Logo UAB

Fundamentals of Economics and Business II

Code: 42141 ECTS Credits: 15
2024/2025
Degree Type Year
4310025 Economics and Business Administration OB 0

Contact

Name:
Francisco Javier Vila Carnicero
Email:
xavier.vila@uab.cat

Teachers

Alejandra Paz Rivera Vicencio
Pau Milán Solé
Miguel Angel López García

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

None


Objectives and Contextualisation

Macroeconomics

This course aims to familiarize students with key analytical concepts and key analytical tools in macroeconomic analysis and related policies.

Upon completion, students must be able (i) to understand fundamental theoretical issues underlying the relationship of some critical macroeconomic variables such as GDP, inflation, unemployment, etc; (ii) to interpret the reasons for, and the effects of, demand and supply-side policies; (iii) to understand the long-run effects of fiscal policy and the determinants of economic growth.

 

 

Public Finance

Public Finance, or equivalently Public Economics, focuses on the study of the effects of government actions on economic activity. It aims at predicting the effects of these actions and at providing guidance on the choice among different alternatives. By restricting attention on a relatively small number of topics, the objective of the course is to illustrate how economic analysis emerges as an extremely helpful instrument in the design and evaluation of public policy.

 

Statistics for Data Analysis

The course main objective is to provide a solid foundation of statistics for the analysis of economic data. Even if the focus of the course is on applied statistics, some mathematical details will be included to help to properly understand the tools presented.

 

Econometrics

The course covers basic tools of econometric analysis for the measurement and testing of economic relationships using regression analysis. Even if the focus of the course is on the application of thesemethods, mathematical details will be included to help to properly evaluate the advantages and limitations of the tools presented.

 


Competences

  • Argue the case for and write a precise, clear and concise report of the problems presented in the English language.
  • Be able to handle the main statistical techniques for evaluating the properties of each method of analysis and relate the different characteristic measures of the data or diagnostics to the appropriateness of a model
  • Carry out empirical studies.
  • Choose the appropriate empirical methodology for the object of study: Contrasting economic hypothesis, policy evaluation, forecasting, etc.
  • Contextualise economic problems through the use of formal models that enable quantitative analysis.
  • Contrast different hypotheses regarding the response of economic agents in the context of the problem under study.
  • Develop the ability to assess sex and gender inequalities in order to design solutions.
  • Familiarise students with basic techniques for conjecture analysis and the necessary predictions for an appropriate interpretation of the cyclical and trend evolution of aggregate variables in the economic market.
  • Identify the limitations associated with the available data and the consequences on empirical analysis.
  • Infer, for each case, the consequences of economic policies or business strategies associated with the object of study.
  • Isolate and analyse the main characteristics of the evolution of economic data.
  • Operate using statistical sources that are relevant to the object of study (company data, individual and family surveys, etc.)
  • Understand academic research in the areas indicated.
  • Use different statistical programs to process data.

Learning Outcomes

  1. Argue the case for and write a precise, clear and concise report of the problems presented in the English language.
  2. Be able to handle the main statistical techniques for evaluating the properties of each method of analysis and relate the different characteristic measures of the data or diagnostics to the appropriateness of a model
  3. Carry out empirical studies.
  4. Choose the appropriate empirical methodology for the object of study: Contrasting economic hypothesis, policy evaluation, forecasting, etc.
  5. Contextualise economic problems through the use of formal models that enable quantitative analysis.
  6. Contrast different hypotheses regarding the response of economic agents in the context of the problem under study.
  7. Familiarise students with basic techniques for conjecture analysis and the necessary predictions for an appropriate interpretation of the cyclical and trend evolution of aggregate variables in the economic market.
  8. Identify the limitations associated with the available data and the consequences on empirical analysis.
  9. Infer, for each case, the consequences of economic policies or business strategies associated with the object of study.
  10. Isolate and analyse the main characteristics of the evolution of economic data.
  11. Know how to carry out a gender-sensitive analysis of taxation.
  12. Know how to identify the different needs and life experiences of women and men as users of public services, consumers, etc.
  13. Know how to identify the differentiated impact of budgets on men and women.
  14. Operate using statistical sources that are relevant to the object of study (company data, individual and family surveys, etc.)
  15. Perform macroeconomic policy analysis including household activities and work (domestic and care work).
  16. Recognise and understand the role of macroeconomic policies and social policies in the production and reproduction of gender inequalities.
  17. Understand academic research in the areas indicated.
  18. Use different statistical programs to process data.

