Public University of Navarre



Academic year: 2015/2016 | Previous academic years:  2014/2015  |  2013/2014  |  2012/2013  |  2011/2012 
International Double Bachelor's degree in Economics, Management and Business Administration at the Universidad Pública de Navarra
Course code: 176403 Subject title: ECONOMETRICS I
Credits: 6 Type of subject: Mandatory Year: 2 Period: 2º S
Department: Economics
Lecturers:
HUALDE BILBAO, JAVIER   [Mentoring ]

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Module/Subject matter

Quantitative Methods: Econometrics.

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Contents

First, we will introduce the idea of econometric model. This model must take into account the special features of economic data. We will focus on the ideas of causality and ceteris paribus analysis, arising from the correct interpretation of these models. From a formal viewpoint, the initial step towards an appropriate conceptual framework will be to introduce the simple regression model. Here, we will study the basic assumptions, interpretation of parameters of interest, ordinary least squares estimation and statistical properties of the estimators.

The second building block of the course is the study of the general regression model. We will analyze its basic properties, focusing on the motivation behind multivariate regression, stressing its usefulness over the bivariate framework which characterizes the simple regression model. Again, we will study in this more general framework the basic assumptions, interpretation of parameters of interest, ordinary least squares estimation and statistical properties of the estimators.

In the last part of the course, we will study different aspects related to the general regression model. First, we will analyze the consequences of the violation of basic assumptions (functional form and specification, heteroskedasticity, autocorrelation). Next, we will introduce the issue of endogeneity, its relation with the instrumental variables estimator (emphasizing the search for appropriate instruments in economics) and a brief discussion of this problem in the context of systems of equations. The course will end up with a brief introduction on qualitative information variables, focusing on dummy variables and on the linear probability model.

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Descriptors

Economic data. Causality. Simple regression model. General regression model. Violation of assumptions. Endogeneity and instrumental variables. Qualitative information variables.

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General proficiencies

CG04. Oral and written communication in a foreign language.
CG05. Developing software knowledge applied to the corresponding subject.
CG06. Ability to analyze and extract information from different sources.
CG07. Capacity to solve problems.
CG09. Capacity to work in teams.
CG16. Capacity to work under pressure.
CG17. Capacity to self-learning.

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Specific proficiencies

CE02. Identify relevant economic information sources.
CE03. Derive from micro and macroeconomic data relevant information impossible to assess by non-specialists.
CE04. Use of professional criteria in the economic analysis, mainly those criteria based on technical tools.

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Learning outcomes

R20. Simple regression and explanatory variables models, econometric models.

 

At the end of the course, the student must be able to translate into mathematical language specific issues from macroeconomics and microeconomics by means of econometric models. Additionally, the student must be able to use the econometric software Gretl and extract conclusions from the estimated models. 

 

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Methodology

Lectures
Presentation of the main theoretical aspects of the course. Student participation: questions made by the lecturer, brief presentations of previous lectures.
Classes
Classes in computer room. Small groups. Presentation and revision of exercises made individually and in small groups. Use of econometric packages (GRETL).
Individual and team work
Preparation of exercises and presentations.
Periodic tutorials with lecturer
Individual and group meetings.
Personal study and exam

 

Activity Hours
On-site 60
Lectures 30
Classes 30
Self-preparation 90
Self-study 38
Individual preparation of exercises and presentations 26
Team preparation of exercises and presentations -
Exam preparation 20
Tutorials 6
Others -

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Languages

English.

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Evaluation

Aspect Criteria Instrument Weight  

Theoretical partial exams

Proficiencies: CG04, CG07, CG16,CG17, CE02, CE03, CE04

Understanding of the theoretical content of the course. Adequate responses. Capacity for analysis and synthesis

Theoretical Tests

20% Recoverable

Participation

Proficiencies: CG04, CG05, CG06, CG07, CG16, CE02, CE03, CE04

Capacity for analysis and synthesis

Participation and exposition in lectures

 10%  Non-recoverable

Computer classes

Proficiencies: CG04, CG07, CG16, CG17, CE02, CE03, CE04

Empirical application. Capacity for analysis and synthesis

 Tests in computer classroom

 20%  Non-recoverable

Course contents

Proficiency: CG04, CG07, CG16,CG17, CE02, CE03, CE04

Understanding of the theoretical content of the course. Adequate responses Final exam  50%  Recoverable

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Agenda

Chapter 1. Introduction: the nature of econometrics and economic data
What is econometrics?
Methodology in econometric analysis
The structure of economic data
Causality and the notion of ceteris paribus in econometric analysis

Chapter 2. The simple regression model
Definition of the simple regression model
Ordinary least squares estimator
Algebraic properties of the ordinary least squares estimator
Units of measurement and functional form
Statistical properties of the ordinary least squares estimator

Chapter 3. The general regression model
Motivation
Algebraic properties of the ordinary least squares estimator
Statistical properties of the ordinary least squares estimator
Gauss-Markov theorem
Hypotheses testing
Asymptotic properties
Prediction
Model selection

Chapter 4. Violation of assumptions
Specification errors
Multicollinearity
Heteroskedasticity
Autocorrelation

Chapter 5. Endogeneity and instrumental variables
Motivation
Instrumental variables estimator
Simultaneous equation models

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Bibliography

Access the bibliography that your professor has requested from the Library.


The main references for the course are:
Wooldridge, J.M. “Introductory econometrics: a modern approach”. South-Western College Pub; 4 edition (2008).

Stock, J.H. and Watson, M.W. “Introduction to econometrics”. Prentice Hall (2010)



Alternative useful textbooks are:
Goldberger, A.S. “Introductory econometrics ”. Harvard University Press (1998).
Gujarati, D.N. “Basic econometrics”. Mc. Graw Hill (2004)

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Location

Classroom and Computer room at the Aulario.

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