ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Student's work ECTS: 99 Hours of tutorials: 3 Expository Class: 24 Interactive Classroom: 24 Total: 150
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Quantitative Economy
Areas: Quantitative Economics (USC-specific)
Center Faculty of Economics and Business Studies
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable
ECONOMETRICS I IS DESIGNED TO GIVE THE NECESSARY KNOWLEDGE SO THAT THE STUDENTS:
- Are able to understand the role of Econometrics in the context of the Economic Science.
-Are able to understand the concepts and the basic econometric tools necessary for the quantitative and empirical
analysis of the economy from an econometric perspective.
-Apply the basic econometric tools to solve concrete economic problems.
-Have the necessary foundation and understanding for further study of Econometrics (Econometrics II)
UNIT 1. INTRODUCTION: ECONOMETRICS AND ECONOMETRIC MODELS
1.1. Econometrics: concept and evolution
1.2. Econometric models: elements and classification
1.3. Process of econometric research
1.4. The role of Econometrics.
UNIT 2. THE CLASSICAL LINEAR REGRESSION MODEL
2.1. The model specification
2.2. Estimation by Ordinary Least Squares (OLS)
2.3. Properties of the OLS estimators
2.4. Analysis of the precision and goodness of fit.
2.5. Units of measure and functional form
UNIT 3. ANALYSIS OF THE SIGNIFICANCE OF THE REGRESSORS
3.1. Introduction
3.2. Confidence intervals
3.3. Hypothesis-testing for the parameters
3.4. Maximum-likelihood estimation
UNIT 4. DUMMY VARIABLES AND STABILITY TESTS
4.1. Dummy variables
4.2. Stability tests
UNIT 5. MULTICOLLINEARITY AND REGRESSORS SELECTION
5.1. Causes and consequences of multicollinearity
5.2. Methods to test multicollinearity
5.3. Solutions to multicollinearity
5.4. Selection of regressors
UNIT 6. PREDICTION IN CLASSICAL MODELS
6.1. Introduction
6.2. Prediction by points and intervals
6.3 Measurements for the predictive capacity
6.4 Post-sample stability
UNIT 7. ECONOMETRIC SOFTWARE PACKAGES AND APPLICATIONS (HOW CAN YOU PERFORM AN EMPIRICAL WORK?)
BASIC BIBLIOGRAPHY:
GUISÁN. M.C. (1997): Econometría. Ed. McGraw-Hill.
GUJARATI, D. N.; PORTER, D. C. (2010): Econometría. Ed. McGraw-Hill. Quinta Ed.
HILL, R. C.; GRIFFITHS, W. E.; LIM, G. C.(2011): Principles of Econometrics. Ed. Wiley.
PULIDO, A.; PÉREZ, J (2001): Modelos econométricos. Ed. Pirámide.
STOCK, J. H.; WATSON, M. M. (2012): Introducción a la Econometría. Ed. Pearson. 3ª ed.
WOOLDRIDGE, J. M. (2006): Introducción a la econometría. Un enfoque moderno. Thomson.
COMPLEMENTARY BIBLIOGRAFHY:
ALEGRE,J. et al. (1995): Ejercicios y problemas de Econometría. Editorial AC
ALONSO, A.;FERNÁNDEZ, J; GALLASTEGUI, I. (2005): Econometría. Prentice Hall
AZNAR, A.; GARCÍA, A.; MARTÍN, A. (1994): Ejercicios de Econometría IyII. Ed. Pirámide.
GREENE, W. H. (1998): Análisis econométrico. Prentice Hall.
JOHNSTON, J. (1989): Métodos de Econometría. Ed.Vicens-Vives.
KENNEDY, P. (1997): A Guide to Econometrics. 3ª ed. MIT Press. Cambridge.
MADDALA, G.S. (1985): Econometría. Ed. McGraw-Hill.,
MARTÍN, G.; LABEAGA, J. M.; MOCHÓN, F.(1997):Introducción a la Econometría. Ed. Prentice Hall Iberia.
PENA TRAPERO, B. Y OTROS (1999): Cien ejercicios de Econometría. Ed. Pirámide..
PÉREZ, C (2006): Problemas resueltos de Econometría. Thomson.
