Research

Working Papers

The Impacts of TRAP Laws on the Supply of Maternal Care Providers, with Pinka Chatterji and Chun-Yu Ho (Job Market Paper)

Under Review 

Abstract: This study examines the impacts of Targeted Regulation of Abortion Providers (TRAP laws) on the supply of maternal care providers by exploiting the staggered enactment of TRAP laws across states. Our findings indicate a significant decrease in the number of Obstetrician-Gynecologists (OB/GYNs) by 3.38 to 3.55 per 100,000 females aged 15-44 following the enactment of TRAP laws. Furthermore, the passage of TRAP laws affects the composition of OB/GYNs. The decline in response to TRAP laws is particularly pronounced among OB/GYNs under the age of 34 and those between the ages of 55 and 64. Newly graduated OB/GYNs, especially those from lower-ranked medical schools, also reduce their presence in states enacting TRAP laws. Although we do not find significant changes in applicants to OB/GYN residency programs or medical schools in response to TRAP laws, in-state applicants tend to shift their applications from private medical schools, which are often higher-ranked, to public medical schools. 

Presented at: 

• Eastern Economic Conference Annual Meeting, New York City, NY 2025

• Allied Social Science Associations Annual Meeting, San Francisco, CA 2025

• Southern Economic Conference Annual Meeting, Washington, DC 2024

• Association for Public Policy Analysis and Management Research Conference, National Harbor, MD 2024

Award:

• Institute for Humane Studies Expense Support (External Funding), $2,189, 2025

• Department of Economics Student Travel Award, University at Albany, $500, 2025

• The Karen R. Hitchcock New Frontiers Fund for Research, Initiatives for Women, $700, 2024

Import Competition and Racial Disparities in Mortality: Evidence from the Japanese Trade Shock, with Pinka Chatterji and Chun-Yu Ho

2nd Revise and Resubmit at Health Economics

Abstract: This paper examines the effects of increased trade between Japan and the U.S. on mortality rates in the U.S. using a shift-share instrumental variables approach. Overall, we find that an increase in Japanese imports is associated with higher rates of drug-related mortality and cardiovascular disease (CVD) mortality, and lower rates of mortality from accidents. These effects exhibit significant racial disparities. Specifically, a $1,000 increase in import competition is associated with a 13.5% increase in drug-related deaths per 100,000 Black individuals aged 20-64 years old compared to a 7.8% increase among white individuals. Additionally, a $1,000 increase in import competition is associated with a 3.0% increase in CVD deaths per 100,000 Black individuals aged 20-64 years old, while there is no statistically significant effect among whites. Effects on mortality rates from accidents are driven by deaths among whites. Our findings also indicate that the rise in drug-related and CVD mortality is concentrated among males and in regions with relatively high shares of employment in the automobile or computer industries.

Presented at: 

• American Society of Health Economists Annual Meeting, San Diego, CA 2024

• Annual Meetings of the Midwest Economics Association, Chicago, IL 2024

• Eastern Economic Association Conference, Boston, MA 2024

Award:

• Graduate Student Association Grant Award, $585, 2025

• Department of Economics Student Travel Award, University at Albany, $400, 2024

Medicare Part D and Retirement Lock: The Role of the Affordable Care Act and Medicaid Expansion (Best Third Year Paper, UAlbany)

Under Review

Award:

• Center for Aging and Policy Studies Travel Grant (External Funding), $1,500, 2022

• The Karen R. Hitchcock New Frontiers Fund for Research, Initiatives for Women, $1,000, 2022

Geographic and Racial/Ethnic Disparities in the Density of Maternal Health Care Providers, with Pinka Chatterji, David Strogatz, Anne M. Gadomski, and Chun-Yu Ho

Selected Publications

(# indicates equal contribution and co-first author)

• Quan Qi#, Yukang Xue#, Najm A. Madani, Randy Tangang, Fangqun Yu, Arshad A. Nair, Xiaobo Romeiko Xue, Gan Luo, Isa Brackett, Chris Thorncroft, and Shao Lin (2025). Individual Effects and Interactions Between Ultrafine Particles and Extreme Temperatures on Hospital Admissions of High Burden Diseases. Environment International, 109348.

• Shao Lin, Yukang Xue, Sathvik Thandra, Quan Qi, Sally W. Thurston, Daniel P. Croft, Mark J. Utell, Philip K. Hopke, and David Q. Rich (2025). Source Specific Fine Particles and Rates of Asthma and COPD Healthcare Encounters Pre-and Post-implementation of the Tier 3 Vehicle Emissions Control Regulations. Journal of Hazardous Materials, 136737.

• Shao Lin#, Quan Qi#, Han Liu, Xinlei Deng, Ian Trees, Xiaojun Yuan, Mary P. Gallant (2024). The Joint Effects of Thunderstorms and Power Outages on Respiratory-related Emergency Visits and Modifying and Mediating Factors of This Relationship. Environmental Health Perspectives, 132(6):67002.

  • Featured on University at Albany News, covered by Medical Xpress.

• Quan Qi, Fangqun Yu, Arshad A. Nair, Sam S. S. Lau, Gan Luo, Imran Mithu, Wangjian Zhang, Sean Li, Shao Lin (2024). Hidden Danger: The Long-term Effect of Ultrafine Particles on Mortality and Its Sociodemographic Disparities. Journal of Hazardous Materials, 134317.

  • Featured on The Conversation and University at Albany News, covered by Medical Xpress.

• Shao Lin#, Yukang Xue#, Sathvik Thandra, Quan Qi, Philip K. Hopke, Sally W. Thurston, Daniel P. Croft, Mark J. Utell, David Q. Rich (2024). 𝑃𝑀2.5 and Its Components and Respiratory Disease Healthcare Encounters - Unanticipated Increased Exposure-response Relationships in Recent Years After Environmental Policies. Environmental Pollution, 124585.

• Arshad A. Nair, Shao Lin, Gan Luo, Ian Ryan, Quan Qi, Xinlei Deng, Fangqun Yu (2023). Environmental Exposure Disparities in Ultrafine Particles and 𝑃𝑀2.5 by Urbanicity and Sociodemographics in New York State, 2013-2020. Environmental Research, 239: 117246.

Selected Work in Progress

Predicting Health Risk for Cardiovascular Diseases Based on Individual, Social, Community and Local Environmental Factors Using Machine Learning Methods, with Shao Lin