Research & Projects

Working Papers

Job Market Paper

Cheap to Keep: Insurance Pricing and the Retirement of Hazardous Capital

In the midst of the clean energy transition, efficient coordination of hazardous capital retirement has become increasingly important. Much of the policy response operates on the adoption margin, and research on retiring capital already in place has focused largely on subsidies and mandates. This paper studies a different decommissioning instrument: pricing the cost of retaining hazardous capital through mandatory environmental insurance. I examine this question at U.S. gas stations, whose buried fuel tanks are the most commonly reported source of groundwater contamination in the country, and where federal law requires operators to carry pollution coverage but states differ in whether premiums are uniformly priced or risk-rated. I identify the effects of risk-based pricing using Texas's 1998 transition from a uniformly priced state insurance fund to risk-rated private insurance, which repriced 16,625 facilities. Using a panel of 5,587,134 tank-years and a difference-in-differences design that compares Texas tanks with tanks of the same construction and vintage in 23 control states, I find that risk-rated pricing increased annual tank closures by 1.3 percentage points, a 65 percent increase. The effect rises with tank age, from 0.4 points for the youngest quarter of tanks to 3.9 points for tanks 20 years or older at the reform. Small facilities disproportionately exited, while larger facilities replaced tanks and remained in operation. I then estimate a dynamic model of facility portfolio choice and entry to compare risk-based pricing with replacement subsidies and age-based retirement mandates. Among these instruments, risk-rated pricing comes closest to a first-best premium that prices both cleanup costs and health damages. Pricing mandatory environmental insurance is therefore a decommissioning policy, and one that outperforms the alternatives considered here.

Food Loss and the New Volume Control: Strategic Enforcement of Minimum Quality Standards with Application to the Fresh Strawberry Market (with Alexandra E. Hill and Richard J. Sexton)

Draft: (Coming Soon)

Minimum quality standards (MQS) are common in agricultural industries, especially for produce commodities. Prior work on MQS has focused on standards imposed and enforced by governments or industries through marketing orders, geographic indications, and related organizations. In this paper we study volume controls implemented under the guise of MQS set by downstream buyers with market power. We develop a conceptual model to show how firms selling differentiated products and facing downward-sloping demands can use MQS to control sales in the face of demand or supply shocks. Food loss, a significant societal problem targeted by the United Nations, European Commission, and United States government, among others, emerges as an equilibrium outcome in the model. The model is tested empirically using transactions data for a large strawberry grower-shipper who operates multiple farms across California. Results show that product rejections increase in response to negative demand or positive supply shocks, supporting the key predictions of the model.

Data Sets

Agricultural Overtime Laws (with Alexandra E. Hill)

Hill, Alexandra E, and Javier, Kaleb Kanoa. Harmonized US H-2A Visa Performance Disclosure Data. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-04-03. https://doi.org/10.3886/E225441V2

This project harmonizes H-2A visa performance data from the U.S. Department of Labor's Foreign Labor Certification Office. The raw data files for fiscal years 2008-2024 were retrieved from: https://www.dol.gov/agencies/eta/foreign-labor/performance and the data for fiscal years 2006 and 2007 were obtained from a previous (and no longer maintained) version of this website: https://www.flcdatacenter.com/CaseH2A.aspx. The final cleaned dataset includes key variables from these datasets with harmonized variable names. This dataset, for fiscal years 2006-2024, is included in the Output folder. Please see the Readme.md file for instructions on how to update this file with future years of data as they become available, or for details on how to add additional variables into the final cleaned dataset.

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