Econometrics

Code:

1EC303

Acronym:

ECONM

Keywords
Classification	Keyword
OFICIAL	Economics

Instance: 2012/2013 - 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	353	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.

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

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

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	60,00
	Total:	-	0,00

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.