Exposure to benzene, toluene, ethylbenzene, and xylenes (BTEX) in indoor and outdoor environments poses significant health risks in rapidly urbanising cities. This study quantified BTEX concentrations and assessed the associated risks of cancer and non-cancer effects in urban (Mirpur) and industrial (Tejgaon) areas of Dhaka, Bangladesh. Six locations—three in each area—representing residential indoor (Mukti Housing, Mirpur), residential outdoor roadside (Mirpur 10 Fire Service Station), residential outdoor park (National Botanical Garden), industrial residential (Tejkunipara, Tejgaon), industrial roadside (Farmgate), and industrial ambient (BITAC, Tejgaon) microenvironments — were selected for sampling campaigns conducted from 30 August to 11 September, 2013. Air samples were collected during daytime hours (09:00–17:00) using active sampling with Tenax TA sorbent tubes and analysed by thermal desorption gas chromatography–mass spectrometry (TD-GC-MS). A total of 44 VOCs were quantified, with BTEX compounds prioritised for detailed health risk assessment. Mean ∑BTEX concentrations ranged from 13.95 µg/m³ at the urban park site to 48.74 µg/m³ at the industrial roadside site. Benzene posed the highest cancer risk, with excess lifetime cancer risk (ELCR) values ranging from 2.5 × 10⁻⁵ to 9.0 × 10⁻⁵, exceeding the U.S. EPA benchmark of 1 × 10⁻⁶. Hazard quotients (HQs) for individual BTEX compounds remained below 1; however, cumulative non-cancer risks (ΣHQ) slightly exceeded unity in industrial sites, indicating potential adverse effects from combined exposures to these compounds. Key limitations include short-term monitoring, daytime-only sampling, and limited temporal coverage (six samples per site), which may result in an underestimate of seasonal or long-term variability. Nevertheless, the findings reveal elevated BTEX levels and associated health risks in densely populated and industrialised areas of Dhaka, underscoring the need for long-term monitoring, emission control, and targeted public health interventions.
This study examines the association between economic growth and selected welfare-related macroeconomic indicators in Bangladesh using annual data from 1995 to 2024. Household consumption expenditure growth, employment-to-population ratios, and remittance inflows are considered as indicators reflecting aggregate household economic conditions. The analysis employs descriptive statistics, correlation analysis, Granger causality tests, and a Chow breakpoint test to explore short-run predictive relationships and the stability of welfare–growth linkages over time. The results indicate a strong association and predictive linkage between household consumption growth and GDP per capita growth, while employment and remittance inflows exhibit weaker or statistically insignificant relationships. The Chow breakpoint test identifies a significant structural change around 2020, suggesting instability in established welfare–growth associations during the COVID-19 shock. The findings are exploratory and diagnostic in nature and should be interpreted as indicative macro-level patterns rather than causal effects. Overall, the study provides updated evidence on consumption-growth dynamics and welfare–growth linkages in Bangladesh.
Using data from the Indonesia Family Life Survey 2007, we examine intergenerational interactions between income and parental choice of madrassas for their children’s education. We first estimate the effects of household income on children’s madrassa enrollment using rainfall variation as an instrument for household income to correct for biases due to unobserved ability and preference heterogeneity and measurement error. Other things being equal, doubling household expenditure reduces children’s probability of madrassa enrollment by about 34 percentage points. The estimated negative income effect is robust to various specifications. We then estimate whether returns to education vary between madrassa and general schools. OLS estimates of returns to education show that the average earnings of junior general school graduates are about 26.5 per cent higher than those of junior madrassa graduates. We exploit selection on observables as a guide to selection on unobservables (Oster, 2016) to estimate the returns to education. The relatively low returns to Madrassa education remain intact even when selection on unobservables is twice as large as the selection on observables. Estimates based on the heteroskedasticity-based identification approach of Klein and Vella (2009b) also suggest a similar pattern. Results from the school choice model in conjunction with the market returns to education indicate that madrassa education generates a low-income trap for households. That is, households with lower income send children to madrassas, and those children are expected to earn less than the general school graduates. In turn, because children of madrassa-educated parents have lower income, they send their offspring to madrassas. This intergenerational persistence in madrassa education can be described as a “madrassa trap”.
This study examines the poverty rate among manufacturing workers in Bangladesh using a unique primary dataset of 3005 workers. It estimates a poverty line for manufacturing workers by applying the Cost of Basic Needs (CBN) method. The paper uncovers two stylised facts. First, the estimated upper and lower poverty rates of these workers are 27.89 per cent and 8 per cent, respectively, both of which are significantly higher than the official rural-urban and national poverty rates. It indicates that poverty is much more intense among these workers. Second, the study identifies significant intra-industry variation in poverty incidence. Workers in export-oriented RMG industries have been found to have a lower poverty rate, followed by workers in domestic industries and export-oriented non-RMG industries. This study finds that intra-industry variation is mainly driven by three dimensions of labour market segmentation: industry size, human capital, and gender-specific employment. The large size of the RMG industry enables firms to offer higher minimum wages, bonuses, and overtime pay than other industries. In addition, the RMG sector employs more women, making it more likely that both husbands and wives are employed and thereby increasing household income. Higher levels of education among RMG workers also contribute to higher wages. Regression results further confirm that human capital, gender-specific employment, and industry-level segmentation are significant determinants of poverty and largely explain the observed variation in poverty across manufacturing industries.
This empirical study examines whether trade unionisation among manufacturing workers in Bangladesh has a significant impact on their gross wages compared to non-unionised workers. A survey of 3,005 manufacturing workers’ households across 20 types of manufacturing industries in three districts around Dhaka (including Dhaka) has been conducted. Apart from using OLS estimation methods, the paper employs the Two-Stage Least Squares (2SLS) IV estimation method to address the issue of endogeneity in the wage determination model associated with the unionisation variable. The study finds that unionised workers receive higher wages than non-unionised workers, but part of this differentiation is explained by their greater “on-the-job” experience. Additionally, workers in the readymade garments (RMG) sector receive higher wages than those in non-RMG industries, and the wage premium is especially large for unionised RMG workers. Results from this study offer important insights into the impact of trade unionisation on the wages of manufacturing workers and its policy implications for the sector’s wage structure, while also highlighting the need for further investigation into other dimensions, such as non-wage benefits for workers.
