ecosystems (socio-economics) estimating the impact of climate change on landscape value aliza...
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Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Estimating the Impact of Climate Change on Landscape Value
Aliza Fleischer1, Denise Fouks1 and
Marcelo Sterenberg2 1Hebrew University of Jerusalem
2Tel Aviv University
GLOWA – Jordan RiverGLOWA – Jordan River
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Objective
Evaluating the impact of climate change on the economic value of different natural landscape with an emphasis on the Galilee
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Economic Impact of Global Climate Change on Grazing Land
Economic Impact
Landscape value Grazing services Ecosystem services
Recreationalists’ welfare Farmer’s income Local population welfare
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Topography South-facing slopes with stony and shallow soil (Terra rossa to desert lithosol on hard limestone and chalk) Temperature Mean annual temperature 140C-230C Rainfall Mainly winter - 5 summer months with no rainfall Range North-South: 780 to 90 mm
~ 48
0 km
Humid Mediterranean - 780 mm
Mediterranean - 540 mm
Semiarid – 300 mm
Arid – 90 mm
The Climatic Gradient
עין יעקב
מטע
להב
שדה בוקר
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Ecosystem type Rainfall (mm)
Temperature (oC) Min. – Mean - Max.
Elevation (a.s.l)
Herbaceous biomass (ton Ha-1)
Mesic Mediterranean)N 33o0' E 35o14('
780 13.5 - 18.1 - 23.4 500 m 0.832
Mediterranean)N 31o42' E 35o3('
540 12.8 – 17.7 - 23.6 620 m 0.741
Semiarid)N 31o23' E 34o54('
300 13.2 – 18.4 – 24.8 590 m 0.576
Arid)N 30o52' E 34o46('
90 13.6 - 19.1 - 26.1 470 m 0.014
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Methodology• A stated preference survey was designed to ask
respondents to choose their preferable program to reduce the ecological impacts from 5 sets of five programs.
• The alternative that has been chosen represent the maximum utility for the respondent.
• Let Uij be the utility for the ith individual from alternative j.
X= attribute [1,k] β= coefficient of the attribute = random error term i.i.d
= ji i ji jiU x
ji
Ecosystems (Socio-economics)Ecosystems (Socio-economics)a
Plan 1
No Action
Plan 2
Forestry and Plant life development.
Plan 3
Reduction of the use of damaging
materials and fuels
Plan 4
Increased forestry & less use of harmful
materials and fuels.
Plan 5
Drastic reduction of the use of damaging materials and fuels
The landscape in the Galilee will become
dry and arid, also lost of plants life will
occur.
The landscape in the Galilee will become semiarid and dry.
The landscape in the Galilee will become semiarid and dry.
The landscape in the Galilee will have less
plant life.
The landscape in the Galilee will not
change.
0 NIS per household monthly.
30 NIS per household monthly.
30 NIS per household monthly.
60 NIS per household monthly.
80 NIS per household monthly.
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Multinomial Logit Model
The utility an individual gets from alternative j is:
This probability an individual will choose this alternative is:
In the Multi Logit Model (MNL) the probability is:
( choice j for individual i ) = = ji i ji jiU U x
Prob[ ] for all ji miU U m j
1
exp( )Prob[ ]
exp( )
i jii Ji
i mim
xy j
x
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
The IIA Assumption
• The MNL is subject to the independence of irrelevant alternatives (IIA) property.
• IIA= the odds ratios are independent of the other probabilities.
• IIA test = if an alternative is irrelevant omitting it from the model will not change parameter estimates systematically.
• We rejected the hypothesis and thus had to use a model not subjected to IIA.
j kp / p
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Random Parameters Logit Model
The utility function associated with the model is from the general form:
is a random term with zero mean iid over alternatives and does not depend on parameters or data.
ji
ijijijijiijij XXXU ~_
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Random Parameters Logit Model
In the RPL model the probability of choice can be simulated as:
This model is not subjected to the IIA.
