Bio-Economic Models applied to Agricultural Systems

233 Pages·2011·2.75 MB·English

by  G. Flichman

Bio-Economic Models applied
to Agricultural Systems

Guillermo Flichman
Editor
Bio-Economic Models
applied to Agricultural
Systems
Editor
GuillermoFlichman
CentreInternationaldeHautesEtudes
AgronomiquesMe´diterrane´ennes
Montpellier,France
[email protected]
ISBN978-94-007-1901-9 e-ISBN978-94-007-1902-6
DOI10.1007/978-94-007-1902-6
SpringerDordrechtHeidelbergLondonNewYork
LibraryofCongressControlNumber:2011937552
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Preface
This book has the purpose of providing the “state of the arts” concerning
bio-economic modelling dealing with agricultural systems. In most cases, the
contributions use a methodology combining the use of biophysical and economic
models, in all cases, an engineering production function approach is totally or
partiallyapplied.
Thispracticeisbeingdevelopedinthelastyearsasaresponsetoconcretepolicy
matters: agricultural policies are increasingly combined with environmental and
natural resources policies, and this reality involves the need of an integrated
assessment, that current economic models are not able to provide. But at the
same time this type of approach involves the use of a multidisciplinary approach,
extremely difficult to develop taking into account on one side the difficulty of
communicationbetweendifferentdisciplinesandontheotherthefactthatinterms
ofscientificevaluation,theexistingsystemisanobstacletothedevelopmentofthis
researchorientation, aslong asresearchersare evaluatedonastrictlydisciplinary
criteria.
PartIdealsprincipallywiththeoreticalandmethodologicalissues,aswellasa
presentationofbiophysicalmodels,animportantsourcethatprovidesengineering
productionfunctionsappropriatetobeusedbybioeconomicagriculturalmodels.
Chapter1discussestherelationsbetweenbioeconomicmodellingandeconomic
theory.Itisclearthatallbioeconomicmodellersdonotsharethepointsofviewthat
arepresentedinthischapter,theintentionistoopendiscussionsthatcanbefruitful
forfutureresearchdevelopmentaswellasforremindingtheyounggenerationsof
economistsaboutsomeoldtheoreticalissuesthatcanbeextremelyusefulforvery
newpracticalmatters.
Chapter2isaboutproductionfunctions;itgivesawideperspectiveonthematter
and provides a strong justification for using biophysical models’ outputs as engi-
neeringproductionfunctions.
Chapter 3 presents a typology of dynamic modelling approaches as well as an
applicationofaninnovativemethodforanalyzingtheproblemofsoildegradation
by salinization in a small irrigated region of Tunisia. The methodological part of
thischaptermaybeofinterestformodellersdealingwiththistypeofproblem.
v
vi Preface
Chapter4presentsinaquitedetailedmannerthestructureandprincipalcharac-
teristicofbiophysicalmodels.Economistswillingtousetheresultsofthesemodels
need to understand how they are able to represent the complexity of agricultural
systemsintegratinginasingleframeworktherelationsbetweenmultipleinputsand
multipleoutputs.
PartIIpresentsapplicationsofbioeconomicmodelsanalysing differentissues
atregionallevels-both“small”and“big”regions.
Chapter 5 Is an application at the level of a big region (California), of a
calibrated agricultural production model presenting an important innovation
concerning the use of outputs generated by a biophysical model to infer adoption
ofanewbioenergycrop.Aspriorinformationonsupplyelasticitiesisnotavailable
tocalibratenon-lineartermsintheobjectivefunction,yieldvariationattheregional
level – a piece of information typically available from highly disaggregated bio-
physicalmodelsofplantgrowthisusedtoconstructsuchterms.
Chapter6presentstheuseofanAgriculturalModelworkingatEuropeanlevel
providingindicatorsofnitratepollutionobtainedbytheoutputofnitratebalances
and different innovative indicators of Nitrogen use at a country level for all
European Union Countries. The calculation of the N-cycle follows a mass-flow
approach.Themodelkeepstrackofthenitrogenavailableateachstep–netofall
emissions that occurred at an earlier step – and uses this as the basis for the
estimationofemissions.
Chapter 7 is an application of a dynamic multiobjective model of animal
production(dairysector)ataspecificregionallevel,ReunionIsland.Theprincipal
objective is to provide policy assessment. It allows simulating the effects of
alternativemanagementpracticesonNitrogenemissions.Thealternativemanage-
ment that are proposed are (a) and increase of spreadable land area for manure,
(b)thetransformationofmanuretootherformsascompostand(c)toutilisemanure
asasourceofenergy.
Chapter8Theaimofthischapteristoprovideabetterunderstandingabouton-
farmriskreducingstrategiesencompassingbothriskanticipationstrategyandrisk
modifytheproductionsystemandprofitdistributionofFrenchsucklercowenter-
prises. Themethod used inthis case is asequence ofrecursivediscrete stochastic
model, close to the method applied on Chap. 4 in a completely different context.
Theadvantageofthisapproachcomparedtothestandardoneofdynamicstochastic
programmingappearsinaveryclearwayinbothcases.
Chapter9 This chapter presents anapplication ofa bio-economic model to the
Lunan Water catchment in Scotland to assess the relative cost-effectiveness of
measures against agricultural nitrate pollution. The model used for this work is
FFSIM-MP,integratingtheoutputsofabiophysicalmodel,COUP.Thiscontribu-
tion explores the challenges related to bio-economic modelling applications,
presents the methodology and results, and evaluates the overall appropriateness
oftheapproachforintegratedpolicyimpactassessment.
Chapter 10 integrates three models to provide a spatialised assessment of
the relationships between alternative agricultural management and biodiversity.
The farm optimization model FAMOS[space], the crop rotation model CropRota,
Preface vii
and the bio-physical process model EPIC are used in this contribution.
Crop rotations and crop yields are inputs to FAMOS[space], which explicitly
considersalternativelanduseintensitiesaswellaslandscapeelements.Biodiversi-
ty effects of land use choices are evaluated with a set of field and landscape
indicators. The specific interest of this chapter is the explicit introduction of the
spatialdimensioninthebioeconomicmodel.
A short conclusion presents the principal achievements of this approach and
the main obstacles for further development, considering the difficulties of multi-
disciplinaryapproaches,andalsothecomplicatedissueoftheinformationneeded
tousethistypeofmodels,evenwhenappliedtorelativelysmallstudycases.
GuillermoFlichman

Acknowledgements
Iwanttogratefullyacknowledgealltheauthorsthatacceptedtogiveacontribution
tothisbook.Ittookalotoftimeandeffort,butthepossibilityofputtingtogether
the work of different researchers developing and applying bio-economic models
allowsprovidingabetterknowledgeaboutthistypeofapproach.
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