Syllabus

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material. Reading (required): Damodar Gujarati and Dawn Porter. Essentials of Econometrics. McGraw-Hill Higher. Education; 4th ed. (ISBN-10: 0073375845) ...

Economic Statistics

FE 331 Course Syllabus Spring Semester 2013

Professor: Office: Telephone: Office Hours: Website: Email: Course meeting times/places:

Ahmed S. Rahman Nimitz 28 Office: 3-6897 MW 1430 – 1630 or by appointment http://www.usna.edu/user/econ/rahman [email protected] Section 1041: TTH8, SA101 Section 3041: TTH9, SA101

Course Objective: In this course, we will focus on basic regression analysis. We will review statistical inference (sampling and hypothesis testing), and then we will (using these tools) learn how to estimate relationships between variables via regression analysis. We will learn some econometric theory but our focus will be on techniques to study concrete data, largely using the Stata 12 software package. This course will give you the tools to perform the statistical analyses required in the Research Seminar (FE475) and to evaluate other questions and problems that you may encounter in the economics major, the media, and in your work in naval service. Our time in the classroom will consist of a mixture of discussion-based teaching, lecture based teaching (primarily using the white board), and both individual and group work on relevant problems. Training in the Stata software will be integrated into the course material.

Reading (required): Damodar Gujarati and Dawn Porter. Essentials of Econometrics. McGraw-Hill Higher Education; 4th ed. (ISBN-10: 0073375845)

Course work: Exams: The midterms will be in class on Thursday February 14 and Thursday March 28. Please notify me in advance if you have a conflict with any of the exam dates. There will be no make-ups for the exams. If you miss an exam for an excused reason, then the weight for that exam will contribute to your final exam instead (unless you miss both midterms for excused reasons; in this event, we will discuss how to proceed). If you miss an exam for an unexcused reason, you will receive zero credit. I will provide the date for the final once it is determined.

In and out-of-class problems: You will have an opportunity to do/solve many problems in this class. They will include both traditional pencil/paper problems (from the text or other sources) and exercises that will require you to use Stata to analyze actual data. You are encouraged to work in groups on these exercises, but you should also write and submit your solutions independently. Be sure that you can demonstrate the relevant work that led to each solution. For Stata problems, you should be comfortable with some coding and reading regression output tables. I believe that if you make a strong effort on these exercises, this will be the best way for you to learn the material. I will plan to allocate some class-time for you to work on them, and please do not hesitate to visit my office for EI (with advance notice of course). Quizzes: We will have a series of quizzes, some which will be “Stata-based.” While problems and exercises in class will also involve Stata-based problems, it is often easy to rely on a classmate to “do the work,” especially for computer-based learning topics. The quizzes will be short but will test your grasp of key concepts and Stata functions as we apply them to the regression topics learned in class. This will benefit you greatly for the end-of-semester project, in particular. Class Participation: You are expected to attend class every day, submit assignments on time, and be alert and engaged in classroom activities. Paper: More details to come. For this project you will be asked to find an interesting question that you will research qualitatively and analyze (and hopefully answer) quantitatively using the regression analysis techniques that you have learned during the semester.

Grade Breakdown: Your final grade shall be weighted as follows: Quizzes Class participation Midterms (2) Final exam (cumulative) Paper:

20% 10% 15% each 20% 20%

Please note: I WILL NOT CHANGE ANY GRADE ONCE I GIVE IT, UNLESS IT IS CLEAR THAT I HAVE MADE A CALCULATION ERROR. AND UNDER NO CIRCUMSTANCES WILL I GIVE ANY EXTRA-CREDIT ASSIGNMENTS TO MAKE UP FOR POOR PERFORMANCE.

Tentative Course Outline and Schedule: * The following schedule is subject to change at my discretion. I will however notify you immediately of any change to the proposed order of topics or any other potential change. Section I: Introduction and Measuring the Macro Economy Topic Week 1:

Week 2:

Important Dates

Introduction Random variables and distributions Sampling Part I – The Linear Regression Model Hypothesis testing Regression Introduction

Readings Appendices

Appendices, Ch 1 - 2

Week 3:

Simple Linear Regression

Ch 3

Week 4:

Simple Regression (cont) Multiple Regression

Ch 3 - 4

Week 5:

Multiple Regression (cont)

Ch 4

Week 6

Functional Forms

Ch 5

Week 7:

Dummy and Categorical Variables

Ch 6

Week 8:

Part II Model Selection and Specification Error

Ch 7

Week 9:

Multicollinearity

Ch 8

Week 10:

Heteroskedasticity

Ch 9

Week 11:

Autocorrelation

Ch 10

Week 12:

Part III Instruments and Simultaneous Equation Models

Ch 11

Week 13:

Simultaneous Equation Models (cont) Selected Topics

Ch 12