Guide in PDF format

Important notice

The course guide is provisional.

The PDF version of the course guide may take a few days to become available in the DDD.

Fundamentals of Economics and Business II

Code: 42141
Credits: 15

2026/2027

Degree programme	Type	Course
Economics and Business Administration	OB	1

Contact lecturer

Name :: Xavier Vila Carnicero
Email :: xavier.vila@uab.cat

Teaching staff

: Carolina Bussotti
: Adel Reka Kálózdi
: Pierre Magontier
: Miguel-Angel Lopez Garcia

Group languages

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

Prerequisites

None

Objectives

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.

Learning outcomes

(CA06) Carry out complete empirical analyses, from the process of obtaining data to the application of inference techniques, for the understanding of complex realities.
(CA07) Investigate new models of economic analysis for the advancement of knowledge on the main problems that affect social welfare.
(CA08) Evaluate the impact and efficiency of different public policy modalities in economies with public intervention.
(CA09) Make predictions with a prior level of confidence of the behaviour of large macroeconomic magnitudes and their impact on social welfare and the sustainability of the evolution of the economy.
(KA07) Identify the main macroeconomic variables and the relationship between them for the analysis and prediction of economic reality.
(KA08) Identify the different sources of public financing to enable the financing of public policies.
(KA09) Recognise the appropriate techniques of empirical analysis for the knowledge, verification and prediction of hypotheses about variables with economic or social content and the relationship between them.
(SA04) Deduce the effect on any economic variable of interest of changes in other related variables in a context of complex interdependence in the economic or social environment.
(SA05) Decide on the appropriate statistical technique for the analysis of the problem under study in the finance and business fields.

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

Learning activities and methodology

Title	Hours	ECTS
Type: Autonomous
Study, Reading, Exercise solving, Essays writing	129.7	5.188
Type: Guided
Lectures with ITC support	75	3
Resolution of exercises	37.5	1.5
Type: Supervised
Tutoring and monitoring work in progress	93.8	3.752

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

Continuous assessment activities

Title	Weight	Hours	ECTS	Learning outcomes
Econometrics Final Exam	25%	9.75	0.39	CA06, CA08, CA09, KA09, SA04, SA05
Macroeconomics Final Exam	25%	9.75	0.39	CA07, CA09, KA07, SA04
Public Finance Final Exam	25%	9.75	0.39	CA07, CA08, KA08, SA04
Statistics for Data Analysis Final Grade	25%	9.75	0.39	CA06, KA09, SA05

A. CONTINUOUS ASSESMENT

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: Students are expected to attend all lectures. Professors might take into account class attendance and in-class participation as part of the final assesment of their subject.

If a module is not successfully passed, and the average grade is larger or equal than 3.5, the MEBA coordinators will ask the student to retake 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 subject(s) retaken, 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:
the highest mark for any subject retaken is 5.5; and
the final grade of the module after the re-take exams cannot be higher than 6.8.
The mark -between 0 and 10- for each subject will be computed by each professor based on his or her own criteria and on the student's performance. As a general rule, the following scheme will be applied:

• Class participation (0%-15%).

• Submission of reports, assignments, and/or exercises (15%-30%).

• Oral presentation/defense of reports and/or assignments (0%-10%).

• Individual written tests (50%-65%).

Be aware that this, as well as the duration and nature of the written examinations, is decided by each professor

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	25%	2 hours	YES
Statistics for Data Analysis – LAB Test	5%	1 hour

Econometrics – Final Exam	25%	2 hours	YES
Econometrics - LAB TEst	5%	1 hour

Public Finance – Final Exam	25%	2 hours	YES

Macroeconomics– Final Exam	25%	2 hours	YES

The procedures forthe 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/

The World Bank (Doing Business Database): https://www.worldbank.org/en/businessready

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:

A.B. Atkinson and J.E. Stiglitz (1980), Lectures on Public Economics, McGraw-Hill.
A.J. Auerbach and M. Feldstein (eds) (1985,1987,2002.a,2002.b), Handbook of Public Economics, Vols. 1-4, North Holland.
A.J. Auerbach, R. Chetty, M. Feldstein and E. Saez (eds) (2013), Handbook of Public Economics. Vol. 5, North Holland.
B. Salanié (2003), The Economics of Taxation, MIT Press.
R. Jha (2010), Modern Public Economics, Routledge, second edition.
R.W. Tresch (2002), Public Finance. A Normative Approach, Aceademic Press, second edition.

Statistics for Data Analysis:

DeGroot, M.H., M.J.Schervish, Probability and Statistics. Pearson.
Larsen, R.J & Marx, M.L. An Introduction To Mathematical Statistics And Its Applications.Pearson.
Mittelhammer, R.C. Mathematical Statistics for Economics and Business. Springer.
Moore, D.S., McCabe,G.P., Alwan,L.C., B.A.Craig, The Practice of Statistics for Business and Economics. Freeman.
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:

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