William Greene
Stern School of Business
New York University
Topics in
Microeconometics:
Discrete Choice Models
Stochastic Frontier Modeling
Curtin University Business School
Perth, Australia
July 22-24, 2013
Professor
Professor William. Greene
e-mail: wgreene@stern.nyu.edu
Home Page: http://people.stern.nyu.edu/wgreene
Abstract
This course will introduce the
student to methods and models used to analyze cross section and panel data.
Days 1 and 2 of the course will depart from the linear regression model and
proceed to specifications for binary and censored data, ordered choices, count
data and multinomial choices. The third day of the course will focus on a more
specialized field, stochastic frontier estimation and efficiency analysis.
Discussion will present basic models for cross section data then introduce
theory and methods for extensions to panel data and stated choice experiments.
The course will include lectures that develop the relevant theory and extensive
practical, laboratory applications. Emphasis in the laboratory sessions will be
on estimation of discrete choice and stochastic frontier models and using them
to describe behavior and to predict discrete outcomes. Course participants will
apply the techniques on their own computers using the NLOGIT computer program and several real data sets that have been
used in applications already in the literature.
Prerequisites
Prior knowledge
is assumed to include calculus at the level assumed in the first year of a
Ph.D. program in economics and a course in econometrics at the beginning Ph.D.
level out of a textbook such as Greene, W., Econometric
Analysis, 7th edition. Familiarity with NLOGIT will be helpful, but is not necessary. Two useful reference
books for the discrete choice part of the course are the primer Applied Choice Analysis by David
Hensher, John Rose and William Greene (Cambridge University Press, 2005) and
the survey monograph, Modeling Ordered
Choices by William Greene and David Hensher (Cambridge University Press,
2010). An up to date and comprehensive survey of econometric theory that is a
bit more advanced than needed for our purposes is Wooldridge, J., Econometric Analysis of Cross Section and
Panel Data, 2nd ed., MIT Press, 2010. A comprehensive reference
on stochastic frontier models is the 2008 survey by Greene.
(download here)
Students in this
course will obtain background in both the theory and methods of estimation for
discrete choice modeling. This course will provide a gateway to the
professional literature as well as practical applications of the methods at the
level of the contemporary research in the field. Emphasis in the course is on
applications of methods in health economics. Derivations of, e.g., asymptotic
properties of estimators, and theoretical fine points, such as the implications
of different types of independence assumptions in panel data models are left
for more advanced treatments.
Course Outline Left click to open. Right click to download. (This is a PDF
file.)
This is a course in econometric
analysis of discrete data and production/cost data. There are a huge variety of
models that are used in this context. We will focus on four discrete choice
models which arguably comprise the foundation for the area: the fundamental
model of binary choice (and a number of variants); models for ordered choices;
the Poisson regression model for count data; and the fundamental model for
multinomial choice, the multinomial logit model. The course will consist of
discussions and laboratory sessions which will apply the techniques to live
data sets and some time devoted to topics, discussions and laboratory work on
student projects. Discussions will cover the topics listed below. Lab sessions
will apply the techniques discussed in the preceding sessions. Practicals will
consist of directed exercises and student assignments to be completed singly or
in groups. The final day of the course will focus on efficiency estimation and
the stochastic frontier model.
No specific textbook is assigned
for the course. Some of the presentation will be based on Econometric Analysis, 7th ed., by Greene, W. (Prentice
Hall, 2012). 7 chapters are included with the course materials:
Left click to open. Right click to download. (These are PDF
files.)
Greene 11-Panel data methods
Greene 12-Estimation methods
Greene 14-Maximum likelihood estimation
Greene 15-Simulation based estimation and inference
Greene 17-Discrete choice models
Greene
18-Count data models
Greene 19-Censoring and truncation
The received literature on
discrete choice models is vast - one could easily compose a list of thousands
of articles. Your course materials include a small handful of articles. The
first set are methodological papers that focus on particular techniques. The
second set are recent applications in health economics that use the techniques
we will discuss in our course:
Methods Left click to open. Right click to
download. (These are PDF files.)
Correcting estimated standard errors in the presence
of clustering.
Modeling endogeneity in nonlinear
models.
Interaction effects in nonlinear models.
Modeling dynamic effects in nonlinear models.
Applications Left click to open. Right click to download. (These are PDF
files.)
Bago d Uva and Jones Latent Class Health Care
Models
Finkelstein et al. Oregon Health
Insurance Experiment
Scott et al. Recursive Bivariate Probit
Analysis of Quality of Diabetes Care
Lagarde Latent Class Logit
Analysis of Infant Care
Johnston, Schurer and Shields
Dynamic Ordered Choice Model
Jones and Schurer Dynamic
Ordered Choice Model
Riphahn, Wambach, Million Mixed Poisson
Models for Health Care Utilization
Contoyannis, Rice,
Jones Dynamic Ordered Choice Model of Health Satisfaction
Winkelmann Econometric Exploration
of Count Models of Health Care
Van Ophem Extension of Winkelmann Hurdle Model
Laporte Quantile Regression
Gannon,
Dynamic Probit Model
Christensen and Kallstrup, Duration
Fair-Extramarital Affairs - Tobit Model
I. Class Notes: Course
description and overview. Notes for use during the class sessions.
