Oral Presentation Ii

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Oral Presentation Ii

  1. 1. Presenter: Jenny Chen 陳瑩珍 Instructor: Dr. Pi-Ying Teresa Hsu November 12, 2009
  2. 2. <ul><li>Saz-Salazar, S. D., & Rausell-Koster, P. (2008). A double-hurdle model of urban green areas valuation: Dealing with zero responses. Landscape and Urban Planning, 84 (3-4), 241-251. </li></ul>
  3. 3. Contents I. Introduction II. Methodology III. Results IV. Conclusion V. Personal Reflection
  4. 4. Introduction <ul><li>In Spain, 77% of the population lives in urban areas. </li></ul>
  5. 5. Introduction <ul><li>Public parks and open spaces: </li></ul><ul><li>improve physical and psychological health </li></ul><ul><li>provide substantial environmental benefits </li></ul><ul><li>have an important aesthetic value in an environment designed around the automobile </li></ul><ul><li>are important for wildlife </li></ul><ul><li>are valuable contributors to wider urban objectives </li></ul>
  6. 6. Introduction <ul><li>hedonic pricing method </li></ul><ul><li>travel cost method </li></ul><ul><li>averting behaviour </li></ul><ul><li>contingent valuation method (CVM) </li></ul>Revealed Preferences Techniques Stated Preferences Techniques
  7. 7. Purpose <ul><li>to estimate the social benefits arising from the use of an urban park in the city of Valencia (Spain) </li></ul>
  8. 8. Study Site
  9. 9. Study Site El Jard í n del T ú ria
  10. 10. Methodology Time spring 2005 Participants 1455 Sampling stratified Payment Vehicle annual increase in local taxes Elicitation Approach open-ended Survey face-to face interview
  11. 11. Methodology
  12. 12. Methodology First Section <ul><li>attitudinal questions </li></ul><ul><li>behavior </li></ul>Third Section <ul><li>demographic and economic questions </li></ul>Second Section <ul><li>valuation question </li></ul><ul><li>“ Now I want to ask you how much you would be willing to pay each year in extra property taxes considering the whole array of benefits that you receive every time you visit the park.” </li></ul>
  13. 13. Methodology <ul><li>indirect utility function </li></ul><ul><li>V = U [ x ( p , y , z ), z ] = V ( p , y , z ) (1) </li></ul><ul><li>x : vector of private goods </li></ul><ul><li>p : prices </li></ul><ul><li>y : income </li></ul><ul><li>z : provision or quality of environmental commodities </li></ul>
  14. 14. Methodology <ul><li>change in utility </li></ul><ul><li>Δ V = V ( p , y , z 1 ) – V ( p , y , z 0 ) (2) </li></ul><ul><li>V ( p , y – CV, z 1 ) = V ( p , y , z 0 ) (3) </li></ul><ul><li>p : prices </li></ul><ul><li>y : income </li></ul><ul><li>z : provision or quality of environmental commodities </li></ul><ul><li>CV: WTP for an improvement </li></ul>
  15. 15. Methodology Zero WTP preference unfamiliarity
  16. 16. Methodology Ordinary Least-Square Regressions biased and inconsistent estimates of the parameters
  17. 17. Methodology <ul><li>only allows for one type of zero observations </li></ul><ul><li>(corner solution) </li></ul><ul><li>treats the decision to participate in the market and the stated degree of support together </li></ul>Tobit Model
  18. 18. Methodology <ul><li>two stages of estimation </li></ul><ul><li>considers the possibility of zero outcomes in the second hurdle </li></ul><ul><li>distinguishes between factors affecting the decision to participate and the stated amount of WTP </li></ul>Double-Hurdle Model
  19. 19. Methodology <ul><li>Participation decision </li></ul><ul><li>y i = y i * , if y i * > 0 and D i > 0 </li></ul><ul><li>y i = 0 , otherwise </li></ul><ul><li>D i = Z i θ + u i (4) </li></ul><ul><li>D i : latent variable </li></ul><ul><li>Z i : a vector of explanatory variables </li></ul><ul><li>θ : a vector of parameters </li></ul>Double-Hurdle Model
  20. 20. Methodology <ul><li>WTP decision </li></ul><ul><li>y i = y i * , if y i * > 0 </li></ul><ul><li>y i = 0 , otherwise </li></ul><ul><li>y i * = X i β + e i (5) </li></ul><ul><li>y i : revealed WTP for individual i </li></ul><ul><li>y i * : corresponding latent value of individual i ’s actual WTP </li></ul><ul><li>X i : vector of the individual’s characteristics </li></ul><ul><li>β : vector of parameters </li></ul>
  21. 21. Methodology Probit Model to evaluate the censoring rule ( Z i θ ) Truncated Regression Model to obtain the bid function ( X i β ) for the subsample of censored observations
  22. 22. Results
  23. 23. Results <ul><li>Average expenditure: </li></ul><ul><li>total cost </li></ul><ul><li>number of households </li></ul><ul><li>= 4.62 € </li></ul>× relative surface (26.76%) < 7.60 €
  24. 24. Results
  25. 25. Results <ul><li>H 0 : Tobit model is the correct specification </li></ul><ul><li>H 1 : Tobit model is not the appropriate specification </li></ul><ul><li>λ = - 2( L T - L P – L TR ) (6) </li></ul><ul><li>L T : log-likelihood for the Tobit model </li></ul><ul><li>L P : log-likelihood for the Probit model </li></ul><ul><li>L TR : log-likelihood for the truncated model </li></ul><ul><li>α = 0.01 </li></ul>Reject H 0
  26. 26. Results
  27. 27. Results <ul><li>Aggregation </li></ul>
  28. 28. Conclusion <ul><li>WTP increases with income and education as expected. </li></ul><ul><li>WTP varies depending on which section of the park the interview was conducted in. </li></ul><ul><li>Distinct sets of variables influence the decision to participate and the decision about how much the individual is willing to pay. </li></ul><ul><li>Demand for various green areas is culturally dependent . </li></ul>
  29. 29. Personal Reflection <ul><li> Sampling procedures were careful. </li></ul><ul><li> WTP question was not detailed and clear enough. </li></ul><ul><li> The WTP question should be revised to induce both use and preservation values. </li></ul><ul><li> Strategic bias was very likely to occur in this study because of the payment vehicle. </li></ul>
  30. 30. Thank you for your attention!

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