Forest Policy2A

Numbering Code G-AGR06 6FA59 LJ43 Year/Term 2022 ・ First semester
Number of Credits 2 Course Type Lecture
Target Year Target Student
Language Japanese Day/Period Fri.2
Instructor name KURIYAMA KOUICHI (Graduate School of Agriculture Professor)
Outline and Purpose of the Course Introduction to the econometric analysis and application to the forest and other natural resource policies using discrete choice models. Includes behavior model, econometric model of discrete choice, heterogeneity, estimation methods with simulation, and others.
Course Goals Students will understand the basic concepts related to discrete choice models and learn how to apply them to address forest and other environmental problems. They will also learn how to use stated choice for the non- market valuation of natural resources.
Schedule and Contents Key topics will be selected from the following:

1. Introduction
2. Properties of Discrete Choice Models (1)
3. Properties of Discrete Choice Models (2)
4. Logit (1)
5. Logit (2)
6. GEV (1)
7. GEV (2)
8. Mixed Logit
9. Mixed Logit
10. Numerical Maximization (1)
11. Numerical Maximization (2)
12. Drawing from Densities (1)
13. Drawing from Densities (2)
14. Simulation-Assisted Estimation
15. Feedback
Evaluation Methods and Policy Grading will be based on an overall assessment of criteria such as attendance, contribution to class discussion, in-class quizzes, and a term report.
Term report (60%) and class performance (40%)
Refer to current year's 'Guide to Degree Programs' for attainment levels of evaluation.
Course Requirements None
Study outside of Class (preparation and review) Read the textbook in advance.
Textbooks Textbooks/References Discrete Choice Methods with Simulation, 2nd Ed., Kenneth Train, (Cambridge University Press), ISBN:0521747384 , https://eml.berkeley.edu/books/choice2.html
References, etc. Applied Choice Analysis, 2nd ed., David A. Hensher et al., (Cambridge University Press), ISBN:1107465923
Best-Worst Scaling: Theory, Methods and Applications, Jordan J. Louviere et al., (Cambridge University Press), ISBN:1107043158
Related URL http://kkuri.eco.coocan.jp/index-e.html
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