Economics - Fall 2017

Christian Traeger

September 2017

Christian Traeger Resource Economics, UiO, Fall 2017 1

Renewable Resources

Fishery Economics

Christian Traeger Resource Economics, UiO, Fall 2017 2 Natural Resource Classifications

Natural resources can be classified as Renewable Resources: can regrow (replenish themselves). Usually biotic (living) resources. Fish, timber,... Non-renewable Resources: cannot regrow (at least within timescale relevant to human activity). Usually geological resources. Oil, coal, minerals, ...

Another classification Exhaustible: Scarce resources are exhaustible. Mostly used for non-renewables. Yet, also fish stocks are exhaustible. Inexhaustible: Resources that are available in (almost) unlimited supply (e.g. sunlight, wind,..)

Christian Traeger Resource Economics, UiO, Fall 2017 3

Fisheries

We analyze fisheries as an example of renewable resources a resource with particularly interesting dynamic behavior an economically important renewable resource a resource inviting substantial improvement in its management

If we had more time, we would next study forestry economics

Both are important because of sustainable use value and preservation value. We focus on use value. We discuss some aspects of valuation and preservation of tropical forests in ECON4910 - Environmental Economics (spring).

Christian Traeger Resource Economics, UiO, Fall 2017 4 - What are we talking about? How much do we catch and what do we use it for?

2014 Total World Capture: 93 (Marine: 82; Inland: 12) 2014 Total World Aquaculture: 74 (= farmed)

source: FAO’s SOFIA 2016 report (http://www.fao.org/3/a-i5555e.pdf)

SOFIA = The State of World Fisheries and Aquaculture

Christian Traeger Resource Economics, UiO, Fall 2017 5

MARINE FISH CATCHES A word of caution - numbers and uncertainty

Pauly and Zeller (2016) FISHERIES - What are we talking about? Where do we catch (most) fish?

source: http://worldoceanreview.com/wp-content/uploads/2010/10/k6 wk fangmengen regionen

Christian Traeger Resource Economics, UiO, Fall 2017 7

FISHERIES - What are we talking about? Who is catching (most) fish?

source: FAO’s SOFIA 2016 report (http://www.fao.org/3/a-i5555e.pdf)

Christian Traeger Resource Economics, UiO, Fall 2017 8 FISHERIES - What are we talking about? Which species?

source: FAO’s SOFIA 2016 report (http://www.fao.org/3/a-i5555e.pdf)

Christian Traeger Resource Economics, UiO, Fall 2017 9

FISHERIES - What are we talking about? State of world fisheries

source: FAO’s SOFIA 2016 report (http://www.fao.org/3/a-i5555e.pdf)

Christian Traeger Resource Economics, UiO, Fall 2017 10 FISHERIES

Some questions we will address 1 What is overfishing? 2 Why does overfishing occur? 3 How to regulate marine fisheries to prevent overfishing?

Christian Traeger Resource Economics, UiO, Fall 2017 11

Economic analysis of (over)fishing in a nutshell

Benefits of catching fish revenue from selling fish on market surplus employment opportunities in fishery

Costs of catching fish direct cost of fishing effort (capital, labor) opportunity costs (“shadow price”) of catch: no further growth of individual fish reduced future stock size decreases future fishing benefits

When overfishing usually second item falls short in benefit-cost analysis.

Christian Traeger Resource Economics, UiO, Fall 2017 12 FISHERIES - What are we talking about? Norway is a major fish exporter

source: FAO’s SOFIA 2016 report (http://www.fao.org/3/a-i5555e.pdf)

Christian Traeger Resource Economics, UiO, Fall 2017 13

FISHERIES - What are we talking about? Norway’s catch in 2016

source: https://www.ssb.no/en/fiskeri

Christian Traeger Resource Economics, UiO, Fall 2017 14 FISHERIES - What are we NOT talking about? Value from keeping the fish in the sea! Example: Whale watching

source: http://worldoceanreview.com/en/wor-4-overview/how-the-sea-serves-us/the-bounty-of-the-sea/3/

Christian Traeger Resource Economics, UiO, Fall 2017 15

FISHERIES - What are we NOT talking about? Value from keeping the fish in the sea! Example: Snorkling & Diving. Guesstimate by DEMA: Contribution of industry to US GDP: 11 Bill. USD

source: http://www.dema.org/store/download.asp?id=7811B097-8882-4707-A160-F999B49614B6

Christian Traeger Resource Economics, UiO, Fall 2017 16 The Model

of Fish(eries)

Christian Traeger Resource Economics, UiO, Fall 2017 17

The Biomass Model of Fish(eries)

Biological resources in general and fish in particular reproduce Key requirement for optimal management is understanding of resource’s regeneration capabilities We model fish as biomass:tonsoffish It is our state variable St

In particular We neglect age structure We neglect interactions across species (or at least do not model them explicitly) More advanced models do not...

