Remy Beauregard
I am a Visiting Assistant Professor of Economics at the University of San Francisco. My office is McLaren 108. My research fields are behavioral, experimental, and development economics. I received my PhD from UC Davis in Summer 2026.
Contact: rbeauregard@usfca.edu remy.g.beauregard@gmail.com
Affiliations: Future of Labor Lab
Research
Publications
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Inflation Expectations and Risk Premia in Emerging Bond Markets: Evidence from Mexico
with Jens H. E. Christensen, Eric Fischer, and Simon Zhu · Journal of International Economics 2024
To study inflation expectations and associated risk premia in emerging bond markets, we provide estimates for Mexico based on an arbitrage-free dynamic term structure model of nominal and real bond prices that accounts for their liquidity risk. Beyond documenting the existence of large and weakly correlated liquidity premia in nominal and real bond prices, our results indicate that long-term inflation expectations in Mexico are well anchored close to the Bank of Mexico’s inflation target. Furthermore, Mexican inflation risk premia are larger and more volatile than those in Canada and the United States.
Working Papers
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Paid With(out) Purpose: Perceptions, Preferences, and the Meaning of Work
Job Market Paper
Many workers value meaningful work and are willing to give up pay for it, but it is not yet known whether a worker's perception of how meaningful a task is can identify the workers who value meaning. I conduct an online experiment with 832 US workers that measures perceptions of work meaning separately from preferences over it. I offer two framings of the same image description task, elicit meaningfulness at the worker-task level, and classify workers by the pay and meaning their choices forgo in incentivized choice rounds. I find that among workers who rank the two tasks strictly, 35.4% make choices consistent with placing no weight on meaning, 17.2% with placing no weight on pay, and 43.9% with valuing both. Perceptions do not cleanly identify these preferences: pay-maximizers and mixed incentive-types, who differ in whether they ever give up pay for meaning, rate both tasks indistinguishably, and meaning-maximizers rate the prosocially framed task no higher than pay-maximizers. Across four randomly assigned work rounds, assigning workers the task rated more meaningful on average leads to quite different conclusions than each worker's own report of meaning, and in exploratory analyses by incentive type, the relationship between perceived meaning and output does not differ between workers who value meaning and pay-maximizers. These results suggest that perceptions of and preferences for work meaning are distinct, and that designs relying on average ratings of meaning may misestimate the effects of meaningful work.
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What Moves Meaning? Investigating Drivers of an Idiosyncratic Incentive
I develop an online experiment with 832 participants on Prolific to examine how five light-touch interventions, drawing on two distinct approaches, information emphasizing the social importance of a task and prompts asking workers to generate their own reasons for a task's importance or to reflect on what they personally find meaningful, affect the subjective experience of work. Each intervention is randomized against a no-intervention arm within the data collection waves in which it was fielded. No intervention detectably moves the average perceived meaningfulness of either task, perceived difficulty, satisfaction, mood, or the incentives workers reveal in paid choices: all ten estimated effects on before-working meaningfulness are positive, but none is significant at the 5% level, and pooled across interventions the effects are bounded below the difference in rated meaning between the two task framings. In exploratory analyses by incentive type, the positive estimates are concentrated among workers whose paid choices reveal that they value meaning, and these estimates are smaller after working. Together, these findings suggest that perceived work meaning is difficult to move with brief prompts, but that any gains are likely to be concentrated among workers who already value meaning.
Ongoing Projects
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What Workers Keep? AI, Task Allocation, and the Meaning of Work
with Yong Suk Lee and Siting Estee Lu · Designing Phase 2 survey
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Benefits on the Bench: Workfare, Mental Health, and the Role of the Team
with Carlos Brito · Design presented at Advances with Field Experiments Conference (UChicago 2025)
Recent studies have found large positive effects of working compared to pure cash transfers on various measures of mental health for labor demand-constrained populations. We hypothesize that some such benefits could stem from belonging to and training with a team even if one is not ultimately selected to work, which we term as "being on the bench". This study proposes a novel field experiment to investigate the effects of being placed on the bench by a randomized employment lottery for forcibly displaced Venezuelan migrants in Roraima, a Brazilian border state. This population is understood to have both high unemployment and job-seeking as well as poor mental health, making them both appropriate and necessary to study. Similar to previous studies, we also include a cash transfer treatment arm and pure control for comparison.
