Journal of South Asian Development

This article provides a gendered, anti-caste critique of Sulabh International’s widely celebrated rehabilitation model for Dalit women manual scavengers, situating it within the broader field of environmental politics. While Sulabh has demonstrably improved the material conditions of thousands of Dalit women—ending their engagement with manual scavenging and offering new forms of livelihood and public visibility—it simultaneously reproduces caste and gender hierarchies through ritual, symbolism and the authority of a Brahmin male founder. The article argues that the domain of environmental reform, particularly when mediated by social organizations, has not been sufficiently interrogated for how it becomes a site for recalibrating Brahminical patriarchy and operationalizing caste power, with women as its central subjects. The article thus highlights the need to critically engage with the intersection of caste, gender and environment and to reimagine environmental justice through anti-caste and Dalit feminist lenses.

This study explores the presence of the trade credit channel and tests the validity of the pecking order theory (POT) and the market power theory (MPT) of firm capital structure utilizing a dataset of 400 listed non-financial firms in Pakistan. This study further analyses the role of GDP growth (GDPG) and financial sector development (FSD) in establishing the effect of monetary policy (MP) shocks on trade credit demand (TCD). The empirical findings of our extended model incorporating the POT and MPT reveal the positive, significant effect of MP shocks on TCD, indicating that firms substitute trade credit with bank credit during episodes of increased MP shocks. Furthermore, the results show that GDPG strengthens MP shocks’ effect on TCD. Finally, the results show that in periods of higher MP shocks, enhanced FSD significantly facilitates firms to obtain external borrowing, which reduces the positive effect of MP shocks on TCD.

The rise of temporary contract labour or agency work is steadily reshaping employment structures across industries in India. This study investigates the impact of rising contractualization on plant-level productivity in India’s formal manufacturing sector, using unbalanced panel data from the Annual Survey of Industries 1999–2000 to 2018–2019. Our findings show that contract-labour-intensive enterprises have witnessed significant productivity losses, exhibiting 14.6% lower labour productivity and 29.4% lower total factor productivity compared to regular-labour-intensive enterprises. The negative effects are particularly severe in small and medium enterprises and labour-intensive industries. Using fixed-effects regressions and propensity score matching to control for unobserved heterogeneity and self-selection bias, we find robust evidence that greater contract labour intensity is associated with reduced productivity, highlighting the urgent need for policy interventions to reverse the ongoing trend of informalization in the industrial sector.

Nightlights data have emerged as a valuable proxy for economic activity, enabling gross domestic product (GDP) prediction at sub-national levels. The availability of district-level GDP plays a crucial role in understanding regional economic disparities and formulating targeted policy interventions. However, the choice between the Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite (VIIRS) nightlights data remains a critical decision in the context of accurate GDP prediction. This research article aims to address the question: ‘DMSP or VIIRS: Which nightlights data to use for the prediction of GDP in South Asian economies?’ The renowned DMSP nightlights data, despite being widely utilized, have been subject to concerns regarding calibration, top coding and blurring, which may lead to biased GDP predictions and spatial inequality estimates. On the other hand, the VIIRS lights data, a more reliable alternative, have not been fully explored by economists for GDP prediction. To achieve the objectives of this study, the predictive performance of DMSP and VIIRS nightlights data for national GDP is compared, and the suitability of each dataset for district-level GDP estimation is assessed. Additionally, the research examines the impact of both datasets in countries with distinct economic characteristics, such as agricultural and industrial dependence, as well as varying population densities. The findings reveal that VIIRS lights data exhibit superior predictive capabilities for the national GDP of South Asian economies compared to DMSP lights data. This advantage becomes more apparent when using DMSP nightlights data in more spatially aggregated units, such as sub-national administrative units. Nevertheless, this performance difference between the two datasets persists across agriculture-dependent countries, industry-dependent countries, low-population-density countries and high-population-density countries. Notably, our results corroborate Gibson’s observations that the limitations of using DMSP lights data are less evident when applied to more aggregate spatial units, particularly at the national level. By shedding light on the comparative performance of DMSP and VIIRS data, this study contributes to advancing the understanding of the complexities involved in harnessing remote sensing data for economic analysis at the sub-national level.

Gender is frequently overlooked in the analysis of contemporary populist politics, despite its significant influence on the policies enacted by populist regimes. This article aims to elucidate how populism in West Bengal strategically employs social welfare schemes to secure electoral support, particularly targeting female constituents. To facilitate a comprehensive investigation of the dynamics associated with these welfare schemes and their effects on women voters, this study utilizes qualitative research methodologies, specifically through in-depth semi-structured interviews with female participants. Following the transcription of these interviews and a thorough review of the respondents’ feedback, qualitative coding was employed for thematic analysis using NVivo 10, qualitative data analysis software. The results indicate that the respondents demonstrated a predominant awareness of welfare schemes instituted by the state government, whereas awareness of initiatives provided by the central government was notably limited, highlighting a critical gap in communication from national authorities. The welfare populism promoted by the All India Trinamool Congress had a profound impact on the electoral landscape. Participants expressed a sense of empowerment derived from these schemes, perceiving them as just compensation for their undervalued unpaid labour. This emerging sense of empowerment may lead to retrospective voting, as individuals reflect on the benefits accrued from these schemes when making their electoral decisions.