Income Inequality from Working While Studying: A Spatial Analysis of Factors and Work Characteristics Influencing Wages among Thai Students

Abstract

This study aims to (1) examine the determinants of hourly wages among students who work while studying, (2) analyze the relationship between working hours and weekly income, and (3) assess income inequality within this group. Using secondary data from the 2022 National Labor Force Survey, the analysis focused on 1,960 student workers. Two empirical approaches were employed: Quantile Regression to capture distributional differences in wage determinants across hourly wage levels, and Ordinary Least Squares (OLS) regression to estimate the association between working hours and weekly income. Quantile Regression results show that age has a positive association with hourly wages (β = 1.102–2.084), with stronger effects at higher wage quantiles. Working hours exhibit a negative relationship with hourly wages (β = –0.312 to –0.525), while part-time student workers earn higher hourly wages than those working full-time (β = –2.980 to –5.310). A significant interaction effect between region and industry (β = 0.012) highlights spatial disparities in labor market returns. The OLS results indicate that each additional working hour increases weekly income by 31.56 baht. Wage inequality among student workers is moderate, reflected by a Gini coefficient of 0.276 and a P90/P10 ratio of 3.62. Inequality is more pronounced in urban areas (0.289) than in rural areas (0.255). This study contributes to the empirical literature by applying Quantile Regression to analyze wage structures among student workers in a developing-country context and provides the first systematic evidence of spatial interaction effects on student wages in Thailand. The findings underscore the need for targeted policies that support working students, reduce regional disparities, and promote access to higher-quality part-time employment opportunities.