Content

Macroeconomics

1. Introduction: Macroeconomics variables

2. Capital Accumulation and economic growth

3. Short-Run Analysis of Fiscal and Monetary Policy in a Small Open Economy

4. Deficits, Debt, and Fiscal Policy

5. Labour market

6. Other topics on macroeconomics

 

Public Finance

1. A framework for normative analysis

2. Commodity taxation

3. Income taxation

4. Tax evasion

5. Intertemporal efficiency

6. Social security 

 

Statistics for Data Analysis

1. Introduction

2. Key concepts for univariate data analysis

3. Key concepts for multivariate data analysis

4. Inferential statistics: estimation

5. Inferential statistics: Hypothesis testing

 

 

Econometrics

1. Introduction to econometric analysis

2. Regression models: estimation

3. Regression models: inference

4. Topics in the analysis of cross sectional data

5. Topics in the analysis of time series data

 


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Lectures with ITC support 75 3 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
Resolution of exercises 37.5 1.5 2, 6, 7, 9
Type: Supervised      
Tutoring and monitoring work in progress 93.8 3.75 2, 6, 7, 9, 11, 12, 13, 15, 16, 17
Type: Autonomous      
Study, Reading, Exercise solving, Essays writing 129.7 5.19 2, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17

The activities that will allow the students to learn the basic concepts included in this course are:

 

1. Theory lectures where the instructor will explain the main concepts.

The goal of this activity is to introduce the basic notions and guide the student learning.

2. Problem Sets

In some subjects, a problem set which students will have to solve individually or in teams will be included in every unit. The goal of this activity is twofold. On one hand students will work with the theoretical concepts explained in the classroom, and on the other hand through this practice they will develop the necessary skills for problem solving.

3. Practice lectures

The aim of this activity is to comment on and solve any possible doubt that students mayhave had solving the problem assignment. This way they will be able to understand and correct any errors they may have had during this process.

4. Essay writing

In some subjects students will produce written essays on the topics proposed.

 5. Tutoring hours

Students will have some tutor hours in which the subject instructors will help them solve any doubts they may have.

 

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Exercises and Essays 35% 30 1.2 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18
Topic Exam: Econometrics 8.125% 2.25 0.09 2, 4
Topic Exam: Public Finance 16.25% 2.25 0.09 6, 9
Topic Exam: Statistics for Data Analysis 8.125% 2.25 0.09 7, 14
Topic exam: Macroeconomics 16.25% 2.25 0.09 8, 10

A. CONTINUOUS ASSESMENT

  1. Except for the Master Thesis, each module consists of a number of different subjects or parts taught by different professors. The final mark for each module will consist of the weighted average of the marks of each subject within the module.
  • A module is considered successfully passed if:

    • the mark for each subject within the module is higher than or equal to 3.0 (in a 0 to 10 scale), and

    • the final mark for that module is higher than or equal to 5.0 (in a 0 to 10 scale).

 IMPORTANT:  Class attendance is compulsory. In order to pass each subject, students must attend all lectures. Special cases, with appropriate justification, will be considered individually by the professors together with MEBA  coordinators

If a module is not successfully passed the MEBA coordinators will ask the student to re-take the exams for those subjects that, according to the coordinators and the professors’ opinions, may help the student to successfully pass the module.

If after the re-take exams the student successfully passes the module, her or his mark for that module will be upgraded accordingly, otherwise the previous grade will remain valid. Two restrictions apply for the results after retaking:

  1. the highest mark for any subject retaken is 5.5; and
  2. the final grade of the module after the re-take exams cannot be higher than 6.8.

  1. Themark -between 0 and 10- for each subject will be computed byeach professor based on his or her own criteria and on the student's performance. As a general rule, 35% of the mark will correspond to the assessment of the continuous work of the student during the course, and 65% will consist of a comprehensive final examination. Be aware that this, as well as the duration and nature of the final examination is decided by each professor. 

