Are Commercial fishers Risklovers

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The Board of Regents of the University of Wisconsin System

Are Commercial Fishers Risk-Lovers?Author(s): Hkan Eggert and Peter MartinssonReviewed work(s):Source: Land Economics, Vol. 80, No. 4 (Nov., 2004), pp. 550-560

Published by: University of Wisconsin PressStable URL: http://www.jstor.org/stable/3655810.

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3/12

80(4)

Eggert

and Martinsson:

Are

Commercial

Fishers

Risk-Lovers?

551

a choice

experiment.

As far

as

we

know,

our

study

is the first to estimate fishers' risk

preferences using

stated

preference

tech-

nique.

We collect informationon the

fish-

ers'

preferences by asking

them to choose

between pairs of different fishing tripsde-

scribed

only by

the mean and

the

spread

of the net revenue.

Thus,

risk is

character-

ized

by

the

spread

of the net revenue and

it is assumed to follow a uniform distribu-

tion

in

order to reduce the

cognitive

bur-

den

for the

respondents

when

making

a

choice. Each fisher makes six

pair-wise

choicesbetween different

ishing

rips.

From

the

choices,

it

is

then

possible

to obtain

a

lower and an

upper

bound of the size

of

the degree of risk aversion. We employ a

utility

function that is

independent

of

ini-

tial wealth levels and allowsthe

respondent

to be

risk-averse, isk-neutral,

r

risk-loving.

This model framework fits into the

pros-

pect theory

framework and

corresponds

to

constant absolute risk-aversion

CARA)

as

well.

Thus,

it

provides

a test of whether

re-

spondents

are

expected-utility

maximizers.

In

the

analysis,

we

classify

our

respon-

dents into three

groups,

which

we label risk-

neutral,modestly risk-averse,and strongly

risk-averse,

with

proportions

of

48%, 26%,

and

26%,

respectively.

The

degree

of

stated

risk aversion is then used as a

regressor

n

a

Cobb-Douglas production

function.

We

find that fishers

with

a

strongdegree

of risk-

aversion have a

significant

lower

landing

value and earn 23% less

compared

to risk-

neutral ishers.Thefractionof a household's

income

generated

from

fishing

is

a

signifi-

cant variable in

explaining

risk attitudes:

the

higher

the

fraction,

the more risk-neu-

tral the fisher. Fishers using trawl as the

only gear

tend to be risk-neutral

compared

to

other

fishers,

which

may

reflect the fact

that

trawl

fishing

in

general implies

more

expensive gear.

Risk-averse fishers

prefer

to

use

gillnet,

as

this

gear

implies

smaller

investment

in

gear.

The Swedish fisheries

are

regulated

open

access

with no element

of individual

quotas

(IQs),

which

implies

a

potential

threat

of

seasonal closure

when

the total allowable catch for a

species

is

caught.We asked fishers their opinion of

IQs

and found that fishers

who are

positive

about

IQs

are also more risk-averse.Nota-

bly,

we find

that

wealth

does

not

seem to

influence

risk

preferences.

Neither

simple

proxies

such

as

boat

size or

a

property

tax

dummy,

nor various measures of

lifetime

wealth could explaindifferences in riskat-

titudes.

Thus,

for

the

fishers

in our

sample,

the

short-run

decision on where and how to

allocate

fishing trips

of a few

days

seems to

be

independent

of initial wealth level.

Bockstael

and

Opaluch(1983)

confirmed

the

hypothesis

that the fishers

in

their sam-

ple

were

homogeneously

risk-averse. In

their

sample,

fishersmade an annual

choice

of location and

species implying

high

stakes.

In

such cases

or when stakes are even

higher such as in the investment decision

of

purchasing

a new

fishing

vessel,

the

ex-

pected-utility prediction

of risk

aversion

seems reasonable.

However,

fishers often

make decisions on

a

more short-term

basis.

