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Targeting Conservation Investments in Heterogeneous Landscapes: A Distance‐Function Approach and Application to Watershed Management
Author(s) -
Ferraro Paul J.
Publication year - 2004
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1111/j.0002-9092.2004.00642.x
Subject(s) - outcome (game theory) , function (biology) , nonparametric statistics , watershed , quality (philosophy) , computer science , variable (mathematics) , parametric statistics , environmental resource management , risk analysis (engineering) , environmental economics , business , economics , econometrics , microeconomics , mathematics , machine learning , mathematical analysis , philosophy , statistics , epistemology , evolutionary biology , biology
To achieve an environmental objective at least cost, decision makers must integrate information about spatially variable biophysical and economic conditions. Although the biophysical attributes that contribute to an environmental outcome are often known, the way in which these attributes interact to produce the outcome is often unknown. We introduce a nonparametric conservation targeting approach that relies on distance functions to cost‐efficiently allocate conservation funds. We apply the approach empirically to the case of conservation contracting for water‐quality objectives. The contract portfolios derived from the application have many desirable properties, including intuitive appeal and robust performance across plausible parametric scoring measures.