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Curriculum(s) for 2024 - Economics (31829)

Optional groups

The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
1016857 | HISTORICAL SERIES ANALYSIS1st2nd6ITA

Educational objectives

The course aims at showing, both from a graphical point of view and from a methodological one, the main tools for analyzing economic and financial time series. Students will also learn to use to the statistical software R as a tool for applying statistical methodologies to real data, as well as for understanding the theory behind a model.
Students who pass the exam will know the main concepts and procedures for model building when analyzing economic and financial time series.
Students who pass the exam will have skills for data analysis: on the basis of the methodologies introduced in the course and of the knowledge of the R software tools, they will be able to choose the best model to represent real economic and financial phenomena. Starting from real data they will be able to find the best strategy to represent data.
They will also be able to analyze in a critical way the obtained results, highlighting pros and cons of the chosen procedures. Students’ skills are stimulated by tackling real case studies and developing a research project which will be discussed in class. The evaluation of the report will also concern students’ communication skills and their ability to explain what they learned and the results of the quantitative analysis.
The deep comprehension of the learned methodologies, will allow the student to understand more general models not explained in the course, evaluating advantages and disadvantages.

1038332 | PUBLIC ECONOMICS - MASTER COURSE1st2nd6ITA

Educational objectives

The course aims to introduce students to the study of public economics at an advanced level. In particular, the aim of the course is to deepen some issues relating to the role of the public sector in the economy and to the main public finance topics in the current debate. The program will enable students to acquire the necessary theoretical knowledge to assess the opportunity of the public sector intervention into the economy. This also will allow to capture specific aspects of the economic and political debate on the role of the public sector. For this purpose, the theoretical aspects (especially regarding public spending, budget balances, debt, inequality and poverty reduction, etc.) will be complemented by some empirical applications of policy instruments used both at national and international levels. Particular attention will be paid to the European context.

At the end of the course and after passing the exam, students will be able to understand the outcome of modern research in public economics. In particular, they will be able to critically assess the main theoretical and empirical models with respect to public spending growth, budget balance sustainability and the formation of political decisions, as a result of different voting systems. Students can use these models for analyzing the economic patterns at an advanced level, interpreting what happens in real economic world, and actively participating to the economic policy debate, interpreting what happens in real economic world, and actively participating to the economic policy debate.

Thanks to the course attendance, after passing the exam, the student acquires an advanced knowledge on many issues and on a variety of tools which can be fruitfully applied in a large number of professional fields in the public and economic sector. In particular, students will be able to prepare economic reports and analyses paying attention to the policy implications, to analyze government data evaluating the main macroeconomic variables related to the role of the public sector into the economy. The understanding of most scientific – even recent – papers in public economics, both theoretical and empirical, will allow students to also draft serious pieces of research on these topics.

The student must acquire 3 CFU from the following exams
LessonYearSemesterCFULanguage
AAF2351 | COMPUTATIONAL TOOLS FOR MACROECONOMETRICS1st2nd3ENG
AAF2257 | LABORATORY PYTHON1st2nd3ENG

Educational objectives

Python è diventato uno dei linguaggi di programmazione più popolari negli ultimi
anni, in particolare nel campo della scienza dei dati e dell'analisi. Offre una vasta
gamma di librerie e strumenti che possono essere utilizzati per la manipolazione,
l'analisi e la visualizzazione dei dati. Python è particolarmente adatto per l'economia
perché è open-source, ha una sintassi semplice e può gestire facilmente grandi set
di dati. In questo corso introduttivo di Python per l'economia di 12 settimane,
esploreremo i concetti di base e gli strumenti della programmazione in Python, con
un focus su come possono essere applicati ai dati economici.

Alla fine di questo corso, gli studenti avranno una solida base nella programmazione
in Python e saranno in grado di applicare le loro competenze a vari compiti legati
all'economia, dalla manipolazione dei dati alla modellazione predittiva. Avranno
anche acquisito un apprezzamento per la potenza e la flessibilità di Python come
strumento per l'analisi economica.
Prerequisiti:
Per ottenere il massimo da questo corso di Python per l'economia, gli studenti
dovrebbero avere una conoscenza di base dell'economia e della statistica.
Familiarità con i concetti di programmazione e la sintassi sarà utile, ma non richiesta.
Gli studenti dovrebbero avere accesso a un computer con una connessione internet
e dovrebbero essere in grado di installare software sui propri dispositivi. In
particolare, dovrebbero installare Python e la distribuzione Anaconda, che include
Jupyter Notebook.
È consigliato che gli studenti portino un laptop a ogni lezione, poiché lavoreremo
insieme su esempi ed esercizi. Inoltre, gli studenti dovrebbero essere pronti a
trascorrere del tempo fuori dalla lezione lavorando su compiti e progetti.