PULIDO, A. (1989): Predicción económica y empresarial. Ed. Pirámide.
THIS COURSE CONTRIBUTES TO THE FOLLOWING SKILLS OF THE ECONOMICS DEGREE:
-Instrumental knowledge, especially regarding the creation of econometric models.
-Contribute to the good management of the allocation of resources in both the private and public sector.
- Identify and anticipate relevant economic problems in relation to the allocation of general resources, both in the private and public sector.
- Provide rationality to the analysis and description of any aspect of economic reality.
- Evaluate consequences of different action alternatives and select the best given objectives.
-Ability to derive from the data relevant information which is not easy to identify by non professionals.
- Apply to the analysis of the problems professional criteria based on the management of technical instruments.
-Contribution to the knowledge of the national and international economic reality, productive
sectors, public sector and economic institutions.
SPECIFIC SKILLS OF THE COURSE:
-Understanding of the concepts and basic econometric tools necessary for the quantitative and empirical
analysis of the economy from an econometric perspective.
- Understanding of the concepts and basic econometric tools that prepare the student for a further and deeper study of Econometrics.
-Understanding of the role of Econometrics in the context of the Economic Science and its analysis.
Since this is an introductory course to the Econometrics field, special attention is paid to class activities and the continuous work of the student.
The big-group sessions are devoted to the introduction and explanation of the basic aspects of each chapter of the program, providing the necessary additional information for a suitable development of the process of autonomous learning.
The small-group sessions take place in the computers class. The aim of these practical classes with computer is that the student attains a better understanding of the basic contents, while getting familiar with the new computer tools and with the solution of concrete economic problems.
These theoretical and practical activities may be combined (if it is stated so in the Course guide) with concrete activities for the students to do on their own. These activities aim to train the students in doing and presenting studies on the current economic reality.
CLARIFICATIONS:
In the case of not being able to have a face-to-face teaching (Scenario 1), the teaching will be carried out as follows:
Scenario 2: It will be a combination of face-to-face and virtual teaching according to the guidelines established by the Deanery and the Rectorate for this scenario and the health measures established at that time. For virtual teaching, the Virtual Campus of the USC and the Teams platform will be used. The tutorials will be mainly by telematic means.
Scenario 3: Virtual teaching. For virtual teaching, the Virtual Campus of the USC and the Teams platform will be used. The tutorials will be online.
The students can choose to start the course between the continuous evaluation system or the single evaluation system (final exam, which will be valued at 100% of the grade). The continuous evaluation system consists of the following:
-The student will get part of the grade ( 30% or 3 points out of 10) from the work done during the course: class participation, tests, activities done… The evaluation of these activities will be specified as follows:
• Final course work 15% of the continuous evaluation (1.5 points out of 10).
• Participation in the interactive classes and results of the different tests 10% of the evaluation (1 point out of 10).
• Participation in the expository classes and results of the different tests 5% of the continuous evaluation (0.5 points out of 10).
- The final exam accounts for the remaining 70%.
The students that have granted the exemption of attendance to classes according to the current regulations may choose to take the final exam, which will be valued with 100% of the grade.
CLARIFICATIONS:
In the case of not being able to have face-to-face classes (Scenario 1) and have to opt for Scenario 2 (combination of face-to-face and virtual teaching) or Scenario 3 (virtual teaching), the classes and the relationship with the students will be telematic using the Virtual Campus from the USC and the Teams platform. Consequently, the continuous evaluation of the students in terms of participation in classes and final work will also be carried out electronically using the indicated platforms.
The final test will be face-to-face in scenario 1, it will be face-to-face or telematic according to the guidelines established by the Dean's Office or the Rectorate and the health measures established at that time in scenario 2, and in scenario 3 it will be telematic.
In the case of plagiarism and / or misuse of technologies in the performance of tasks or tests, the following is reported: “For cases of fraudulent performance of exercises or tests, will be of application the collected in the Normativa de avaliación do rendemento académico dos estudantes e de revisión de cualificacións”.
Since the study load of each credit for the student is estimated in 25 hours, the estimated total study load and personal work necessary to pass this course is 150 hours, which are divided among class and non-class work.
