Ian Fletcher

with Stefano Carattini, Chad Kendall, Michael Price, and Arthur Vu

Experience with Washington’s cap-and-invest program transformed initial opposition to carbon pricing into broader support for the policy. Voter data and survey evidence show that firsthand experience, rather than ideology, drove this shift—boosting approval specifically for the policy voters lived under.

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with Faith Fatchen, Uditi Karna, Faisal Kattan, and John List

The paper develops an economic model explaining how countries shift early childhood development investments from health to education as they grow richer and survival improves. Using global data, it finds that nations first focus on survival-related spending, then sharply increase education investment with rising income and health quality—highlighting the importance of sequencing and tailoring ECD policies to the development stage rather than adopting uniform strategies.

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with Todd Cherry and George Loewenstein

The paper investigates how making disaster outcomes more tangible—by revealing whether losses were preventable—affects individual investment in risk mitigation. Using a theoretical model and a 2×2 lab experiment, it shows that when people can attribute outcomes to their own actions, they invest more in prevention after both success and failure, highlighting that causal feedback and observability are key to sustaining preventive behavior.

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with David Finnoff and Sean Bertalot

This paper develops a seasonal dam-management model for Jackson Lake that accounts for competing water uses, ecological processes, and institutional constraints under changing environmental conditions. The results show that observed release decisions are best explained by the value of unpriced ecological services rather than compact restrictions alone, suggesting that models that ignore ecological dynamics can incorrectly characterize water management as inefficient.

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with Todd Cherry and George Loewenstein

The paper investigates how making disaster outcomes more tangible—by revealing whether losses were preventable—affects collective investment in risk mitigation. Using a theoretical model and a 2×2 lab experiment, it shows that when people can attribute outcomes to their own actions, they invest more in prevention after both success and failure, highlighting that causal feedback and observability are key to sustaining preventive behavior.

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with Todd Cherry

Prevention policies that successfully avert disasters—epidemics, bridge collapses, catastrophic wildfires—rarely earn political credit because their success is the absence of an event, leaving no detectable outcome and no clear actor to reward. This paper develops a framework built on two dimensions, outcome detectability and cause–effect attribution, to explain this "curse of intangibility" and proposes institutional reforms—dedicated multi-year prevention budgets, risk-weighted leading indicators, and independent prevention scorekeeping—to make avoided harms visible, auditable, and rewardable.

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