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Multi-level regression and post-stratification for discrete choice modelling and stated preference research

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  • Lloyd-Smith, Patrick

Abstract

Obtaining valid answers from respondents has been a central concern of stated preference (SP) studies. In contrast, sample representativeness is the main focus of current public polling accuracy debates, largely due to declining survey response rates. We introduce the multi-level regression and post-stratification (MRP) modelling approach to welfare estimation using discrete choice models. Through Monte Carlo simulations and two water resource valuation surveys, we demonstrate how MRP can help researchers to (i) generate population-relevant welfare measures from non-representative samples, (ii) estimate preference heterogeneity and distributional impacts across people, and (iii) evaluate the impacts of removing potentially invalid responses using a consistent target population frame. We propose MRP as a complementary modelling approach for non-market valuation data and discuss its opportunities and limitations.

Suggested Citation

  • Lloyd-Smith, Patrick, 2026. "Multi-level regression and post-stratification for discrete choice modelling and stated preference research," Journal of Environmental Economics and Management, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:jeeman:v:138:y:2026:i:c:s0095069626000355
    DOI: 10.1016/j.jeem.2026.103315
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