SlideShare a Scribd company logo
1 of 30
Presenter:  Jenny Chen  陳瑩珍 Instructor: Dr. Pi-Ying Teresa Hsu November 12, 2009
[object Object]
Contents   I.  Introduction   II.  Methodology III.  Results IV.  Conclusion V.  Personal Reflection
Introduction ,[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],Revealed Preferences Techniques Stated Preferences Techniques
Purpose ,[object Object]
Study Site
Study Site El Jard í n del T ú ria
Methodology Time spring 2005 Participants 1455 Sampling stratified Payment Vehicle annual increase in local taxes Elicitation Approach open-ended Survey face-to face interview
Methodology
Methodology First Section ,[object Object],[object Object],Third Section ,[object Object],Second Section ,[object Object],[object Object]
Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Methodology Zero WTP preference unfamiliarity
Methodology Ordinary Least-Square Regressions biased and inconsistent estimates of the parameters
Methodology ,[object Object],[object Object],[object Object],Tobit Model
Methodology ,[object Object],[object Object],[object Object],Double-Hurdle Model
Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Double-Hurdle Model
Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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
Results
Results ,[object Object],[object Object],[object Object],[object Object],×  relative surface (26.76%) <  7.60 €
Results
Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Reject H 0
Results
Results ,[object Object]
Conclusion ,[object Object],[object Object],[object Object],[object Object]
Personal Reflection ,[object Object],[object Object],[object Object],[object Object]
Thank you for your attention!

More Related Content

Viewers also liked

Research Writing and Publishing I - Oral Presentation 2
Research Writing and Publishing I - Oral Presentation 2Research Writing and Publishing I - Oral Presentation 2
Research Writing and Publishing I - Oral Presentation 2
Jenny Chen
 
Pros and cons of community based natural resource management.
Pros and cons of community based natural resource management.Pros and cons of community based natural resource management.
Pros and cons of community based natural resource management.
Dr. Pauline Gitonga
 
Sampling distribution
Sampling distributionSampling distribution
Sampling distribution
Danu Saputra
 
community based natural resource management
community based natural resource managementcommunity based natural resource management
community based natural resource management
Shravan Rajur
 
Sampling distribution concepts
Sampling distribution conceptsSampling distribution concepts
Sampling distribution concepts
umar sheikh
 
Hypothesis Testing-Z-Test
Hypothesis Testing-Z-TestHypothesis Testing-Z-Test
Hypothesis Testing-Z-Test
Roger Binschus
 
Normal distribution and sampling distribution
Normal distribution and sampling distributionNormal distribution and sampling distribution
Normal distribution and sampling distribution
Mridul Arora
 
Test of hypothesis
Test of hypothesisTest of hypothesis
Test of hypothesis
vikramlawand
 
Definition and types of research
Definition and types of researchDefinition and types of research
Definition and types of research
fadifm
 

Viewers also liked (17)

The State of Small Business [infographic]
The State of Small Business [infographic]The State of Small Business [infographic]
The State of Small Business [infographic]
 
Research Writing and Publishing I - Oral Presentation 2
Research Writing and Publishing I - Oral Presentation 2Research Writing and Publishing I - Oral Presentation 2
Research Writing and Publishing I - Oral Presentation 2
 
Hypothesis
HypothesisHypothesis
Hypothesis
 
Community based natural resource management
Community based natural resource managementCommunity based natural resource management
Community based natural resource management
 
Pros and cons of community based natural resource management.
Pros and cons of community based natural resource management.Pros and cons of community based natural resource management.
Pros and cons of community based natural resource management.
 
Sampling distribution
Sampling distributionSampling distribution
Sampling distribution
 
community based natural resource management
community based natural resource managementcommunity based natural resource management
community based natural resource management
 
Sampling distribution concepts
Sampling distribution conceptsSampling distribution concepts
Sampling distribution concepts
 
Hypothesis Testing-Z-Test
Hypothesis Testing-Z-TestHypothesis Testing-Z-Test
Hypothesis Testing-Z-Test
 
Z test
Z testZ test
Z test
 
Sampling Distributions
Sampling DistributionsSampling Distributions
Sampling Distributions
 
Normal distribution and sampling distribution
Normal distribution and sampling distributionNormal distribution and sampling distribution
Normal distribution and sampling distribution
 
Final taj hotel
Final taj hotelFinal taj hotel
Final taj hotel
 
Test of hypothesis
Test of hypothesisTest of hypothesis
Test of hypothesis
 
Hypothesis testing; z test, t-test. f-test
Hypothesis testing; z test, t-test. f-testHypothesis testing; z test, t-test. f-test
Hypothesis testing; z test, t-test. f-test
 
Research hypothesis....ppt
Research hypothesis....pptResearch hypothesis....ppt
Research hypothesis....ppt
 
Definition and types of research
Definition and types of researchDefinition and types of research
Definition and types of research
 

Similar to Oral Presentation Ii

Proposal Defense Presentation
Proposal  Defense  PresentationProposal  Defense  Presentation
Proposal Defense Presentation
Jenny Chen
 
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
felicidaddinwoodie
 
Dissertation Defense_Md Sakoat Hossan
Dissertation Defense_Md Sakoat HossanDissertation Defense_Md Sakoat Hossan
Dissertation Defense_Md Sakoat Hossan
Md.Sakoat Hossan
 

Similar to Oral Presentation Ii (20)

Final defense
Final defenseFinal defense
Final defense
 
Presentation on quantitative methods for valuaing the environment farah (roll...
Presentation on quantitative methods for valuaing the environment farah (roll...Presentation on quantitative methods for valuaing the environment farah (roll...
Presentation on quantitative methods for valuaing the environment farah (roll...
 