Target species, gear

choice,

and location

choice are recurrent decisions made

by

fisherson a

per-trip

basis,

indicating

a time

span

of 1

to 30

days

for

each

trip.

The

standard

point

of

departure

for economics

is that rational

agents

have a

long-term

planninghorizon,forexample, dynamic a-

bor

supply

and lifetime wealth

suppose

that

an

individual evaluates choices

over

many years.

This idea is

frequently

chal-

lenged by

modern

research

in behavioral

economics. Camerer

et

al.

(1997)

find

that

wage elasticity

is

negative

for New

York

cabdrivers,

that

is,

they

would rather take

one

day

at a

time

and work shorter hours

during

good

days

while

working longer

hours

during

bad

days.

Moreover,

expected

utility heory

cannot

explainwhy

stockshave

outperformedbonds over the last century

by

a

surprisingly large margin,

which

is

referred to as the

equity premium puzzle

(Mehra

and Prescott

1985).

In

fact,

the

standard

theory

of

expected utility

is

ques-

tioned and some influential scholars even

claim that it is

plainly

wrong

and fre-

quently

misleading

(Rabin

and Thaler

2001,

230).

Two useful

concepts

from mod-

em

researchon choice under

uncertainty

re

loss aversion and mental

accounting,

both

of whichmay explainmodest-scaleriskaver-

sion. Lossaversion

s

part

of

prospect heory

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4/12

552

Land Economics

November

2004

(Kahneman

and

Tversky 1979),

where deci-

sion

makersreactto

changes

n

wealthrather

than to levels of

wealth.

It is found

that

individuals

are

roughly

twice

as

sensitive

to losses

than to

gains,

that

is,

a

coin-flip

bet is only accepted if the odds are better

than

two-to-one. Mental

accounting (Kah-

neman and

Tversky 1984)

refers to the

im-

plicit

methods individualsuse

to

code and

evaluate

outcomes

from,

for

example,

in-

vestments or

gambling.

One

example

relat-

ing

to

mental

accounting

is that

long-term

investors seem to evaluate their

portfolio

more

frequently

than the actualtime hori-

zon of

the investment.

Benartzi

and Thaler

(1995)

call

the combination of short evalu-

ation periods and loss aversion, myopic

loss

aversion,

and hold that this

phenome-

non

explains

the

equity premium

puzzle.

Loss

aversion is

probably

also

an

impor-

tant

aspect

of

fishers,

which

in

our

results

is

reflected

by

the

majority

of

respondents

being

risk-averse.

Short evaluation

periods

or narrow

bracketing

is a

way

of

simpli-

fying

decisions

by

isolating

them from the

entire

streamof decisionsin which

they

are

embedded

(Read

and

Loewenstein

1996).

The sub-optimal expected utilitybehaviorof the fishers in the Mistiaen and Strand

(2000)

study

makes

sense

if

we

take narrow

bracketing

nto account. The fishers do not

evaluate

the annual

outcome

of several

trips,

but more

probably

evaluate each

trip

separately.

Our

study

also seems to reflect

myopic

risk

aversion

among

the

strongly

risk-averse.

These

fishers,

26%

of

the re-

spondents,

were

willing

to

accept

a 23%

reduction

in

expected

net revenue for a

modest

reduction in risk.

Probably

these

fishers will continue choosing the risk-

averse

strategy

all

year

round

earning

23%

less than

they

could,

because

they

evaluate

each

fishing trip

separately,

instead of

evaluating

less

frequently.

II.

BACKGROUND

The

seminal

paper by

Bockstael

and

Opaluch

(1983)

studied choice

under

un-

certainty

among

fishers in New

England,

who made annualdecisionson targetspecies

and location

choice;

substantial ncome

lev-

els were at

stake.

The

results showed

that

all

fishers

in

the

sample

had constant rela-

tive risk aversion

(CRRA) equal

to

one,

that

is,

the wealthier the

fisher,

the

less

risk-averse,

which

is

the

expected

outcome

within the

expected

utility

framework. Du-

pont

(1993) applied

the same

framework,

again

to

study

annual

choices of

species

and

location,

but added

price uncertainty

to the

analysis.

