Tuna Price in Relation to
Economic Factors and Sea
Surface Temperature
Minling Pan, Ph.D.
Samuel G. Pooley, Ph.D.
Pacific Islands Fisheries Science Center, NMFS
Acknowledgments
„
This project was funded by cooperative
agreement #658848 between JIMAR and
NOAA
„ Kurt Kawamoto and other PIFSC staff
Previous Studies on Tuna Price in
Hawaii Market
„
McConnell, et. al. 1998
‹ Fish quality (grade) vs. price
‹ Evaluate price on the basis of the grade of fish,
not on a species basis
„
Bartram, et. al. 1996
‹
Fish grading vs. pricing
‹
Graded based on species, size, body defects,
& muscle quality
‹
Price varied by species and grade
Previous Studies on Tuna Price in
Hawaii Market (cont’d)
„
Pooley, 1991
‹ Yellowfin price (monthly) vs. landings
‹ Correlation w/ landings insignificant
‹ Suggested to use weekly data & evaluate
substitutive effect
„ Pooley, 1990
‹
Pelagic price (weekly) vs. landings
‹
Tuna price correlation w/ landings is weak
Objective of the Current Study
„
Evaluate the main factors that affected
seasonal variation of tuna price for
individual species
‹ Weekly price
‹ Landings
‹ Substitutes
‹ Seasonal demand (holidays)
‹ Quality change caused by oceanographic
factors
Tuna production & Revenue
Composition
Tunas 68%
Non-Tunas
32%
Bigeye
Yellowfin
Albacore
Skipjack
Total Commercial Revenue of Hawaii Fisheries in 2001
$48.5 million
Price Variation by Species
Price ($/lb)
3.5
3
2.5
2
1.5
1
0.5
0
Bigeye
Yellowfin
Skipjack
Albacore
Annual Average Price by Species in Hawaii Market, 2001
Market Preference vs. Price
„
Market preference toward fresh tuna in
Hawaii market
Bigeye > yellowfin > albacore/skipjack
„
World market price (mainly cannery)
Albacore > yellowfin > bigeye > skipjack
Tuna Price Variation by Season
Bigeye
Skipjack
Price ($/lb)
7.00
Yellowfin
Albacore
6.00
5.00
4.00
3.00
2.00
1.00
0.00
0
3
6
9
12 15 18 21 24 27 30 33 36 39 42 45 48 51
Week
Weekly Tuna Prices in Hawaii Market, 1996
Short-term Demand of Fresh Fish
Seasonal variation
Price
Low supply
High supply
• Short shelf life
• Supply depends on
biological availability
• Price goes down as
supply increases
Quantity
Price-dependent Equation
Commonly used in estimating demand of
agricultural products where price and
quantity is determined recursively
„ Fishermen may not be able to change
supply in response to price change in shortterm
„ Price is dependent variable
„
Price = f (Supply, Substitutes, Lagged price, Seasonal demand)
Yellowfin Landings and Price, 1994-1996
Price
($/lb)
Yellowfin Price
Yellowfin Landings
Landings
(1,000 lbs)
4.50
300
1994
4.00
1995
1996
250
3.50
200
3.00
2.50
150
2.00
100
1.50
1.00
50
0.50
0
0.00
0
8 16 24 32 40 48 3 11 19 27 35 43 51 6 14 22 30 38 46
Week
Estimated Price Dependent Equation Yellowfin
Constant
Coefficient
2.140
t - statistic
9.81*
Landings of yellowfin
- 0.003
- 3.60*
Landings of bigeye
Landings of skipjack
- 0.002
- 0.003
- 2.18*
- 3.50*
0.308
0.346
3.33*
4.37*
One-week lagged price
Holiday Dummy
* 5% significance level
R2 adjusted: 0.30
Observations: 158 (1994-1996 weekly data)
Skipjack Landings and Price, 1994-1996
Price
($/lb)
3.00
2.50
Skipjack Price
1994
Skipjack Landings
