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EuMed Agpol Project Annual meeting Montpellier, 17th - 19th, May, 2006

EuMed Agpol Project Annual meeting Montpellier, 17th - 19th, May, 2006. The EU Fruit & Vegetable Synthetic Regional Vulnerability Index (SRVI) Jean-Louis Rastoin, Nassima Ayadi, Jean-Claude Montigaud Agro.Montpellier, Inra, UMR Moisa. Theoretical Background.

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EuMed Agpol Project Annual meeting Montpellier, 17th - 19th, May, 2006

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  1. EuMed Agpol Project Annual meeting Montpellier, 17th - 19th, May, 2006 The EU Fruit & Vegetable Synthetic Regional Vulnerability Index (SRVI) Jean-Louis Rastoin, Nassima Ayadi, Jean-Claude Montigaud Agro.Montpellier, Inra, UMR Moisa

  2. Theoretical Background • Vulnerability depends on capabilities level (Sen, 1985) • Capabilities are constituted by actors resources & competencies (RBV, Wernerfelt, 1984) and macro-economic & institutional framework (North, 1990) • To estimate regional vulnerability, we have to characterize the “filière” (supply chain, marketing channels), and its embeddedness (economic & institutional environment)

  3. Methodology • Survey at regional level (EU nuts 2) • Construction of a multi-criteria Index for each region based on “supply to consumer chain” analysis with SSP (Scherer, 1973) and GVC (Gereffi, 1994) models • Identification of forecast scenarios • Benchmarking (ranking) of the Regions sample on a synthetic index basis

  4. The Synthetic Regional Vulnerability Index (SRVI) • Linear function of 4 “scores” IVR = 1/ (FF&V) x  + (PF&V) x  + (MCE) x  + (RWI) x  • , , , , weighting coefficients • The 4 scores (“strategic levels” of SCC) • FF&V : Fresh fruit & vegetable sector • PF&V : Processed Fruit & vegetable • MCE : Marketing channels enterprises • RWI : Regional Wealth Indicator • Weighting coefficient are estimated by expertise and simulations

  5. The SRVI Components

  6. The SRVI Components

  7. The SRVI Components

  8. The SRVI Components

  9. The RVI calculation principle • For each indicator i : Value for region j / Average of all regions • Algebraic sum of i values = score value (FF&V, PF&V, MCE, RWI)

  10. The sample

  11. The 4 scenarios

  12. Main results (scenario 4)

  13. Discussion • Results are globally conform to empiric observations (i.e. F&V SCC is a global value chain driven by retailers) • SRVI reflects industry performances, but also economic environment situation • Limits of databases : RICA, Amadeus representativeness and errors • Strong heterogeneity of F&V sector between regions and products • Asymmetries between chain actors • Corporate governance : localization of firms headquarters (where is the decision-making ?)

  14. Conclusion : Some proposals to link together WPs • Assumptions • - EU Import increase from SEMC (CAPRI & Delphi results) => • - Market loss for EU med countries => • - F&V production decrease (Yd) => • - F&V producers revenue loss • Yd regional estimation (for each EU med country): • Yd for region j = (RVIj / Sum RVIj) x (National import increase or loss in national agricultural income)

  15. Proposal to link up WPs: possible weighting coefficient for loss calculation by region

  16. Proposal to link together WPs • Possibility to estimate impact by sub-sector: • Fresh Fruit (23 EU SEMC regions) • Fresh vegetable (24 regions) • Fresh F&V (34 regions) • Processed F&V (63 regions) (Biggest EU SEMC production regions)

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