Fish Price Volatility
Atle Oglend
Roy Endré Dahl
FAO FPI Workshop, Ischia, 03.10.13
Introduction
• Fishing is a risky venture
– Price variability is a significant risk component
• Few studies on fish-price volatility, relative to
other agricultural commodities
– Data availability
– Single species volatility studies (e.g. Oglend and
Sikveland, 2008; Oglend, 2013, Sollibakken, 2012;
Buguk et. al. 2003)
– Forecast studies (e.g. Guttormsen, 1999; Vukina
and Anderson, 1994; Gu and Anderson, 1995).
Introduction
• We utilize trade-data to analyse fish-price
volatility on a global scale
– Fish is a highly traded commodity group
• Accounts for 10 percent of total agricultural exports
(FAO, 2012)
– Data allows statistical analysis of volatility
• 2012 State of World Fishers report (FAO):
“In the next decade, with aquaculture accounting for a
much larger share of total fish supply, the price swings
of aquaculture products could have a significant impact
on price formation in the sector overall, possibly leading
to more volatility”
Volatility in Agricultural Prices
• Price volatility suggests a fundamental level of
uncertainty and risk
– Generally considered undesriable
– Not all price variations imply uncertainty
• Terms of trade variability can have a negative
impact on economic growth
• Variability in agricultural prices are generally
considered high
– Varies over time and across products
Volatility in Agricultural Prices
• Supply shocks generally considered more important
than demand shocks in terms of price movements
– Variations in catches, stocks, quotas, growth conditions,
climate, diseases etc.
• Elasticity of demand and short-run supply is low
– Higher el. of supply for aq. than capture fisheries
• Elasticity of income is low => macro-economic
fluctuations are of less direct importance to prices
– Impact through input factor prices
• Storability reduces volatility
– Higher volatility for fresh fish
• National trade policies can influence global prices
The FAO fish-price index
• The FAO fish price index summarizes common
trends in fish prices world-wide
100
150
200
Food Price Index
Meat Price Index
Fish Price Index
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Data
• Monthly trade-data on fish and fishery products
imported to the U.S., Japan and EU
– Important import markets
– Reliability of data
• Data provided by the Norwegian Seafood Council in
cooperation with the FAO
• The data is characterized along four dimensions:
1. Markets: EU, Japan, U.S.
2. Technology: Aquaculture, Capture Fisheries
3. Species groups: White Fish, Salmonidae, Crustaceans,
Tuna, Pelagic excluding Tuna, Other Fish,
4. Product forms: fresh, frozen, filet, whole and fishmeat
• Observations from January 1990 to October 2012
Data
• Price = unit import-value
• Volatility = std.dev. of month-by-month log-returns
– Avoids potential trend effects
• 106 unique prices
– Some missing values in the data
– We exclude prices with less than 30 observations
• Additional variables considered when comparing
volatilities:
–
–
–
–
# Obs. used to calculate volatility
Sampling heterogeneity
Monthly average trade volume
C.V. of trade volume
Volatility for different groups
Method
Method
2. Regime Analysis
– Iterated Cumulative Sum of Squares (Inclan and
Tiao, 1994)
• Originally developed to identify volatility regimes in
financial time-series
– We look for differences in volatility across time for
each category
– Only applied to prices with complete observations
– Volatilities in each category is weighted by trade
volume
Accounts for statistical variations across time
Conditioning Variables and Volatility
Regression of Log Std. Dev. on different conditioning variables.
Variable
Constant
Log Mean Trade Volume
Log # obs.
Log C.V. Trade Volume
Log sampling
Heterogeneity
Coefficient
t-stat
Specification Tests (p-values)
-0.213
-0.435
AR 1-2 test:
0.547
-0.170
-6.670
ARCH 1-1 test:
0.165
-0.023
-0.185
Normality test:
0.334
0.548
6.180
Hetero test:
0.459
0.023
0.065
Hetero-X test:
0.722
RESET23 test:
0.087
Conditioning Variables and Volatility
2
R² = 0.2638
log C.V. trade volume
1.5
1
0.5
0
-0.5
2
3
4
5
6
7
-1
-1.5
-2
-2.5
Log trade volume
8
9
10
11
Volatility Across Markets
1. Regression Analysis Results
– No statistically significant differences in volatility across
markets
2. Regime Analysis Results
0.5
0.4
0.3
0.2
0.1
EU
USA
Japan
2012
2011
2010
2010
2009
2008
2008
2007
2006
2006
2005
2004
2004
2003
2002
2002
2001
2000
2000
1999
1998
1998
1997
1996
1996
1995
1994
1994
1993
1992
1992
1991
1990
1990
0
Volatility Across Technology
1. Regression Analysis Results
– Aquaculture prices significantly lower volatility than
capture fisheries(wild) prices
2. Regime Analysis Results
0.6
0.5
0.4
0.3
0.2
0.1
Aquaculture
Wild
2012
2011
2010
2010
2009
2008
2008
2007
2006
2006
2005
2004
2004
2003
2002
2002
2001
2000
2000
1999
1998
1998
1997
1996
1996
1995
1994
1994
1993
1992
1992
1991
1990
1990
0
Volatility Across Species
1. Regression Analysis Results
– Significantly higher volatility for the pelagic group
• Supply from capture fisheries
• Robust against trade volume and trade variations
– Some evidence that the Salmonidae group has
lower volatility
• Significant only when trade variation is accounted for
Volatility Across Species
2. Regime Analysis Results
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Other fish
White fish
Salmon
Crustaceans
Pelagic (other than Tuna)
Tuna
2012
2012
2011
2010
2010
2009
2008
2008
2007
2006
2006
2005
2004
2004
2003
2002
2002
2001
2000
2000
1999
1998
1998
1997
1996
1996
1995
1994
1994
1993
1992
1992
1991
1990
1990
0
Volatility Across Product Forms
1. Regression Analysis Results
– Fresh vs. Frozen
• No evidence for significant differences in volatility
– Filet, Fish-meat and Whole fish
• Filet has significantly lower volatility than whole fish
and fish-meat
• Robust across trade quantity and variation
fresh
frozen
2012
2011
2010
2010
2009
2008
2008
2007
2006
2006
2005
2004
2004
2003
2002
2002
2001
2000
2000
1999
1998
1998
1997
1996
1996
1995
1994
1994
1993
1992
1992
1991
1990
1990
Volatility Across Product Forms
2. Regime Analysis Results
0.6
0.5
0.4
0.3
0.2
0.1
0
filet
whole
fish meat
2012
2011
2010
2010
2009
2008
2008
2007
2006
2006
2005
2004
2004
2003
2002
2002
2001
2000
2000
1999
1998
1998
1997
1996
1996
1995
1994
1994
1993
1992
1992
1991
1990
1990
Volatility Across Product Forms
2. Regime Analysis Results
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Volatility rankings
(lower is higher volatility)
Volatility rankings
(lower is higher volatility)
To Summarize…
• Differences in volatility across fish categories
– No significant difference in volatility across import
markets
– Aquaculture lower volatility than capture fisheries
– Pelagic highest volatility of the species group
– No significant differences between fresh and frozen fish
– Filets lower volatility than whole fish and fish-meat
• Fish vs. other commodities
– Aquaculture comparable volatility to other commodities,
but above chicken and feeder-cattle
– Wild fish (pelagic) very high volatility