The Economic Value of The Economic Value of Ecosystem Conservation Ecosystem Conservation

in Japan: in Japan: Reduction of elicitation effect by Reduction of elicitation effect by

Bid Effect FunctionBid Effect Function

Mitsuyasu YABEMitsuyasu YABEKyushu UniversityKyushu University

ContentsContents

1.1. Background and Purpose Background and Purpose

2.2. Analytical ModelAnalytical Model

3.3. Survey Design and Explanatory Survey Design and Explanatory VariablesVariables

4.4. Estimation ResultsEstimation Results

5.5. ConclusionConclusion

Background of the StudyBackground of the Study

National Park National Park Aso Aso Over 18 million people visit and enjoy tOver 18 million people visit and enjoy t

he view of he view of AsoAso grassland. grassland. Many valuable flora and fauna were maMany valuable flora and fauna were ma

intained by traditional human activities. intained by traditional human activities. With decline of farmer and the change With decline of farmer and the change

of farming pattern, the of farming pattern, the AsoAso grassland v grassland verge to crisis of maintaining erge to crisis of maintaining

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Endangered Species in Endangered Species in Aso GrasslandAso Grassland

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Purpose of the StudyPurpose of the Study

Estimating the conservation value Estimating the conservation value of Aso Glass Landof Aso Glass Land

Improving the Contingent Improving the Contingent Valuation Method (CVM):Valuation Method (CVM):

Deceasing Elicitation Effects Deceasing Elicitation Effects

1) Starting Point Effects1) Starting Point Effects

2) Yea-saying 2) Yea-saying

Elicitation Effects in CVElicitation Effects in CV

Dichotomous choice CV is most Dichotomous choice CV is most commonly applied since commonly applied since respondents only need to select respondents only need to select “accept” or “not accept”“accept” or “not accept”

However, even when the bid is However, even when the bid is higher than the latent willingness higher than the latent willingness to pay, the respondents tend to to pay, the respondents tend to “accept” the bid. “accept” the bid.

Characteristics of the Characteristics of the ModelModel To decreaseTo decrease Elicitation Effects on Elicitation Effects on

the WTPthe WTP

→ →Introducing Bid Effect FunctionIntroducing Bid Effect Function

→ →Applying DC Approach for Five Applying DC Approach for Five choice choice

　　

Formulation of Bid Formulation of Bid EffectsEffects

Latent WTP for the Latent WTP for the ii respondent:respondent:

The gap between the bid The gap between the bid ttii and latent and latent WTP:WTP:

Bid effect function:Bid effect function:)( i

'*ln ii xy

*lnln iii yt

0/,0)0( idtd

Stated WTPStated WTP

the stated WTP can be expressed:the stated WTP can be expressed:

The probability that the stated WTP The probability that the stated WTP yyii is larger than the bid is larger than the bid ttii ::

iiii xy )( ln

)/))(((ln1

)/))(Pr((ln

))(Pr(ln)Pr(

iii

iiii

iiiiiii

xt

zxt

xtyt

The Hypothetical The Hypothetical QuestionQuestion （（ 11 ） ）

““suppose that grassland could be suppose that grassland could be converted to forest and grassland could converted to forest and grassland could be lost as grazing and open burning are be lost as grazing and open burning are discontinued in discontinued in Aso Aso region.region.

In order to prevent that happens, we set In order to prevent that happens, we set up the “up the “AsoAso Grassland World Heritage Grassland World Heritage Fund” to register and conserve the Fund” to register and conserve the grasslandgrassland

The activity cost of “The activity cost of “AsoAso Grassland World Grassland World Heritage Fund” is supported by the public Heritage Fund” is supported by the public contribution. contribution.

The hypothetical The hypothetical questionquestion （（ 22 ））

If the fund costs (***) per household per If the fund costs (***) per household per annum, you may pay the amount of money? annum, you may pay the amount of money? (Select only one)(Select only one)

　　　　 1. will pay1. will pay 　　 > “YES” in Model 1 & 2> “YES” in Model 1 & 2

　 　 2. probably will pay > “YES” in Model 3 & 2. probably will pay > “YES” in Model 3 & 44

　 　 3. probably will not pay3. probably will not pay

　　　　 4. will not pay4. will not pay

　 　 5. don’t know5. don’t know

The Log-likelihood The Log-likelihood Function in DC-CVMFunction in DC-CVM

Where Where ddii1 1 andand d dii

22 are coded 1 when are coded 1 when respondent chose the option and respondent chose the option and otherwise 0. otherwise 0.

Form of Bid Effect Form of Bid Effect FunctionFunction If bid effect function is liner function If bid effect function is liner function

::

We have a relation as follows:We have a relation as follows:

)(ln)( ' iii xt

)1/(

ln1

)/))(((ln1

))(Pr(ln)Pr(

ii

iii

iiiiiii

xt

xt

xtyt

Bid Effect function Bid Effect function based on logistic based on logistic function function

Hypotheses:Hypotheses:

>>>>0:,0:0 aHH

}21))](lnexp(1{)( 1' iii xt

iaiiia

iii

xyH

xyH

)(ln:

ln:'

0'

0

Summary of Survey Summary of Survey QuestionnaireQuestionnaire Survey PeriodSurvey Period ：： December 1998December 1998 　　　　　　　　 RespondentsRespondents ：： Residents of Residents of

Kumamoto PrefectureKumamoto Prefecture SamplesSamples ：： 10001000 Samples used for AnalysisSamples used for Analysis ：： 418418

Attributes of Survey Attributes of Survey RespondentsRespondents Average AgeAverage Age ： ： 59 years old59 years old

Average IncomeAverage Income ：　：　 5,740,000 yen per an5,740,000 yen per ann.n.