Obiettivi:
L'obiettivo principale di questo corso di Python per l'economia è fornire agli studenti
le conoscenze e le competenze necessarie per applicare la programmazione in
Python ai dati economici. Alla fine del corso, gli studenti dovrebbero essere in grado
di:
1. Comprendere i concetti di base e la sintassi del linguaggio di
programmazione Python.
2. Utilizzare Python per eseguire analisi, visualizzazione e manipolazione dei
dati economici.
3. Applicare tecniche di analisi statistica ai dati economici con librerie Python
come SciPy e StatsModels.
4. Creare e utilizzare modelli di machine learning per prevedere risultati
economici.

5. Sviluppare una familiarità con varie librerie Python, come NumPy, Pandas,
Matplotlib, Seaborn e Scikit-learn, e comprendere quando utilizzarle per
compiti specifici.
6. Utilizzare Python per lavorare con diversi tipi di dati e sviluppare una
comprensione di come analizzare e interpretare queste informazioni.
7. Lavorare su progetti finali che permetteranno loro di applicare le
competenze e le conoscenze acquisite a problemi economici reali.
Per il progetto finale di questo corso di Python per l'economia, a ciascun gruppo
verrà fornito un dataset. Ogni gruppo riceverà un sottoinsieme del dataset con cui
lavorare. Il progetto coinvolgerà l'esecuzione di tecniche standard di ispezione e
visualizzazione dei dati, nonché l'implementazione dei vari modelli trattati durante il
corso. Il progetto finale sarà valutato in base alla qualità e completezza del progetto.

AAF2251 | laboratory EXPERIMENTAL ECONOMICS1st2nd3ENG
The student must acquire 9 CFU from the following exams
LessonYearSemesterCFULanguage
10606822 | ECONOMICS AND POLICIES OF INNOVATION2nd1st9ITA

Educational objectives

Knowledge and understanding:
The course aims at providing the basic concepts and theoretical elements of the Economics of Innovation by referring both to the innovation process as such - emphasising the determinants, obstacles and nature of such process – as well as to its economic implications. Using the theoretical and analytical tools they will receive during the course, students will be able to define and analyse technological and innovative phenomena, their economic consequences and related policies.

Applying knowledge and understanding:
By applying the theoretical and analytical tools provided during the course, students will be able to analyse key phenomena for the Economics of Innovation such as the introduction of process and product innovation, the relationship between innovative inputs and outputs, the dynamics of patents, the economic and employment impact of innovation and the linkage between innovation and market structure.

Making judgement:
Students will develop autonomy of judgement regarding the analysis of the economic impact of innovation, including heterogeneities between different types of innovation and the link between the potential economic consequences of innovation and the characteristics of the economic context where these consequences occur.

Communication skills:
Students will develop the ability to use analytical tools in order to understand and illustrate in written and oral form the characteristics, determinants and economic implications of technological innovation.

Learning skills:
Students will learn about the salient features and evolutionary process that characterizes technological change and innovation by recognizing the heterogeneity that characterizes such process and by critically interpreting the economic implications of different forms of innovation.

1055979 | GLOBAL ECONOMIC HISTORY2nd2nd9ITA

Educational objectives

The course is divided into a module that includes lectures and activities of working groups consisting in the preparation of presentation, analysis and discussion of articles, essays and books and processing of data sets and the use of historical series that contribute to forming the skills of the student. The latter will be able to apply the acquired knowledge in a concrete way, so as to favor independent judgment and refine problem solving skills.
Specifically, the student will know:
 Understand theories of change and the transformation of an economic system in the long term;
 Apply the knowledge acquired on the economic system in reference to the different national and international models;
 Communicate and implement the skills acquired in the concrete analysis of case studies;
 To pursue and develop, in an autonomous manner, the tools of analysis and comparison in the course of one's professional life in order to have a critical attitude towards the variety and dynamics of the development models.
 The role and the socio-economic impact of the institutions

These objectives are achieved starting from a clear definition of the economic system that represents the system of customs, rules and rules. During the course, study cases related to particular regional areas will be analyzed: Europe (Italy, Germany, England, France, Spain) United States, China, Japan, India, Russia and Asia.
During the course the aspects related to the relationship between the regional context and the global one will be explored; in this perspective the differences between the Civil Law, the Common Law and, above all, the mechanisms of the Path Dependance will be explored. The course will then focus on some topics: international migration; economic crises; inequalities in the long run.

