The Swachh Bharat Mission (SBM) in rural India subsidized the construction of over 100 million latrines, aiming to reduce open defecation and improve child health, but it also creates water pollution externalities when fecal sludge is not adequately treated. The study estimates that one more latrine per square kilometer raises river fecal coliform by 3%, and the total SBM policy increases river pollution by about 72% [page::29]. Although diarrheal post-neonatal mortality falls overall, this health gain is offset in areas with inadequate wastewater infrastructure, resulting in a net health effect of about a 10% reduction in diarrheal post-neonatal mortality across districts, with the magnitude depending on upstream treatment capacities [page::22][page::3]. The results highlight the importance of complementary wastewater treatment infrastructure—without which the health benefits of latrine expansion can be substantially weakened—informing the design of phase II SBM and similar sanitation policies [page::30].
This paper develops an analytical general equilibrium model to study carbon offsets, revealing that increasing offset prices can have ambiguous effects on aggregate emissions and welfare. It shows offsets can be over-credited or under-credited due to economy-wide spillovers, and introduces four margins of adjustment (including a newly identified one) by which offsets respond to payments. The study defines conventional and aggregate carbon accounting, demonstrating their divergent implications for welfare and emissions, and highlights potential backfire scenarios in general equilibrium. Policy implications stress the importance of market spillovers when evaluating offsets and suggest MVPF as a welfare-relevant metric over conventional accounting [page::0][page::1].
This paper provides evidence on the impact of the 2022 Dobbs decision on the labor supply of young women (ages 18–24). [page::1]
Exploiting the implementation of state-level abortion bans, I use monthly CPS micro data from January 2021 to December 2023 and estimate Difference-in-Differences (DiD) and Triple-Difference (DDD) models. [page::1]
In a simple DiD comparing young women in ban versus protected states, labor force participation increases by 3.6 percentage points (p < 0.05), while young men’s participation in ban states falls by 2.9 percentage points (p < 0.05). [page::1]
My preferred DDD specification with state-by-month and gender-interacted fixed effects implies a 6.6 percentage point (p < 0.05) increase in labor force participation for young women in ban states relative to young men in the same states. [page::1]
School enrollment does not change, whereas employment rises by about 3 percentage points. [page::1]
These findings indicate that restricted reproductive rights are associated with an immediate increase in young women’s labor market attachment, potentially shifting focus toward current earnings over human capital accumulation in the short run. [page::1]
The study introduces an effort-centric fairness framework for credit scoring that measures the minimum weighted effort for rejected applicants to reach approval, distinguishing feature-independent recourse from causal downstream effects [page::6][page::7]. It derives tractable local surrogates for general differentiable classifiers and exact expressions for logistic regression, enabling in-processing training that embeds effort parity into model fitting and yields explicit pathways to approval [page::9][page::11]. Empirical analysis on a mortgage dataset (HMDA+Freddie Mac) reveals masked inequality: even when predictive parity holds, rejected female applicants face higher recourse burdens; feature-independent regularisation reduces the gap by over 50%, while causal regularisation can achieve reductions above 90% but with larger predictive and risk-return trade-offs [page::21][page::23][page::24][page::25]. Under feature-independent parity, portfolio risk remains broadly stable and RAROC stays positive; under causal parity, losses rise but revenue remains near baseline and RAROC stays positive, illustrating the trade-offs involved [page::23][page::25]. The framework also provides actionable, applicant-level pathways to improve credit outcomes and supports transparent governance and regulatory discussions, with potential by-products of improved predictive parity [page::21][page::26][page::27].