Christian Traeger Resource Economics, UiO, Fall 2017 18 Net Growth

Growth rate of biomass St constant r > 0 for small stock sizes (exponential growth) decreasing with stock size: “” (, , etc.)

simplest assumption: growth rate decreases linearly with St St+1 − St r St = r − St = r 1 − (1) St K K

r: growth rate at St =0

K: (for St = K no more growth) This prominent example is called the logistic growth model

(Net growth = difference between fish (in tons) born minus fish (in tons) dying

Christian Traeger Resource Economics, UiO, Fall 2017 19

GROWTH OF FISH STOCK   − St rSt 1 K rSt t S − +1 t S fish stock growth

0

0 S ∗ K fish stock St

r: intrinsic growth rate (growth rate at St =0) K: carrying capacity

Christian Traeger Resource Economics, UiO, Fall 2017 20 GROWTH OF FISH STOCK t S K fish stock

S ∗

St St St 0 0 time t

Christian Traeger Resource Economics, UiO, Fall 2017 21

BIOMASS MODELS

In general: St+1 = St + g(St )

biomass growth function g(St ) assumption 1: the growth function is positive for stocks that are not too small or too large: an Smin ≥ 0andan Smax > Smin exist such that g(Smin)=0 g(Smax)=0 g(St ) > 0forallSt ∈ (Smin, Smax) assumption 2: the growth function is globally concave: g (St ) < 0forallSt ∈ (Smin, Smax)

Christian Traeger Resource Economics, UiO, Fall 2017 22 WESTERN AND CENTRAL PACIFIC BIG EYE TUNA

source: Froese and Pauly (2011)

Christian Traeger Resource Economics, UiO, Fall 2017 23

WESTERN AND CENTRAL PACIFIC BIG EYE TUNA

0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 growth of big eye tuna [100000 t] 0012345678 current biomass of big eye tuna [100000 t] ρ S ζ St −ψ ( t ) g(St )= − St 1 − e κ St 1+β κ

source: Grafton et al. (2007), Hampton et al. (2003)

Christian Traeger Resource Economics, UiO, Fall 2017 23 WESTERN AND CENTRAL PACIFIC YELLOWFIN TUNA

source: Froese and Pauly (2011)

Christian Traeger Resource Economics, UiO, Fall 2017 24

WESTERN AND CENTRAL PACIFIC YELLOWFIN TUNA

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

growth of yellowfin tuna [100000 t] 00 5 10 15 20 25 30 35 current biomass of yellowfin tuna [100000 t] ρ S ζ St −ψ ( t ) g(St )= − St 1 − e κ St 1+β κ

source: Grafton et al. (2007), Hampton et al. (2003)

Christian Traeger Resource Economics, UiO, Fall 2017 24 ATLANTIC MENHADEN

source: Froese and Pauly (2011)

Christian Traeger Resource Economics, UiO, Fall 2017 25

ATLANTIC MENHADEN

2 − γ g(St )=r1 St + r2 St r3 St

r1 =4.36, r2 =0.0008, r3 =0.38, γ =1.36.

source: Tahvonen (2008)

Christian Traeger Resource Economics, UiO, Fall 2017 25 PACIFIC HALIBUT

source: Froese and Pauly (2011)

Christian Traeger Resource Economics, UiO, Fall 2017 26

PACIFIC HALIBUT

γ S g(S )=rS 1 − t t t K γ =1.07

source: Tahvonen (2008)

Christian Traeger Resource Economics, UiO, Fall 2017 26 Minimum Viable

Definition The minimum viable population (MVP) is the smallest possible size at which a biological population can exist without facing extinction

Previous growth functions exhibit positive net growth for all 0 < St < Smax Immediate implication: no minimal viable population

Not necessarily the case ⇒ critical depensation

Christian Traeger Resource Economics, UiO, Fall 2017 27

Critical Depensation

A net growth function exhibits critical depensation if there exists a minimum viable population Smin > 0

For example, extension of logistic growth model: St St g(St )=rSt − 1 1 − , r > 0 , K2 > K1 > 0 K1 K2

The minimum viable population is given by S = k1: ⎧ ⎨⎪K2 if S0 > K1

lim St = K1 if S0 = K1 t→∞ ⎩⎪ 0ifS0 < K1

Christian Traeger Resource Economics, UiO, Fall 2017 28 Harvesting Biomass

(capturing fish)

Christian Traeger Resource Economics, UiO, Fall 2017 29

BIOMASS AND HARVEST Harvest Ht = biomass taken away from the fish stock Formulation 1: harvest after growing season

St+1 = St − Ht + g(St ) Formulation 2: harvest before growing season

St+1 = St − Ht + g(St − Ht ) Notation: stock left after fishing

Xt ≡ St − Ht ‘escapement’ Then stock dynamics can be written as

St+1 = Xt + g(Xt ) Consider stock dynamics under constant harvest H,then

⇔ Xt+1 = Xt − H + g(Xt ) Next slide’s graph identical between 1 & 2 with S ↔ X on horizontal