In order to develop critical and judgmental skills and consequently make students able to master economic development models, the course will refer to techniques and tools able to promote learning and knowledge; in this direction during the course some activities will take place, such as:
 Exercises of a theoretical and practical nature on the issues dealt with during the course;
 Presentation of cases studies and related written reports, also with the support of external testimonials;
 Testimonies of eminent scholars in the socio-economic field;
 Group work consisting of project work presentations and discussion of papers

At the end of the course the student will have a good knowledge of the global socio-economic context and its implications in the various historical periods. The student will be able to know and interpret critically the different models of development. Therefore, the student will be able to contribute critically and with his own operational capacity to economic analysis

The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
10606478 | ECONOMICS OF MIGRATION2nd1st6ITA
10606476 | APPLIED MACROECONOMICS POLICIES2nd1st6ITA
10616771 | Economics and territorial analysis2nd1st6ITA

Educational objectives

The course aims to provide students the theoretical, methodological and practical tools needed to understand the spatial and geographical organization of the economy. It will focus on the most recent advancements in the field of economic geography about the following themes: regional development and regional inequality; the logic and geography of firms’ location; the spatiality of local and global economic networks; the relation between innovation, technology and geographical space; business clusters and learning regions; the economic geography of cities; economic policies and space. The course will include seminars and workshops. In the workshops, students will learn how to use geographical information systems, how to manage and analyze spatial data and to produce thematic maps.

The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
10592625 | ADVANCED STATISTICS FOR FINANCE1st2nd6ENG
10616773 | Macroeconomics and financial markets1st2nd6ENG

Educational objectives

Mastering state–of–the art modelling approaches and computational techniques
in macroeconomics and finance. The MACROFIN course is intended for master students,
serving as a bridge between intermediate-level macroeconomics and PhD-level
macroeconomics. This course introduces students to the analysis of real business cycle
models in complete and incomplete markets, with heterogeneous agents and financial
frictions. A first part of the course focuses on: building benchmark business cycle models,
deriving competitive vs social planner equilibria, defining models in recursive form (Bellman
equation), solving and simulating them with local and global methods. A second part of the
course advances towards general equilibrium models with incomplete markets,
heterogeneous agents, and financial frictions.

1051814 | PUBLIC FINANCE1st2nd6ENG
The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
AAF2251 | laboratory EXPERIMENTAL ECONOMICS1st2nd3ENG
AAF2257 | LABORATORY PYTHON1st2nd3ENG

Educational objectives

Python è diventato uno dei linguaggi di programmazione più popolari negli ultimi
anni, in particolare nel campo della scienza dei dati e dell'analisi. Offre una vasta
gamma di librerie e strumenti che possono essere utilizzati per la manipolazione,
l'analisi e la visualizzazione dei dati. Python è particolarmente adatto per l'economia
perché è open-source, ha una sintassi semplice e può gestire facilmente grandi set
di dati. In questo corso introduttivo di Python per l'economia di 12 settimane,
esploreremo i concetti di base e gli strumenti della programmazione in Python, con
un focus su come possono essere applicati ai dati economici.

Alla fine di questo corso, gli studenti avranno una solida base nella programmazione
in Python e saranno in grado di applicare le loro competenze a vari compiti legati
all'economia, dalla manipolazione dei dati alla modellazione predittiva. Avranno
anche acquisito un apprezzamento per la potenza e la flessibilità di Python come
strumento per l'analisi economica.
Prerequisiti:
Per ottenere il massimo da questo corso di Python per l'economia, gli studenti
dovrebbero avere una conoscenza di base dell'economia e della statistica.
Familiarità con i concetti di programmazione e la sintassi sarà utile, ma non richiesta.
Gli studenti dovrebbero avere accesso a un computer con una connessione internet
e dovrebbero essere in grado di installare software sui propri dispositivi. In
particolare, dovrebbero installare Python e la distribuzione Anaconda, che include
Jupyter Notebook.
È consigliato che gli studenti portino un laptop a ogni lezione, poiché lavoreremo
insieme su esempi ed esercizi. Inoltre, gli studenti dovrebbero essere pronti a
trascorrere del tempo fuori dalla lezione lavorando su compiti e progetti.