The class work consists of:
-Big-group classes.
-Computer classes in small groups.
-Tutorships in very small groups or for individual students.
-Other sessions with the professor: exams and exam viewing.
Non-class work consists of:
-Autonomous study, in groups or individually.
-Writing of exercises, conclusions or other activities.
-Programming/experimenting or other activities with computer/lab
-Recommended readings, activities in the library or such.
The student should have the basic knowledge of the courses Mathematics, Statistics and Economic Theory from the previous years of this degree.
CONTINGENCY PLAN:
A) Teaching methodology
CLARIFICATIONS:
In the case of not being able to have a face-to-face teaching (Scenario 1), the teaching will be carried out as follows:
Scenario 2: It will be a combination of face-to-face and virtual teaching according to the guidelines established by the Deanery and the Rectorate for this scenario and the health measures established at that time. For virtual teaching, the Virtual Campus of the USC and the Teams platform will be used. The tutorials will be mainly by telematic means.
Scenario 3: Virtual teaching. For virtual teaching, the Virtual Campus of the USC and the Teams platform will be used. The tutorials will be online.
B) Assissment system
CLARIFICATIONS:
In the case of not being able to have face-to-face classes (Scenario 1) and have to opt for Scenario 2 (combination of face-to-face and virtual teaching) or Scenario 3 (virtual teaching), the classes and the relationship with the students will be telematic using the Virtual Campus from the USC and the Teams platform. Consequently, the continuous evaluation of the students in terms of participation in classes and final work will also be carried out electronically using the indicated platforms.
The final test will be face-to-face in scenario 1, it will be face-to-face or telematic according to the guidelines established by the Dean's Office or the Rectorate and the health measures established at that time in scenario 2, and in scenario 3 it will be telematic.
In the case of plagiarism and / or misuse of technologies in the performance of tasks or tests, the following is reported: “For cases of fraudulent performance of exercises or tests, will be of application the collected in the Normativa de avaliación do rendemento académico dos estudantes e de revisión de cualificacións”.
Xose Anton Rodriguez Gonzalez
Coordinador/a- Department
- Quantitative Economy
- Area
- Quantitative Economics (USC-specific)
- Phone
- 881811529
- xoseanton.rodriguez [at] usc.es
- Category
- Professor: University Lecturer
Mª Del Carmen Lopez Andion
- Department
- Quantitative Economy
- Area
- Quantitative Economics (USC-specific)
- Phone
- 881811641
- carmen.lopez.andion [at] usc.es
- Category
- Professor: University Lecturer
| Monday | |||
|---|---|---|---|
| 11:45-12:45 | Grupo /CLE_01 | Galician | Classroom 24 |
| 17:45-18:45 | Grupo /CLE_02 | Galician | Classroom 22 |
| Tuesday | |||
| 11:45-14:15 | Grupo /CLIL_01 | Galician | Computer room 1 |
| 17:45-20:15 | Grupo /CLIL_03 | Galician | Computer room 1 |
| Wednesday | |||
| 09:30-12:00 | Grupo /CLIL_02a | Galician | Computer room 1 |
| 17:45-20:15 | Grupo /CLIL_04a | Galician | Computer room 1 |
| Thursday | |||
| 11:45-14:15 | Grupo /CLIL_02b | Galician | Computer room 1 |
| Friday | |||
| 16:00-18:30 | Grupo /CLIL_04b | Galician, Spanish | Computer room 1 |
| 01.20.2021 16:00-19:00 | Grupo /CLE_02 | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_01 | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_02a | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_02b | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_03 | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_04a | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_04b | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLE_01 | Classroom A |
| 01.20.2021 16:00-19:00 | Grupo /CLE_01 | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLE_02 | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_01 | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_02a | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_02b | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_03 | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_04a | Classroom B |
| 01.20.2021 16:00-19:00 | Grupo /CLIL_04b | Classroom B |
| 06.30.2021 09:30-12:30 | Grupo /CLIL_04a | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLIL_04b | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLE_01 | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLE_02 | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLIL_01 | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLIL_02a | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLIL_02b | Classroom A |
| 06.30.2021 09:30-12:30 | Grupo /CLIL_03 | Classroom A |