Abstract

Measuring Sustainable Agricultural Productivity: Data, Methods, and Policy Implications
Submitted by
Spiro Stefanou, Professor Emeritus, Penn State Univ (USA)
Maria Vrachioli, Senior Researcher at Technical University Munich (DE)

Rationale for the Session
Reliable measurement of agricultural productivity is crucial for sustainable growth, food security, and environmental stewardship. Despite new data sources, from surveys and administrative records to remote sensing and AI, measurement challenges persist, limiting policy-relevant insights. This session highlights innovative methods and technologies to improve agricultural statistics, integrating environmental and social dimensions, and generating evidence that supports effective, sustainable agricultural policies.

Economists draw on a wide range of data sources: farm and household surveys, administrative records, market data, experimental and trial data, and increasingly remote sensing and geospatial products. Yet applied research often overlooks the nature and limitations of the measurement processes that underlie these data products.
Measurement is imperfect. Key variables are measured with error or not measured at all. While our ability to store, process, and analyze data has dramatically expanded in recent decades, measurement challenges and limitations could threaten data integrity. These challenges are particularly important in agriculture, where capturing the interplay between environmental conditions, production decisions, and social outcomes is critical. The implications for economic research and its ability to inform policy and decision-making related to sustainable agricultural productivity and inclusive growth related to sustainable agricultural productivity growth remain underexplored.
Agricultural productivity is a central driver of economic growth, food security, and environmental sustainability. With increasing global demand for food and shifts in supply conditions due to climate change, understanding how to measure and support sustainable productivity growth is essential. Reliable and comprehensive measurement enables evidence-based policies that account not only for agricultural output but also for environmental and social dimensions of agriculture.
What are the gaps in data that can enable more precise and policy-relevant measures of sustainable productivity in agriculture? How can we leverage AI and advanced analytical tools to integrate diverse datasets, including geospatial, survey, market, and experimental data, to capture both quantities and values?
Potential topics of interest include, but are not limited to:
• Studies analyzing the consequences and proposing solutions to important measurement error in the agricultural economy
• Analyses exploring the role of previously unmeasured indicators that are critical for evaluating sustainability and policy impacts
• Studies addressing and exploring the consequences of quality adjustments in agricultural inputs and outputs
• Work documenting rising challenges related to sampling and attrition in agricultural surveys and experiments and potential ways to address them
• Frameworks to evaluate tradeoffs in measurement precision, frequency, and resolution with a focus on policy relevance
• Studies analyzing technological change and innovation in measurement technology (broadly defined)
• Studies showcasing or quantifying the benefits of satellite and remote-sensed data for monitoring environmental impacts, resource use efficiency, and sustainable production practices

Moderator: Spiro Stefanou
Discussant: Maria Vrachioli
Presenters will be drawn researchers
• Joint Research Center, European Commission
• EUROSTAT
• UNFAO
• OECD/Trade and Agriculture Directorate
• US Department of Agriculture

Format
• Moderator: 1 (to introduce the session, manage time, and facilitate Q&A)
• Speakers: 4–5 (each presenting for 15–20 minutes)
• Discussants: 1–2 (to provide synthesize insights and critical commentary)
• Q&A / Discussion: 15–20 minutes at the end, moderated to engage the audience and link presentations to broader policy and research implications.
Total Duration: ~90 minutes