Stated Farmers’ Preferences and Willingness to Pay for Climate Resilient Potato Varieties in Kenya: A Discrete Choice Experiment

Kimathi, Sally Mukami; Ayuya, Oscar Ingasia; Mutai, B. K.

doi:10.2139/ssrn.3903923

Cited by 1 publication

(2 citation statements)

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“…A D-optimal design is an algorithmic approach used in choice experiments to maximize the determinant of the information set used in the design of experiments with multiple treatments. It is designed to maximize the differences in attribute levels across alternatives, provide the best subset of all possible combinations and yield data that enables the estimation of parameters with low standard errors (Kimathi et al, 2022). Our generated design had a D-efficiency value of 99.28, indicating a high level of D-optimality (Kuhfeld, 2010).…”

Section: Design Of the Discrete Choice Experimentsmentioning

confidence: 99%

“…Whenever prices are included in a discrete choice experiment, individual choices can be expressed in terms of willingness-to-pay for one attribute rather than another. A large amount of literature has documented agricultural growers' trait preferences using choice experiments, with a particular emphasis on sub-Saharan African countries (among others, see Labarta, 2009;Waldman et al, 2017;Kimathi et al, 2022). Discrete choice experiments present non-negligible drawbacks as method, among others the susceptibility to hypothetical biases and the limitation in the number of traits that can define a crop, without risking decision fatigue with an overwhelming number of choice sets or traits per profile (Burns et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Intra-household discrete choice experiment for trait preferences: a new method

Mukerjee,

Faye,

Badji

et al. 2023

Front. Sustain. Food Syst.

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Crop trait and varietal preferences are socially shaped, varying by gender, experience, and on-farm roles. This drives preference heterogeneity, between households but also within households. Adhering to the common practice of only interviewing the household head as a representative of households, leads to breeding programs collecting trait preferences that do not represent the experiences of other members within that household. This dearth of data on trait preferences of multiple household members could be hindered by the lack of robust and agile methods to collect this data. Here we present a method that explores intra-household differences between husbands and wives in trait preferences through choice experimentation, coupled with questions that capture decision-making, experience and time spent on farm to explore how these drive preferences. Dissecting crop management into three dimensions, we explore what drives intra-household heterogeneity in varietal preferences between husbands and wives, as well as, decision-making, crop experience and time spent working on the crop. We present preliminary results from testing this combined protocol with 270 cowpea growing households (540 respondents) in Senegal. The findings from this work hold promise to inform crop breeding programs on the value of intra-household analysis for trait priority setting, while offering a new method which is applicable by National Agricultural Research Organizations globally.

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Section: Design Of the Discrete Choice Experimentsmentioning

confidence: 99%