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Discount Rates in Small‐Scale Fisheries Discount Rates in Small Scale Fisheries

LOUISE TEH

IN HONOUR OF DR. COLIN CLARK CONFERENCE

UBC MAY 15 2012 UBC, MAY 15, 2012

C O R A L R E E F S

Reef Fisheries

• Small‐scale, multi‐species & multi‐gear;
• Extensive overexploitation;
• Extensive overexploitation;
• Over 55% of coral reefs worldwide

threatened by overfishing and threatened by overfishing and destructive fishing (Burke et al. 2011).

Reef Guardian

Threatened coral reef species

Chris Johnson, Odyssey Reef Guardian

Discount rates and fisheries sustainability fisheries sustainability

How willing are fishers to sacrifice their t fi h b fit i d t j current fishery benefits in order to enjoy higher benefits in the future? g

Discount rates and fisheries

• Private discount rate measures one’s willingness to

f i di b fi i d j f forgo immediate benefits in order to enjoy future, bigger benefits; Di ti ff t l t t i bilit f

• Discounting affects long term sustainability of

fisheries resources (Clark 1973, Sumaila 2004);

• Few empirical studies:
• Few empirical studies:

– High discount rates increased intensity of violating fisheries regulations (Akpalu 2008); g ( p ); – Low discount rates associated with less intense fishing pressure (Fehr & Liebbrandt 2008).

Research Questions Research Questions

1 What are the private discount rates of small‐

• 1. What are the private discount rates of small

scale fishers? 2 Under what socio economic conditions do

• 2. Under what socio‐economic conditions do

fishers have low discount rates? 3 A di fl i f fi h

• 3. Are discount rates reflective of fishery

exploitation status?

Study site 1

Study site 2

A li

Fiji

Australia

Fishing Villages

Discount rates of fishers in open access d di i ll d f fi h i

Open access (Sabah):

and traditionally managed reef fisheries

Open access (Sabah):

• No assurance of future benefits from the fishery;
• Forced to entirely discount the future i e use a
• Forced to entirely discount the future, i.e., use a

discount rate of infinity (Clark, 1990). Customary marine tenure (Fiji): Customary marine tenure (Fiji):

• Traditional management of fishing grounds;
• Stewardship of marine resources

lower discount

• Stewardship of marine resources – lower discount

rate.

Teh et al. (submitted)

Eliciting discount rates

• Semi‐structured interviews:

– 75 interviews in Sabah (April/May 2009) – 45 interviews in Fiji (May/June 2008)

• Binary choice series using

hypothetical payments:

– Choose between an immediate, smaller payment or delayed, larger payment

Estimating Discount Rates

Now

($)

1 month

($)

Discount rate (annual%)

Discount Function: ( ) ( )

(annual%)

100 105 29 100 110 86

di t t Discount Function:

100 115 141 100 120 193

r = discount rate y = present value x = future value

100 125 243 100 130 291

t = time delay

100 135 337 100 140 381 100 145 424

Discount rates of fishers in Sabah for 1 month delay

M 265% 33 Mean = 265%  33 Median = 29%

cy requenc Fr Annual discount rate (%)

Discount rates of fishers in Fiji for 1 month delay

Mean = 208%  27 Mean = 208%  27 Median = 121%

cy requenc Fr Annual discount rate (%)

Proportion of fishers choosing each choice i b i

Sabah Fiji

• ption by site

Sabah (%) Fiji (%) ‘Impatient’

30 20

Impatient

30 20

‘Patient’

51 27

Other

19 53

Patience proxy (=ri/r )

0.39* 0.44

( ri/rmax)

*p<0.05

Percentage of respondents at each village who chose the ‘patient’ option who chose the patient option Village Site %

Sibogo Balak Banggi 14 Sibogo Balak Banggi 14 Mabul Semporna 20 Dogoton Banggi 38 Dogoton Banggi 38 Hampalan Laut Semporna 40 Damaran Banggi 67 gg Omadal Semporna 67 Batu Sireh Banggi 70 Sibogo Air Banggi 71 Manawali Banggi 83 Maligu Banggi 100

Defining a low discount rate

Now

($)

1 month

($) Low discount rate = ($) ($)

100 105 100 110

Choosing smallest future payment

• ffered

100 110 100 115 100 120

• ffered

All other choices = non low discount

100 120 100 125 100 130

non-low discount rate

100 130 100 135 100 140 100 140 100 145

Logistic regression model

Identify which socio‐economic factors predict the probability that a fisher chooses a low discount rate a fisher chooses a low discount rate