1995
Landings
(1,000 lbs)
1996
120
100
2.00
80
1.50
60
1.00
40
0.50
20
0.00
0
0 8 16 24 32 40 48 3 11 19 27 35 43 51 6 14 22 30 38 46
Week
Estimated Price Dependent Equation Skipjack
Constant
Landings of skipjack
Landings of ahi (bigeye
& yellowfin)
Landings of albacore
One-week lagged price
Coefficient
1.326
- 0.007
- 0.001
t - statistic
9.48*
- 5.13*
- 3.09*
- 0.001
0.429
- 1.74
6.69*
* indicates 5% significance level
R2 adjusted: 0.36
Observations: 158 (1994-1996 weekly data)
Albacore Landings and Price, 1994-1996
Price
($/lb)
Albacore Price
Landings
(1,000 lbs)
Albacore Landings
3.50
350
1994
3.00
1995
1996
300
2.50
250
2.00
200
1.50
150
1.00
100
0.50
50
0.00
0
0
8 16 24 32 40 48 3 11 19 27 35 43 51 6 14 22 30 38 46
Week
Estimated Price Dependent Equation Albacore
Constant
Landings of albacore
Landings of Ahi (bigeye
& yellowfin)
Landings of skipjack
One-week lagged price
Coefficient t - statistic
1.18
7.55*
- 0.002
- 2.96*
- 0.001
- 2.07*
- 0.003
0.429
* indicates 5% significance level
R2 adjusted: 0.49
Observations: 158 (1994-1996 weekly data)
- 1.78
5.97*
Bigeye Price and Landings, 1994-1996
Price
($/lb)
Hawaii Bigeye Price
Hawaii Bigeye Landings
Landings
(1,000 lbs)
9.00
300
8.00
250
7.00
1994
1995
1996
6.00
200
5.00
150
4.00
3.00
100
2.00
50
1.00
0.00
0
0
8 16 24 32 40 48 3 11 19 27 35 43 51 6 14 22 30 38 46
Week
Estimated Price Dependent Equation Bigeye
Constant
Landings of bigeye
Coefficient t - statistic
8.646
5.60*
- 0.004
- 3.18*
Landings of yellowfin
- 0.007
Landings of skipjack
- 0.006
One-week lagged price
0.277
Holiday dummy
0.560
Sea surface temperature (°F) - 0.209
* indicates 5% significance level
R2 adjusted: 0.50
Observations: 158 (1994-1996 weekly data)
- 4.47*
- 1.98*
4.24*
3.04*
- 3.74*
Summary
Price fluctuation is related to a series of
seasonal variables, such as landings and
holiday demand;
„ Each tuna species appeared to have its
unique price dependant equation;
„
Weekly Bigeye and Yellowfin Price, 1996
Price ($/lb)
Bigeye
Yellowfin
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
0
3
6
9
12 15 18 21 24 27 30 33 36 39 42 45 48 51
Week
Summary
„
„
„
„
„
Price fluctuation is related to a series of seasonal
variables, such as landings and holiday demand;
Each tuna species appeared to have its unique
price dependant equation;
Substitutive effect between yellowfin & bigeye is
stronger than that between albacore & skipjack;
Holiday demand may lead to higher price on more
preferable tunas (like bigeye and yellowfin), but
unlikely affect price of skipjack and albacore;
Bigeye price strongly correlates to seasonal
change in sea temperature.
Monthly Wholesale Price in Japan 10 Major
Wholesale Markets, 1998-2000
Volume (M.T.)
Bigeye
Price (Yen/K g)
1,900
1,700
1,500
1,300
1,100
900
700
500
Price
1,900
1,700
1,500
1,300
1,100
900
700
500
Volume
1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
1998
1999
2000
Price (Yen/K g)
1,500
Volume (M.T.)
3,000
Yellowfin
1,300
2,500
1,100
2,000
900
1,500
700
Price
1,000
Volume
500
500
1 2 3 4
5 6 7 8
1998
9 10 11 12 1 2 3 4
5 6 7 8
1999
9 10 11 12 1 2 3 4
5 6 7 8
2000
9 10 11 12
Question……
„
Further research