Econometrics

Code:

1EC303

Acronym:

ECONM

Keywords
Classification	Keyword
OFICIAL	Economics

Instance: 2015/2016 - 1S

Active?	Yes
Responsible unit:	Agrupamento Científico de Economia
Course/CS Responsible:	Bachelor in Economics

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
LECO	317	Bologna Syllabus since 2012	3	-	6	63	162

Teaching language

Portuguese

Objectives

The course is designed for a one-semester introduction to Econometrics. Pre-requisites for the course are a solid background in Economic Theory (both Micro- and Macroeconomics), in Statistics and in Linear Algebra. The course's main objective is in interpreting, understanding and evaluating the findings of elementary econometric analyses.

Learning outcomes and competences

The student is expected to be able to read, interpret and evaluate elementary econometric findings. Hands-on experience with specialized  econometric software is required.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Pre-requisites for the course are a solid background in Economic Theory (both Micro- and Macroeconomics), in Statistics and in Linear Algebra. Good knowledge of Mathmatical Statistics is fundamental.

Program

0. INTRODUCTION: subject and methodology of Econometrics 1. THE CLASSICAL LINEAR REGRESSION MODEL: elementary concepts and notation; least squares (OLS) estimators of the regression coefficients; coefficient of determination; assumptions of the classical linear regression model; properties of the OLS estimators; the estimator of the variance of the disturbances 2. INFERENCE IN THE LINEAR REGRESSION MODEL: the normality assumption; maximum likelihood (ML) estimators; testing hypothesis about a single coefficient; testing hypothesis about linear restrictions on coefficients; testing the overall significance of the regression 3. SOME EXTENSIONS OF THE LINEAR REGRESSION MODEL: choosing a functional form; NLS estimators; dummy variables; models for the trend and seasonal components ; forecasting; testing the equality between sets of coefficients in two regressions 4. THE GENERALIZED LINEAR REGRESSION MODEL: assumptions; GLS and EGLS estimators 5. HETEROSKEDASTICITY: the nature of the problem; detecting heteroskedasticity: White and Breusch-Pagan tests; estimation methods 6. AUTOCORRELATION: the nature of the problem; the 1st-order autoregressive process; detecting autocorrelation: Durbin-Watson and Breusch-Godfrey tests; estimation methods: Cochrane-Orcutt, Durbin in two steps and NLS methods

Mandatory literature

M. Mendes de Oliveira, Luis Delfim Santos e Natércia Fortuna; Econometria, Escolar Editora, 2011

Complementary Bibliography

Damodar Gujarati; Basic Econometrics, 4th ed., McGraw-Hill
Jeffrey M. Wooldridge; Introductory Econometrics, South-Western College Publishing, 2000. ISBN: 0-538-85013-2

Comments from the literature

The first textbook is written in Portuguese. Should you prefer to read in English, any of the other two listed books will be a valuable guide.

Teaching methods and learning activities

Econometrics aims to provide the basic theoretical principles of estimation and inference in Econometrics. Classes will be held in computer labs, allowing students' access to hands-on experience with computer applications using specialized econometric software.

Software

EViews

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	60,00
Participação presencial	0,00
Teste	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	126,00
Frequência das aulas	63,00
Total:	189,00

Eligibility for exams

Grades will be assigned according to the general rules of the University of Porto. A final written exam will be held at the end of the term. Two and half hours is the time allowed for completion of the exam.
Alternatively, the student may choose to submit to three tests in the course of the semester. The first one (approximately, 45 minutes) will take place in October; it is a multiple-choice test, designed to check knowledge of the preliminary basic concepts. In November, the student's ability to use a computer for estimation and testing will be tested. The third test is a comprehensive written exam following the end of regular classes. The final grade is the weighted average of the three scores, with weights of 20% to the first and second tests and 60% to the third. A positive grade requires a weighted average of 10 (out of 20) and no partial score below 6.
Upon previous request, English versions of the questions will be made available. In tests and exams, students should provide a valid ID and bring their own writing materials, the course formulary and standard statistical tables. All other materials are excluded.

Calculation formula of final grade

The final grade will be assigned in the 0/20 points scale. A grade lower than 10 is taken to mean a failure. See above for details.

Examinations or Special Assignments

Erasmus students are required to submit to tests and/or exams. No special work or project will substitute for the regular method of assessment.