The paper develops a methodology whereby a Principal–Agent model is combined with Linear Programming in order to deal with the design of environmental regulation in agriculture. Linear Programming is intended here mainly as a tool to estimate an agent's cost/profit function for the purpose of the Principal–Agent model. Two variants of the methodology are considered. First, agents' profit functions are estimated through the interpolation of the results of the parametrisation of the Linear Programming model. In the second option, relevant corner points of the discontinuous profit function generated by the parametrisation of the Linear Programming models are identified. These relevant corner points are then fed into a discrete-action Principal–Agent model. An exploratory application is provided, using a case study related to the purchase of environmental services from agriculture. The results show that Linear Programming may represent a useful way to estimate cost/profit functions to feed Principal–Agent models as long as it allows to incorporate more information from the point of view of how decision making is carried out, particularly when the underlying agent's cost/profit function is generated by a bundle of different production activities. However, the choice of the specific procedure should be cautiously evaluated in order to fit the actual properties of the underlying production process. Also, particular attention should be placed on the manner in which constraints and technical coefficients affect the result of the downstream model.
Environmental Modelling & Software – Elsevier
Published: Jun 1, 2009
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera