Discrete Choice Modeling

1
Discrete Choice Modeling

• William Greene
• Stern School of Business
• New York University

Lab Sessions
2
Lab Session 6

• Ordered Choice Models

3
Data Set

• Data for this session are
• healthcare.lpj
• Refer to healthcare.lim for full list of the
  variables.
• This is an unbalanced panel. The group counter
  is already in the data set. Use PDS_Groupti
  for panel models

4
Binary Dependent Variables

• DOCTOR visited the doctor at least once
• HOSPITAL went to the hospital at least once.
• PUBLIC has public health insurance (1YES)
• ADDON additional health insurance.(1Yes)
• ADDON is extremely unbalanced.

5
Dependent Variables Ordered

• HSAT ordered reported health
  satisfaction, coded 0,1,,10.
• Use with ORDERED
• or ORDERED Logit
• Request marginal effects with
• Marginal
• as usual.

6
Ordered Choice Models

• Ordered Lhs dependent variable
• Rhs One, independent
  variables
• Remember to include the constant term
• For ordered logit in stead of ordered probit, use
• Ordered Logit Lhs dependent variable
• Rhs One,
  independent variables
• To get marginal effects, use Margin as usual.
• There are fixed and random effects estimators for
  this model
• FEM PDS _Groupti
• Random PDS
  _Groupti

7
Sample Selection in Ordered Choice
8
Sample Selection Ordered Probit

• PROBIT Lhs Rhs HOLD
• ORDERED Lhs Rhs
  Selection
• This is a maximum likelihood estimator, not a
  least squares estimator. There is no lambda
  variable. The various parameters are present in
  the likelihood function.

9
Zero Inflated Ordered Probit
10
Zero Inflated Ordered Probit Model

• Zero inflated ordered probit model with
  correlation
• A probit model for the zero cell
• (E.g., You can use DOCTOR for a model.)
• Create y1 y gt 0
• Probit HOLD
• Ordered probit with excess zeros
• Orde Lhs Rhs ZIOP
• Correlation between w (in probit) and e in
  ordered probit model
• CORRELATION is optional. Rho0 is the
  default.

11
Hierarchical Ordered Probit

• Hierarchical ordered probit. Ordered probit in
  which threshold parameters depend on variables.
  Two forms
• HO1 µ(i,j) exp?(j) dz(i).
• HO2, different d vector for each j.
• Use ORDERED HO1 list of variables or
• ORDERED HO2 list of variables.
• Can combine with SELECTION models and zero
  inflation models.
• This is also the Pudney and Shields generalized
  ordered probit from Journal of Applied
  Econometrics, August 2000, with the modification
  of using exp() and internally, a way to make
  sure that the thresholds are ordered..