Proposal Defense Presentation
Proposal  Defense  PresentationProposal  Defense  Presentation
Proposal Defense Presentation
 
Additive Smoothing for Relevance-Based Language Modelling of Recommender Syst...
Additive Smoothing for Relevance-Based Language Modelling of Recommender Syst...Additive Smoothing for Relevance-Based Language Modelling of Recommender Syst...
Additive Smoothing for Relevance-Based Language Modelling of Recommender Syst...
 
Managerial Economics - Demand Estimation (regression analysis)
Managerial Economics - Demand Estimation (regression analysis)Managerial Economics - Demand Estimation (regression analysis)
Managerial Economics - Demand Estimation (regression analysis)
 
Evaluating factors WTP freight transportation crossing the Pyrenees- EWGT-201...
Evaluating factors WTP freight transportation crossing the Pyrenees- EWGT-201...Evaluating factors WTP freight transportation crossing the Pyrenees- EWGT-201...
Evaluating factors WTP freight transportation crossing the Pyrenees- EWGT-201...
 
Demand estimation and forecasting
Demand estimation and forecastingDemand estimation and forecasting
Demand estimation and forecasting
 
Goodness–of–fit tests for regression models: the functional data case
Goodness–of–fit tests for regression models: the functional data caseGoodness–of–fit tests for regression models: the functional data case
Goodness–of–fit tests for regression models: the functional data case
 
Adaptive Machine Learning for Credit Card Fraud Detection
Adaptive Machine Learning for Credit Card Fraud DetectionAdaptive Machine Learning for Credit Card Fraud Detection
Adaptive Machine Learning for Credit Card Fraud Detection
 
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
 
#2ECcourse.ppthjjkhkjhkjhjkjhkhhkhkhkhkj
#2ECcourse.ppthjjkhkjhkjhjkjhkhhkhkhkhkj#2ECcourse.ppthjjkhkjhkjhjkjhkhhkhkhkhkj
#2ECcourse.ppthjjkhkjhkjhjkjhkhhkhkhkhkj
 
#2ECcourse.pptgjdgjgfjgfjhkhkjkkjhkhkhkjhjkj
#2ECcourse.pptgjdgjgfjgfjhkhkjkkjhkhkhkjhjkj#2ECcourse.pptgjdgjgfjgfjhkhkjkkjhkhkhkjhjkj
#2ECcourse.pptgjdgjgfjgfjhkhkjkkjhkhkhkjhjkj
 
Managerial Economics (Chapter 5 - Demand Estimation)
 Managerial Economics (Chapter 5 - Demand Estimation) Managerial Economics (Chapter 5 - Demand Estimation)
Managerial Economics (Chapter 5 - Demand Estimation)
 
Chapter 6 valuation of environmental resources copy
Chapter 6 valuation of environmental resources   copyChapter 6 valuation of environmental resources   copy
Chapter 6 valuation of environmental resources copy
 
DATA COLLECTION IN RESEARCH
DATA COLLECTION IN RESEARCHDATA COLLECTION IN RESEARCH
DATA COLLECTION IN RESEARCH
 
Dissertation Defense_Md Sakoat Hossan
Dissertation Defense_Md Sakoat HossanDissertation Defense_Md Sakoat Hossan
Dissertation Defense_Md Sakoat Hossan
 
Método Topsis - multiple decision makers
Método Topsis  - multiple decision makersMétodo Topsis  - multiple decision makers
Método Topsis - multiple decision makers
 
SMART Seminar Series: Formal Models of Social Processes
SMART Seminar Series: Formal Models of Social ProcessesSMART Seminar Series: Formal Models of Social Processes
SMART Seminar Series: Formal Models of Social Processes
 
A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Bi...
A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Bi...A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Bi...
A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Bi...
 