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Do Social Expectations Discourage Graduates From Accepting Low-paid Jobs? Evidence From Ghana
with Grace Abban-Ampiah (CEGA Fellow) and Leila Budgha · Conducting survey and baseline analysis
High unemployment rates among tertiary-educated people pose challenges in low and middle income countries, particularly affecting graduates in Sub-Saharan African countries. This study specifically examines the role of social norms and how they affect Ghanaian business school graduates' willingness to take low-paid jobs as potential stepping stones to better career opportunities. We use surveys and interviews to inform a future randomized controlled trial aimed at modifying graduates' misconceptions and at increasing acceptance of low-paid employment. The findings should guide universities and policymakers to mitigate social pressures and help graduates navigate the labor market.
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pAIn or gAIn? Meaningful Work in the Age of AI
Designing experiment
Teaching
As an instructor, I am committed to promoting equity and excellence in the field of Economics. I believe strongly in the empowerment of students from historically underrepresented backgrounds and support the free and open exchange of ideas in the classroom.
Teaching materials are available on my teaching resources page.
University of San Francisco
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ECON 110 Introductory Economics
This course serves as a comprehensive introduction to a diverse array of economic principles, theories, and analytical methodologies, spanning both microeconomics and macroeconomics.
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ECON 365 Behavioral Economics
This course is an introduction to behavioral economics. We will study the standard economic model of rational choice alongside evidence from psychology and experimental economics on how people actually make decisions, and ask when and why the two diverge. The course considers choice in four settings. We begin with choice under certainty, where reference points, framing, and seemingly irrelevant options shape decisions in ways the standard model does not predict. We then turn to judgment and choice under risk and uncertainty, where intuitive probability judgments and attitudes toward gains and losses depart from the rules of probability and expected utility theory. Next we study choice over time, including why people procrastinate, struggle to save, and seek out commitment. Finally, we consider strategic interaction, where concerns for fairness and reciprocity lead people away from the predictions of game theory, and close by asking what these departures imply for public policy.
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ECON 463/663 Experimental Economics (Graduate)
This course is an introduction to experimental economics for first-year master's students and advanced undergraduates with the goal for every student to leave the course able to design a credible economic experiment from start to finish. The course has three parts. We begin with the logic of the experimental method: why randomization identifies causal effects, how laboratory and field experiments differ, and how induced values and salient incentives give the experimenter control over the economic environment. We then turn to the practical work of design: writing instructions, choosing a sample size, randomizing, deciding between within-subject and between-subject comparisons, and meeting our ethical and institutional obligations to participants. Finally, we survey what experiments have taught us about markets, individual choice, strategic interaction, and development, and close by asking when experimental results replicate and generalize beyond the setting that produced them.
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ECON 672 Economics of Development (Graduate)
This course is an introduction to development economics at the graduate level. We will read and discuss research from across the field to understand both the questions development economists ask and the methods they use to answer them. The course considers development at both the macro and micro level. We begin with aggregate macroeconomic patterns: why income differences across countries are so large and so persistent, and what happens to output and the distribution of income as economies structurally transform. We then turn to the microfoundations of markets, institutions, and household decisions that produce these aggregate patterns, and to the programs and policies designed to address them.
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ECON 473/673 Development Microeconomics (Graduate)
This course is an introduction to microeconomic theory for development, designed for first-year master's students and advanced undergraduates. We build and solve the classic models economists use to understand how households and firms in low-income countries produce, consume, invest, and protect themselves against risk when markets are missing or imperfect, and we read empirical research that tests each model's predictions. The course has three parts. We begin with the farm household and the markets for land and labor, asking why contracts such as sharecropping exist and how insecure property rights shape investment. We then turn to capital and firms: credit markets under asymmetric information, the returns to capital and management in small firms, smoothing consumption in the face of risk, and the difficulty of saving. Finally, we study investment decisions inside households and communities, including technology adoption, bargaining within the household, schooling, and migration.
University of California, Davis
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ECN 102 Analysis of Economics Data
This course aims to provide both a theoretical and applied understanding of how variables and the relationships between variables are visualized and analyzed in Economics. We will use standard statistical software Stata to read, clean, visualize, and analyze data. The course serves as a bridge between introductory statistics courses and more advanced courses in Econometrics (e.g. ECN 140, 141, 142).
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ECN 099/199 Independent Study
Undergraduate lower- and upper-division independent study in economics: supervised research projects, directed readings, and individual study developed with a faculty member or graduate student.