Luca Camanzi, Luca Mulazzani, Giulio Malorgio EAFE Workshop: “Optimising Value Chains in...

Luca Camanzi, Luca Camanzi, Luca Mulazzani, Luca Mulazzani, Giulio MalorgioGiulio Malorgio

EAFE Workshop: “Optimising Value Chains in Fisheries” 1-2 June 2010 - University of Helsinki, Finland


Introduction: EU policy frameworkMain 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 resources in 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”.



Providing empirical insights on the relevant geographical scale of the market for the most important pelagic fish species:

- European Anchovy - Engraulis encrasicolus - Sardine - Sardina pilchardus

Objective of the study

Veneto and Emilia Romagna

Pelagic pair trawlers


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)

Supply chain description: catches

Italia Emilia Romagna Veneto Anchovies 45.039 100% 9.021 20,0% 6.294 14,0%

Sardines 12.025 100% 1.046 8,7% 2.286 19,0%

Total 216.567 100% 23.763 11,0% 21.549 10,0%


Supply chain description: supply balancerelevant exposure to international trademain trade partners:

import – Croatia (86% anchovies, 55% sardines)export – Spain (90% anchovies, 60% sardines)

45.039

2.987

-12.282

35.744

15.315

759

-8.965

7.109

-20.000

-10.000

-

10.000

20.000

30.000

40.000

50.000

catches import export internal availability

Anchovies

Italia Emilia+Veneto

12.025

4.470

-3.116

13.379

3.332 2.232

-2.347

3.216

-5.000

-

5.000

10.000

15.000

catches import export internal availability

Sardines



Supply chain description: supply balancecatches allow to attain self sufficiency

(especially anchovies)higher internal availability for anchovies

largely demanded by national processing industry (main species together with yellowfin tuna)



Self sufficiency(catches / internal availability)Import penetration(import / internal availibility)Export propensity(export / catches)Export to import ratio(export / import)

Anchovies Sardines

126% 215% 90% 104%

8% 11% 33% 69%

27% 59% 26% 70%

411% 1181% 70% 105%


About 70 markets scattered along the coast6 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

Supply chain description: markets


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 variabilityPrincipal Component Analysis (PCA)

empirical regression model

Data and methodology


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

Descriptive analysis: price-quantity relation

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0,00

0,50

1,00

1,50

2,00

2,50

3,00

(ton)

(€/k

g)Italia - anchovies

quantity price

0

500

1000

1500

2000

2500

3000

3500

0,00

0,20

0,40

0,60

0,80

1,00

1,20

1,40

1,60

1,80

(ton)

(€/k

g)

Italia - sardines

quantity price

price quantityanchovies 40% 48%sardines 53% 163%

Variability index


Descriptive analysis: PCA anchovies

Cattolica

Rimini

Cesenatico

Goro

Chioggia

Pr_Ca

Pr_IT

Qt_ChEsQt_IMP

Pr_IMP

Qt_EXP

Pr_EXP

Qt_Ca

Qt_Ri

Pr_RiQt_Go

Pr_Go

Qt_Ce

Pr_Ce

Qt_IT

Pr_ChEs

Qt_ChNa

Pr_ChNa

Qt_ChLo

Pr_ChLo-0,600

-0,400

-0,200

0,000

0,200

0,400

0,600

0,800

1,000

-1,000 -0,800 -0,600 -0,400 -0,200 0,000 0,200 0,400 0,600 0,800 1,000

Quantities Prices

Import qt.


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)

Market definition and market integration


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)

Price formation on ex-vessel markets


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.

Price-quantity relation and market geographical scale


The purpose of the empirical model is therefore to calculate price 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.

The empirical regression model


Full model specification:ln Pit = a0 + a1 ln Qlocit + a2 ln Qnatit

+ a3 ln Qlocjt + a4 ln Qnatit

+ a5 ln Qimpit + a6 ln Yt + et

Estimation results show that the following variables are not significant:

cross species effects import income

The empirical regression model


Estimation results: AnchoviesMarket National production Variance

explainedCattolica -0,06 (0,039)* Adjusted R2 = 0,43Cesenatico -0,20 (0,078)** Adjusted R2 = 0,70Chioggia -0,24 (0,073)*** Adjusted R2 = 0,49Goro -0,08 (0,033)*** Adjusted R2 = 0,80Rimini -0,32 (0,080)*** Adjusted R2 = 0,67

Market Market quantity National production Variance explained

Cattolica -0,06 (0,017)*** 0,00 (0,036) Adjusted R2 = 0,58

Cesenatico -0,08 (0,034)** -0,15 (0,078)** Adjusted R2 = 0,72

Chioggia 0,06 (0,056) -0,36 (0,106)*** Adjusted R2 = 0,53

Goro -0,01 (0,014) -0,07 (0,035)** Adjusted R2 = 0,80

Rimini -0,02 (0,043) -0,34 (0,088)*** Adjusted R2 = 0,66


Estimation results: Sardines

Market National production Variance explainedCattolica -0,05 (0,070) Adjusted R2 = 0,21Cesenatico -0,27 (0,098)*** Adjusted R2 = 0,48Chioggia -0,15 (0,071)** Adjusted R2 = 0,27Rimini -0,05 (0,045) Adjusted R2 = 0,39

Market Market quantity National production Variance explained

Cattolica -0,10 (0,025)*** 0,09 (0,071) Adjusted R2 = 0,38

Cesenatico -0,14 (0,028)*** -0,04 (0,094) Adjusted R2 = 0,57

Chioggia -0,15 (0,036)*** 0,03 (0,067) Adjusted R2 = 0,48

Rimini -0,09 (0,032)*** -0,02 (0,043) Adjusted R2 = 0,47


The results of the empirical assessment conducted showed:a negative relation between price and quantity of

the pelagic species consideredprice 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

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.

Conclusions

Luca Camanzi, Luca Mulazzani, Giulio MalorgioUniversity of Bologna

Department of Agricultural Economics and [email protected]

[email protected]@unibo.it

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