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agriregionieuropa A minimum cross entropy model to generate disaggregated agricultural data at the local level António Xavier 1, Maria de Belém Martins 1 and Rui Fragoso 2 1 Sciences and Technology Faculty-University of Algarve and CEFAGE-UE, 2 Management Department, University of Évora The authors gratefully acknowledge partial financial support from FCT, program FACC. 122 nd European Association of Agricultural Economists Seminar Evidence-Based Agricultural and Rural Policy Making Methodological and Empirical Challenges of Policy Evaluation February 17 th – 18 th, 2011, Ancona (Italy) associazioneAlessandroBartola studi e ricerche di economia e di politica agraria Centro Studi Sulle Politiche Economiche, Rurali e Ambientali Università Politecnica delle Marche
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Introduction – The problem’s description – Previous studies – The methodological approach – The empirical implementation – Results – Validation Conclusions Contents
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Introduction The lack of data-Portugal The objective of the presentation – Overcome Lack of disaggregated agricultural data – Necessity of methods for different situations – A method for certain specific situations in Portugal the approach presented here results from a series of experiences carried out by the authors and it’s still under development Relevant for policy evaluation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) The problem’s formulation In Portugal the specific situation may be described as follows: – Existence of aggregated data – Other co-variables: Land use cartography Biophysical data –Slope –Soils Meteorological data … Necessity of disaggregated data at the following levels: County Parish Local (pixel,...)
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) DATA DISAGGREGATION ????????? Administrative units Local level FARMS’DATA-REGIONAL LEVEL CLIMATE DATA MAPS LAND USE MAPS SLOPE HIPSOMETRY METEO STATIONS DATA SOIL CAPACITY The problem’s formulation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Previous studies Howitt and Reynaud (2003) presented a two stages dynamic disaggregation process which was able to recover a complete sequence of disaggregated data. Kempen et al. (2005) You and Wood (2006) have used a spatial disaggregation procedure combining a logit model with posterior density estimators to break down production data available at the regional level to a homogeneous spatial mapping unit level (HSMU) proposed a spatial disaggregation model for crop production statistics based on a cross-entropy approach.
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Chakir (2009) Fragoso et al. (2008) Martins et al. (2010) proposed a model which estimates incomplete information at disaggregated level through an entropy approach used agricultural data in conjunction with biophysical processes to break down agricultural FADN regional data into 100m × 100m pixel spatial units. presented disaggregated data regarding land use for the Montado ecosystem area. In Portugal: Previous studies
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) The methodological framework BASED MOSTLY IN THE WORKS OF C HAKIR (2009), Y OU AND W OOD (2006) AND Y OU ET AL. (2007, 2009) – COMBINATION OF THE DIFFERENT EXPOSED IDEAS, IN ORDER TO VALORIZE ALL THE EXISTING INFORMATION It’s composed by 2 steps: – 1ºstep-Prior information database creation – 2ºStep-The cross entropy approach
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) The methodological framework
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) 1ºstep description There are several ways of creating this prior and the diversity of information leaded to the exclusion of some predefined methods combination of the following information: land use cartographical data, soil capacity maps, climate data, and other biophysical data, namely slope and hypsometric data. – Information is reclassified in a Geographical Information System (GIS) – accurate estimation for the biophysical conditions for which the use may be developed experts’ opinions or the available cartographical land use data-prior estimation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) 2ºstep description Subject to: Land use Biophysical restrictions
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Calculation of the area 2ºstep description
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Empirical implementation it was necessary to define concretely the study area: – Region of Algarve – 16 counties and 84 parishes
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Region of Algarve Empirical implementation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) The data used Empirical implementation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Considered the following farms’ uses: – cereals (CC); – Other temporary crops (OCT); – Fallows (PO); – citrines (CT); – other fresh fruits (OFF); – olive trees (OL); – almond trees (AM); – Other permanent crops (OCP); – permanent pastures (PP) – “other occupations” (OO) Empirical implementation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Applied to the year 1999 Used the Agricultural Census data Necessity of validation Empirical implementation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) The model was applied following two variants: – 1) disaggregation of data of the different administrative units (counties); – 2) disaggregation at a local pixel level (1 km2) The errors’ limits definition The lack of data Some considerations Other adaptations Empirical implementation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Results 1º Variant of the model
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Results 2ºvariant of the model Data at pixel level Olive treesCitrines
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Validation Deviation measures
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Validation 1ºvariant of the model
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Validation 1ºvariant of the model – The WPADi – The WPAD 17,787%. The counties‘ WPADi
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Validation 2ºVariant – Limited to a sample of counties – It’s under development in some aspects
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Validation
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Conclusions The model proved for the first time for Portugal a new way of disaggregating data Some problems need still solution Some results of the studies being carried out and now provide better results Some examples The future Innovations
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agriregionieuropa 122 nd EAAE Seminar, February 17 th – 18 th, 2011, Ancona (Italy) Thank you for your atention!
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