PPT-Discrete Choice Models

William Greene Stern School of Business New York University Part 12 Stated Preference and Revealed Preference Data Panel Data Repeated Choice Situations Typically RPSP constructions experimental. William Greene. Stern School of Business. New York University. Part 7-1. Latent Class Models. Discrete Parameter Heterogeneity. Latent Classes. Latent Class Probabilities. Ambiguous – Classical Bayesian model?. William Greene. Stern School of Business. New York University. 0 Introduction. 1 . Summary. 2 Binary Choice. 3 Panel Data. 4 Bivariate Probit. 5 Ordered Choice. 6 Count Data. 7 Multinomial Choice. 8 Nested Logit. William Greene. Stern School of Business. New York University. Part 5. Multinomial Logit Extensions. What’s Wrong with the MNL Model?. I. .I.D. .  IIA . Independence from irrelevant alternatives. University of Texas at Austin. Chandra R. . Bhat. Introduction: . Choice Modeling. A set of tools to predict the choice behavior of a group of decision-makers in a specific choice context.. Picture Reference: Future and Simple-Choice Modeling (by Steve Cook and Michael McGee). David K. . Guilkey. Demographic Applications:. Single Spell. 1. Time until death. 2. Time until retirement. 3. Time until first marriage. 4. Time until first birth. Multiple Spell. 1. Time until birth of each child. William Greene. Stern School of Business. New York University. Part 5. Panel Data Models. Application: Health Care Panel Data. German Health Care Usage Data. , 7,293 Individuals, Varying Numbers of Periods. William Greene. Stern School of Business. New York University. 0 Introduction. 1 . Summary. 2 Binary Choice. 3 Panel Data. 4 Bivariate Probit. 5 Ordered Choice. 6 Count Data. 7 Multinomial Choice. 8 Nested Logit. William Greene. Stern School of Business. New York University. Part 11. Modeling Heterogeneity. Several Types of Heterogeneity. Observational: Observable differences across. choice makers. Choice strategy: How consumers make. William Greene. Stern School of Business. New York University. Part 6. Modeling Heterogeneity. Several Types of Heterogeneity. Differences across choice makers. Observable: Usually demographics such as age, sex. William Greene. Stern School of Business. New York University. Part 6. Modeling Latent Parameter Heterogeneity. Parameter Heterogeneity. Fixed and Random Effects Models. Latent common time invariant “effects”. William Greene. Stern School of Business. New York University. Part 6. Modeling Latent Parameter Heterogeneity. Parameter Heterogeneity. Fixed and Random Effects Models. Latent common time invariant “effects”. William Greene. Stern School of Business. New York University. 0 Introduction. 1 . Summary. 2 Binary Choice. 3 Panel Data. 4 Bivariate Probit. 5 Ordered Choice. 6 Count Data. 7 Multinomial Choice. 8 Nested Logit. Discrete Choice Modeling William Greene Stern School of Business New York University Part 2 Estimating and Using Binary Choice Models Agenda A Basic Model for Binary Choice Specification Maximum Likelihood Estimation Yuanyuan . Gu, PhD. Senior Research Fellow. CENTRE FOR THE HEALTH ECONOMY. Co . authors:. Henry Cutler, PhD. Director. Emma Olin. Research Fellow. AHES Conference 2017. Introduction. Background and study objectives.