Conference Agenda

The use of pesticides by farmers is thought to harm human health and the environment. It also provides a classical example of decision-making under un- certainty, by a single agent. In our model, a farmer first decides about preventive measures (self-protection), before deciding ex-post about pesticides application (self- insurance). In order to understand the determinants of these decisions, we provide a theoretical analysis, then an analysis of the results of a survey of a group of French farmers, and finally some simulation exercises.

This study investigates barriers to organic farming adoption in developing countries, fo- cusing on ambiguity and risk among 611 Vietnamese farmers. We develop an α-MaxMin Expected Utility model predicting that information reduces the level of ambiguity rather than altering ambiguity preferences. Our key theoretical contribution formalizes how infor- mation should disproportionately benefit ambiguity-averse farmers. We test this mechanism through a lab-in-the-field experiment estimating the interaction between information and ambiguity aversion. Results from inverse-propensity weighted fractional response models show that information significantly increases intended conversion by 34 percentage points and attenuates the negative effect of ambiguity aversion. Robustness checks using beta regression confirm these findings. The interaction effect represents a novel empirical contri- bution, demonstrating that information’s value is heterogeneous and largest for those most hampered by ambiguity.

This study examines the influence of information sharing and cooperation among farmers on the adoption of organic agriculture, utilizing data from a lab-in-field experiment conducted in northern Vietnam. We constructed a game in which farmers choose their land allocation to organic agriculture under three scenarios. We implemented the Nash-Bargaining game inside this allocation game. We find that a lack of information on organic technology hampers the allocation of land to organic agriculture. Our analysis reveals that farmers engage in cooperative behavior, as evidenced by their willingness to participate in a Nash bargaining model to access information and share benefits. Furthermore, our results support the hypothesis that equal gains serve as a focal point in cooperative agreements, aligning with theoretical predictions in bargaining theory. Additionally, we highlight the significant impact of non-monetary factors, such as social value orientation, on farmers' decision-making processes. This research provides valuable insights for policymakers seeking to promote information dissemination and facilitate the transition to sustainable agricultural practices.

This study investigates the determinants of solar pump utilization and its impacts

in India, using a two-period before-after panel dataset from a primary survey of 955

farmers across nine districts in four major states—Uttar Pradesh, Rajasthan, Odisha,

and Tamil Nadu. We address two core questions: what drives solar pump utilization

post-adoption, and what are the impacts on energy use, agricultural outcomes, and

farm profitability. A Two-Stage Least Squares (2SLS) strategy addresses endogeneity in installed capacity, followed by a fixed-effects panel model to estimate causal impacts. Utilization is significantly influenced by installed capacity, groundwater depth, and operational experience, proxied by pump age. Solar pump adoption reduces average diesel consumption by 34–86%, with the largest declines among large farms and diesel-reliant users. Electricity impacts are heterogeneous: reductions of 20–42% are observed in two districts, while others show increases up to 13%, reflecting irrigation expansion or insignificant results. Gross cropped area increases by 16.7–53%, driven by landholding size and constrained by pre-existing electric pump access. Annual farm profits rise across all districts, ranging from 27% to over 100%. These findings highlight the transformative potential of solar irrigation for energy transition, agricultural productivity, and rural incomes, while underscoring the importance of tailoring interventions to local agro-economic and infrastructural conditions.