(1) To study the theory of Discrete Choice Model (DCM, 離散選択モデル), which is one of the most popular methods of market demand analysis.
-Theoretical Basis: Microeconomics, Applied Statistics, Optimization Theory, Simulation
-Applications: Predicting future demands in transportation or other markets, Economic evaluation of transport infrastructures
(2) To learn knowledge on practical applications of DCM through some exercises and assignments (model estimations with some dataset).
-``BIOGEME": Free software for estimation and simulation
-Computer laboratories with the dataset from various research fields such as transportation, telecommunication, energy and marketing.
(1) To study the theory of Discrete Choice Model (DCM), which is one of the most popular methods of market demand analysis.
(2) To learn knowledge on practical applications of DCM through some exercises and assignments (model estimations with some dataset).
Travel behavior analysis, Discrete choice model, Applied statistics, Applied econometrics, Simulation, Probability model, Marketing science, Individual decision-making
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
While teaching theoretical foundations of DCM, five computer exercises will be conducted. Also, five writing assignments corresponding to each computer exercise will be given.
Course schedule | Required learning | |
---|---|---|
Class 1 | Choice Behavior and Binary Choice Models (BCM) | 1 Simple Example 2 Framework of Discrete Choice Models 3 Random Utility Model 4 Binary Choice Model |
Class 2 | Estimation of BCM | 1 Deviation of Binary Choice Models 2 Estimation of Binary Choice Models 3 Evaluation and Interpretation of Estimation Results |
Class 3 | Computer Lab. (1): Estimation of BCM | Estimating binary choice models |
Class 4 | Multinomial Choice Models: Logit and Probit | 1 Review of Random Utility Model 2 Multinomial Probit 3 Multinomial Logit 4 IIA Property of Logit |
Class 5 | Specification and Estimation of Multinomial Logit Models (MNL) | 1 Specification Issues of Logit Model 2 A Case Study of Specification Issues 3 Estimation Issues of Logit Model |
Class 6 | Computer Lab. (2): Estimation of MNL | Estimating multinomial logit models |
Class 7 | Statistical Tests of Discrete Choice Models | 1 Introduction: What is "statistical test"? 2 Informal Tests 3 Classical Statistical Tests 4 Likelihood Ratio Test 5 Goodness-of-Fit of the Entire Model 6 Advanced Tests |
Class 8 | Independent from Irrelevant Alternatives, Forecasting and Microsimulation | 1 Introduction 2 IIA (Independence from Irrelevant Alternatives) property of Logit 3 IIA Tests 4 Forecasting and Microsimulation |
Class 9 | Computer Lab. (3): Statistical Testing and Forecasting | 1 Testing IIA 2 Forecasting and Microsimulation |
Class 10 | Nested Logit Model (NL) | 1 Review of IIA Property 2 Correlation among Choice Alternatives 3 Nested Logit Model 4 A Case Study: Choice of A Residential Telephone Service |
Class 11 | Issues on Sampling | 1 Introduction: Why focus on sampling? 2 Examples of Sampling Strategies 3 Formulation of Sampling Strategies 4 Estimation Considering Sampling |
Class 12 | Computer Lab. (4): NL and Sampling Issues | 1 Estimating Nested Logit Model 2 Estimation considering sampling |
Class 13 | Mixed Logit Model (MXL) and Simulation-based Estimation | 1 Introduction 2 Mixed Logit Model: Formulation 3 Mixed Logit Model: Estimation |
Class 14 | Computer Lab. (5): Estimation of MXL | Estimating Mixed Logit Models |
Class 15 | Advances of DCM in Transportation Studies | Introducing the state-of-art of DCM in transportation science |
Lecture materials will be provided at OCWi.
Ben-Akiva M. & Lerman S. (1985) Discrete Choice Analysis: Theory and Applications to Travel Demand, MIT Press.
Train K. (2003) Discrete Choice Methods with Simulation, Cambridge University Press.
- Five assignments (75%)
- Correspondence/reaction to the questions during the class (25%)
Students are recommended to take the above-mentioned relevant courses.