Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/4762
Title: Accuracy of measuring relative poverty: Using Hong Kong as an example
Author(s): Chiu, Dah Ming 
Wong, Yu Cheung 
Cheng, Stephen Chun Chung 
Ng, Felix Sai Kit 
Issue Date: 2025
Publisher: Tsinghua University Press
Journal: Journal of Social Computing 
Volume: 6
Issue: 1
Start page: 51
End page: 62
Abstract: 
Defining poverty based on relative income, intended to identify individuals who are significantly worse off than the mainstream living standard—is widely adopted by more developed countries and regions, such as those in the Organization for Economic Co-operation and Development (OECD). There are, however, different ways income is counted, sometimes only counting earnings (e.g., from employment), sometimes counting government transfers (e.g., social welfare distributions), sometimes counting that generated from savings and investments as well. While some simpler form of income may be used for calculating relative poverty for ease of measurement (or other practical considerations), the intention of the relative poverty definition should be based on full income from all sources (including assets). This paper studies a method for evaluating the inaccuracy caused by using a simpler (and easier to measure) income distribution and understanding where the inaccuracy comes from. We test our method by using a 2000-household dataset from Hong Kong Special Administrative Region, to evaluate the relative poverty approach once adopted there. We also recommend practical alternatives: focusing on economically active households only or using disposable income instead of market income. We show how much such alternatives can improve accuracy and explain why.
URI: https://repository.cihe.edu.hk/jspui/handle/cihe/4762
DOI: 10.23919/JSC.2025.0002
CIHE Affiliated Publication: Yes
Appears in Collections:SS Publication

Files in This Item:
File Description SizeFormat
View Online87 BHTMLView/Open
SFX Query Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.