Luca Camanzi , Luca Mulazzani , Giulio Malorgio

1. EAFE Workshop: “Optimising Value Chains in Fisheries” 1-2 June 2010 - Universityof Helsinki, Finland Northern Adriatic ex-vessel markets’ integration:an empirical investigation on small pelagic species Luca Camanzi, Luca Mulazzani, Giulio Malorgio

2. Introduction: EU policy framework • Main issues at stake in EU fisheries: - stocks’ overexploitation and - socio-economic sustainability • Management plans institution - Reg. No. 104/2000, 2371/02, 1198/06; 1967/06 (Mediterranean sea) – as a means to move towards a long-term perspective on fisheries management, to consider regional differences and to increase stakeholder involvement

3. Introduction:the Northern Adriatic Strategic Agenda • The Italian Regions of Emilia-Romagna, Friuli Venezia Giulia and Veneto have established a collaborative relationship with the other coastal communities of the Northern Adriatic Sea, • For the implementation of shared common policies for the coordinated management of common resourcesin order to promote sustainable development in the Northern Adriatic fisheries sector. • Institutional agreements and common program document called “Strategic Agenda for Sustainable Development of the Northern Adriatic ichthyic sector”. EAFE Workshop: “Optimising Value Chains in Fisheries” 1-2 June 2010 - Universityof Helsinki, Finland

4. Objective of the study • Providing empirical insights on the relevant geographical scale of the market for the most important pelagic fish species: • European Anchovy - Engraulisencrasicolus • Sardine - Sardinapilchardus Pelagic pair trawlers Veneto and Emilia Romagna

5. Supply chain description: catches • Anchovies and Sardines are the two most important fish species and the first and third seafood products in Italy • Emilia Romagna and Veneto account for a large share of national catches (tons)

6. Supply chain description: supply balance • relevant exposure to international trade • main trade partners: • import – Croatia (86% anchovies, 55% sardines) • export – Spain (90% anchovies, 60% sardines)

7. Supply chain description: supply balance • catches allow to attain self sufficiency (especially anchovies) • higher internal availability for anchovies • largely demanded by national processing industry (main species together with yellowfin tuna)

8. Supply chain description: markets • About 70 markets scattered along the coast • 6 in Emilia Romagna and 6 in Veneto • the study considers 4 markets in Emilia-Romagna and 1 in Veneto that account for almost 100% of pelagic species market transactions • share of market transactions on landings (ER+VE): • anchovies - 37% • sardines - 77% • important role of markets in price formation (auctions) –> benchmark for other transactions

9. Data and methodology • data consist of 5 years monthly time series of price and quantity for: • 5 ex-vessel markets transactions (Orei) • import and export (Eurostat) • national catches and price (Irepa) • preliminary descriptive analysis of data: • market observations variability • Principal Component Analysis (PCA) • empirical regression model

10. Descriptive analysis: price-quantity relation • Variability is higher for quantity rather than for price • Variability is higher for sardines than for anchovies, both for quantity and price • Observations suggest a negative relation between price and quantity

11. Descriptive analysis: PCA anchovies Quantities Prices Import qt. Chioggia Goro Cesenatico Rimini Cattolica

12. Market definition and market integration • The market is the area within which price is determined(Marshall 1961, Stigler and Sherwin 1985). • If there is a single price over a given area, than must mean that either buyers or sellers (or both) consider transaction at any point within the area to be an excellent substitute for transactions at other points within the area (Stigler and Sherwin 1985). • The concept of market integration is not clearly defined, and often based more on statistical criteria than on economic phenomena (McNew 1996)

13. Price formation on ex-vessel markets On seafood ex-vessel markets, production quantity is not greatly affected by the prices, since the supply is closely connected to exogenous factors such as: biological cycles, the weather, and fishing regulations. Supply is exogenously determined and price represents the dependent variable. It is therefore correct to apply an inverse demand model: pi = f(m,qi,qj)

14. Price-quantity relation and market geographical scale • Normally, empirical investigations do not consider the influence of product availability at different geographical levels to analyse price-quantity relationships. • BUT, if two quantity time series are strongly correlated (such as local and national production) an inappropriate price-quantity relationship could result statistically significant even without any real economic relation.

15. The empirical regression model The purpose of the empirical model is therefore to calculateprice flexibility in the ex-vessel markets of the Emilia Romagna and Veneto Regions, affected by changes in local production (quantity landed and sold in each port) and national production. To quantify the price-quantity relationship a double logarithmic inverse demand system is used, where the product price on a market is a function of both the local catches and the larger market’s catches (Nielsen, 2005) Other determinants of price will be tested in addition at the basic model, such as income, cross effects between species, imports, trends and seasonal dummies.

16. The empirical regression model Full model specification: lnPit = a0 + a1lnQlocit+ a2 lnQnatit+ a3lnQlocjt+ a4 lnQnatit+ a5 lnQimpit + a6 lnYt + et Estimationresults show that the followingvariables are notsignificant: • cross species effects • import • income

17. Estimation results: Anchovies

18. Estimation results: Sardines

19. Conclusions • The results of the empirical assessment conducted showed: • a negative relation between price and quantity of the pelagic species considered • price flexibility coefficients are smaller than 1, according to most literature results • a statistical significance of both national and local quantity, varying across to the species and markets considered

20. Conclusions • When empirical models do not consider the different geographical levels of markets, estimation results can be statistically significant without explaining the relevant economic phenomena • even for some of these markets we cannot exclude that the most appropriate level of integration is neither the local nor the national, but some sort of intermediate regional level. • If policy intervention is targeted on price and income, the governance system (i.e. management plans) should consider the actual level of market integration • where markets are integrated at different geographical levels a pure local management would prove ineffective, requiring at least some common coordination among all the areas within the market boundaries.

21. Thankyouforyourattention. Luca Camanzi, Luca Mulazzani, Giulio Malorgio University of Bologna Department of Agricultural Economics and Engineering luca.camanzi@unibo.it luca.mulazzani@unibo.it giulio.malorgio@unibo.it