Anna Josephson

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Associate Professor, University of Arizona

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Anna Josephson

My research centers on the measurement and mismeasurement and how these elements can result in misestimation of food security, welfare, and agricultural outcomes. I focus on how data, methods, and assumptions shape (and sometimes distort) our understanding of well-being. Across settings around the world, my work examines the links between people and their risky environments, exploring how they pursue survival, recovery, and resilience in the face of uncertainty and risk.

I also study the process of economic research, including ethics and generative AI in research and gender in the profession. My book with Jeffrey Michler, Research Ethics in Applied Economics: A Practical Guide, is available from Routledge and Amazon.

Measurement in weather and agriculture

Estimating the Impact of Weather on Agriculture: This work seeks to quantify the significance and magnitude of the effect of measurement error in satellite weather data on modeling agricultural production, agricultural productivity, and resilience outcomes. We combine geo-spatial weather data from a variety of satellite sources with the geo-referenced household survey data from seven sub-Saharan African countries that are part of the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture initiative. Our goal is to provide systematic evidence on which weather metrics have strong predictive power over a large set of crops and countries and which metrics are only useful in highly specific settings. More details available on OSF with a working paper on arXiv and from the World Bank. Collaborators: T. Kilic (World Bank), J.D. Michler (UArizona), S. Murray (World Bank).

Our two publications from this project have been published in the Journal of Development Economics: Privacy protection, measurement error, and the integration of remote sensing and socioeconomic survey data and The Mismeasure of Weather: Using Earth Observation in Applied Economic Contexts
We also have a working paper available on arXiv: The Mis-Measure of Weather: Using Remotely Sensed Earth Observation Data in Economic Contexts

Leveraging in Situ Sensors to Improve Measurement of Weather, Climate Variability, and Links to Socioeconomic Outcomes: This work investigates how improvements in local weather measurement can enhance our understanding of the links between climate variability and agricultural outcomes in Sub-Saharan Africa. Accurate rainfall data are essential for modeling agricultural production, yet existing weather information remains limited due to the sparse coverage of high-quality ground stations. We combine rainfall measurements from professional weather stations, community-level in situ sensors, and widely used remote sensing earth observation (RSEO) products to evaluate how differences in data quality and granularity affect estimates of maize yields in Uganda. We have a working paper, available upon request. Collaborators: A. Paolantonio (World Bank), E. Clemente (World Bank).

Uses and Misuses of Weather, Land Use, and Land Cover Data in Geospatial Impact Evaluations: This work explores the opportunities and challenges of incorporating gridded weather and earth observation (EO) data into impact evaluations. These data sources offer powerful tools for capturing environmental context, external shocks, and even outcomes that may be missed by traditional surveys due to spatial or temporal limitations. We identify several of the most common pitfalls researchers face when using gridded weather, vegetation, land cover, and extreme event data in applied research. The objective of this work is to provide practical guidance and resources to help researchers thoughtfully select, process, and integrate these datasets, ensuring robust and transparent impact evaluation design in geospatial contexts. We have a working paper, available upon request. Collaborators: E. Benami (Virginia Tech), M. Cecil (University of Maryland), J.D. Michler (UArizona), G. Maskell (Potsdam Institute for Climate Impact Research)

Households and food security

Agricultural Commercialization and Gender: This work explores agricultural commercialization, which is frequently promoted as a pathway to rural development in Sub-Saharan Africa. We investigate how gender shapes participation in agricultural markets in Ethiopia, Nigeria, and Tanzania. We find that gender disparities in agricultural commercialization are context-specific, underscoring the need for country-tailored interventions that address institutional and market barriers faced by women farmers. We have a working paper on arXiv. Collaborators: K. Kafle (TAMU), W. Li (TAMU).