Analyzing experimental research data
Analyzing experimental research dataAnalyzing experimental research data
Analyzing experimental research data
 

More from Jenny Chen

Thesis Writing IV - Oral 1
Thesis Writing IV - Oral 1Thesis Writing IV - Oral 1
Thesis Writing IV - Oral 1
Jenny Chen
 
Proposal Defense (Final)
Proposal Defense (Final)Proposal Defense (Final)
Proposal Defense (Final)
Jenny Chen
 
質化研究 Study Group 7
質化研究 Study Group 7質化研究 Study Group 7
質化研究 Study Group 7
Jenny Chen
 
質化研究 Study Group 2
質化研究 Study Group 2質化研究 Study Group 2
質化研究 Study Group 2
Jenny Chen
 
Oral Presentation II
Oral Presentation IIOral Presentation II
Oral Presentation II
Jenny Chen
 
Oral Presentation 1(Research Writing and Publishing III)
Oral Presentation 1(Research Writing and Publishing III)Oral Presentation 1(Research Writing and Publishing III)
Oral Presentation 1(Research Writing and Publishing III)
Jenny Chen
 
Proposal Defense Oral Presentation
Proposal Defense Oral PresentationProposal Defense Oral Presentation
Proposal Defense Oral Presentation
Jenny Chen
 
電子商務溝通 – 期中考
電子商務溝通 – 期中考電子商務溝通 – 期中考
電子商務溝通 – 期中考
Jenny Chen
 
Research Method - Oral Presentation I I (Quantitative Research)
Research Method - Oral Presentation I I (Quantitative Research)Research Method - Oral Presentation I I (Quantitative Research)
Research Method - Oral Presentation I I (Quantitative Research)
Jenny Chen
 
休閒管理專題 – 期末考
休閒管理專題 – 期末考休閒管理專題 – 期末考
休閒管理專題 – 期末考
Jenny Chen
 
老街觀光休閒產業
老街觀光休閒產業老街觀光休閒產業
老街觀光休閒產業
Jenny Chen
 
Final Oral Presentation
Final Oral PresentationFinal Oral Presentation
Final Oral Presentation
Jenny Chen
 
Speaking Lesson Plan – In A Pub
Speaking Lesson Plan – In A PubSpeaking Lesson Plan – In A Pub
Speaking Lesson Plan – In A Pub
Jenny Chen
 

More from Jenny Chen (13)

Thesis Writing IV - Oral 1
Thesis Writing IV - Oral 1Thesis Writing IV - Oral 1
Thesis Writing IV - Oral 1
 
Proposal Defense (Final)
Proposal Defense (Final)Proposal Defense (Final)
Proposal Defense (Final)
 
質化研究 Study Group 7
質化研究 Study Group 7質化研究 Study Group 7
質化研究 Study Group 7
 
質化研究 Study Group 2
質化研究 Study Group 2質化研究 Study Group 2
質化研究 Study Group 2
 
Oral Presentation II
Oral Presentation IIOral Presentation II
Oral Presentation II
 
Oral Presentation 1(Research Writing and Publishing III)
Oral Presentation 1(Research Writing and Publishing III)Oral Presentation 1(Research Writing and Publishing III)
Oral Presentation 1(Research Writing and Publishing III)
 
Proposal Defense Oral Presentation
Proposal Defense Oral PresentationProposal Defense Oral Presentation
Proposal Defense Oral Presentation
 
電子商務溝通 – 期中考
電子商務溝通 – 期中考電子商務溝通 – 期中考
電子商務溝通 – 期中考
 
Research Method - Oral Presentation I I (Quantitative Research)
Research Method - Oral Presentation I I (Quantitative Research)Research Method - Oral Presentation I I (Quantitative Research)
Research Method - Oral Presentation I I (Quantitative Research)
 
休閒管理專題 – 期末考
休閒管理專題 – 期末考休閒管理專題 – 期末考
休閒管理專題 – 期末考
 
老街觀光休閒產業
老街觀光休閒產業老街觀光休閒產業
老街觀光休閒產業
 
Final Oral Presentation
Final Oral PresentationFinal Oral Presentation
Final Oral Presentation
 
Speaking Lesson Plan – In A Pub
Speaking Lesson Plan – In A PubSpeaking Lesson Plan – In A Pub
Speaking Lesson Plan – In A Pub
 

Recently uploaded

Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfBreaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
UK Journal
 
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
FIDO Alliance
 

Recently uploaded (20)

Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties ReimaginedEasier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
 
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfBreaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
 
Introduction to FIDO Authentication and Passkeys.pptx
Introduction to FIDO Authentication and Passkeys.pptxIntroduction to FIDO Authentication and Passkeys.pptx
Introduction to FIDO Authentication and Passkeys.pptx
 
The Metaverse: Are We There Yet?
The  Metaverse:    Are   We  There  Yet?The  Metaverse:    Are   We  There  Yet?
The Metaverse: Are We There Yet?
 
ERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage IntacctERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage Intacct
 
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdfHow Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
 
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4jYour enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4j
 
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
 
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
 
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
 
Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024
 
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireMicrosoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - Questionnaire
 
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...Hyatt driving innovation and exceptional customer experiences with FIDO passw...
Hyatt driving innovation and exceptional customer experiences with FIDO passw...
 
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
 
How we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdfHow we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdf
 
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
 
WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024
 
AI mind or machine power point presentation
AI mind or machine power point presentationAI mind or machine power point presentation
AI mind or machine power point presentation
 
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The InsideCollecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
 
Overview of Hyperledger Foundation
Overview of Hyperledger FoundationOverview of Hyperledger Foundation
Overview of Hyperledger Foundation
 

Oral Presentation Ii