A Comprehensive Understanding the Informal Economy: Income Determinants of Street Hawkers in Dhaka City

Abstract

This study assesses the socio-economic status and income determinant of street hawkers in Dhaka City, Bangladesh, using descriptive statistics and predictive modeling. Structural questionnaires and interviews were conducted to obtain information from 140 street hawkers from four densely populated municipalities. Descriptive analysis revealed street vending to predominantly be a matter for the youths and middle-age group with predominant gender imbalances in favor of males. Majority of them have medium-scale families and minimum educational levels indicative of socio-economic constraints. For predictive modeling, XGBoost with stratified bootstrap sampling was utilized to predict monthly income. The model yielded an average R2 value of 0.336 (±0.044) and an average RMSE of 7,794.30 (±254.89), with the best iteration producing an R2 of 0.465. Importance analysis for features produced gender, age, and education as high predictors, with significant interactions between age and education showing non-linear trends. Gender proved to be the most significant predictor, indicating consistent income inequalities. The age-by-education interaction implies differential economic returns on education by age groups, calling for specialized programs. Non-linear terms established the sophisticated association between age and income. Policymakers should focus on strengthening the informal sector by expanding access to basic education and providing targeted support for older street hawkers to address income disparities and enhance the economic resilience of informal workers in Dhaka