Rr
rmk
k
X
X
ijirik
ijij
e
e
RP
1
1
)(
)(1
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Alternatives Description
• Each alternative contains all four attributes.
• Alternatives differ in the levels of attributes.
Attributes Levels Used
Landscape Changes
(measured in landscape pictures)
4 levels; Ein ya’ako’v, Matta, Lahav, Sde
boqer
In biomass units
Forestry2 levels; Utilized or
Not Utilized
Abatement 3 levels; None,
Limited, Vigorous
Program Cost
(measured in NIS per month)
14 levels; 0, 10, 15, 20, 30, 40, 50, 60, 70, 80,
90, 100, 150, 200
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Econometric Analysis - Specification
The indirect utility function V is specified as linear in parameters. “Price” enters linearly. One dummy variable for “forestry”, two for “abatement” (in this estimation we only used one due to singularity) and three dummy variable for “landscape changes”
The indirect utility function would look as follow:
ij p matta matta lahav lahav sdeboqer sdeboqer
forestry forestry abatement abatement
v price I I I
I I
Ecosystems (Socio-economics)Ecosystems (Socio-economics)Econometric Results Biomass
***significant at 1% ** significant at 5% * significant at 10%
Variable Parameter Value Std. Error
Cost Mean of coefficient -0.033* 0.008
Std. dev. of coefficient 0 0
Biomass loss Mean of coefficient -0.069* 0.018
Std. dev. of coefficient 0.260* 0.081
Forestation Mean of coefficient -0.221 0.194
Std. dev. of coefficient 2.507* 0.223
Reduction Mean of coefficient 1.664* 0.794
Std. dev. of coefficient 2.752* 0.977
R2 (a) 0.18
Number of obs. 1500=(500 x 3)
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Econometric Results - WTP
The willingness to pay in order to prevent landscape changes was calculated as the coefficient of the “landscape change” divided by the coefficient of “price”.
is the utility differences between the state
and without the programs to prevent landscape change
v 1Q0Q
1 0( , , ) ( , , )v v p m A Q v p m Q
wtpPr(WTP> )=1-G ( )=F ( )b b v
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Welfare from landscape loss ($/ha) as a function of biomass loss
real
predictedy = 1756.5Ln(x) - 6443.9
0
1000
2000
3000
4000
5000
6000
0 100 200 300 400 500 600 700 800 900
Loss of grassy biomass
$/h
a
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Income Loss as a Result of Decreases in Grassy Biomass
Income Loss in Cattle Growing ($/ha)
0.00
20.00
40.00
60.00
80.00
100.00
0 91 256 818
Loss of grassy bio mass
/$ha
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Income Loss as a Result of Decreases in Grassy Biomass
Loss of grass bio mass
/$ha Income Loss in Sheep Growing ($/ha)
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
0 91 256 818
Ecosystems (Socio-economics)Ecosystems (Socio-economics)YEARLY LOSS VALUE OF ECOSYSTEM SERVICES IN THE TRANSFORMATION FROM MESIC MEDITERRANEAN TO
MEDITERRANEAN, SEMIARID AND ARID CLIMATES Loss of total biomass(ton ha-1)
Total WTP to prevent loss of biomassb
($ 106 ha-1)
Loss of herbaceous biomass (ton ha-1)
Loss of grazing services for cattlec
($)
Loss of grazing services for sheepc
($)
Mesic Med. Med.
7.8 51.5 0.009 5,733 8,001
Mesic Med. Semiarid
13.0 85.8 0.256 16,128 22,554
Mesic Med. Arid
16.3 107.6 0.818 51,534 72,135
Ecosystems (Socio-economics)Ecosystems (Socio-economics)
Conclusions
• Local community is eliciting utility from landscape and is willing to pay for government mitigation measures.
• Loss of welfare for recreation services is larger than grazing services
• The higher the conceived landscape loss the higher is the payment.
• Policy makers have the public consent for taxing this generation in order for future generations to enjoy the landscape.