Econometrics

Fall 2015

Course Description:  This class provides an introduction to fundamental theories and practices of econometrics.

Course Objectives

• Economic Literacy: Students who complete this course should understand and be able to articulate, both orally and in writing, the core economic principles, concepts and theories that form the foundation of  modern econometric analysis.

• Economic Numeracy: Students who complete this course should be familiar with the tools, techniques and methods of empirical economics for various economic issues. They should be able to analyze data using computer applications and should be familiar with regression methods and other statistical techniques. They should be able to read and assess general interest articles on various economic issues. In addition, they should be able to understand and evaluate key findings in published economic research from a wide range of sources including academic economists, public policy ‘think tanks,’ and government agencies.

• Economic Citizenship: Upon completion of this course students should be able to apply their understanding of core concepts and quantitative tools to analyze and research real world problems and evaluate alternative economic policy proposals on various economic issues.

• This class provides both theoretical and practical tools for applying economic theory and models to real economic data.   We use statistical tools to answer "how much" type questions; by doing so, we are able to confirm or refute whether the economic theory or model actually operates in real world.  By the end of this class you should have a solid understanding of many (not all!) important concepts and theories in econometrics.  Also, you should have a command of the statistical tools and be able to do independent research using economic data.

Learning Objectives: After completing this course, students will be able to

• explain how simple and multiple regressions are different
• explain what dependent and independent variables are
• explain how to interpret regression estimates and test significance of them
• explain how to measure goodness of fit using a joint hypothesis test
• explain assumptioins of the least square method
• explain Gauss-Markov theorem
• explain multicolinearity, heteroscedasticity, and serial correlation
• explain dummy variable trap
• explain probit/logit model

Program Outcomes: The completion of this course will contribute to the outcomes of the economics major/minor.

Prerequisite: Economics 3230. The prerequisite is taken seriously and you are expected to have a command over this material.  A firm knowledge of algebra and basic calculus such as differentiation greatly improves the odds for successful completion of this course.

Office Hours: Tuesday 2:00-3:00 PM or by appointment. Room: Tilton Hall 310, 862-8356.   My email address is msyun@tulane.edu.

Computer Lab:  Tilton 307 is reserved during Wednesday 10:00 - 11:00 AM.

Readings: The following should be available at the bookstore:

You may choose any textbook since undergraduate textbooks are very similar, e.g., James H. Stock and Mark W. Watson, Introduction to Econometrics 3rd Edition, Addison-Wesley 2011.  The text above is one of the best on the market. I will follow the text closely. However, I may lecture on some things that are not in the text.  The text should be viewed as a complement to the lectures, not a substitute. You are responsible for the material in the texts and in the lectures. I make every effort to have class attendance a necessary (though not sufficient) factor in performing well on examinations. Note that I have deliberately kept the amount of reading down. This is because I expect you to read and thoroughly understand all the material in the text.  

Online Study Resources: Online study tools are available at http://principlesofeconometrics.com/poe4/poe4.htm.   Data, SAS handouts and useful links are available there.  You should make use of this site.

Statistical Program: You may use any statistical packag to do the homeworks and a research paper (MA students only).  You may go to the computer labs in the campus.  The computer labs have PC version SAS and SPSS.  Economics Department also maintains a computer lab (Tilton 307) which has STATA. Note that the departmental computer lab is reserved during Wednesday 10:00-11:00 AM. A good introduction to statistical packages can be found from WWW (e.g., http://www.ats.ucla.edu/stat/).

You may purchase SAS or Stata programs.  For SAS, check out eAcademy at Technology Service website of Tulane (https://tulane.onthehub.com/WebStore/Welcome.aspx?JSEnabled=1).  For Stata, http://www.stata.com/order/new/edu/gradplans/student-pricing/.