Obiettivi:
L'obiettivo principale di questo corso di Python per l'economia è fornire agli studenti
le conoscenze e le competenze necessarie per applicare la programmazione in
Python ai dati economici. Alla fine del corso, gli studenti dovrebbero essere in grado
di:
1. Comprendere i concetti di base e la sintassi del linguaggio di
programmazione Python.
2. Utilizzare Python per eseguire analisi, visualizzazione e manipolazione dei
dati economici.
3. Applicare tecniche di analisi statistica ai dati economici con librerie Python
come SciPy e StatsModels.
4. Creare e utilizzare modelli di machine learning per prevedere risultati
economici.

5. Sviluppare una familiarità con varie librerie Python, come NumPy, Pandas,
Matplotlib, Seaborn e Scikit-learn, e comprendere quando utilizzarle per
compiti specifici.
6. Utilizzare Python per lavorare con diversi tipi di dati e sviluppare una
comprensione di come analizzare e interpretare queste informazioni.
7. Lavorare su progetti finali che permetteranno loro di applicare le
competenze e le conoscenze acquisite a problemi economici reali.
Per il progetto finale di questo corso di Python per l'economia, a ciascun gruppo
verrà fornito un dataset. Ogni gruppo riceverà un sottoinsieme del dataset con cui
lavorare. Il progetto coinvolgerà l'esecuzione di tecniche standard di ispezione e
visualizzazione dei dati, nonché l'implementazione dei vari modelli trattati durante il
corso. Il progetto finale sarà valutato in base alla qualità e completezza del progetto.

AAF2152 | STATA LABORATORY1st2nd3ENG

Educational objectives

The course aims to teach the basics of the use of Stata statistical software, with particular attention to the management of microdata datasets for the analysis of the main phenomena related to health economics.
At the end of the course students will be able to import data into Stata starting from different formats (.txt, .csv, .dta, etc.) and in different ways, to sort and prepare the data for subsequent statistical processing and to independently perform descriptive and inferential statistics.

The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
10616775 | Advanced economic history2nd1st6ENG

Educational objectives

The aims of this course are to provide an introduction to the methods of quantitative economic history together with a review of some major findings of historical research of interest to economists. Even though the course is designed in European perspective, the global economy is taken into account for comparison.

1047863 | MONETARY ECONOMICS2nd1st6ENG

Educational objectives

The course aims at introducing students to the recent debate on the theory of monetary policy. To this end, students learn the concepts, methodologies and analytical tools which are necessary to understand the advanced theoretical models on the subject matter. Special attention is devoted to the analysis of dynamical system, to the methods of expectation formation and to the foundations of game theory. Based on these conceptual and analytical elements, the course pursues the general objective of deepening the main theoretical issues which contributed to design the monetary policy regimes actually realised in the last decades. In this way, the course allows students to understand the current debate on the accomplished realizations and on the limits encountered by the central banks of the main industrialized countries. This requires to devote a specific part of the course to the theoretical models recently employed to identify the optimal behaviour of central banks. In this way, the course offers students the possibility to learn both advanced theoretical notions, which are useful to understand the real economic world and which are necessary for those who wish to continue the study of economics, and the actual behaviour of monetary authorities, of particular relevance for those who are interested in monetary and financial issues and wish to enter the labor market after the Laurea. The acquisition of all the tools that are necessary to achieve the teaching targets is guaranteed by specific sections of the program.

Students passing the exam know at an upper intermediate level the most recent theory of monetary policy and they understand the most recent theoretical models underlying the behavior of the central banks of the main industrialized countries. They possess the advanced mathematical and economic tools required by this task and have a particularly good knowledge of game theory and economic dynamics. They understand the problems introduced into monetary economic modelling by the presence of multiplicative uncertainty. Specific knowledge refers to both New Classical and New Keynesian theorizing in monetary policy, to the design of constraints on central banking and to the problem of transparency in monetary policy. The simulation of dynamical economic systems is known at an introductory level.

Students passing the exam are able to understand the current debate on the theory of monetary policy and to read without any problem National and International reports on central banking by private and public institutions (starting from the monthly bulletins and the annual reports by central banks, the Bank for International Settlements, the International Monetary Fund and the other main international institutions). They read without difficulties scientific papers on the studied topics at an upper intermediate level. They are also able to construct upper intermediate models employing game theory and dynamic optimisation methods. They can simulate the response of economic variable to shocks in basic dynamic stochastic general equilibrium models by use of the Dynare freeware software. Finally, they can understand the motivations underlying the actual choices of central banks and to derive their effects on the (current and expected) main economic variables.

