Quantitative Research Methods in Applied Research in Economics and Business
Code: 42620Credits: 15
| Degree programme | Type | Course |
|---|---|---|
| Applied Research in Economics and Business | OB | 0 |
Contact lecturer
- Name :
- Josep Rialp Criado
- Email :
- josep.rialp@uab.cat
Teaching staff
- Josep Rialp Criado
- Karen Davtyan Darchinyan
- Isabel Narbón Perpiña
- David Castells Quintana
- Manuel Flores Mallo
Group languages
You can consult this information at the end of the document.
Prerequisites
There are not prerequisits.
Objectives
To provide the students with the technical and quantitative tools necessary to carry out applied research in economics and business.
Learning outcomes
- Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context
- Student should possess an ability to learn that enables them to continue studying in a manner which is largely self-supervised or independent
- Identify the main scientific methodologies of a quantitative nature that are usable in the field of research applied to business and economics.
- Understand the mathematical, statistical and econometric fundaments and instruments required for statistical inference.
- Apply the main quantitative techniques of multivariate analysis for the testing of scientific hypotheses.
- Utilize existing IT tools and packages (STATA, SPSS, etc.) for the quantitative analysis of statistical, business and bibliographic databases.
- Work in international and inter-disciplinary teams.
- Produce and draft projects, technical reports and academic articles in English, making use of the appropriate terminology, argumentation, communication skills and analytical tools for each context, and rigorously evaluate those produced by third parties.
Contents
This module has 4 units. The contents of these topics are the following:
Mathematics:
1- Fundamental concepts
2- Linear algebra
3- Calculus
4- Optimization
Applied Statistic:
1- Variables and measurement scales
2- Descriptive statistics
3- Inferential statistics
4- Test of hypotheses
5- Contingency tables
6- ANOVA
7- Correlation analysis
Econometrics:
1. Introduction
2. Simple Linear Regression
3. Multiple Linear Regression
4. Statistical Inference for Multiple Linear Regression
5. Specification Issues in Multiple Linear Regression
6. Qualitative Variables and Multiple Linear Regression
Multivariate Analysis
1. Introduction and classification of multivariate analysis techniques
2. Anova and MANOVA
3. Factor analysis
4. Cluster analysis
5. Discriminant Analysis
6. Logistic regression
7. Panel Data
8. Structural Equation Models
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Type: Autonomous | |||
| Study and research activities | 212 | 8.48 | 1, 2, 3, 4, 5, 6, 7, 8 |
| Type: Guided | |||
| Classes | 93.75 | 3.75 | 1, 2, 3, 4, 5, 6, 7, 8 |
| Type: Supervised | |||
| Essays and tutorials | 56.25 | 2.25 | 1, 2, 3, 4, 5, 6, 7, 8 |
Classes, essays and tutorials. Study and research activity.
The proposed teaching methodology may undergo some modifications according to the restrictions imposed by the health authorities on on-campus courses.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Class attendance | 5% | 0 | 0 | 1, 2, 3, 4, 5, 6, 7, 8 |
| Exams | 60% | 8 | 0.32 | 1, 2, 3, 4, 5, 6, 7, 8 |
| Presentation and discussion of essays and problems | 35% | 5 | 0.2 | 1, 2, 3, 4, 5, 6, 7, 8 |
Calendar of evaluation activities
The dates of the evaluation activities of the module (final exams, exercises in the classroom, assignments...) will be announced well in advance during the semester.
\"The dates of evaluation activities cannot be modified, unless there is an exceptional and duly justified reason why an evaluation activity cannot be carried out. In this case, the degree coordinator will contact both the teaching staff and the affected student, and a new date will be scheduled within the same academic period to make up for the missed evaluation activity.\" Section 1 of Article 115. Calendar of evaluation activities (Academic Regulations UAB). Students of the Faculty of Economics and Business, who in accordance with the previous paragraph need to change an evaluation activity (mainly final exam/s) date must process the request by filling out an Application for exams' reschedule: https://eformularis.uab.cat/group/deganat_feie/application-for-exams-reschedule
Grades
The overall grade for the module will be determined as the average of the final grades obtained for the individual units of the module, weighted by their ECTS, under the condition that:
- None of the final grades for the individual units is less than 3.5;
- Not more than one of the final grades for the individual units is less than 5.0.
