Do elderly want to work? Modeling elderly's decision to fight aging Thailand

TL;DR

This study models the factors influencing elderly Thai individuals' decisions to continue working post-retirement using statistical and machine learning methods, aiding policymakers in designing inclusive labor markets.

Contribution

It identifies key demographic and socioeconomic factors affecting elderly work desire and develops predictive models with over 68% accuracy.

Findings

Age, education, health, assets, and family size significantly influence work desire.

Random forest and lasso logistic regression models achieve around 68-70% prediction accuracy.

Results can inform policies to better integrate elderly into the workforce.

Abstract

Thailand has entered into an aging society since the year 2000. Using the 2017 Survey of the Older Persons in Thailand collected by Thailand National Statistical Office, 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.