1. Interpreting price elasticities and flexibilities of demand at internationally integrated seafood markets
Max Nielsen
Institute of Food and Resource Economics, University of Copenhagen
Workshop in Nantes, April 2011
”Modelling Global Demand for tuna”

2. Outline Issue What determine the price of fish?
Integration of fish markets
Fish price formation
Modeling fish demand
Consequences for fisheries and management

3. 1. Issue Focus: Raw material flow Product flow
To overview fish price formation based on market integration and demand analysis.
To discuss suitable demand models irt.
Marshallian vs. Hicksian
Ordinary vs. inverse
Focus:
Raw material flow Product flow
Fishermen
Contracts and auction market
Processing
Transport and storage
Wholesale trade
Retail trade and catering

4. 2. What determine the price of fish?
Price level determined by:
Catch method and quality
Size of fish
Competition
Eco-labeling
Price development determined by
Supply own/substitutes AC, MC, productivity
Demand population, income, preference growth
Exchange rates
Market structure/integration decisive

5. 3. Integration of fish markets
A market is ”the area within which the price is determined” (Stigler 1969)
Testing the Law of One Price (LOP)
Stationary data
, when A=1 LOP in force
Non-stationary data (VAR model in ECM form)
decomposed into with co-integrating vectors in
A common integrating factor (n-1) is sought
Given rank (n-1) LOP is a test of:
Test results
M. integration
Demand modelling
LOP accepted
Perfect
Aggregate variables
Rank = (n-1)
Partial
Model var. with substitutes
Rank < (n-1)
None
Exclude variables

6. Market integration internationally/inter-species Whitefish
Selected results
Market integration internationally/inter-species
Whitefish
Intern. integration in single species – relative perfect
Between species – exist, not perfect
Salmon
Intern. integration in farmed salmon – perfect
Intern. Integration farmed/wild pacific salmon – probably exist
Integ. large trout/salmon perfect, small trout/salmon absent
Herring
Norwegian-Danish market integration – relative perfect
Close market integration internationally
- only between species in some cases

7. 4. Fish price formation What determine the price of cod?
Whitefish = cod, hake and haddock.

8. 5. Modelling fish demand
Market integration - pre-test of aggregation in demand analysis
Choice of model
Marshallian Hicksian demand
Inverse ordinary demand
Applying inverse demand models
Dual approach

9. Marshallian and Hicksian demand
Marshallian – double-log
Hicksian – AIDS
Restrictions: Adding up
Homogeneity
  Symmetry
Choice
Theoretical consistency
AIDS - preference structure approximated around the optimal point for the true preference structure
Double-log – arbitrary preference ordering
Statistical fit - testability of model
AIDS restrictions testable, many do not test if tested many reject but impose anyway
Double-log not testable

10. Inverse and ordinary demand
Inverse : p = f(q, m)
Price flexibility = “%-change in price due to a 1% increase in quantity”
Ordinary: q = f(p, I)
Assumptions: p p p
Supply
Supply
Supply q q q
Inverse demand
Ordinary demand
“Real supply”
Choice of model
Inverse – landing markets and analyzing price formation
Ordinary – retail and wholesale markets – aquaculture?
Mixed demand systems
Test inverse and ordinary for statistical fit

11. Empirical studies finds:
Comparing
Theory states:
Empirical studies finds:
Houck (1966)/Huang (1994) also find systematic difference
Difference due to degree of substitution included:
Ordinary – price exogenous, influenced by substitutes
Inverse – quantity exogenous, only influenced by one fishery
unreliable approximation for
Average
Inverse demand
Ordinary demand
- of 75 own price flexibilities
-0.30 [-1.00; 0.00] .
- of 66 own price elasticities (inverted)
-0.94 [-4.76; -0.05]

12. Applying inverse demand models
Price effects of a 10% reduction in quantity on the total market

13. European fish market integration (JAE 2009)
Issue – identify total fish demand in Europe
Assume perfect market integration for single species in Europe
Identify market integration between 23 species fresh/frozen
Estimate inverse demand –species with m. integration included
Market integration test – VAR in ECM non-stationary price series
Market integration:
Data and estimation
Monthly data from EU-15, NO, ICE and FAR
Co-integration for up to 4 species search procedure
Potential substitutes clustered irt. type, color of meet, size price level and fat content
Results – 20 reliable co-integrated models identified
LOP holds in 7 models

15. Demand for fish in Europe (MRE resubmission)
Model – double-log inverse co-integrated demand model estimated for non-stationary variables
Own-price flexibilities for fresh fish
Average – 1.10
Cod – 1.26
Sole – 1.17
Hake – 0.21
Plaice not ident., own quantity unimportant – many subst.
Larger own-price flexibilities than for country-wise studies
A larger share of global markets included
Other reasons? Co-integrated demand?

16. 6. Consequences for fisheries and management
Depend on:
Extent of transforming price changes through value chain
The fisheries share of total world supply
Small – fishery price taker, management does not affect prices
Large – price is relevant in setting optimal fisheries management
Quota changes can be coordinated
Ex. a recovery plan
Elastic demand
lower long-run prices
But: what about the
transition period? p
SOA=AC
SOM=MC A B D q

17. Taking price effects into account might ease recovery plans
Effect on turnover of changing quantities at internationally integrated markets – transition period for recovery plans
Turnover = price*quantity
Taking price effects into account
might ease recovery plans