In case any of these conditions are not fulfilled, the student will be given the option to recover the corresponding units. Also in the case that the conditions are fulfilled but the overall, weighted-average grade for the module is less than 5.0, the student will be given the option to recover the individual unit graded with less than 5.0.
Each unit is evaluated with an applied task (30-40%) an a final exam (70-60%).
The format of the recovery of a unit will be determined by its professors and the maximum grade that can be obtained for each recovered subject is 5.0.
Revision process
After all grading activities of the module have ended, students will be informed of the date and way in which the module grades will be published. Students will be also be informed of the procedure, place, date and time of grade revision following University regulations.
Retake Process
\"To be eligible to participate in the retake process of the module, it is required for students to have been previously evaluated for at least two thirds of the total evaluation activities of the module.\" Section 3 of Article 112 ter. The recovery (UAB Academic Regulations). Additionally, it is required that the student will have achieved an average grade of the module between 3.5 and 4.9.
The date of the retake exam will be duly announced by the coordination of the program. Students who take this exam and pass, will get a grade of 5 for the module. If, after completing the retakes, the student still has a grade below 3.5 in any of the units that make up the module, or has more than one unit with a grade below 5.0 within the same module, the module's weighted average will not be calculated, even if it would otherwise be equal to or greater than 5.0. In such cases, the final grade for the module recorded in the student's academic transcript will be 3.5.
Irregularities in evaluation activities
In spite of other disciplinary measures deemed appropriate, and in accordance with current academic regulations, \"in the case that the student makes any irregularity that could lead to a significant variation in the grade of an evaluation activity, it will be graded with a 0, regardless of the disciplinary process that can be instructed. In case of various irregularities occur in the evaluation of the same module, the final grade of this module will be 0\" Section 10 of Article 116. Results of the evaluation. (UAB Academic Regulations).
Not Assessed Grade
A student can obtain \"Not Assessed\" grade in the module only when he/she has not participated in any of the evaluation activities within it. Therefore, students who perform even only one evaluation component cannot obtain \"Not Assessed\" grade in the module.
The proposed evaluation activities may undergo some changes according to the restrictions imposed by the health authorities on on-campus courses.
Bibliography
- Angrist, Joshua David, Jörn-Steffen Pischke, and Jörn-Steffen Pischke. Mostly harmless econometrics: an empiricist's companion. Princeton: Princeton university press, 2009.
- Cameron, Adrian Colin, and Pravin K. Trivedi. Microeconometrics using Stata. College Station, TX: Stata press, 2009.
- Davison, R. and J. MacKinnon, (2004), Econometric Theory and Methods.Oxford Univ.Press.
- Dougherty, Christopher. Introduction to econometrics. Oxford University Press, 2011.
- Green, W. (2008), Econometric Analysis. Prentice Hall.Sixth edition.
- Hair, J.F.; Black, W.C.; Babin, B.J. and R.E. Anderson(2010), Multivariate Data Analysis. Prentice Hall (7th edition).
- Hayashi, F. (2000), Econometrics.Princeton University Press.
- Hubbard,J H. (1999).Vector Calculus, Linear Algebra and Differential forms (a unified approach),Prentice Hall
- Newbold, P.(2009) \"Statistics for Business and Economics\". Prentice-Hall, 7th Edition.
- Sydsaeter, K., Hammond,P. and A. Strom (2012).Essential Mathematics for Economic Analysis, Pearson.
- Verbeek, Marno. A guide to modern econometrics. John Wiley & Sons, 2008.
- Wooldridge, Jeffrey M. (2013), Introductory Econometrics: A Modern Approach, 5th Edition. Cengage Learning.
Software
- Text editors (Word, Pages, LaTeX, ...).
- Spreadsheets (Excel, Numbers, LaTeX, ...).
- Slide show presentation (PowerPoint, Keynote, LaTeX, ...).
- Statistical/Econometric software and/or for data management (Stata, R).
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TEm) Theory (master) | 1 | English | first semester | morning-mixed |
| (PLABm) Practical laboratories (master) | 1 | English | first semester | morning-mixed |