10606494 | ADVANCED ECONOMETRICS2nd2nd6ENG
10616774 | Macroeconomics theories and policies2nd2nd6ENG

Educational objectives

Learning outcomes and attributes developed [1] :
 
      Develop an understanding of macroeconomic theory and policy (C,K)
      Understand and interpret economic models based on the rational inter-temporal optimizing
behavior of agents (C,K,P,T)
      Introduction to solving and simulating DSGE models using Matlab and Dynare, and using them
for policy analysis (C,K,P,T)
      Read and interpret academic papers and books related to the material covered (K,T)
      Apply the concepts, tools, and results to economic problems (C,K,P)

[1] K=Knowledge and Understanding, C=Intellectual / Cognitive skills, P=Professional practical
skills, T=Key / Transferable skills

The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
1051814 | Public finance1st2nd6ENG
10616735 | Behavioural economics1st2nd6ENG

Educational objectives

Behavioral economics is an area of research that aims to combine the optimization approach typical of the economic sciences with insights from studies in psychology, thus allowing for a more realistic analysis of how individuals make their economic decisions when emotions, heterogeneous preferences and the possibility of making systematic errors are allowed for.
After a long struggle to establish itself as an independent branch within traditional economics, it is now one of the most productive areas of academic research. At least six of the Nobel Prizes in Economics awarded in the 21st century have been given to behavioral economists: Daniel Kahneman (2002), Vernon Smith (2002), Alvin Roth (2012), Richard Thaler (2017), Elinor Ostrom (2009), and Esther Duflo (2019), the latter being the only two women to receive such a prize.
Behavioral economics teaches us that good decisions often depend on the small details that make each person psychologically unique. Behavioral economics tells us that the world is complex, that not everyone processes information in the same way, and that our emotions matter in making economic choices. Thus, to find optimal solutions to complex problems, we must not only consider human heterogeneity, but we must also learn how other individuals react psychologically to our choices. These lessons are often derived from experiments in the laboratory. In fact, behavioral economics combines psychological intuition with experiments specifically designed to test whether our decisions and theories will work in the particular context in which we want to apply them. In this sense, behavioral economics is an empirical evidence-based approach to decision making.
In recent decades, economists have also begun to conduct experiments - in the laboratory and in the field - with the goal of testing the predictions of economic models, looking for behavioral regularities, formulating new theories capable of integrating behaviors not in line with traditional theories, and/or producing economic and social policy recommendations by testing new market mechanisms and/or refining existing ones.
This course is an introduction to the theory and practice of experimentation in economics, with a look at its implications from a methodological perspective and from the perspective of integrating economics, cognitive psychology, and social psychology.
With the attending students, we will conduct a series of experiments in the CIMEO lab to allow them to test some of the most important theories among those learned during Microeconomics or Political Economy courses and to identify systematic deviations of choices during the experiment from the predictions of these theories.
The course also aims to show students how to implement economic experiments and the usefulness of these experiments in providing an interdisciplinary approach to economic choice analysis. In formulating the theoretical hypotheses to be tested during the experiment, the main reference theoretical models will be presented and analyzed. In analyzing the experimental data, the main statistical techniques characteristic of experimental economics ('experimetrics') will be presented.

10616787 | Development economics1st2nd6ENG
10616772 | Statistics for policy evaluation1st2nd6ENG
1051823 | ECONOMICS OF INSTITUTIONS1st2nd6ENG
The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
AAF2351 | COMPUTATIONAL TOOLS FOR MACROECONOMETRICS1st2nd3ENG
AAF2251 | laboratory EXPERIMENTAL ECONOMICS1st2nd3ENG
AAF2257 | LABORATORY PYTHON1st2nd3ENG

Educational objectives

Python è diventato uno dei linguaggi di programmazione più popolari negli ultimi
anni, in particolare nel campo della scienza dei dati e dell'analisi. Offre una vasta
gamma di librerie e strumenti che possono essere utilizzati per la manipolazione,
l'analisi e la visualizzazione dei dati. Python è particolarmente adatto per l'economia
perché è open-source, ha una sintassi semplice e può gestire facilmente grandi set
di dati. In questo corso introduttivo di Python per l'economia di 12 settimane,
esploreremo i concetti di base e gli strumenti della programmazione in Python, con
un focus su come possono essere applicati ai dati economici.

