Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/27113
Title: Do elderly want to work? Modeling elderly’s decision to fight aging Thailand
Authors: Kantachote K.
Wiroonsri N.
Keywords: Aging society
Elderly retirement
Lasso logistic regression
Machine learning
Random forest
Thailand
Issue Date: 2022
Publisher: Springer Science and Business Media B.V.
Abstract: Thailand has entered into an aging society since the year 2000. Using the 2017 Survey of the Older Persons in Thailand collected by National Statistical Office of Thailand, this study uses cross tabulation, random forest with variable importance measure and lasso logistic regression to examine factors that have effects on the elderly’s decision to remain in the labor market after retirement. This study reveals that these following variables: age, education level, healthcare eligibility, marital status, health condition, total assets, gender, residential type, percent of elderly in the household, and number of children have strong influences on an elderly’s desire to continue work. By knowing which factors contribute to the elderly wish to continue work in the market, this research allows for future prediction of the labor market that can accommodate elderly in Thailand. Our final models of random forest and lasso logistic regression provide prediction accuracy of 68.19 and 69.58 percent on the elderly’s desire to work, respectively. This study has a significant impact as policymakers can utilize our models in predicting elderly’s desire to work after retirement age and design a labor market that can accommodate elderly in Thailand in the future. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127308404&doi=10.1007%2fs11135-022-01366-0&partnerID=40&md5=6e7c854661bdecd91cefcf2f0d9cc332
https://ir.swu.ac.th/jspui/handle/123456789/27113
ISSN: 335177
Appears in Collections:Scopus 2022

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