Market Completeness in Labor Markets: This work delves into the neoclassical agricultural household model and its assumptions that production and consumption decisions are independent when markets are complete. In low-income settings where many households are both producers and consumers of agricultural goods, this assumption may not hold. This project tests whether production decisions are separable from household characteristics among rice-farming households in the Central Luzon provinces of the Philippines. Using four decades of household data, we examine how household demographics relate to labor demand and how these relationships have evolved alongside major economic and institutional changes. This work demonstrates the importance of context in assessing market completeness and demonstrate the continued relevance of testing separability assumptions when modeling farm household decision making. We have a working paper, available upon request. Collaborators: E. Kee Tui (Cornell), J. Michler (UArizona).

Climate, crises, and resilience

Valuation of climate and human behavior: This project explores how individuals and institutions perceive and value the economic and social dimensions of climate change and adaptation. We combine a synthesis of the literature on the costs and benefits of climate adaptation with experimental evidence on individuals’ willingness to support climate action financially and observational data on behavior in both mitigation and adaptation strategies. Together, these analyses reveal that while estimates of adaptation value often rely on uncertain assumptions and incomplete data, particularly concerning non-market outcomes and local inequities, individuals demonstrate a strong intrinsic concern for climate issues that is sensitive to information framing and imagery. The findings highlight a key tension in climate economics: valuation is shaped not only by methodological and data limitations but also by how people interpret and emotionally engage with climate risks, underscoring the need for approaches that integrate behavioral and economic insights in assessing the true value of adaptation and action.

The Cost of Climate Action: Experimental Evidence on the Impact of Climate Information on Charitable Donations to Climate Activism, with Samantha Wetherell (Oxford) is currently under review and available as a working paper on arXiv.
The Economics of Climate Adaptation: An Assessment, with R. Guerra Su (TAMU), G. Collins (TANGO), and K. Jacobs (UArizona) is currently under review and available as a working paper on arXiv.

Measuring food security in disasters: Current food insecurity measures have been used in disaster contexts, but there are distinct challenges to food security in a post-disaster context. Providing sufficient calories while also addressing dietary quality and nutrition is difficult to do in a disaster setting, with widespread disruption to infrastructure, supply chains, and organizational and social systems. Thus, this research works to establish a new metric that captures dimensions of food insecurity affected in a disaster context is necessary to improve food security measurement, better estimate food insecurity prevalence during community-level disruptions, and enhance emergency food assistance to support families coping with widespread disruption to infrastructure, supply chains, organizational and social networks, personal property, and daily routines. Collaborators: N. Konratty (IFPRI), L. Clay (University of Maryland), M. Niles (Brown).

A publication from this project was published in the Journal of the Academy of Nutrition and Dietetics: A Mixed-Methods Approach to the Development of a Disaster Food Security Framework.

Ethics, generative AI, and machine learning

Mining Meaning: Generative AI and Literature Reviews: This work evaluates whether large language models (LLMs) can support rigorous, high-stakes literature review tasks in economics. We focus on research that uses weather shocks, such as rainfall variation or temperature extremes, as instrumental variables to identify causal effects. Weather IVs are widely used but actively debated, making them a useful stress test for whether LLMs can synthesize complex and contested literatures. We assess LLM’s ability to compile and summarize requested information from a large body of work. Our working paper is forthcoming and we have a working paper available, upon request. Collaborators: C.Agme (Cornell), K. Douglas (UC Davis), T. Leavy (UArizona), J.D. Michler (UArizona).

AI and the Future of Economic Research: This work reviews how artificial intelligence is reshaping applied economics research and outlines directions for the agricultural and applied economics community. We treat AI as a tool, not a coauthor, and emphasize a central through line: meaningful human oversight is essential. We synthesize what AI can and cannot do well as research support alongside the key conceptual and ethical risks. We also discuss AI use in peer review, arguing that potential conveniences are outweighed by practical and ethical concerns. We then review evolving publisher, journal, and institutional guidelines for authors and reviewers, highlighting the importance of disclosure and clear standards, and offer recommendations for best practices that balance time savings with skill development, identify points of consensus and disagreement, and anticipate how norms and incentives may need to adapt as the technology continues to change.. We have a working paper, available upon request. Collaborators: J. Ricker-Gilbert (Purdue).