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2020/2021

Quantitative Methods

Code: 40094 ECTS Credits: 15
Degree Type Year Semester
4313805 Economic Analysis OB 1 1
The proposed teaching and assessment methodology that appear in the guide may be subject to changes as a result of the restrictions to face-to-face class attendance imposed by the health authorities.

Contact

Name:
Maria Teresa Cabeza Gutes
Email:
Maite.Cabeza@uab.cat

Use of Languages

Principal working language:
english (eng)

Teachers

Jordi Caballé Vilella
Katerina Chara Papioti

Prerequisites

There are no specific prerequisits.

Objectives and Contextualisation

 

This   module   provides   students   advanced    quantitative    tools.     These   tools   are   necessary    for    economic    analysis.    

This    module    covers    optimization,   and  probability,    statistics .    The    module    is    organized    in    two

sections.  The    first    section    covers    the    foundations    of    optimization    theory.    The    second    section   provides    students    

with  the    theoretical    foundations    of    probability    and    statistics    necessary    for    econometric    and    financial    analysis.    


    

Competences

  • Capacity to articulate basic economic theory, analytically deriving them from mathematical reasoning
  • Capacity to identify basic statistical analysis and econometric techniques deriving them from the laws of probability and statistics
  • Conceptually analyse a specific economic problem using advanced analytical tools
  • 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 the learning skills that enable them to continue studying in a way that is largely student led or independent

Learning Outcomes

  1. Describe statistical topics on which stochastic economic analysis and empirical analysis is based
  2. Distinguish the element to be included and the necessary assumptions for proposing a decision-making problem with very simple strategic interactions
  3. Framing an economic question of decision within a strategic context in simple math problem and derive its response through mathematical logic
  4. 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
  5. Student should possess the learning skills that enable them to continue studying in a way that is largely student led or independent
  6. Use of mathematics to analyse economic problems

Content

I. Optimization

 

1. Sets and Metric Spaces:

2. Functions and Correspondences:

3. Linear Spaces and Linear Algebra:

4. Smooth functions, Optimization and Comparative Statics:

5. Difference and Differential Equations: 

II. Probability and Statistics

1. Probability

2. Measure Theory

3. Random Variables and Distributions

4. Expectation

5. Special Distributions

6. Functions of Random Variables7. Stochastic Processes and Limiting Distributions

8. Sampling

9. Estimation

10. Hypothesis Testing

 

Methodology

 

•     Theory  classes        

•     Practical  classes        

•     Learning    based    on    problem    solving    

•     Tutorials  

•     Personal  study        

•     Study  groups        

•     Textbook  reading        

•     Article  reading       

 

Activities

Title Hours ECTS Learning Outcomes
Type: Directed      
Problems sets, tutorials 112.5 4.5 1, 2, 3, 5, 4, 6
Theory classes 112.5 4.5 1, 2, 3, 5, 4, 6
Type: Autonomous      
Personal study, study groups, textbook readings, article readings 150 6 1, 2, 3, 5, 4, 6

Assessment

 

 

Final  Exams   

50%  

Class  attendance    and    active    participation    

20%  

Problem  sets    and    assignments    

30%  

A module consists of different courses which are evaluated through final exams, problem sets and assignments and other class activities sucha as class attendance, presentations, etc.

Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Class Attendance and Problem sets and assignments 50% 0 0 1, 2, 3, 5, 4, 6
Final Exams 50% 0 0 1, 2, 3, 5, 4, 6

Bibliography

Axler, S.J., 1997. Linear algebra done right (Vol. 2). New York: Springer.
Carter, M., 2001. Foundations of mathematical economics. MIT Press.
Sydsæter, K., Hammond, P., Seierstad, A. and Strom, A., 2008. Further mathematics for economic analysis. Pearson education
Ash, R.B. (1972), Real Analysis and Probability, Academic Press.
Bierens, H.J. (2004), Introduction to the Mathematical and Statistical Foundations of Econometrics, Cambridge University Press.
Billingsley, P. (1995), Probability and Measure, Wiley.
DeGroot, M.H. and Schervish (2012), M.J., Probability and Statistics, Pearson.
Hogg, R.V., McKean, J. and Craig (2012), A.T., Introduction to Mathematical Statistics, Pearson.
Lindgren, B.V., Statistical Theory (1993), Chapman and Hall/CRC.
Rice, J.A. (2007), Mathematical Statistics and Data Analysis, Cengage Learning.