APPLIED ECONOMETRICS
Bob Escudero
Office: Appleby Center 222D
Phone: (310) 506-4378
Fax: (310) 506-7271
ourselves, or we know where we can find information upon it.""Students have unnecessary difficulty learning... because textbooks generally do not have enough good examples of real-world applications."
--Gary Becker (Business Week, October 1996)
"Knowledge is of two kinds. We know a subject
--Samuel Johnson
"A person's judgment is only as good as his or her
information."--Unknown
Course Description
This course is designed to teach students basic skills in empirical economics. This course provides the student with a set of statistical tools that are necessary for empirical research in economics. Parameter estimation techniques involved in postulated economic relationships between variables and the methods of testing propositions will be developed. Topics that will be discussed include: a review of descriptive vs. inferential statistics, probability distributions, sampling and estimation, hypothesis testing, analysis of variance, regression, correlation, time-series, and forecasting. The multiple regression model will be covered, and students will be required to complete a course project involving the application of multiple regression.
Course Objectives
Students will:
be engaged in "headline" situations to motivate analyses. Examples that incorporate events reported in the newspapers, magazines, and journals that public administrators, economists, business executives, and professors read will be used.
apply the tools of statistics and econometrics to actual situations related to policy-specific topics.
learn to use both basic and more advanced quantitative methods, which will be made "real" with reference to the popular press.
use short case studies to demonstrate a specific form of analysis while giving them an opportunity to observe how concepts and theories are used to examine a diverse array of issues.
learn how to use Excel to analyze data sets that they have collected.
use the Web in search of information (major news and data sources) to be used throughout the semester for data analysis.
develop teamwork by assisting each other in obtaining information regarding their stated interests and goals.
learn research techniques and obtain pertinent information that will be of use in their careers.
Required Text
Kohler, Heinz and Ramanathan, Ramu. Applied Statistics and Econometrics. Mason, Ohio: South-Western Publishing, 2002.
Exams
There will be one midterm exam and one final exam.
Multiple Regression Analysis ProjectStudents are required to perform a multiple regression analysis on a policy-specific topic, such as crime, health care, education, immigration, social security, etc. Separate handouts will be distributed throughout the semester detailing the project.
Attendance
Attendance at every class meeting is expected of each student. Any exceptions to this rule must be made by the instructor, who is responsible for keeping attendance records.
Grading
The quality of achievement in the course is measured as follows: "A" indicates superior work; "B" indicates average or satisfactory, and "C" is the lowest passing grade.
A- 90-93%A 94-100% (indicates outstanding achievement)
Office Hours
My office hours will be scheduled on an individual basis. Call or speak to me during class to arrange for an appointment.
Tentative Course Schedule
UNIT 1
Week 1
Nature of Statistics and the Collection of Data
The Presentation of Data: Tables, Graphs and Summary Measures
The Theory of Probability
Week 2
Discrete and Continuous Probability Distributions
Sampling Distributions and Estimation
Week 3
Classical Hypothesis Testing Techniques
Week 4
Analysis of Variance
Week 5
Introduction to Econometrics
Simple Regression and Correlation Analysis
Week 6
Ordinary Least Squares and the Classical Model
Learning to Use Regression and Correlation Analysis
Week 7
Exam 1
UNIT 2
Week 8
Time-Series vs. Cross-Sectional Data Models
Introduction to Excel
Week 9
Specification: Choosing Independent Variables & Functional Form
Week 10
Violation of an Assumption: Multicollinearity
Week 11
Violation of an Assumption: Serial Correlation
Week 12
Violation of an Assumption: Heteroskedasticity
Regression User's Handbook and the Ethical Econometrician
Week 13
Research for Project
Week 14
Independent Research
Week 15
Review for Final Exam and Project
Dead Day - No Class; no exams or papers due
Week 16
Turn in Final Exam
Presentation of Multiple Regression Analysis Projects
Graduation
Any student with a documented disability (physical, learning, or psychological) needing academic accommodations should contact the Disability Services Office (Tyler Campus Center 225, ext. 6500) as early in the semester as possible. All discussions will remain confidential. Please visit http://www.pepperdine.edu/studentaffairs/disabilityserv for additional information.