          W Z X Y

Y = Probability of choosing a low discount rate X, Z and W = matrices of demographic, socio-economic and location variables location variables

3 models: (i) pooled (n=118) (ii) Sabah only (n=73) (iii) Fiji only (n=45)

Prevalence of low discount rates among ll l fi h small‐scale fishers

ents respond % of r

Logistic regression output

Significant predictors of low discount rates among fishers

Variable Pooled Sabah Fiji Variable Pooled Sabah Fiji Protection

+ +

Site

+

Boat ownership

+ ‐

Relative catch

‐ +

Relative catch

‐ +

+ Increases likelihood of a fisher choosing a low discount rate ‐ Decreases likelihood of a fisher choosing a low discount rate

Teh et al. (2011) Sustainability

Coral reefs worldwide

Coral reefs

Economics of overexploition

Theory: Even under restricted access, the sole y ,

• wner of a fishery has an incentive to deplete

the resource if their discount rate  satisfies the condition

 > 2r  > 2r

where r = intrinsic population growth rate of h fi h k (Cl k 1973) the fish stock (Clark 1973).

Data

• 1. Economic

Di t t Discount rates

• Managers = official discount rate ()
• Fishers = private discount rate ( )
• Fishers = private discount rate (p)

2 Biological 2. Biological

Intrinsic growth rates

• Species level (r )

Species level (rs)

• Fishery level (rf)

Species % of catch

0.5 5

rs

0.6 20 1 0 10 1.0 10 0.4 15 0.5 5

0.875 yr-1 Fishery level rf

0.2 15 1.8 22 2.2 5 2.2 5 0.3 3

Comparing discount rates to l exploitation status

Status* Official discount rate () rate () Underexploited  < rf Overexploited  > rf Depleted  > 2r Depleted  > 2rf

rf : Fishery level intrinsic growth rate * Source: Newton et al. 2007 Current Biology

Inferring private discount rates Inferring private discount rates

Status Private discount rate (p) ( p) Underexploited 0.29* < p < rf O l i d  2 Overexploited rf < p< 2rf Fully exploited p= rf y p

p f

* Minimum discount rate from Fiji and Sabah case studies

Fishery level rf

f)

e per yr (rf rowth rate trinsic gr Mean= 0.88 ±0.02 Fiji In Fiji Sabah

Fishery case

Fishery level rf

rf)

Mauritius

Rabbitfish e per yr (r

Mauritius Philippines

Parrotfish rowth rat Surgeonfish Snapper ntrinsic g Grouper In

Bahamas Turks & Caicos

Fishery case

Caicos Teh et al. (submitted)

Official discount rates

1.8 2

ate

1.4 1.6

scount ra

0 8 1 1.2

nnual dis

0.4 0.6 0.8

Official an

0.2

Fishery cases

O

Fishery cases

Official discount rate vs. fishery rf

1 8 2

y rf

1.4 1.6 1.8

/ Fishery

1 1.2 Fishery rf Official

• unt rate/

0.6 0.8 Official discount rate

ial disco

0.2 0.4

Offic

Fishery cases

Inferred private discount rates

Caribbean 102% Southeast O i 89% Southeast Asia 145% Indian Ocean 142% Sabah 110% Fiji 104% Oceania 89% Sabah 110%

Overall mean = 107%

Official vs. private discount rates

2 5 3 2 2.5

Private

nt rate 1.5

Private discount rate Official discount

discoun 1

discount rate

Annual 0.5

Fishery cases

Concluding Remarks

Need to start paying attention to fishers’ discount rates

A k l d fi h ’ h t ti ti – Acknowledge fishers’ short time perspective – Better understanding about why fishers discount the way they do y

ACKNOWLEDGEMENTS

Rashid Sumaila Colin Clark Mike Meitner Dirk Zeller Rashid Sumaila, Colin Clark, Mike Meitner, Dirk Zeller In the field: Lydia Teh, Prof. Dr. Ridzwan Abdul Rahman, UMS Seaweed Project staff (Banggi) ,WWF team (Kudat & Semporna), Nanise Kuridrani, Vily Tuiwakaya and Fiji Fisheries Department Funding: SSHRC, Kingfisher Foundation, Cosmos International Graduate Travel Award (UBC) ( ) All the fishers who made this research possible… Maksukul, Terima kasih, Vinaka

Estimating intrinsic population h growth rate

• Based on Euler‐Lotka method (McAllister et al

Based on Euler Lotka method (McAllister et al. 2001)

• Solve for r iteratively using a numerical

i i i i f i minimisation function

• Assume Beverton‐Holt recruitment function,

expressed as a function of the steepness parameter h