Econometrics

Econ. 333

Spring Semester 2005

Instructor: Dr. Ken Smith

Office: McComsey 326

Tel.: 872-3582

E-mail: kenneth.smith@millersville.edu

Office Hours: Mon. 11:00 – 12:30, Wed. 11:00 – 12:00, and Tues. & Thurs. 9:00 – 10:30 (or by appointment – I’m usually pretty flexible on Tues. & Thurs.)

Course Overview: This course applies the tools of statistics to analysis of problems and issues traditionally studied by economists. Increasingly econometrics is becoming a fundamental tool of economic research in virtually all areas of study. The emphasis of this course will be on econometric application as opposed to theory. Primarily we will look at econometric analysis using cross-sectional data – data gathered at a point in time, and time series data – data gathered over time.

The following competencies considered fundamental to an understanding of economics are covered in this course:

E. Develop and apply economic modeling skills, including

(1) determination of main variables involved in an economic problem.

(2) specifying relationships between variables.

(3) specifying direction of causation between variables.

(4) recognition of interdependence and inter-linkages across relationships.

F. Develop and apply research and information management skills, including

(1) locating primary and secondary economic sources of information with traditional and emerging library technologies.

(2) evaluating the quality of a research source.

(3) summarizing the content of a research source.

(4) synthesizing, analyzing, and critiquing information across research sources.

(5) creating a working hypothesis using economic modelling skills.

(6) evaluating a working hypothesis using qualitative, logical, and quantitative methods.

(7) recognizing the benefits and limitations to understanding attained from economic methods of analysis.

G. The ability to compute, measure, estimate, and evaluate in order to solve theoretical and practical problems using

(1) economic modelling procedures such as concepts of patterns, functions and relationships.

(2) a variety of mathematical techniques such as linear algebra, simultaneous equations analysis and calculus (as appropriate in various courses and major options.)

(3) empirical data gathering skills including finding and analyzing data from pre-existing data sources as well as gathering unique data sets.

(4) charts, tables and graphs, showing the relationships between economic data and real-world situations.

(5) a variety of statistical techniques such as averages, standard deviations, indexing procedures, regression analysis and other econometric tools.

(6) modern technology such as calculators, spreadsheets, data base programs, and statistical software.

Prerequisites: Econ. 101, Econ. 102, & Econ. 231 (or a reasonable substitute)

Required Text: Introductory Econometrics: A Modern Approach, Jeffrey M. Wooldridge

Core Reading (supplemental readings will be assigned when appropriate)

Recommended review reading – Appendices A, B, & C

I. Introduction and Regression Analysis with Cross-Sectional Data

a) Ch. 1 – The Nature of Econometrics and Economic Data

b) Ch. 2 – The Simple Regression Model

c) Ch. 3 – Multiple Regression Analysis: Estimation

d) Ch. 4 – Multiple Regression Analysis: Inference

e) Ch. 5 – Multiple Regression Analysis: OLS Asymptotics

f) Ch. 6 – Multiple Regression Analysis: Further Issues

g) Ch. 7 – Multiple Regression analysis with Dummy Variables

h) Ch. 8 – Heteroskedasticity

II. Time Series Analysis

a) Ch. 10 – Basic Regression Analysis with Time Series Data

b) Ch. 11 – Further Issues in Using OLS with Time Series Data

c) Ch. 12 – Serial Correlation and Heteroskedasticity in Time Series Regressions

Grading System

Grades will be determined by cumulative point totals based on the following:

Midterm Exam #1 – 100 pts. (Wed. Feb. 16)

Midterm Exam #2 – 100 pts. (Fri. March 25)

Problem Sets – 120 pts. (to be handed out periodically)

Data Analysis Project – 80 pts. (due Thurs. May 5)

Final Exam – 150 pts. (Thurs. May 5, 10:15 – 12:15)

The midterm exams will be given in class and last 75 minutes. The final exam will be a 2 hour cumulative exam. Make-up exams will not be given without an excellent reason supported by documentation (i.e., a note from a doctor in case of illness). Cheating on an exam will result in a zero score on that exam. Cooperation on problem sets is encouraged though everyone must hand in each problem set. The Data Analysis Project will give you a chance to work with actual data from some country to formulate an interesting question regarding some aspect of economics and examine your question empirically. Late problem sets will be penalized 4 pts. for each day or partial day they are late. A missed deadline on the data analysis project will result in a 10 pt. penalty.

The following is a reference representing the Maximum cumulative point total necessary to fall in each grade category. I may curve downward depending on overall class performance.

A – 90-100%

B – 80-89%

C – 70-79%

D – 60-69%