• Brief introduction to course
• Why study econometrics?
• What is an econometric model?
• Sources of data.
• Mark Killingsworth, A Simple Introduction to Econometrics 
• Nisbet and Vakil, "Some Estimates of Price and Expenditure Elasticities of Demand for Marijuana Among U.C.L.A. Students," Review of Economics and Statistics, 1972, 473-75

• Random Variables
• Controlled vs. uncontrolled experimental data
• Discrete vs. continuous random variables
• Review of probability concepts
• Expected value
• Sample moments of a random variable
• The joint density function
• Marginal density, conditional density and independence
• Covariance and correlation
• The Normal density
• Yun, "Earnings Inequality in USA, 1969-1999: Comparing Inequality Using Earnings Equations," Review of Income and Wealth, 2006, 127-144 

• The econometric model
• The least squares principle
• Estimating the econometric model and interpreting the results
• The properties of the least squares estimates of an econometric model
• Inference and prediction in the Simple Linear Regression Model
• Interval estimation and hypothesis testing
• Evaluating the Simple Linear Regression Model

• The econometric model with more than one independent variable
• The least squares principle
• Estimating the multiple regression and interpreting the results
• Inference and prediction in the multiple regression
• Single and joint hypothesis tests of the parameters of the econometric model
• Model specification issues
• Collinear variables

• Binary variables
• Interactions between binary variables
• Functional form

• Heteroskedasticity
• Serial corrleation
• Random regressors - instrument variable

• Estimating regression models with panel data (Chapter 15)
• Regression models with binary dependent variable (Chapter 16)

• Stationary time series
• Spurious regression
• Tests for stationarity
• Cointegration

• Note:  I reserve the right to alter this schedule during the semester. All exams are cumulative. Of course, new material covered since the last exam (in bold letter) will be emphasized, but you are responsible for all the material.
• Sample Questions: Sample questions are provided for the exams 1 and 2.  However, there is NO sample questions for the exam 3.
• Makeup Policy:  Students who simply do not show up for exams should not expect to be given a makeup.  You should present a valid documentation in order to avoid receiving zero point on the missing exam.
• Extra-Credit Policy: There are no extra-credit assignments. There is no way to ex post improve your grade on an examination. Plan to do well on the required material.
• Final Project: The final project will be assigned at the beginning of November, 2015.  The report on the project is to be emailed by central standard time 11AM, December 11, 2015 (Friday).
  
• Homework: Due to the nature of the course, homework assignments are necessary to enhance your understanding of the material covered in class.  Several assignments will be handed out.  The assignments will ask you to (1) work through some statistical theory and /or (2) estimate economic models given a data set with your choice of statistical tools. 
  
• Research Paper (MA students ONLY): One major goal of this course is to provide you with skills and knowledge of both the theory and the practical tools necessary to start your own research.  The best way to achieve this goal is to write an original research paper.  The paper is to be emailed by central standard time 11AM, December 11, 2015 (Friday).    The paper will discuss why you chose the topic, economic model, econometrics specification, data and empirical finding.  To avoid last minute chaos, a proposal (two pages long) is required by October 29, 2015 (Thursday).  The proposal should include why the topic is interesting, how you will obtain data, and how you estimate equations of interest.  The term paper should not be taken lightly.  The starting point is finding what interesting topic is; you may have glance over titles of articles in top notch journals (e.g., American Economic Review) or search Econlit.
  

0. All students are responsible for knowing and adhering to Tulane University’s Honor Code, available at http://tulane.edu/college/code.cfm.
1. If you are having problems, please seek out help early. Come in prepared, having gone over the lectures, text, and problems in the text. If you have missed any classes, make sure you have gotten the missed notes from classmates. In cases like this, it usually pays to get the notes from at least two of your class mates.
2. Some students slack off. Econometrics is very demanding a course even though I keep the coverage to minimal. The only way to learn it is to keep going over it, work the problems in your text, and  THINK about what you are doing at each step. I suggest that you first read through the entire book. This will help you to begin to think about econometrics. Go over the lectures and think about what problems I raise and what problems are raised in the book. Furthermore, let me urge you to read as much of the material as possible early on in the course. You will find this will help you develop a perspective on the course material and lead to a better understanding of econometrics.  Also it is essential to have a command of the statistical package(s) to complete this course successfully.  Be familiar with the program(s) as soon as possible.  Knowledge on statistical package(s) will not only help your homeworks and the research paper during this semester but also your future job search or higher education in graduate or professional schools.
3. Do not wait until after I have lectured on something to read the material work on it yourself. Come to class  prepared!
4. The emphasis in this class is on developing your ability to apply analytical techniques and on your understanding of fundamental concepts. Exams will emphasize this.  They will assume you have a complete understanding of the lectures, text and study guide, and will ask you to apply what you have learned to "new" circumstances.
5. The course material builds on earlier work. It is essential that you master every part of the material. I will integrate the material as we go along, but you will be ahead of the game if you make extended efforts to learn and integrate it yourself.