Course Syllabus

JOHN CABOT UNIVERSITY

COURSE CODE: "EC 360"
COURSE NAME: "Econometrics"
SEMESTER & YEAR: Fall Semester 2012

SYLLABUS

INSTRUCTOR: Ciferri Davide
EMAIL: [email protected]
HOURS: TTH 18:00-19:15
TOTAL NO. OF CONTACT HOURS: 45
CREDITS:
PREREQUISITES: Prerequisites: EC 201, EC 202, MA 209
OFFICE HOURS:

COURSE DESCRIPTION:

This is an introductory course in econometrics and it will introduce students to the basic principles of the filed. The course attempts to provide a balance between theory and applied research with a focus on learning the usage of econometrics in practise. Students will present a project that demonstrates their skills to use computer software as well as to describe the empirical results obtained.

SUMMARY OF COURSE CONTENT:

Single-equation regression model, classical normal linear regression model, statistical inference, hypothesis testing, misspecification, autocorrelation, heteroscedasticity, multicollinearity, dummy variable regression models, qualitative response regression models.

LEARNING OUTCOMES:

Students should gain a solid foundation in both theoretical and empirical econometrics. and the basic skills needed to develop an empirical research.

TEXTBOOK:

Book Title	Author	Publisher	ISBN number	Library Call Number	Comments	Format	Local Bookstore	Online Purchase
Basic Econometrics	D.N. Gujarati and D.C. Porter	McGraw-Hill	978-007-127625-2

REQUIRED RESERVED READING:

NONE

RECOMMENDED RESERVED READING:

NONE

GRADING POLICY
-ASSESSMENT METHODS:

Assignment	Guidelines	Weight
Exam I	Review of some Statistics and mathematical tools, Single and Two variable Regression Model	15%
Exam II	Multiple Regression  Analysis and Hypothesis Testing	15%
Exam III	Dummy variables, Multicollinearity, Heteroscedasticity	15%
Project	Estimation and analysis of empirical results using econometric software	15%
Final		40%

-ASSESSMENT CRITERIA:

A: 90 to 99%

B: 80 to 89%

C: 70 to 79%

D: 60 to 69%

F: below 60%

A: Work of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensiveknowledge of relevant information or content. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the course.B: This is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments.C: This is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings.D: This level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.In effect, the student has barely done enough to persuade the instructor that s/he should not fail.F: This work fails to show any knowledge or understanding of the issues raised in the question. Most of the material in the answer is irrelevant.
-ATTENDANCE REQUIREMENTS:

Strongly encouraged

ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic dishonesty will receive a failing grade on the work in which the dishonesty occurred. In addition, acts of academic dishonesty, irrespective of the weight of the assignment, may result in the student receiving a failing grade in the course. Instances of academic dishonesty will be reported to the Dean of Academic Affairs. A student who is reported twice for academic dishonesty is subject to summary dismissal from the University. In such a case, the Academic Council will then make a recommendation to the President, who will make the final decision.

STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap. Students with approved accommodations must inform their professors at the beginning of the term. Please see the website for the complete policy.

SCHEDULE

Week 1: Sep 4, 6

Review of some Statistics and mathematical tools: Appendix A, B

Week 2: Sep 11, 13

Single-Equation Regression Model: Chapters 1 and 2

Two-Variable Regression Model: Chapter 3

Week 3: Sep 18, 20

Classical Normal Linear Regression Model: Chapter 4

Week 4: Sep 25, 27

Review

First Exam, Sep 27, Chapters 1,2,3 and 4

Week 5: Oct 2, 4

Interval Estimation and Hypothesis Testing: Chapter 5

Extension of the Two-Variable Linear Regression Model: Chapter 6

Week 6: Oct 9, 11

Multiple Regression Analysis Chapters 7 and 8

Week 7: Oct 16, 18

Review

Second Exam, Oct 16: Chapter 5,6,7,8

Week 8: Oct 23, 25

Dummy variables: Chapter 9

Multicollinearity: Chapter 10

Week 9: Oct 30

Multicollinearity: Chapter 10

Heteroscedasticity: Chapter 11

Week 10: Nov 6, 8

Heteroscedasticity: Chapter 11

Week 11: Now 13, 15

Review

Third Exam, Nov 15

Week 12: Nov 20, 22

Autocorrelation Chapter 12

Week 13: Nov 27, 29

Qualitative Response Regression Models: Chapter 15

Time series econometrics, Basic Concepts: Chapter 21

Week 14: Dec 4, 6

Review

Project due: Dec 6.

Final Exam: Comprehensive Exam (see University schedule for date and time)

Session	Session Focus	Reading Assignment	Other Assignment	Meeting Place/Exam Dates