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Omicron Delta Epsilon Graduate Student Session

Paper Session

Friday, Jan. 3, 2025 10:15 AM - 12:15 PM (PST)

Hilton San Francisco Union Square, Union Square 23
Hosted By: Omicron Delta Epsilon
  • Chair: Elizabeth Moorhouse, Lycoming College

Are Nutrient Policy Impacts on Recreation in Lake Erie as Murky as the Water?

Farzaneh Sabbaghziarani
,
University of New Hampshire

Abstract

Lake Erie (LE) provides over $50 billion annually to the regional economy through recreation, fishing, and tourism (Watson et al., 2016). However, it’s torturous history with nutrient pollution has triggered need for environmental reforms like the Clean Water Act in 1972. Despite years of progress, LE is experiencing nutrient pollution again marked by harmful algal blooms (HABs). The Great Lakes Water Quality Agreement, signed by Canada and the US, aims to reduce annual phosphorus loads to LE by 40% by 2025. While lower nutrient loads may reduce HABs and improve water quality, it may lead to lower fish production (IJC, 2020) jeopardizing sustainability of fisheries. These potentially competing ecological impacts could have major implications on the economy and recreation.

Using a random effects Poisson regression, we have results from two preliminary regressions (a basic demographic model and one that includes ecological regressors). From the demographic model, we find that men and younger individuals take more trips, and as expected the number of trips is inversely related to the travel cost. Adding ecological regressors, results indicate that algae and water advisories tend to, counterintuitively, increase trip frequency. We will explore these results in detail and complete the linking of the EwE ecological data once we’ve completed collection of angler survey data to fully quantify the economic impacts of 40NR.

Judicial Gender Bias: the Impact of Victim Gender on Sentencing in Brazil

Camila Gomes
,
Georgetown University

Abstract

Gender-based violence remains a pervasive issue globally, affecting approximately one in three women during their lifetimes (WHO 2021), with significant impacts in regions like Latin America. In Brazil, known for its high rates of femicide, it is not uncommon to hear that impunity is at the root of gender violence. Such impunity is argued to be related to bias against female victims in the criminal justice system. This study investigates potential gender biases in judicial sentencing, specifically detecting whether the sentencing disparities observed can be attributed to gender discrimination by judges related to the gender of the victim.

I use a comprehensive dataset of over 10,000 first-degree criminal cases involving more than 600 judges in the state of Sao Paulo, Brazil, from 2013 to 2018. Compiled by employing extensive text analysis and algorithmic techniques, the dataset is narrowed down to cases resulting in death, primarily homicides and manslaughter, where the defendants are male. This focus allows for the examination of gender biases potentially influencing sentencing outcomes when the victim's gender varies.

I leverage the random assignment of cases to judges, which mitigates potential omitted variable bias, allowing for a cleaner estimation of judicial bias effects. Preliminary findings indicate that sentencing outcomes for crimes against female victims systematically differ from those against male victims, and that this gap cannot be solely explained by statistical discrimination. The results are consistent across various model specifications and robustness checks, and indicate the significant presence of gender bias among judges in Brazil.

Can Technology Enabled Supply Chain Interventions Reduce Market Imperfections? A Case of Mom and Pop Shops in Pakistan

Maham Ashfaq
,
American University

Abstract

In emerging markets, the retail sector and its supply landscape are characterized by a network of highly fragmented family-owned micro-retail stores. Despite the ubiquitous presence of nano stores, they are confronted by distinct operational, logistical, and financial challenges, especially with regard to the backward interactions in their supply chain. In this setting, technological interventions aimed towards digitizing supply chains for small retailers may improve market performance, reduce information asymmetries, and increase welfare for nano store owners. Beginning in 2021, an app-based marketplace that connects nanostores directly to their suppliers was introduced throughout Lahore, a district in Pakistan with a large presence of micro retailers. Collecting micro-level survey data from 850 micro-retail stores in Lahore and using an instrument variable approach, I show that the adoption of technology by nano retailers was associated with a significant reduction in price asymmetry. The welfare of the store owners increased however, the burden of transaction costs shifted from retailers to the suppliers resulting in a significant presence of noise in demand signals.

Risk Adjustment, Selection, and Plan Design in Medicare Advantage

Zhu Liang
,
Stony Brook University

Abstract

This paper explores plan design and selection mechanisms under risk adjustment in Medicare Advantage (MA), unveiling a novel selection mechanism that leverages beneficiaries' private health perceptions. In this government-subsidized market, firms' primary revenue comes from risk-adjusted capitation payments. However, existing risk adjustment methods do not completely neutralize selection biases. Our findings suggest that individuals with optimistic health perceptions tend to be systematically overcompensated, and this heterogeneity in health perceptions drives plan choice. This incentivizes MA firms to design their offerings in ways that attract such individuals, thereby boosting profitability. Our analysis demonstrates how MA firms can feasibly engage in favorable selection on a large scale, even within a tightly regulated environment, elucidating the observed high profit margins, overpayments, and the prevalence of low-premium, low-generosity in MA plans. Employing a structural model, we quantify the impact of private information on plan choice and illustrate how firms exploit this in plan design. This approach provides a comprehensive framework for understanding both consumer and firm behavior in a subsidized insurance market, shedding light on the welfare consequences of imperfect risk adjustment. These findings provide essential insights for policymakers dedicated to improving market efficiency.

Discussant(s)
Zhu Liang
,
Stony Brook University
Farzaneh Sabbaghziarani
,
University of New Hampshire
Camila Gomes
,
Georgetown University
Maham Ashfaq
,
American University
JEL Classifications
  • A1 - General Economics
  • Y8 - Related Disciplines