Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data

We elicit risk preferences of French farmers in a field experimental setting under expected utility theory and cumulative prospect theory. We use two different estimation methods, namely the interval approach and the estimation of a random preference model. On average, farmers are risk averse and loss averse. They also exhibit an inverse S-shaped probability weighting function, meaning that they tend to overweight small probabilities and underweight high probabilities. We infer from our results that CPT explains farmers’ behaviour better than EUT in the context of our experiment. We also investigate how preferences correlate with individual socio-demographic characteristics. We find that education and agricultural innovation are negatively linked with risk aversion. Our results also show that age, education, household size and the level of secured income tend to lower farmers’ loss aversion. Finally, older farmers and farmers with large farms distort probabilities less than the others. These findings contribute to the literature which compares expected utility with competing decision theories. They also give important insights into farmers’ behaviour towards risk, which is critical for relevant public policy design.risk preferences, field experiment, experimental economics, prospect theory, Risk and Uncertainty, C91, D81, J16, Q12,

Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data

We elicit risk preferences of French farmers in a field experimental setting under expected utility theory and cumulative prospect theory. We use two different estimation methods, namely the interval approach and the estimation of a random preference model. On average, farmers are risk averse and loss averse. They also exhibit an inverse S-shaped probability weighting function, meaning that they tend to overweight small probabilities and underweight high probabilities. We infer from our results that CPT explains farmers’ behaviour better than EUT in the context of our experiment. We also investigate how preferences correlate with individual socio-demographic characteristics. We find that education and agricultural innovation are negatively linked with risk aversion. Our results also show that age, education, household size and the level of secured income tend to lower farmers’ loss aversion. Finally, older farmers and farmers with large farms distort probabilities less than the others. These findings contribute to the literature which compares expected utility with competing decision theories. They also give important insights into farmers’ behaviour towards risk, which is critical for relevant public policy design

Risk and Refugee Migration

This paper uses the experimental setup of Tanaka et al. (2010) to measure refugees’ risk preferences. A sample of 206 asylum seekers was interviewed in 2017-18 in Luxembourg. Contrary to studies which focus on risk aversion in general, we analyze its components using a cumulative prospect theory (CPT) framework. We show that refugees exhibit particularly low levels of risk aversion compared to other populations and that CPT provides a better fit for modelling risk attitudes. Moreover, we include randomised temporary treatments provoking emotions and find a small significant impact on probability distortion. Robustness of the Tanaka et al. (2010) experimental framework is confirmed by including treatments regarding the embedding effect. Finally, we propose a theoretical model of refugee migration that integrates the insights from our experimental outcomes regarding the functional form of refugees’ decision under risk and the estimated parameter values. The model is then simulated using the data from our study

Developing country-wide farm typologies: An analysis of Ethiopian smallholders’ income and food security

Ethiopia’s agricultural sector is highly diverse and subject to change due to different factors such as climate and population growth. Consequently, competition for available land, water, energy, and other inputs increases, posing pressure on the rural population’s livelihoods and food security. It is therefore imperative to analyze farmer’s production choices under these changing circumstances. The objective of this paper is to develop a methodology to establish country-wide farm typologies allowing for both a spatial and temporal analysis of the evolution of the agricultural sector, and in particular smallholders' food security and income in Ethiopia. First, household survey data is employed to categorize smallholder farming systems according to their agro-ecological zone, farm size, main activities and degree of intensification. Second, farming systems are extrapolated using a multinomial logit-regression. Resulting combinations of farming-system occurrence and their production activities are harmonized with national statistics and subsequently equipped with the potential to intensify. Compared with other typologies that commonly only focus on the distribution of farming systems, this study fills the typology with data, allowing for the analysis of income and food security over space and time. It is concluded that livestock-oriented systems are less profitable than crop-oriented systems and more prone to food-insecurity. Increased input intensification is one way to reduce pressure on cropland expansion caused by the expected increase in population, but has to go together with other methods to fully alleviate pressure on land and thereby poverty and food insecurity