2026 Theses Doctoral

Essays in Environmental and Labor Economics

Farkas, Hannah

This dissertation is a collection of chapters on the adaptive capacity of individuals to respond and recover from shocks, and how private, public, and political institutions help or hinder their resilience. I focus largely on the incidence of weather and climate events, examine who bears the risk associated with these hazards, and investigate the policy landscape that impacts recovery ability.

The first chapter studies the economic incidence of schedule unpredictability among hourly workers in the U.S. Workers in hourly service jobs frequently experience shift cancellations, schedule adjustments, and unpredictable hours, often referred to as ‘just-in-time’ scheduling. Despite imposing significant costs on workers, we know surprisingly little about the prevalence and costs of this practice. I use a large administrative dataset featuring information on nearly 1 million employees’ scheduled and worked hours to first illustrate patterns of schedule unpredictability at thousands of small food and drink and retail businesses across the U.S. I show that baseline schedule unpredictability is widespread, and is the most severe for the lowest-wage and least-tenured workers. Using exogenous weather shocks which are known to diminish consumer demand, I examine how these customer-facing establishments pass risk of slow business days onto workers through unpredictable scheduling. I then leverage the fact that most hourly service workers earn at or near the minimum wage to examine the tradeoff between schedule predictability and wages. Following large exogenous minimum wage increases, schedule unpredictability increases by 20% per week and schedules become even more responsive to weather shocks. This highlights how some of the welfare gains workers realize from a minimum wage may be offset by increased schedule unpredictability.

The second chapter examines whether bureaucrats preemptively reflect the executive politician’s preferences in their decisions. Combining novel administrative data from the Federal Emergency Management Agency (FEMA) with hydrological models, we find that a standard deviation decrease in a county’s alignment with the president leads to a 1.5-5 percentage point drop in the probability of bureaucrats flagging a county as requiring federal aid following small to average-sized flooding events. This bias disappears in the most severe floods. We find evidence suggesting that such biases are significantly reduced when a career civil servant is overseeing the bureaucratic process rather than a political appointee.

The third chapter systematically reviews the literature that quantifies the economic benefits of weather observations and forecasts in four weather-dependent economic sectors: agriculture, energy, transport, and disaster-risk management. The review covers 175 peer-reviewed journal articles and 15 policy reports. Findings show that the literature is concentrated in high-income countries and most studies use theoretical models, followed by observational and then experimental research designs. Forecast horizons studied, meteorological variables and services, and monetization techniques vary markedly by sector. Estimated benefits even within specific subsectors span several orders of magnitude and broad uncertainty ranges. An econometric meta-analysis suggests that theoretical studies and studies in richer countries tend to report significantly larger values. Barriers that hinder value realization are identified on both the provider and user sides, with inadequate relevance, weak dissemination, and limited ability to act recurring across sectors. Policy reports rely heavily on back-of-the-envelope or recursive benefit-transfer estimates, rather than on the methods and results of the peer-reviewed literature, revealing a science-to-policy gap.

These findings suggest substantial socioeconomic potential of hydrometeorological services around the world, but also knowledge gaps that require more valuation studies focusing on low- and middle-income countries, addressing provider- and user-side barriers and employing rigorous empirical valuation methods to complement and validate theoretical models.