Four Recent Publications: Nima Rafizadeh on Energy, Water, and the Price of Scarcity : Department of Resource Economics : UMass Amherst

Nima has had a standout run, with four recent publications in leading economics journals. His work examines how energy and water markets respond to scarcity, subsidies, and the shift to renewables, and he also gives economists a practical guide to using machine learning in causal research.

"Welfare loss in electricity markets: economic and environmental Perspectives"

With Pierre-Olivier Pineau, Nima estimates that global electricity subsidies caused about $43.2 billion in welfare losses a year, based on 2016 data, once environmental damage is counted. That equals 4.5% of the electricity market's value in the countries that subsidize power.
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https://doi.org/10.1080/13504851.2025.2569707

"The economics of negative price phenomenon in renewable-integrated electricity markets"

Using more than 14 million observations from New York's electricity markets, Nima shows why wholesale prices sometimes drop below zero. Renewables are the main driver: wind pushes prices negative, while solar makes negative prices less frequent.
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https://doi.org/10.1016/j.eneco.2025.109086

"Pricing scarcity: A machine learning test of water futures efficiency"

Nima uses machine learning to test California's water futures market, the first of its kind. He finds the market loses efficiency as drought deepens, so its price signals are least reliable exactly when they matter most.
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https://doi.org/10.1016/j.frl.2026.110486

"Double/Debiased Machine Learning for Economists: Practical Guidelines, Best Practices, and Common Pitfalls"

With fellow graduate student Maryam Feyzollahi, Nima offers economists a clear roadmap for using machine learning to answer causal questions. The guide covers best practices and clears up a common confusion between cross-validation and cross-fitting.
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https://doi.org/10.1515/snde-2025-0011