Numbering Code	G-AGR06 6FA58 LJ43	Year/Term	2022 ・ Second 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. Individual-level parameters (1) 3. Individual-level parameters (2) 4. Bayesian procedures (1) 5. Bayesian procedures (2) 6. Bayesian procedures (3) 7. Endogeneity (1) 8. Endogeneity (2) 9. Endogeneity (3) 10. EM algorithms (1) 11. EM algorithms (2) 12. EM algorithms (3) 13. Experimental design and choice experiments (1) 14. Experimental design and choice experiments (2) 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