Quantitative Methods

This course contributes to the acquisition of specific and cross-curricular skills of the Module "Quantitative Methods".

Economist.

- Empirical applications of techniques for econometric modelling of limited dependent variables and panel data.

- Empirical applications of techniques for econometric modelling of time series data.

The skills to be developed in this course contribute to the student acquiring those established in the Module “Quantitative Methods” (skills that are included in the Report of the Bachelor’s Degree in Economics).

Specifically, the following skills are developed:

Basic/General skills

- Learning to apply econometric methods in an empirical context.

- Ability to judge the results of the application of quantitative methods in data analysis.

- Training to discern between alternative methods of analysis.

- Competency in the use of statistical and econometric software.

- A certain degree of development of their capacity to carry out their own empirical research.

- Developing the ability to choose the most suitable econometric techniques between those known for data analysis in a particular case. It covers competence CE.4 of the Bachelor’s Degree in Economics.

- Learning to apply the econometric methods studied in an empirical context, maintaining a critical sense when assessing the uncertainty associated to the results. It covers competence CE.3 of the Bachelor’s Degree in Economics.

- Ability to judge the results of econometric analyses obtained by themselves, and/or to start conducting empirical researches leading to those results. It covers competences CE5, CE.10, CE.12 and CE.17 of the Bachelor’s Degree in Economics.

- Competency to read and communicate effectively in English within a professional environment. It covers competence CE. 14 of the Bachelor’s Degree in Economics.

- Autonomous learning ability. It covers competence C.23 of the Bachelor’s Degree in Economics.

- Adaptability to new situations. It covers competence C.24 of the Bachelor’s Degree in Economics.

- Ability to develop scientific criticism and self-criticism. It covers competence C.25 of the Bachelor’s Degree in Economics

Hamilton, J. (1994). Time Series Analysis. Princeton.

Hsiao, C. (2007). Analysis of Panel Data. Cambridge University Press.

Matilla-García, M., Pérez-Pascual,  P. y B. Sanz-Carnero (2017), Econometría y predicción. McGraw-Hill.

Wooldridge, J.M. (2010). Econometric Analysis of Cross Section and Panel Data Modeling. The MIT Press.

Wooldridge, J.M. (2013), Introducción a la Econometría: Un Enfoque Moderno. 5ª Edición. CENGAGE Learning.

Verbeek, M. (2012). A Guide to Modern Econometrics.  Wiley. UK.

Baltagi, B.H. (2013), Econometric analysis of panel data. Wiley. 5^th edition.

Software EViews (program for the econometric analysis of economic data installed in the computer rooms).

Software Stata (program for the econometric analysis of economic data installed in the computer rooms).

The course requires an average dedication of 150 hours (6 ECTS): 45 hours (30%) correspond to face-to-face dedication or mandatory interaction with the teacher and 105 hours (70%) correspond to autonomous work.

Assessment criteria:

• 40% of the final grade (continuous assessment grade): evaluation of the student work during the course.
• 60% of the final grade: writing an essay/paper and giving a final presentation or alternatively doing a final exam.

To pass the course, a definitive grade equal to or higher than 5 (out of 10) is required, without a minimum of grade in the continuous assessment or in the performance of the essay/paper and its presentation or alternatively in the final exam (but always the sum of both must be equal to or higher than 5).

The assessment criteria will be the same in the ordinary call and the extraordinary call. Since the continuous assessment requires a follow-up throughout the course, you cannot resit this part in the extraordinary call or in the calls corresponding to the early evaluation.

Class attendance is mandatory and, consequently, is not part of the final grade.

The student must have fulfilled 80% of their face-to-face dedication so that their work is considered part of the final grade.

- Questionnaires.

- In-class assessment.

- Essay/paper.

- Presentations.

- Final exam (if necessary).

It is recommended that the student strives to pass the continuous assessment.

The grade obtained in the continuous assessment cannot be resat and will be maintained for all the calls that are made during the corresponding academic year, as well as for the call for early evaluation corresponding to the next academic year or the successive ones.