The strict

assumption

of

risk-averse fishers was not

rejected

in

three

of four

vessel

types.

However,

fishers

often

make

decisions on a more short-term

basis.

Target species, gear

choice,

and

location

choice are

decisions

often made

by

fishers

at the

trip

level,

where

trip

duration nor-

mally is 1 to 30 days. Mistiaen and Strand

(2000)

studied fishers' location choice at

trip

level,

where a

majority

was

using

fish-

ing grounds

that were

easily

accessed.

They

found

heterogeneous

risk

preferences

among

fishers and

that

at

least 95% of the

trips

could be characterized as

risk-averse.1

As

noted

above,

expected-utility theory

predicts

risk

neutrality

as the

optimal

strat-

egy,

not

only

over modest

stakes,

but also

for

quite

sizable and

economically impor-

tant stakes (Rabin 2000). Risk-averse be-

havior for

repeated

modest stakes will lead

to

substantial income reduction

in

the

long

run,

that

is,

the more risk averse a fisher

is,

the lower the

aggregate

income

he

will

earn.

Eggert

and Tveteris

(2004)

study

risk

preferences

among

fishers

who

generally

carry

out

trips

of

less

than five

days,

assum-

ing

that risk

preferences

are

independent

of

initial wealth

levels,

that

is,

CARA. The

results indicate that not more than

70%

of the trips can be characterized as risk-

averse.

Another

study inspired by

Bock-

stael and

Opaluch

(1983)

is Holland and

Sutinen

(2000).

Their

results indicated risk-

loving

behavior

among

fishers,

but

according

to

the

authors,

fishers

in their

sample

tried

to

reduce

their risk

in

ways

that were not

captured by

their model.

1

Fishers are assumed to be

normally

distributed in

risk

preferences

and

the

5% risk lovers are

to some

extent an artifact of this assumption (Revelt and

Train

1998).

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5/12

80(4) Eggert

and Martinsson: Are

Commercial

Fishers Risk-Lovers? 553

III. MEASURING FISHERS'

RISK PREFERENCES

In

real world

fisheries,

fishers have to

make

several decisions

concerning

choices

and trade-offs between potentially large

numbers

of

discrete

choices.

These choices

may

include

selecting targeted

species,

gear

type,

and

location

choice,

and can be

thought

of as trade-offs between

expected

mean net revenue and net revenue

risk,

but

aspects

such as

comfort,

safety,

and

trip

length may

also influence their choices.

In

our

experiment,

all these

complex

issues

are

condensed

into a

single

choice between

two

alternatives,

where each alternative

is

characterizedby the two parameters mean

and

spread

of net

revenue)

alone.

If

fishers

are risk-neutral

only

the mean

matters,

while risk-averseand

risk-loving

isherswill

make a trade-off between the mean and

the

spread

of

net revenue.

Alternatively,

prospect theory predicts

risk aversion for

gains

at stake and risk

preferences

being

independent

of initial wealth levels. In or-

der to test the standard

expect

utility

the-

ory

as

well as

the

prospect

theory,

we need

a utility function specification, indepen-

dent

of

wealth and

where risk

preferences

can be tested

in an

easy way.

The

CARA

utility

function

specification

meets these

requirements.

This

function

corresponds

to the

mean-standard deviation

represen-

tation within

expected

utility

theory2sug-

gested by

Meyer (1987).

For the

empirical

analysis

we have

U(y)

=

-e-r, [11

where r

corresponds

to the Arrow-Pratt

measure

of

absolute

risk

aversion

(-u /u')

and

y

is

income. This function

is

concave

for r

>

0,

that

is,

reflecting

risk

aversion,

and

correspondingly

reflects risk neutral-

ity

and

risk

loving

for

r

=

0

and

r

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