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Design and Analysis of Simple Choice Surveys for Natural Resource Management
Author(s) -
FIEBERG JOHN,
CORNICELLI LOUIS,
FULTON DAVID C.,
GRUND MARRETT D.
Publication year - 2010
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.2193/2009-030
Subject(s) - multinomial logistic regression , discrete choice , choice set , mixed logit , preference , rank (graph theory) , computer science , econometrics , attractiveness , simple (philosophy) , set (abstract data type) , logit , multinomial distribution , revealed preference , logistic regression , statistics , economics , mathematics , machine learning , psychology , philosophy , epistemology , combinatorics , psychoanalysis , programming language
We used a simple yet powerful method for judging public support for management actions from randomized surveys. We asked respondents to rank choices (representing management regulations under consideration) according to their preference, and we then used discrete choice models to estimate probability of choosing among options (conditional on the set of options presented to respondents). Because choices may share similar unmodeled characteristics, the multinomial logit model, commonly applied to discrete choice data, may not be appropriate. We introduced the nested logit model, which offers a simple approach for incorporating correlation among choices. This forced choice survey approach provides a useful method of gathering public input; it is relatively easy to apply in practice, and the data are likely to be more informative than asking constituents to rate attractiveness of each option separately.