Guías Docentes Electrónicas
1. General information
Course:
ECONOMETRIC METHODS AND MODELLING
Code:
54323
Type:
CORE COURSE
ECTS credits:
6
Degree:
329 - UNDERGRADUATE DEGREE PROGRAMME IN BUSINESS MANAGEMENT AND ADMINISTRATION (TA)
Academic year:
2022-23
Center:
15 - FACULTY OF SOCIAL SCIENCES OF TALAVERA
Group(s):
60 
Year:
3
Duration:
C2
Main language:
Spanish
Second language:
English
Use of additional languages:
English Friendly:
Y
Web site:
Bilingual:
N
Lecturer: IVAN MARTIN LADERA - Group(s): 60 
Building/Office
Department
Phone number
Email
Office hours
Facultad CC. SS. 2.10
926051584
ivan.my@uclm.es
Tue 12-1PM, 3-4PM & 6-7PM Wed 12-1PM, 3-4PM & 5-6PM

2. Pre-Requisites

Mandatory requirements:

1.- Matrix algebra

2.- Statistical inference

3.- Introduction to Econometrics: Basic econometrics linear regression models

4.- Economic theory

5.- Economic structure and national accounting

6.- English B1, B2 recomended

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

1. Contribution to the curriculum:

Econometric Methods and Models studies has as its central purpose ilustarte students to the theoretical and theoretical basic knowledge of econometric modeling, model's construction from the technical point of view. This includes:

- Ability to diagnose the technical quality of a model and to establish a strategies to improve the model based on its diagnosis.

- Management of the different techniques and methods for model optimization and for a correct use of the constructed econometric model.

- Ability to construct a univariate model of time series, as a type of modeling alternative to the economic ones.

It is intended that the student get a set of skills that allow you to apply the theoretical knowledge acquired in the construction of an econometric model, which will form the course work that will be developed throughout the course, under the supervision of the teacher and with the support of computer equipment and econometric software.

2. Relationship with other subjects:

The subject taught is related to the content of subjects in which numerical information is manipulated. In particular, a good mathematical training is necessary. It is the continuation of the subject Statistical Inference and Introduction to Econometrics. It is also related to other matters such as portfolio management in the area of ¿¿Finance and estimation of models in Macroeconomics, and applications of modeling to different forecasts of strategic variables of the company (sales forecasts, treasury models, budget forecast, market forecasts, etc.)

3. Relationship with the profession:

The general objective will be to train professionals who can analyze, in a critical and rigorous way, the economic and business reality, as well as to make decisions in an environment of uncertainty, which will enable them to choose the best alternative to act. This includes:

- 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.

- Design and construction of prediction models in the short 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 (for example, the impact of advertising campaigns, changes in the product, in the organization, etc.) and measure the effectiveness of the adopted policies.

- Incorporate strategic planning into mathematical-econometric models that allow establishing alternative scenarios for the time horizon and evaluate the different policies.

- 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.

- Data management and external and internal indicators of the company, relevant for decision making.

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

- 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 at the service and as a basis for decision making.


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.
E11 Know the workings and consequences of the different economic systems
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
-Management of specific software for the construction of econometric models and quantitative analysis.
-Advance use and management on Excel, Word and PowerPoint, Numbers, Pages, Keynote, Prezi and/or others for preparing worksheets and reporting.
6. Units / Contents
  • Unit 1: REGRESSION MODEL EXTENSIONS
  • Unit 2: STRUCTURAL CHANGE
  • Unit 3: COLINALITY
  • Unit 4: AUTOCORRELATION
  • Unit 5: HETEROSCEDASTICITY
  • Unit 6: DYNAMIC MODELS I
  • Unit 7: DYNAMIC MODELS II
  • Unit 8: SIMULTANEOUS EQUATIONS MODELS: SPECIFICATION
  • Unit 9: SIMULTANEOUS EQUATIONS MODELS: ESTIMATION
  • Unit 10: USING MULTIPLE REGRESSION MODELS
  • Unit 11: BUSINESS MODELS AND STRATEGIC PLANNING
  • Unit 12: FORECASTING, 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 E11 E13 1.2 30 N N
Computer room practice [ON-SITE] Combination of methods E05 E07 E11 E13 G01 G04 0.8 20 N N
Other off-site activity [OFF-SITE] Combination of methods E05 E07 E11 E13 G01 G04 0.4 10 Y N
Other on-site activities [ON-SITE] Combination of methods E05 E07 E11 E13 G01 G04 0.32 8 Y N
Study and Exam Preparation [OFF-SITE] Self-study E05 E07 E11 E13 G01 G04 3.2 80 N N
Final test [ON-SITE] Assessment tests E05 E07 E11 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
Other methods of assessment 30.00% 0.00% [Continuous Evaluation]
Individual work, participation and positive result of the practical sessions carried out during the classes dedicated to this end, participation and completion of tasks, seminars, tutorials and resolution of the questions raised. Individual or team course work designed for compulsory students. Attention will be paid not only to the content, but also to the correct use of scientific forms, presentation and oral presentation.

