Interpreting Price Elasticities in Global Seafood Markets: Workshop Insights

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, 14-15 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 • 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

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:

6. 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. 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

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 1995-2006 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. 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