Guías Docentes Electrónicas
1. General information
Course:
ECONOMETRIC METHODS AND MODELLING
Code:
54323
Type:
CORE COURSE
ECTS credits:
6
Degree:
320 - UNDERGRADUATE DEGREE IN BUSINESS MANAGEMENT AND ADMINISTRATION (CR)
Academic year:
2021-22
Center:
403 - FACULTY OF LAW AND SOCIAL SCIENCES OF C. REAL
Group(s):
20  21  29 
Year:
3
Duration:
C2
Main language:
Spanish
Second language:
Use of additional languages:
English Friendly:
Y
Web site:
Bilingual:
N
Lecturer: FERNANDO EVARISTO CALLEJAS ALBIÑANA - Group(s): 20  21  29 
Building/Office
Department
Phone number
Email
Office hours
Facultad Derecho y CCSS de Ciudad Real /1.05 Módulo E
ECO .ESP. E INT.,ECONOMET. E Hª E INS.EC
3573
fernando.callejas@uclm.es

Lecturer: ISABEL MARTINEZ RODRIGUEZ - Group(s): 20  21  29 
Building/Office
Department
Phone number
Email
Office hours
Facultad de Derecho y Ciencias Sociales. Ciudad Real. Despacho 1.11
ECO .ESP. E INT.,ECONOMET. E Hª E INS.EC
6662
isabel.mrodriguez@uclm.es

2. Pre-Requisites

Necessary requirements:

1.- Matrix algebra

2.- Statistical inference

3.- Introduction to econometrics: Basic model of simple linear regression.

4.- Economic theory.

5.- Economic structure and national accounting

3. Justification in the curriculum, relation to other subjects and to the profession

- Introduce the student in the theoretical basic knowledge of the Econometric Methods.

- Management of basic techniques and tools for the quantification of relationships between relevant variables in the business world.

- Ability to recognize a problem, analyze it and solve it using the scientific method of modeling.

- Management of data and external and internal indicators of the company relevant for decision making.

- Apply the acquired theoretical knowledge to the realization of a paper in which the student will be able to elaborate an econometric model under the direct supervision of the professor and with the support of the computer equipment.

- Acquire the capacity for debate and informed discussion about the issues and problems that affect the business decision-making process from a quantitative perspective.

- Train the business economist to deal with situations of prediction and simulation of company policies and as a basis for making decisions.

- Design and construction of prediction models in the short-term and medium-term, of the strategic variables of the company: sales, costs, human resources, prices, business investments, etc.

- Quantify the effects of business policy changes on business results (eg: impact of advertising campaigns, changes in the product, in the organization, etc.) and measure the effectiveness of the implemented policies.

- Implement the relations and relevant variables of strategic planning in mathematical-econometric models that allow establishing alternative scenarios for the time horizon and evaluate the different policies.
 


4. Degree competences achieved in this course
Course competences
Code Description
E05 Develop the ability to analyze any information on the situation and possible development of a company and transform it into a business opportunity.
E07 Understand the economic environment as a result and application of theoretical or formal representations on how the economy works. To do so, it will be necessary to be able to understand and use common handbooks, as well as articles and, in general, leading edge bibliography in the core subjects of the curriculum.
E13 Ability to make logical representative models of the business reality
G01 Possession of the skills needed for continuous, self-led, independent learning, which will allow students to develop the learning abilities needed to undertake further study with a high degree of independence.
G04 Ability to use and develop information and communication technologies and to apply them to the corresponding business department by using specific programmes for these business areas.
5. Objectives or Learning Outcomes
Course learning outcomes
Description
Work out problems in creative and innovative ways.
Know the tools and methods for the quantitative analysis of the company and its environment, including models for business decision making as well as economic forecast models.
Additional outcomes
Description
6. Units / Contents
  • Unit 1: Expand of the basic regression model
  • Unit 2: Structural change
  • Unit 3: Collinearity
  • Unit 4: Models with autocorrelation
  • Unit 5: Heteroscedasticity models
  • Unit 6: Dynamic models (I): Distribution of delays
  • Unit 7: Dynamic models (II): Time series models
  • Unit 8: Multiple-equation models: specification
  • Unit 9: Multiple-equation models: estimating
  • Unit 10: Use of multiple-equation models: prediction and simulation
  • Unit 11: Business models and strategic planning
  • Unit 12: Prediction, simulation and strategic information systems
7. Activities, Units/Modules and Methodology
Training Activity Methodology Related Competences ECTS Hours As Com Description
Class Attendance (theory) [ON-SITE] Lectures E05 E07 1.2 30 N N
Computer room practice [ON-SITE] Projects based learning E13 G04 0.8 20 N N
Writing of reports or projects [OFF-SITE] Cooperative / Collaborative Learning E05 E07 G04 0.4 10 Y Y
In-class Debates and forums [ON-SITE] Group Work E05 E07 0.32 8 Y N
Study and Exam Preparation [OFF-SITE] Self-study G01 3.2 80 N N
Final test [ON-SITE] E05 E07 E13 G01 G04 0.08 2 Y Y
Total: 6 150
Total credits of in-class work: 2.4 Total class time hours: 60
Total credits of out of class work: 3.6 Total hours of out of class work: 90

