Econometrics

GADE "E" (English group)

Instructor: Miguel Jerez

Class schedule (2013-14):

• Lectures: Thursday (15,00-17,00) and Friday (13,00-15,00) at classroom 310, Aulario building
• Room: No. 322, Building #1 (Prefabricado), 3rd floor, North Wing
• Office Hours: Thursday, 11.30-13.00; Friday, 11,30-13,00. Appointments can be made by email (to do so, please click here)

About this course: This is a 14 weeks introductory course to Econometrics. It provides a wide overview of both, theoretical an practical issues, with emphasis in practical work with real data. The students need a solid background in Statistics and Mathematics. After completing this course, the student should be able to prepare reports answering relevant questions in business or economics, managing forecasts, measuring the effect of a given policy or testing hypotheses both, with cross-section and/or time series data.

Requisites: Students must fill this personal data form


Grading policy. Semi-continuous evaluation based on the following items:

• Final exam (60%) in June and September
• Individual work and partial exams (30%)
• Active participation (10%)

A student not taking the final exam in June will be graded with "Exam: not taken" if either he/she: (a) has no grades in the "Individual work and partial exams" item, or (b) gives me a signed notification before April 16th. Otherwise his grade will be computed with the above mentioned weights, considering that the "Final exam" grade was zero.

In September any student not taking the exam will be graded with "Exam: not taken."

Syllabus:

1. Introduction to Econometrics. (1 week).

Complementary readings and other materials:

• Wikipedia articles about: Econometrics, Criticisms of Econometrics, Cross-sectional_data, Time series and Panel data
• Givens, G.H. and J.A. Hoeting (2002). Comunicating Statistical Results, Mimeo. This very useful document can be freely downloaded from this site.
• Installation guide for GRETL
• Two Nobel lectures about the econometrics of cross-section data
• Two Nobel lectures about the econometrics of time series data

2. Simple linear regression: foundations and graphical analysis. (2 weeks).

Complementary readings and other materials:

• Simulated data
• CEO compensation (Wooldridge's ceosal2 dataset)
• Video: A short intro to Linear Regression

3. Multiple regression: estimation and inference. (3 weeks).
    3.1 Estimation
    3.2 Inference

Complementary readings and other materials:

• Many least squares calculations done (almost) by hand
• Weight vs. age for a sample of children
• Exercise sheet #1

4. Topics in regression analysis. (2 weeks).
    4.1 Discrete and semi-continuous regressors. Polynomial terms
    4.2 Collinearity

Complementary readings and other materials:

• Wooldridge's "Beauty" dataset
• Wooldridge's hprice1 dataset

5. Regression with cross-section data. (2 weeks).
    5.1 Heteroscedastic and non-normal data
    5.2 Influential observations and outliers

Complementary readings and other materials:

• OCDE dataset
• Simulated data for the topic: "Influential observations and outliers"

6. Time series modeling. (3 weeks).
    6.1 Univariate models
    6.2 Regression with time series data

Complementary readings and other materials:

• Simulated time series
• Airline passengers
• US GDP vs. melanoma incidence
• Yield of UK sovereign debt
• Yield of spanish shares vs. IBEX35 (CAPM model)

Some WEBs that you may use to revise basic concepts:

• Algebra: matrices and vectors, linear equations, matrix operations, inverse of a matrix
• Statistics: descriptive statistics (mean, variance, correlation,...), estimation, hypotheses testing

References:

• Wooldridge, J.M. (2009). Introductory Econometrics: A Modern Approach, 4ed., South Western Cengage Learning
• Givens, G.H. and J.A. Hoeting (2002). Comunicating Statistical Results, Mimeo. This very useful document can be freely downloaded from this site.
• United Nations Economic Comission for Europe (2009). Making data Meaningful. Part 1 and Part2
• Box, G.E.P.; G. M. Jenkins y G. C. Reinsel (2008). Time Series Analysis: Forecasting and Control, 4th Edition. Wiley, New York
• Cottrell, A. y R. Luchetti (2011). Gretl User's Guide.
• Greene, W.H. (2011). Econometric Analysis, 7 ed., Prentice-Hall
• Hansen, B.E. Econometrics, a free (but somewhat complex) ebook
• Heij, C., Boer, P., Franses, P.H. Kloek, T. y van Dijk, H.K. (2004). Econometric Methods with Applications in Business and Economics, Oxford University Press

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
• I have written a short step-by-step Instalation guide for GRETL, that you can use to download and install this program in your home computer
• In this website you can find PQRS. PQRS is a free tool for students using computer aided instruction of statistics in order to make printed tables obsolete. It allows one to calculate probabilities and quantiles associated with a large number of probability distributions. Furthermore, one can draw random samples from all these distributions and store them to a file
• Here you can find a complete course of econometrics, based on Wooldridge´s textbook, and implemented in Powerpoint slides