Review of the Application of Tobit, Sample Selection, and Hurdle Models to Data from Discrete Choice Experiments

Discrete Choice Experiments (DCEs) are commonly applied in agricultural and environmental economics to elicit stakeholder preferences, particularly regarding various contract types, such as nature protection or product supply contracts. Beyond simply predicting the likelihood of stakeholders choosing such agreements, it is also valuable to estimate quantities, such as the hectares of land farmers are willing to allocate for nature protection or the volume of produce they are willing to supply. Selecting an appropriate econometric model is essential for analysing data effectively. This article reviews three key models (Tobit, Sample Selection, and Hurdle models) that are suitable for this type of analysis. It then critically reviews peer-reviewed studies that apply these models in agricultural and environmental contexts, highlighting that model selection is often not grounded in a thorough assessment of data characteristics or model fit. Moreover, it underscores the methodological challenges posed by the panel structure of DCE data, particularly for sample selection models. Finally, the article offers practical guidance for improving the design, model selection, and estimation strategies when eliciting both participation and quantity allocation decisions.

Review of the Application of Tobit, Sample Selection, and Hurdle Models to Data from Discrete Choice Experiments

Discrete Choice Experiments (DCEs) are commonly applied in agricultural and environmental economics to elicit stakeholder preferences, particularly regarding various contract types, such as nature protection or product supply contracts. Beyond simply predicting the likelihood of stakeholders choosing such agreements, it is also valuable to estimate quantities, such as the hectares of land farmers are willing to allocate for nature protection or the volume of produce they are willing to supply. Selecting an appropriate econometric model is essential for analysing data effectively. This article reviews three key models (Tobit, Sample Selection, and Hurdle models) that are suitable for this type of analysis. It then critically reviews peer-reviewed studies that apply these models in agricultural and environmental contexts, highlighting that model selection is often not grounded in a thorough assessment of data characteristics or model fit. Moreover, it underscores the methodological challenges posed by the panel structure of DCE data, particularly for sample selection models. Finally, the article offers practical guidance for improving the design, model selection, and estimation strategies when eliciting both participation and quantity allocation decisions.

No 397909, 100th Annual Conference, March 23-25, 2026, Wadham College, University of Oxford, Oxford, UK from Agricultural Economics Society (AES)

Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
Pages: 40
Date: 2026-03
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aes026:397909

DOI: 10.22004/ag.econ.397909

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