PanelDataNotes-15

PanelDataNotes-15 - Econometric Analysis of Panel Data...

Info iconThis preview shows pages 1–12. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Econometric Analysis of Panel Data William Greene Department of Economics Stern School of Business Econometric Analysis of Panel Data 15. Models for Binary Choice Agenda and References Binary choice modeling the leading example of formal nonlinear modeling Binary choice modeling with panel data Models for heterogeneity Estimation strategies Unconditional and conditional Fixed and random effects The incidental parameters problem JW chapter 15, Baltagi, ch. 11, Hsiao ch. 7, Greene ch. 23. Two Fundamental Building Blocks Underlying Behavioral Theory: Random utility model The link between underlying behavior and observed data Empirical Tool: Stochastic, parametric model for binary choice A p latform for models of discrete choice Behavioral Assumptions Preferences are transitive and complete wrt choice situations Utility is defined over alternatives: U it Utility maximization assumption If U it1 > U it2 , consumer chooses alternative 1, not alternative 2. Revealed preference (duality) If the consumer chooses alternative 1 and not alternative 2, then U it1 > U it2 . Random Utility Functions U it = + x it + z i + u i + it x it = Attributes of choice presented to person = T aste or preference weights z i = Characteristics of the person = Weights on person specific characteristics it = Unobserved random component of utility Mean: E[ it ] = 0, Var[ it ] = 1 Health Satisfaction Scale 0 = Not Healthy 1 = Healthy A Model for Binary Choice Yes or No decision (Buy/Not buy) Example, choose to fly or not to fly to a destination when there are alternatives. Model: Net utility of flying U fly = + 1Cost + 2Time + Income + Choose to fly if net utility is positive Data: X = [1,cost,terminal time] Z = [income] y = 1 if choose fly, U fly > 0, 0 if not. What Can Be Learned from the Data? (A Sample of Consumers, i = 1,,n) Are the attributes relevant? Predicting behavior- Individual- Aggregate Analyze changes in behavior when attributes change Application 210 Commuters Between Sydney and Melbourne Available modes = Air, Train, Bus, Car Observed: Choice Attributes: Cost, terminal time, other Characteristics: Household income First application: Fly or other The Data Listing of raw data (Current sample) Line Observ MODE GC TTME HINC 1 1 0 70 69 35 2 5 0 68 64 30 3 9 0 129 69 40 4 13 0 59 64 70 5 17 0 82 64 45 6 21 0 70 69 20 7 25 1 160 45 45 8 29 0 137 69 12 9 33 0 70 69 40 10 37 0 65 69 70 11 41 0 68 64 15 12...
View Full Document

This note was uploaded on 01/05/2012 for the course B 55.9912 taught by Professor Willamgreene during the Fall '11 term at NYU.

Page1 / 61

PanelDataNotes-15 - Econometric Analysis of Panel Data...

This preview shows document pages 1 - 12. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online