Objectives:

To provide a basic-to-intermediate-level introduction to the theory and practice of Econometrics through the medium of English. The course examines in detail the General Linear Regression Model. The main objective of the course is that students are able to use a regression model to solve a simple economic problem both from a theoretical and from a practical standpoint. More specifically, at the end of the course students will be able to use analytical tools and software in order to quantify and validate relevant relationships that explain some economic phenomenon through the estimation and testing of an econometric model fitted to the available data.

Background:

An elementary knowledge of linear algebra and calculus (Mathematics I, II & III or equivalent) and of basic statistical theory (Elements of Probability and Statistics, and Business Statistics or equivalent) will be useful. Related & follow-up subjects: Applied Econometrics; Econometric Non-linear Models.

Specific competences:

1. To analyse critically the basic elements of Econometrics in order to understand the logic of econometric modelling and be able to specify causal relationships among economic variables.

2. To identify the relevant statistical sources in order to be able to search for, organise and systematically arrange available economic data.

3. To use with confidence appropriate statistical methods and available computing tools in order to correctly estimate and validate econometric models.

4. To handle econometric prediction tools in order to estimate unknown or future values of an economic variable.

5. To interpret adequately the results obtained in order to be able to write meaningful reports about the behaviour of economic data.

6. Make well-informed judgements on relevant socio-economic and environmental issues using available data and appropriate econometric models.

7. Social commitment (critical understanding of global socio-environmental issues).



General competences (see Spanish descriptors).



This subject aims to provide a comprehensive, flexible training adapted to the needs of society in line with the IKD model and the EHU's 2030 agenda. To achieve this goal, the framework of the United Nations Sustainable Development Goals (2015) has been incorporated into quantitative analysis of real economic problems through a research-based learning approach. In this way, the aim is to strengthen the relationship between classroom teaching, the SDG framework and the research and professional orientation that the Econometrics teaching team has been giving to this subject in recent years.

1. Introduction to Econometrics.

Elements of Econometrics. Concept of model: Economic model and econometric model. Example. The error term. Data types. Quantitative and qualitative variables. Dummies: Examples. Stages in the development of a model. Uses the model.



2. General Linear Regression Model (I): Specification.

GLRM Specification: basic assumptions. Functional form. Changes of scale and origin. Dummies: use in GLRM. Interpretation of quantitative variables coefficients. Interpretation of the coefficients of dummies. Interaction between quantitative and dummy variables.



3. General Linear Regression Model (II): Estimation.

Estimator Ordinary Least Squares (OLS): Example. Properties of the sample regression function. Goodness of fit: the coefficient of determination: Example. Estimator of the variance of the disturbances. Finite sample properties of the OLS estimator: Gauss Markov theorem. OLS estimation under restrictions.



4. General Linear Regression Model (III): Inference and prediction.

Distribution of the OLS estimator under normality. Tests of individual significance. Tests with qualitative variables. Interval estimate. General test of linear restrictions. Tests based on the sum of squared residuals. Tests of joint significance. Specification problems. Multicolinearity. Point and interval prediction.

Methodology:

Classroom lectures (one-hour exposition of methodological and/or theoretical lessons in the classroom with the purpose of general instruction about the subject); practice classes (one-hour development of practical materials, exercises and study cases in the classroom); computer laboratory classes (one-hour computer sessions in the computer lab with the purpose of econometric software know-how acquisition); workshops and seminars (one-hour informal discussions of aspects related to the individual assignments and group project); (see calendar for dates).

Tutorials in person and virtual tutorials through subject forum and by email (see GAUR for office hours). The eGela subject page will be used to store, among other things, all the teaching material used throughout the course (contents, timetable, exercises, handouts, data, etc.). Use of virtual discussion fora will be encouraged. See also the teaching support platform at https://egela.ehu.eus/.

An intermediate/advance level of English is required. Note that under current regulations, subjects under the Plan of Multilingualism will be reflected in the academic record; therefore, classroom attendance may be recorded in order to demonstrate the level of technical English appropriate to the subject.

Teaching Material: Projection Slides, Lecture Notes and Handouts.

Written and on-line work: Practical exercises will be provided and discussed in the practice classes. Students are expected to hand in written answers to set problems and on-line assignments. Active participation in the subject fora and construction of an Econometric data-base wiki could also be evaluated.

