PPT-Binary Choice Models

1 Topic Overview Introduction to binary choice models The Linear Probability model LPM The Probit model The Logit model 2 Introduction In some cases the outcome of interest . 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. Panel Data Models. Application: Health Care Panel Data. German Health Care Usage Data. , 7,293 Individuals, Varying Numbers of Periods. Modeling Binary Choice. Agenda. Models for Binary Choice. Specification. Maximum Likelihood Estimation. Estimating Partial Effects. Measuring Fit. Testing Hypotheses. Panel Data Models. Application: Health Care Usage. Niall Deacon (MPIA). Michael Liu, Eugene . Magnier. , Will Best, Kimberly . Aller. , Michael . Kotson. (Hawaii), Brendan bowler (Caltech), Adam Kraus, Trent . Dupuy. , Andrew Mann (. texas. ). Breaking The Degeneracy. Professor William Greene. Stern School of Business. IOMS Department. Department of Economics. Statistics and Data Analysis. Part . 10 . – . Qualitative Data. Modeling Qualitative Data. A Binary Outcome. 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 12. Stated Preference and Revealed Preference Data. Panel Data. Repeated Choice Situations. Typically RP/SP constructions (experimental). Hypothesis Testing in Binary Choice Models. Hypothesis Tests. Restrictions: Linear or nonlinear functions of the model parameters. Structural ‘change’: Constancy of parameters. Specification Tests: . 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). March 22, 2012. Prof. Rodger. Lecture adapted from Bruce Maggs/. Lecture developed at . Carnegie Mellon, primarily by Prof. Steven Rudich.. Announcements. More on Counting. Recitation tomorrow – bring laptop for one problem. Erik Sabina. Jennifer Malm. Suzanne Childress. John Bowman. DeVon Culbertson. Erik’s recommendations . (and the price you’ll have to pay). Get into the critical path. Though it will put the hurt on schedule. Jordan Louviere, Research Professor, Marketing, U. of South Australia; Chief Research Scientist, Strategy Analytics, Newton, MA; Co-Founder, . ChoiceFlows. , Raleigh, NC.  . Tiago Ribeiro, . Indera. 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 Rajesh . Paleti. Important Specification Issues. Only differences in the utilities matter. Not possible to estimate all alternate specific constants and all parameters on decision maker characteristics.