Christian Traeger Resource Economics, UiO, Fall 2017 30 BIOMASS AND HARVEST

H constant harvest H growth g(X ) )/harvest X ( g growth

0

MSY 0 X− X X+ K escapement X

Christian Traeger Resource Economics, UiO, Fall 2017 31

BIOMASS AND HARVEST

H constant harvest H growth g(X ) )/harvest X ( g growth

0

MSY 0 X− X X+ K escapement X

Christian Traeger Resource Economics, UiO, Fall 2017 31 BIOMASS AND HARVEST

H constant harvest H growth g(X ) )/harvest X ( g growth

0

MSY 0 X− X X+ K escapepemt X

Christian Traeger Resource Economics, UiO, Fall 2017 31

BIOMASS AND HARVEST H HMSY )/harvest X ( g growth

0 ‘maximum sustainable yield’ HMSY growth g(X )

0 X MSY K escapement X

Christian Traeger Resource Economics, UiO, Fall 2017 31 BIOMASS AND HARVEST H )/harvest X ( g growth

0 unsustainable harvest growth g(X )

0 X MSY K escapement X

Christian Traeger Resource Economics, UiO, Fall 2017 31

Maximum Sustainable Yield Definition The maximum sustainable yield is the maximum level of resource that can be harvested per period for an indefinite future.

In general: HMSY =maxg(X ) X

Example: logistic growth function

Christian Traeger Resource Economics, UiO, Fall 2017 32 Maximum Sustainable Yield Definition The maximum sustainable yield is the maximum level of resource that can be harvested per period for an indefinite future.

In general: HMSY =maxg(X ) X

Example: logistic growth function rK HMSY = 4

(independent of whether escapement Xt or stock St formulation) We sometimes refer to biological overfishing if

MSY St < S

Christian Traeger Resource Economics, UiO, Fall 2017 32

Fishery Production Function

In fishery harvest itself is not decision variable of resource manager This is different to, for example, forestry! In general, we consider a fishery production function

Ht = h(St , et )

depending on resource stock St and fishing effort et in period t Assumptions:

∂h(St , et )/∂St > 0 ,∂h(St , et )/∂et > 0 2 ∂ h(St , et )/(∂St ∂et ) ≥ 0 2 2 2 2 ∂ h(St , et )/(∂St ) ≤ 0 ,∂h(St , et )/(∂et ) ≤ 0

Christian Traeger Resource Economics, UiO, Fall 2017 33 Fishery Production Functions: Examples

Often the catch-per-unit-effort production function (CPUE) is used: h(St , et )=qSt et , q > 0

With CPUE catch-per-unit-effort is proportional to stock St

Other often used production functions are:

, α β , ,α,β> h(St et )=qSt et q 0

h(St , et )=[1− exp(−qet )] St , q > 0

q is called catchability coefficient

Christian Traeger Resource Economics, UiO, Fall 2017 34

The Yield-Effort Function

Consider a resource with net growth function g(St )and production function h(St , et ):

St+1 − St = g(St ) − h(St , et )

In steady state St+1 = St = S :

g(S)=h(S, e)

Solving for S = ψ(e) and inserting into production function gives yield-effort function: H = h ψ(e), e

Yield-effort function characterizes relationship between yield (harvest) and effort in steady state

Christian Traeger Resource Economics, UiO, Fall 2017 35 The Yield-Effort Function: Example Example: S g(S )=rS 1 − t logistic growth function t t k

h(St , et )=qSt et CPUE production function

Solving for S in steady state (using catch after growth) S rS 1 − = qSe k q ⇒ S = k 1 − e +RPHZRUN r Inserting in CPUE production function: q H(e)=qke 1 − e r

Christian Traeger Resource Economics, UiO, Fall 2017 36

Open Access

Christian Traeger Resource Economics, UiO, Fall 2017 37 Open Access

Definition An open-access resource is a resource which can be extracted without restrictions or barriers.

Fish in high sea is an open-access resource Fish in high sea does not belong to anyone You can privatize high sea fish by catching it

Open-access resources are common goods in the terminology of rivalry and excludability: rival but non-excludable

rival non-rival excludable private goods club goods non-excludable common goods public goods

Christian Traeger Resource Economics, UiO, Fall 2017 38

Froese, R. and Pauly, D. (2011), ‘Fishbase’, World Wide Web electronic publication. www.fishbase.org, version (02/2011). Grafton, R. Q., Kompas, T. and Hilborn, R. (2007), ‘Economics of revisited’, Science 318, 1601. Hampton, J., Kleiber, P., Takeuchi, Y., Kurota, H. and Maunder, M. (2003), ‘Stock assessment of bigeye tuna in the western and central pacific ocean, with comparisons to the entire pacific ocean’, Standing Committee on Tuna and Billfish, SCTB16, Working Paper BET-1. Pauly, D. and Zeller, D. (2016), ‘Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining’, Nature Communications 7, article number 10244. Tahvonen, O. (2008), ‘Harvesting age-structured as a biomass. does it work?’, Natural Resource Modelling 21(4), 525–550.

Christian Traeger Resource Economics, UiO, Fall 2017 46