ECN 140: Econometrics

Instructor: Miguel Jerez, Office: 1144 SSH (Office Hours: Tuesdays 9:00-10:30 am and Thursdays 11:00-12:30 am). Email: mjerez@ucdavis.edu

 Teaching Assistant: Qi Han, Office Hours: Wednesday, 2:00-4:00 pm, 138 SSH (this schedule may change if it is in conflict with other obligations). Email: qhan@ucdavis.edu
Class schedule (2013-14):
  • Meeting: Tuesdays and Thursdays 3:10 pm - 4:30 pm, ART 00204
  • Discussion Sessions: Wednesdays, 5:10 pm - 6:00 pm and 6:10 pm - 7:00 pm, HUTCH 00093

 About this course: This is an introductory course to econometric methods. Its goal is to provide students with the knowledge to do their own empirical research in economics, to evaluate economic/business policies and to forecast economic variables. In addition to using the computer as a tool for regression analysis, the course will focus upon the underlying statistical models so that students understand when particular methods are likely to be valid (or invalid!).

Pre-requisites: ECN 100(105), 101(104); MAT 16A & 16B or 21A & 21B, STA 13, ECN 102 (or any upper division STA course) are prerequisites for ECN 140. Statistics 13 and ECN 102 are the most important as the material in class assumes knowledge from these courses. Algebra (including matrix algebra) and some calculus are extensively used. Homework sets will require use of the computer but no previous experience with the software is assumed.

Textbook: I will follow my own slides that you can download from this website. However, it is a good idea to have at hand one of the following textbooks:
  • Wooldridge, J.M. (2012). Introductory Econometrics: A Modern Approach, 5th ed., South Western Cengage Learning
  • Greene, W.H. (2011). Econometric Analysis, 7 ed., Prentice-Hall
  • Heij, C., Boer, P., Franses, P.H. Kloek, T. and van Dijk, H.K. (2004). Econometric Methods with Applications in Business and Economics, Oxford University Press

Software: Students are required to use the statistical package Gretl in this course. It can be freely downloaded from the Gretl Project Website, which also provides a complete documentation, add-on modules and many datasets referred to “classical” textbooks.

Another interesting piece of software is PQRS: a free tool to calculate probabilities and quantiles for many probability distributions. It can be freely downloaded from this site.

Course Grading:
  • Assignments (15%). There will be four Homework sets.
  • Empirical Project (15%): To be delivered in paper before the Dec. 4th Lab class. Please follow these guidelines.
  • Midterm exam: (30%): Oct. 29
  • Final exam: (Comprehensive, 40%): Thursday Dec 12, 8-10 am

Syllabus (to download a PDF version, click here):

1. Introduction to Econometrics. (1 class).

Complementary readings and other materials:

2. Linear regression: foundations and graphical analysis. (2 weeks).

Complementary readings and other materials:

3. Multiple regression. (3 weeks).
    3.1 Model basics and Estimation
    3.2 Inference

Complementary readings and other materials:

4. Topics in regression analysis. (3 weeks).
    4.1 Discrete and semi-continuous variables
    4.2 Collinearity
    4.3 Heteroscedastic and non-normal data

Complementary readings and other materials:

5. Regression with time series data (To be published) (2 weeks).

Complementary readings and other materials:

Other resources and interesting links:
  • GRETL project website. This is a free and cross-platform software package for econometric analysis. We will use it for the practical work
  • In this website you can find PQRS.
  • Here you will find a complete course of econometrics, based on Wooldridge´s textbook, and implemented in Powerpoint slides
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