tail distribution cannot be rejected. But the Pareto tail hypothesis is rejected for estimating the top 1.0% or 0.5% income shares at the 5% significance level. A supplement containing proofs and data descriptions is available online.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - School of Economics > Economics Major > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/3386)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.