A. Discrete Choice Models
Left click to open. Right click to download. (These are
.pptx files)
Notes
0. Outline
Notes
1. Descriptive Statistics and Linear Regression
Notes
2. Binary Choice Estimation
Notes
3. Binary Choice Inference
Notes
4. Binary Choice Panel Data
Notes
5. Extensions of Discrete Choice Models
Notes
6. Ordered Choice
Notes
7. Count Data Models
Notes
8. Latent Class Models
Notes
9. Random Parameters Models
Notes
10. Multinomial Choice
Notes
11. Nested Logit
Notes
12. Random Parameters Logit
Notes
13. Latent Class Logit
Notes
14. Scaling and Heteroscedasticity
Notes
15. Stated Choice Experiments
Notes
16. Censored
Regression and Hurdle Models
Notes
17. Duration
Models
B. Stochastic Frontier Models
This part of the course will draw on a larger (several days)
course on frontier and efficiency modeling. Reference papers and materials can
be obtained from the home page of the course
2013 Stochastic Frontiers Modeling
Course
Two useful references on this topic are
1977 Classic Paper that Introduced the Stochastic Frontier Model
(Aigner, Lovell, Schmidt)
2008 Survey of Stochastic
Frontier Modeling by Greene
These are excerpts from the materials for the full course.
Left click to open. Right click to download. (These are
.pptx files)
Frontier
Models Notes 1. Modeling Inefficiency
Frontier
Models Notes 2. Stochastic Frontier Model
Frontier
Models Notes 3. Frontier Model Building
Frontier
Models Notes 4. Model Extensions
Frontier
Models Notes 5. Panel Data
Frontier
Models Notes 6. Applications
These are data sets that we will use for our lab exercise.
They are in the form of an NLOGIT project (lpj) file.
They are also posted in the portable (ASCII) comma separated
values, or csv format.
Spanish Dairy Farms Panel Data (csv)
U.S. Electricity Cost and
Production Data (csv)
Swiss Railways Panel Data on Production Costs (csv)
Airlines Panel Data on Production and Costs (csv)
American Banks Panel Data on Production Costs (csv)
This is a set of exercises that we will carry out in our lab
session. The exercises use the data files listed above.
Stochastic Frontier Modeling Lab Exercises (pdf) (Command File for Exercises (lim))
Stochastic Frontier Modeling Self Directed
Exercise (pdf)
II. Scripted Exercises: These
are scripted applications that will illustrate using NLOGIT to carry out some
of the
computations discuss in class. There are two parts to each,
the .pdf file for the exercise and the .lim file that contains
the NLOGIT
commands. You can first load the indicated data sets, open the command files,
then execute the script
and follow along as the computations are completed.
Left click to open. Right click to download. (These are .pdf
files)
Scripted Exercise 1: Basic Regression, Binary Choice (NLOGIT Commands for Exercise 1)
Scripted Exercise 2: Binary Choice: Estimation and
Testing, Panel Data (NLOGIT Commands for Exercise 2)
Scripted Exercise 3: Binary Choice Modeling with
Heterogeneity (NLOGIT Commands for Exercise 3)
Scripted Exercise 4: Ordered Choice and Count Data Models
(NLOGIT Commands for Exercise 4)
Scripted Exercise 5: Multinomial Choice Models, Stated
Preferences (NLOGIT Commands for Exercise 5)
III. Assignments: These are
exercises for the student to do on
their own.
Left click to open. Right click to download. (These are .pdf
files)
Exercise 1: Basic Regression, Binary Choice
Exercise 2: Binary Choice with Panel
Data; Delta Method, Bootstrapping
Exercise 3: Count Data;
Modeling with Heterogeneity, Latent Class and Mixed Models
Exercise 4: Multinomial Choice
IV. Lab Notes: These are
Powerpoint slide presentations (pptx) that show how to use NLOGIT.
Left click to open. Right click to download. These are pptx
files
Getting started tutorial
Lab 1: Descriptive Tools, Basic
Regression, Panel Data
Lab 2: Binary Choice
Lab 3: Useful Tools
Lab 4: Ordered Choice and Count Data Models
Lab 5: Random Parameters and
Latent Class Models
Lab 6: Multinomial Choice Models
V. Data Sets: These
datasets are provided in two forms, NLOGIT project (.lpj) files and portable
CSV files.
Left click to open. Right click to download. CSV files will open
Excel.
Small
Demonstration Income/Education Data, 14 observations (lpj) (csv)
Combined
Travel Mode and Brand Choices Data, 12800 observations (lpj) (csv)
Health
Economics, Small Subset of GSOEP Data, 2039 observations (lpj) (csv)
Manufacturing
Innovation Data, 6350 observations (lpj) (csv)
Multinomial
Choice Stated Preference Experiment, 9408 observations (lpj) (csv)
Labor
Supply Data, 753 observations (lpj) (csv)
Health
Care Panel Data 27326 observations (lpj) (csv)
Southern
California Fishing Data (long form), 4728 observations (lpj) (csv)
Rand
Study Data, 19339 observations (lpj) (csv)
General
Practitioner Visits Data, 342 observations (lpj) (csv)
VI.
NLOGIT Software: This section contains a brief introduction and two
manuals: The short introduction is a getting
started guide. The LIMDEP manual
explains the basics of using LIMDEP
and NLOGIT. (LIMDEP is embedded in NLOGIT).
The NLOGIT manual contains
descriptions of how to use the special features for discrete choice modeling
with NLOGIT (as well as some
additional material on other discrete choice models that are also contained in LIMDEP). The setup file contains an
installation kit for installing a copy of NLOGIT
made specially for this course on your own computer. You should download the
setup file to your own computer and execute it there, rather than launching it
from your web browser.
Left click to open. Right click to download.
Quickstart Introduction to NLOGIT (Command script file to use with Quickstart)
LIMDEP Student User Manual
NLOGIT Student User Manual
NLOGIT Software Setup for Installing NLOGIT
on Your Computer