Risk attitude elicitation using a multi-lottery choice task: Real<i>vs</i>. hypothetical incentives

Barreda‐Tarrazona, Iván; Jaramillo-Gutiérrez, Ainhoa; Navarro-Martínez, Daniel; Sabater-Grande, Gerardo

doi:10.1080/02102412.2011.10779713

Cited by 13 publications

(12 citation statements)

References 15 publications

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“…Readers are referred to the working paper on the implementation note on S-GG panel lotteries for the advantages and limitations of this risk elicitation method [37] et. Applications of the previous version of S-GG panel lotteries can be found in [38][39][40] Rice farmers were sampled across 46 different rice growing locations within the 4 agricultural zones in Ogun State Agricultural Development Programme (OGADEP), Nigeria between March and May, 2016. Two smart android phones, aided by open data kit (ODK collect) software were used for data collection.…”

Section: Source Of Datamentioning

confidence: 99%

Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

Ambali

Georgantzı́s

2021

Agriculture

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This study analyses farmers’ adoption of improved rice technology, taking into account farmers’ risk preferences; the unobserved spatial heterogeneity associated with farmers’ risk preferences; farmers’ household and farm characteristics; farm locations, farmers’ access to information, and their perceptions on the rice improved varieties (i.e., high yield varieties, HYV). The study used data obtained from field experiments and a survey conducted in 2016 in Nigeria. An instrumental-variable probit model was estimated to account for potential endogenous farmers’ risk preference in the adoption decision model. Results show that risk averse (risk avoidant) farmers are less likely to adopt HYV, with the spatial lags of farmers’ risk attitudes found to be a good instrument for spatially unobserved variables (e.g., environmental and climatic factors). We conclude that studies supporting policy action aiming at the diffusion of improved rice varieties need to collect information, if possible, on farmers’ risk attitudes, local environmental and climatic conditions (e.g., climatic, topographic, soil quality, pest incidence) in order to ease the design and evaluation of policy actions on the adoption of improved agricultural technology.

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Section: Source Of Datamentioning

confidence: 99%

Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

Ambali

Georgantzı́s

2021

Agriculture

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“…The S-GG has been applied in different contexts and countries, but we follow the specifications in [49], with modifications to the nomenclatures. Other applications of this risk attitude elicitation method can be found in some European studies [50,51]. The panel lotteries have four treatments each, with the nomenclature being small gain one (SG 1 ), small gain two (SG 2 ), large gain one (LG 1 ), and large gain two (LG 2 ).…”

Section: Source Of Datamentioning

confidence: 99%

On Spatially Dependent Risk Preferences: The Case of Nigerian Farmers

Ambali

Georgantzı́s

2021

Sustainability

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Rice farmers’ attitudes toward risk-taking have been identified as one of the factors affecting investment decisions and wealth accumulation. While existing studies have identified the socio-economic factors driving farmers’ risk attitudes, spatial variables that may correlate with decisions are often ignored in the risk models due to difficulties in measurement. We studied unobserved spatial heterogeneity in farmer’s risk preferences by incorporating spatial dependency into a farmer’s risk preference model. We used data from a survey conducted with Nigerian farmers between March and May 2016. The survey collected information on 2016 farmers’ socio-demographic characteristics and farm attributes including its geographical location as well as information on the quality of roads. In addition, a set of experiments design to elicit famers’ attitudes toward risk were conducted. We estimated a spatial autoregressive model using the instrumental variable method. We found that unobserved spatial heterogeneity (e.g., soil, topographic farmers emulating each other) was present in farmer’s risk preferences along with socio-demographic variables such as age, gender, marital status, and religion and farm characteristics such as farm size and road quality. These results are relevant for policy decision-making processes.

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“…In the financial domain, studies use either real decisions (performance-contingent payoffs) or hypothetical decisions (where the choices made in the experiment have no bearing on participant payment), which is why it is important to understand whether they are comparable. Data on whether the use of real or hypothetical rewards influences risk-taking is equivocal, with some studies reporting no difference [46,47], others reporting reduced risk-taking [48] or increased risk-taking [49] with real rewards. However, this has not been studied with respect to surrogate decision-making and the question remains open.…”

Section: Introductionmentioning

confidence: 99%

Do our risk preferences change when we make decisions for others? A meta-analysis of self-other differences in decisions involving risk

2019

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Background Are we more risk-averse or risk-seeking when we make decisions on behalf of other people as opposed to ourselves? So far, findings have not been able to provide a clear and consistent answer. Method We propose a meta-analysis to assess whether self-other differences vary according to particular features of the decision. We reviewed 78 effect sizes from 49 studies (7,576 participants). Results There was no overall self-other difference, but there were moderating effects of domain and frame . Decisions in the interpersonal domain were more risk-averse for self than for other. Decisions in the medical domain were more risk-seeking for self than for other. There were no overall self-other differences in the financial domain, however there was a moderating effect of frame : decisions in a gain frame were more risk-averse for self than other whereas decisions in a loss frame were more risk-seeking for self than other. This effect of frame was slightly different overall and in the medical domain, where self-other differences occurred in a loss frame but not in a gain frame. Conclusion Future work should continue to investigate how the specific content and context of the decision impacts self-other differences in order to understand the effects of domain and frame we report.

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Risk attitude elicitation using a multi-lottery choice task: Realvs. hypothetical incentives

Cited by 13 publications

References 15 publications

Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

On Spatially Dependent Risk Preferences: The Case of Nigerian Farmers

Do our risk preferences change when we make decisions for others? A meta-analysis of self-other differences in decisions involving risk

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