Alla fine di questo corso, gli studenti avranno una solida base nella programmazione
in Python e saranno in grado di applicare le loro competenze a vari compiti legati
all'economia, dalla manipolazione dei dati alla modellazione predittiva. Avranno
anche acquisito un apprezzamento per la potenza e la flessibilità di Python come
strumento per l'analisi economica.
Prerequisiti:
Per ottenere il massimo da questo corso di Python per l'economia, gli studenti
dovrebbero avere una conoscenza di base dell'economia e della statistica.
Familiarità con i concetti di programmazione e la sintassi sarà utile, ma non richiesta.
Gli studenti dovrebbero avere accesso a un computer con una connessione internet
e dovrebbero essere in grado di installare software sui propri dispositivi. In
particolare, dovrebbero installare Python e la distribuzione Anaconda, che include
Jupyter Notebook.
È consigliato che gli studenti portino un laptop a ogni lezione, poiché lavoreremo
insieme su esempi ed esercizi. Inoltre, gli studenti dovrebbero essere pronti a
trascorrere del tempo fuori dalla lezione lavorando su compiti e progetti.

Obiettivi:
L'obiettivo principale di questo corso di Python per l'economia è fornire agli studenti
le conoscenze e le competenze necessarie per applicare la programmazione in
Python ai dati economici. Alla fine del corso, gli studenti dovrebbero essere in grado
di:
1. Comprendere i concetti di base e la sintassi del linguaggio di
programmazione Python.
2. Utilizzare Python per eseguire analisi, visualizzazione e manipolazione dei
dati economici.
3. Applicare tecniche di analisi statistica ai dati economici con librerie Python
come SciPy e StatsModels.
4. Creare e utilizzare modelli di machine learning per prevedere risultati
economici.

5. Sviluppare una familiarità con varie librerie Python, come NumPy, Pandas,
Matplotlib, Seaborn e Scikit-learn, e comprendere quando utilizzarle per
compiti specifici.
6. Utilizzare Python per lavorare con diversi tipi di dati e sviluppare una
comprensione di come analizzare e interpretare queste informazioni.
7. Lavorare su progetti finali che permetteranno loro di applicare le
competenze e le conoscenze acquisite a problemi economici reali.
Per il progetto finale di questo corso di Python per l'economia, a ciascun gruppo
verrà fornito un dataset. Ogni gruppo riceverà un sottoinsieme del dataset con cui
lavorare. Il progetto coinvolgerà l'esecuzione di tecniche standard di ispezione e
visualizzazione dei dati, nonché l'implementazione dei vari modelli trattati durante il
corso. Il progetto finale sarà valutato in base alla qualità e completezza del progetto.

The student must acquire 6 CFU from the following exams
LessonYearSemesterCFULanguage
10606495 | ECONOMICS OF INEQUALITY2nd1st6ENG

Educational objectives

Students that will successfully pass the exam on Economics of Inequality fully understand issues related to measuring and defining economic inequalities and know main theories which try to explain their trend. In addition they will fully understand welfare system models, in particular pension systems, and will be able to evaluate how State and market can achieve many objectives in terms of equity and efficiency. In addition, they will know the characteristics of pension systems and the link between income distribution and standard of living. Such knowledge is extremely useful both for those people who want to continue studying economics within the academia and for those students who want to enter the labour market in the social field and or in research centres.

SKILLS ACHIEVED:

Students that will successfully pass the exam on Economics of Inequality will be able to measure and assess trends and determinants of income distribution. Further, they will be able to analyse welfare systems and distributive effects of different policies. Hence they will fully comprehend ongoing debate on economic inequalities and on welfare state policies and they will be able to read and understand official documents provided by various economic institutions and scientific papers dealing with welfare state systems.

10616737 | Global networks and regional development2nd1st6ENG

Educational objectives

Students will learn about the theoretical and methodological background needed to understand the spatial and geographical organization of the economy. In particular, students will focus on the most interesting spatial economics issues: regional growth and development; firm location; stages of urbanization and the role of cities in a globalized world; globalization and competitiveness; policies and plans for territorial development. This work will enable students to have an integrated spatial dimension of economics.

SKILLS ACHIEVED:

The theoretical and methodological background to understand the spatial and geographical organization of the economy will enable students to have an integrated spatial dimension of economics.