Dynamic Field Experiments in Development Economics: Risk Valuation in Morocco, Kenya, and Peru

Abstract

The effective design and implementation of interventions that reduce vulnerability and poverty require a solid understanding of underlying poverty dynamics and associated behavioral responses. Stochastic and dynamic benefit streams can make it difficult for the poor to learn the value of such interventions to them. We explore how dynamic field experiments can help (i) intended beneficiaries to learn and understand these complicated benefit streams, and (ii) researchers to better understand how the poor respond to risk when faced with nonlinear welfare dynamics. We discuss and analyze dynamic risk valuation experiments in Morocco, Peru, and Kenya.Key Words: poverty, risk and uncertainty, dynamics, experiments, Kenya, Morocco, Peru Recent research in development economics has improved our theoretical conception of poverty and empirical methods for measuring it. As one significant improvement, economists now pay much greater attention to dynamic dimensions of poverty and vulnerability. This appreciation for asset and poverty dynamics and for the crucial intertemporal dimensions of poverty in rural agropastoral settings is manifest in both theoretical and empirical advances and is starting to influence policy in some settings.The effective design and implementation of interventions that reduce vulnerability and poverty require a solid understanding of underlying poverty dynamics and associated behavioral responses. When introducing insurance products or risk-reducing crops, for example, understanding how the target beneficiaries assess and value risk in the context of these underlying dynamics is critical. Of course, the success of these interventions hinges not only on our understanding as researchers of the underlying dynamics and behavioral responses but turns critically on how well

An integrated agro-ecosystem and livelihood systems approach for the poor and vulnerable in dry areas

“…The project conducted extensive survey work and worked with the target community in a participatory process to identify constraints and possible entry points. Once IBLI was identified as a candidate intervention, the project worked to: identify institutional innovations needed to support this new concept in insurance provision and financial service delivery; established partnerships with commercial entities, regulatory bodies and other agencies; established novel public-private agreements for market-mediated provision of the product; and, initiated extension and marketing efforts to educate the target clientele on a previously alien concept and new product (Lybbert et al 2010;Matsaert et al 2011;McPeak et al 2010;Notenbaert et al 2009;Ouma et al 2011).…”

Drought insurance for agricultural development and food security in dryland areas

“…In the US and Canada, biophysical models are used to estimate rangeland productivity given observed rainfall outcomes, and insurance contracts are indexed to the model predictions (IFAD and WFP 2010). Given panel household data, it is also possible to model the relationships between weather events and household incomes rather than yields, leading to even more relevant indices with low basis risk for insuring household welfare (Lybbert et al 2010). But the cost of this kind of "designer" research can be high and the indices that follow may prove too site specific to scale up.…”

“…Yet studies in drought prone areas have shown that most farmers are risk averse and behave as if they would be willing to pay 12-20% above the pure risk cost for an insurance product that has low basis risk (Gautam et al 1994;Sakurai and Reardon 1997;Binswanger 1980;Binswanger and Sillers 1983;McCarthy 2003;Lybbert et al 2010). One reason for the discrepancy between hypothetical and actual demand is that farmers often do not understand how index insurance works and hence are reluctant to buy it.…”

Explaining index‐based livestock insurance to pastoralists

“…This would help us think through targeting, marketing, and possible contract design issues and also allow us to report back to the insurance companies what kind of response they might find when this product becomes commercially available. This motivated the current and related studies conducted by team members (Lybbert et al 2009 As one goal of this paper is documenting how we went about explaining index insurance, this section describes how the work was conducted. In May 2008, three team members met in Nairobi to discuss the game and we began formulating a plan to be ready to conduct the game in the field by August 2008.…”