(Approx. (Approx. 52,000 US$)52,000 US$) Conservation Activities of Aso Glass land:Conservation Activities of Aso Glass land: 　　 Highly AppreciatedHighly Appreciated

Explanatory Variables and Explanatory Variables and MeansMeansVariablesVariables DescriptionDescription

MeanMean S.E.S.E.

INCOMEINCOME Income Income ((million yenmillion yen ） ） 5.7485.748 3.4223.422

LAGELAGE Logarithm of age Logarithm of age 4.0704.070 2.7732.773

BEAUTYBEAUTY Beauty of Aso grassland Beauty of Aso grassland （（ Log(Log(1=not good, , 5=very 1=not good, , 5=very goodgood ））

1.5561.556 0.1260.126

TRIPTRIP 1/0, 1=visit within 5 years 1/0, 1=visit within 5 years 0.7650.765 4.1244.124

ACTACT 1/0, 1=conservation should be 1/0, 1=conservation should be expandedexpanded

0.3940.394 0.4900.490

BEEFBEEF 1/0, 1=would buy meet of cows 1/0, 1=would buy meet of cows

fed grass at more than 20 fed grass at more than 20 % %

higher price higher price

0.1960.196 0.3970.397

POSSIBILITPOSSIBILITYY

1/0, 1=possibility that grassland 1/0, 1=possibility that grassland isis

conserved by fund is more than conserved by fund is more than 70% 70%

0.5390.539 0.4990.499

Comparison of Estimated Comparison of Estimated ResultsResults

Model 1Model 1 Model 2Model 2 Model 3Model 3 Model 4Model 4

ConstantConstant 0.7660.766 0.5120.512 5.391**5.391** 5.701***5.701***

INCOMEINCOME 0.0440.044 0.081*0.081* 0.0280.028 0.0370.037

LAGELAGE 0.8120.812 1.013*1.013* 0.3260.326 0.1070.107

BEAUTYBEAUTY 0.7390.739 0.3090.309 1.1361.136 1.412**1.412**

TRIPTRIP 0.652*0.652* 0.624**0.624** 0.0260.026 0.258***0.258***

ACTACT 0.833***0.833*** 0.800***0.800*** 0.636**0.636** 0.646***0.646***

BEEFBEEF 1.279***1.279*** 0.747**0.747** 0.806**0.806** 0.9220.922

POSSIBILITYPOSSIBILITY 0.662**0.662** 0.652**0.652** 0.0220.022 -0.058***-0.058***

BID EFFECTBID EFFECT 3.683***3.683*** 3.647***3.647***

ERRORERROR 1.682***1.682*** 0.494***0.494*** 1.079***1.079*** 0.252***0.252***

Log Log LikelihoodLikelihood

-148.300-148.300 -145.321-145.321 -96.110-96.110 -94.204-94.204

Comparison of Latent Comparison of Latent WTPs: Definitely Pay WTPs: Definitely Pay (Unite: Yen)(Unite: Yen)

Model 1Model 1

Without Bid Without Bid effect Func.effect Func.

Model 2Model 2

With Bid effect With Bid effect Func.Func.

MeanMean 3,9043,904 1,0281,028

95% CI95% CI 2,055 to 8,8842,055 to 8,884 799 to 1,374799 to 1,374

MedianMedian 948 948 909909

95% CI95% CI 714 to 1,252714 to 1,252 715 to 1,163715 to 1,163

Comparison of Latent Comparison of Latent WTPs: Probably Pay WTPs: Probably Pay (Unite: Yen)(Unite: Yen)

Model 3Model 3

Without Bid Without Bid effect Func.effect Func.

Model 4Model 4

With Bid effect With Bid effect Func.Func.

MeanMean 15,87515,875 9,6339,633

95% CI95% CI 10,144 to 10,144 to 27,46127,461

7,274 to 7,274 to 12,41512,415

MedianMedian 8,871 8,871 9,3339,333

95% CI95% CI 6,867 to 6,867 to 11,34511,345

7,096 to 7,096 to 12,41512,415

Results of Bid Effect Results of Bid Effect FunctionFunction

Bid effect coefficient was Bid effect coefficient was statistically significantstatistically significant

The error term was reduced by The error term was reduced by more than 70%more than 70%

Difference between Mean and Difference between Mean and Median was also reducedMedian was also reduced

Conservation Value of Aso Conservation Value of Aso GrasslandGrassland

Estimated Value who definitely payEstimated Value who definitely pay ：：Mean 1,028 Yen ( = US$ 9.3)Mean 1,028 Yen ( = US$ 9.3)

Return rate of this survey:Return rate of this survey: 　　 41.8%41.8% Number of households of Kumamoto Number of households of Kumamoto

prefecture:prefecture: 　　 594,197 594,197 Total Conservation Value per YearTotal Conservation Value per Year

= 1,028 x 0.418 x 594197= 1,028 x 0.418 x 594197

　　 = 255 Million Yen/Year= 255 Million Yen/Year

= US$ 2.3 Million/Year= US$ 2.3 Million/Year 　　

ConclusionConclusion

Removal of influence from the bid Removal of influence from the bid effect bias enabled a more appropriate effect bias enabled a more appropriate WTP estimationWTP estimation

Price Oriented Attribute affected the Price Oriented Attribute affected the WTP more than incomeWTP more than income

The estimated total environmental The estimated total environmental value was more than the amount of value was more than the amount of the environmental gross investment at the environmental gross investment at HTBHTB

Thank you very much Thank you very much for your attentionfor your attention