As: Assessable training activity
Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).

8. Evaluation criteria and Grading System
Evaluation System Continuous assessment Non-continuous evaluation * Description
Final test 70.00% 100.00% The preparation of the work is mandatory, whether in face-to-face or not, so the final test, for all, will be 70%.
It is necessary to obtain a 4 in the exam to be able to pass the subject
Oral presentations assessment 10.00% 0.00% .
Other methods of assessment 20.00% 0.00% .
Total: 100.00% 100.00%  
According to art. 6 of the UCLM Student Evaluation Regulations, it must be provided to students who cannot regularly attend face-to-face training activities the passing of the subject, having the right (art. 13.2) to be globally graded, in 2 annual calls per subject , an ordinary and an extraordinary one (evaluating 100% of the competences).

Evaluation criteria for the final exam:
  • Continuous assessment:
    Evaluation criteria not defined
  • Non-continuous evaluation:
    Evaluation criteria not defined

Specifications for the resit/retake exam:
Evaluation criteria not defined
Specifications for the second resit / retake exam:
Evaluation criteria not defined
9. Assignments, course calendar and important dates
Not related to the syllabus/contents
Hours hours
In-class Debates and forums [PRESENCIAL][Group Work] 8
Final test [PRESENCIAL][] 2

Unit 1 (de 12): Expand of the basic regression model
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 3
Computer room practice [PRESENCIAL][Projects based learning] 1
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] .5
Study and Exam Preparation [AUTÓNOMA][Self-study] 4

Unit 2 (de 12): Structural change
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 3
Computer room practice [PRESENCIAL][Projects based learning] 1
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] .5
Study and Exam Preparation [AUTÓNOMA][Self-study] 6

Unit 3 (de 12): Collinearity
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 1
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] .5
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Unit 4 (de 12): Models with autocorrelation
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 1
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 6

Unit 5 (de 12): Heteroscedasticity models
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Unit 6 (de 12): Dynamic models (I): Distribution of delays
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Unit 7 (de 12): Dynamic models (II): Time series models
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 8

Unit 8 (de 12): Multiple-equation models: specification
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 4
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 10

Unit 9 (de 12): Multiple-equation models: estimating
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 4
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 8

Unit 10 (de 12): Use of multiple-equation models: prediction and simulation
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 8

Unit 11 (de 12): Business models and strategic planning
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 10

Unit 12 (de 12): Prediction, simulation and strategic information systems
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Projects based learning] 2
Writing of reports or projects [AUTÓNOMA][Cooperative / Collaborative Learning] .5
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Global activity
Activities hours
10. Bibliography and Sources
Author(s) Title Book/Journal Citv Publishing house ISBN Year Description Link Catálogo biblioteca
 
Callejas Albiñana, F.E. Diapositivas y presentaciones Archivos Moodle Ciudad Real 2014 Documentación a disposición de los estudiantes en Moodle  
Greene, Willian H (1951) Análisis econométrico Madrid Prentice Hall 84-8322-007-5 1999  
Gujarati, Damodar N. Econometría Mexico McGraw-Hill 970-10-3971-8 2003 Ficha de la biblioteca
Intriligator, Michael D. Modelos econométricos, técnicas y aplicaciones Fondo de Cultura Económica 968-16-3140-4 1990 Ficha de la biblioteca
Pulido SanRomán, A. y PérezGarcía, J. Modelos econométricos Madrid Piramide 84-368-1534-3 2001 Ficha de la biblioteca
Wooldridge, Jeffrey M. Introducción a la econometría: un enfoque moderno Thomson 84-9732-268-1 2006 Ficha de la biblioteca



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