  1. Final exams are compulsory. Re-take exams are only for those students that have previously written a final exam, and have not successfully passed a module.

     

B. COMPRENHENSIVE ASSESMENT

 This module provides for the comprehensive assessment option (Art. 265 of the UAB Academic Regulations).

The request for a comprehensive evaluation implies the waiver of the continuous evaluation. The comprehensive assessment must be requested within the deadline and according to  the procedure established by the Faculty of Economics and Business.

The comprehensive assessment consists of the following activities:

Evaluation Activity

Weight

Duration

Classroom activity (in-person)

Statistics for Data Analysis – Final Exam

20%

2 hours

YES

Statistics for Data Analysis - LABTEST

5%

1 hour

YES

 

 

 

 
Econometrics – Final Exam

20%

2 hours

YES

Econometrics - LABTEST 

5%

1 hour

YES

 

 

 

 

Public Finance – Final Exam

25%

2 hours

YES

 

 

 

 

Macroeconomics– Final Exam

25%

2 hours

YES

The procedures for the revision of the qualifications and the retake process, as well as the regulations on irregularities in the evaluation acts are the same as for the continuous evaluation, as described in the “Evaluation Policy” Section of the MEBA Information Brochure. 


Bibliography

Macroeconomics: 

Textbooks:

Romer, D. Advanced Macroeconomics. McGraw Hill.

Sørensen, P.B. and H.J. Whitta-Jacobsen. Introducing Advanced Macroeconomics: Growth and Business Cycles. McGraw Hill.

Williamson, S.D. Macroeconomics. Pearson.

Specific additional academic papers will be supplied during the course.

Databases:

Eurostat: http://ec.europa.eu/eurostat/data

OECD: http://www.oecd-ilibrary.org/statistics

IMF: http://data.imf.org/

European Comission: http://ec.europa.eu/economy_finance/db_indicators/

The World Bank (Doing Business Database): http://www.doingbusiness.org/data

 

Public Finance:

The basic reference for the course is J. Hindriks and G.D. Myles (2013), Intermediate Public Economics, MIT Press, second edition.

Further, more specialized references, are:

  1. A.B. Atkinson and J.E. Stiglitz (1980), Lectures on Public Economics, McGraw-Hill.

  2. A.J. Auerbach and M. Feldstein (eds) (1985,1987,2002.a,2002.b), Handbook of Public Economics, Vols. 1-4, North Holland.

  3. A.J. Auerbach, R. Chetty, M. Feldstein and E. Saez (eds) (2013), Handbook of Public Economics. Vol. 5, North Holland.

  4. B. Salanié (2003), The Economics of Taxation, MIT Press.

  5. R. Jha (2010), Modern Public Economics, Routledge, second edition.

  6. R.W. Tresch (2002), Public Finance. A Normative Approach, Aceademic Press, second edition.

 

Statistics for Data Analysis:

  1. DeGroot, M.H., M.J.Schervish, Probability and Statistics. Pearson.
  2. Larsen, R.J & Marx, M.L. An Introduction To Mathematical Statistics And Its Applications.Pearson.
  3. Mittelhammer, R.C. Mathematical Statistics for Economics and Business. Springer.
  4. Moore, D.S., McCabe,G.P., Alwan,L.C., B.A.Craig, The Practice of Statistics for Business and Economics. Freeman.
  5. Peck,R., Olsen,C., Devore,J., Introduction to Statistics and Data Analysis. Cengage.

 

Additional readings will be recommended for each specific unit.

Software: TBA

 

Econometrics:

  1. Stock, J. & Watson, M., Introduction to Econometrics.
  2. Verbeek, M., A Guide to Modern Econometrics.
  3. Winkelmann, R. Econometric Analysis of Count Data.
  4. Wooldridge, J.M., Introductory Econometrics.

Additional readings will be recommended for each specific unit.

Software: TBA


Software

Data Analysis Software (TBA)

Word Processor

Data spreadsheets


Language list

Name Group Language Semester Turn
(TEm) Theory (master) 30 English first semester morning-mixed