• Continuous Assessment System
• Final Assessment System
• Tools and qualification percentages:
  • Written test to be taken (%): 70
  • Realization of Practical Work (exercises, cases or problems) (%): 20
  • Exhibition of works, readings ... (%): 10

All specific skills are assessed, followed by an evaluation of the proposed activities.

Achievement grade will be as follows: o active participation in the classroom,

individually or collectively, plus resolution of virtual assignments: 30% of the mark.

written exam (official date): 70% of the mark. A minimum of 4 points out of 10 will be

required in the final written exam.



Students who are assessed by continuous assessment, will receive the grade of "No Show" if not present at the final test. This involves the waiver of the corresponding call.



The student wishing to be exempt from continuous assessment must submit a request in writing to the teacher responsible within the first nine weeks of the course.

Assessment for students excepted of continuous evaluation in the first call and for all students in

any resit of the same academic year will consist of a 100% mark final written test that will assess

the skills listed above as well as the degree of compliance with the targets set in the program.

Class notes, handouts, proposed exercises, homework, etc. See the subject webpage in eGela: https://egela.ehu.eus

Basic bibliography

Basic bibliography

1. AFG: Alonso, Fernández & Gallastegui (2004), Econometría, Prentice-Hall (Pearson); ISBN: 84-205-4460-4.

2. Fernández J. & González P.: Introducción a la Econometría, EHU OpenCourseWare, (hyperlink: ocw.ehu.es, [2009/03][Cas]).

3. Fernández J.: Introductory Econometrics, EHU OpenCourseWare, (hyperlink: ocw.ehu.es, [2009/03][Eng]).

4. Wooldridge, J.M., (2003), Introductory Econometrics, 2nd ed., Thomson.

5. Collection of econometric exercises. (DMetCuan, EHU).

In-depth bibliography

6. Gujarati (2003), Basic Econometrics, 4ª ed., McGraw-Hill.
7. Ramanathan (2002), Introductory Econometrics with Applications, 5ªed, SouthWestern.
8. Dougherty (2007), Introduction to Econometrics, 3ª ed., Oxford University Press.
9. Stock & Watson (2008), Introduction to Econometrics, 2ª ed., Pearson Education.
10. Greene, W.H. (2008). Econometric Analysis. Ed. Prentice Hall, 7.ed.
11. Phillips & Wickens (1978), Exercises in Econometrics, Vols. I & II, Philip Allan Publishers Ltd./Ballinger Publishing Co.

Journals

Some economics and econometrics journals:
English:
− Computational Economics
− Econometrica
− Econometric Reviews
− Econometric Theory
− Empirical Economics Journal
− International Journal of Forecasting
− Journal of Applied Econometrics
− Journal of Business and Economic Statistics
− Journal of Econometrics
− Journal of Economic Dynamics and Control
− Journal of Forecasting
− Oxford Bulletin of Economics and Statistics
− Review of Economics and Statistics
− Review of Economic Studies
− Studies in Nonlinear Dynamics and Econometrics
− SERIEs Journal of the Spanish Economic Association
Español:
− Revista Estadística Española
− Revista de Economía Aplicada
− Revista de Estudios Regionales
− Investigaciones Económicas
− Ekonomiaz
…and many more (browse UPV/EHU -> library -> online journals).

Web addresses

Subject page: https://egela.ehu.eus/course/view.php?id=48815

Software:
http://gretl.sourceforge.net; Gretl: Free and open source econometric software, user manual and data (language versions including English, Spanish, Basque, and many others).
Institutions:
− http://www.eustat.es; Basque Statistical Institute (EUSTAT)
− http://www.ogasun.ejgv.euskadi.net; Basque Government
− http://www.ine.es; Spanish Statistical Institute (INE)
− http://www.meh.es; Spanish Ministry of Economy and Finance
− http://www.bde.es; Bank of Spain
− http://ec.europa.eu/eurostat; European Statistical Institute (EUROSTAT)
− http://www.oecd.org; OECD
− http://www.imf.org; International Monetary Fund
− http://www.worldbank.org; World Bank
− http://www.bolsamadrid.es; Madrid Stock Market
− http://www.ecb.int; European Central Bank
Other data sources:
− Ikerbide
− Udalmap
− http://www.nber.org/data_index.html
− http://www.estadief.minhac.es/
− http://fisher.osu.edu/fin/osudown.htm
− http://econ.queensu.ca/jae/
− http://www.psidonline.isr.umich.edu/data/
− http://www.census.gov/