[Non Continuous Evaluation]
Individual course work designed for compulsory students. Attention will be paid not only to the content, but also to the correct use of scientific forms, presentation and oral presentation.
Final test 70.00% 0.00% [Continuous Evaluation]
The final test represents 70% of the grade, being necessary to obtain a minimum of 4 points to pass. The presentation in time and form of the course work is an essential requirement to be able to take the final evaluation test.

[Non Continuous Evaluation]
The final test represents 100% of the grade. The presentation in time and form of the course work is an essential requirement to be able to take the final evaluation test.
Final test 0.00% 100.00% Individual mandatory coursework necessary.
Total: 100.00% 100.00%  
According to art. 4 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. 12.2) 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:
    There will be mandatory tasks and a course works all of them evaluable and non-recoverable where the participation and result of the practical sessions, tasks, seminars, tutorials and other activities will be valued. The presentation in term and form of the course work is a mandatory requirement to be able to take the final evaluation test.

    Final exam: To make the average with the rest of the grades in the final exam, it is necessary to obtain a minimum score of 4 points out of 10.
  • Non-continuous evaluation:
    online final test, The final test represents 100% of the grade. The presentation in term and form of the course work is a mandatory requirement.

Specifications for the resit/retake exam:
[Continuous assessment]
All the criteria, grades and percentages of the ordinary call are maintained.
Individual mandatory coursework necessary.



Students who, even having done evaluable activities, wish to be evaluated with the non-continuous evaluation criteria must inform the teacher before the end of the class period, provided that they have not participated during the class period in evaluable activities that together account for at least 50% of the total evaluation of the subject.

If the student has reached this 50% of evaluable activities or if, in any case, the class period has ended, he/she will be considered in continuous evaluation without the possibility of changing the evaluation modality.


[Non-Continuous Evaluation]
All the criteria of the ordinary call are maintained.
Individual mandatory coursework necessary.
Specifications for the second resit / retake exam:
Specific final test. The presentation in time and form of the course work is an essential and mandatory.
9. Assignments, course calendar and important dates
Not related to the syllabus/contents
Hours hours
Other on-site activities [PRESENCIAL][Combination of methods] 8
Final test [PRESENCIAL][Assessment tests] 2

Unit 1 (de 12): REGRESSION MODEL EXTENSIONS
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 3
Computer room practice [PRESENCIAL][Combination of methods] 1
Other off-site activity [AUTÓNOMA][Combination of methods] .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][Combination of methods] 1
Other off-site activity [AUTÓNOMA][Combination of methods] .5
Study and Exam Preparation [AUTÓNOMA][Self-study] 6

Unit 3 (de 12): COLINALITY
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 1
Other off-site activity [AUTÓNOMA][Combination of methods] .5
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Unit 4 (de 12): AUTOCORRELATION
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 1
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 6

Unit 5 (de 12): HETEROSCEDASTICITY
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Unit 6 (de 12): DYNAMIC MODELS I
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 5

Unit 7 (de 12): DYNAMIC MODELS II
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 8

Unit 8 (de 12): SIMULTANEOUS EQUATIONS MODELS: SPECIFICATION
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 4
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 10

Unit 9 (de 12): SIMULTANEOUS EQUATIONS MODELS: ESTIMATION
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 4
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 8

Unit 10 (de 12): USING MULTIPLE REGRESSION MODELS
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 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][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] 1
Study and Exam Preparation [AUTÓNOMA][Self-study] 10

Unit 12 (de 12): FORECASTING, SIMULATION AND STRATEGIC INFORMATION SYSTEMS
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 2
Computer room practice [PRESENCIAL][Combination of methods] 2
Other off-site activity [AUTÓNOMA][Combination of methods] .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
Gujarati, Damodar N. Principios de econometría McGrawHill 84-481-4632-8 2006 Ficha de la biblioteca
Greene, William H.1951- Análisis econométrico Prentice Hall 84-8322-007-5 1999 Ficha de la biblioteca
Gujarati, Damodar N. Econometría McGraw-Hill Interamericana 978-607-15-0294-0 2009 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
Intriligator, Michael D. Modelos econométricos, técnicas y aplicaciones Fondo de Cultura Económica 968-16-3140-4 1990  
Maddala, G. S. Introducción a la econometría Prentice-Hall Hispanoamericana 968-880-697-8 1996 Ficha de la biblioteca
Novales Cinca, Alfonso Econometría McGraw-Hill 84-481-0128-6 1997 Ficha de la biblioteca
Pindyck, Robert S. Econometría: modelos y pronósticos McGraw-Hill 970-10-2925-9 2000 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 978-84-9732-268-3 2008 Ficha de la biblioteca



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