850 - APPLIED ECONOMICS
Academic Year 2021/2022
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STEFANO USAI (Tit.)
- Teaching style
- Lingua Insegnamento
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The course aims to ensure that students acquire knowledge and skills related to the quantitative and empirical analysis of economic phenomena. The skills acquired will prove useful both in academic research and in the professions. In particular, these skills will be refined with the study of the phenomena concerning the localization of production activities and innovation activity in the European regions.
In particular, at the end of the course the students will have acquired:
a) Knowledge and understanding:
knowledge and understanding of the main phenomena relating to the location of economic activities, innovation activity and technological progress, with particular reference to the Italian and European context
b) Ability to apply knowledge and understanding:
- ability to read and interpret empirical analyzes, with particular reference to those based on the use of georefenced data
- familiarity with the analysis of economic data through the use of basic econometric methods
- familiarity with the use of the main sources of economic data
c) Autonomy of judgment
thanks to the acquisition of awareness of the importance of the empirical approach for the study of economics and of the problems and criticalities encountered in conducting applied analyzes, the ability to autonomously judge empirical analyzes presented in scientific publications is developed
d) Communication skills
through applied studies to be carried out in groups, students develop communication skills, both in written and oral form, with particular reference to the use of the technical language typical of quantitative disciplines
e) Learning skills
through applied studies to be carried out in the laboratory and the study of scientific articles, students acquire the tools to independently conduct studies in the economic field.
The knowledge and skills acquired in the Applied Economics course are also complementary to those that students will acquire in the courses of Innovation and Creativity, Market Analysis, Entrepreneurship and Business Creation, and represent a useful basis for students who will conduct analyzes. empirical type during a possible PhD program.
As the main object of the Econometrics course is the study of the quantitative methodologies used to assess economic phenomena, students are supposed to have already acquired the basic knowledge of economics (this prerequisites is very important) during their undergraduate degree course. Other prerequisites relates to basic knowledge in statistics (essential), mathematics (essential), informatics (useful) and English language (very important).
In particular, it is highly recommended that students are already familiar with the following knowledge:
- statistics: probability theory (random variables and their probability distributions), properties of the probability distribution functions (expected value, mean, variance, covariance), main sample distributions, how to draw inference on population from sample evidence, point estimation, confidence intervals, hypothesis testing;
- mathematics: set theory (relations, functions, numerical sets, natural, rational and real numbers), one variable function (properties, graphic representation, elementary functions such as linear, logarithmic, exponential, polynomial) limits, derivatives, integrals, functions of two or more independent variables (properties, graphic representation, necessary and sufficient conditions for maxima and minima of two variables functions);
- informatics: ability in the use of text (Word) and spreadsheets (Excel) software;
- English: good knowledge of the English language is required because some reading material is provided in English.
The first part of the course is dedicated to the main themes of the economics of growth and development applied at the regional level.
The second part is devoted to a statistical laboratory applied to the study of economies at the regional level.
The third and last part of the course aims to address, through a review of analytical and empirical contributions, the issues related to:
- distribution of production activities
- determinants of innovative activity
- knowledge flows between European regions
- EU cohesion policies and S3 strategy,
The course includes lectures (36 hours) and possible group work for the statistical analysis laboratory.
Each topic of the course is based on those previously developed, therefore each student is strongly encouraged to follow the lessons regularly and to prepare the exercises assigned from time to time. Only in this way, in fact, will it be possible to gradually acquire the knowledge and skills required by the course and, in particular, those that in the second part will allow you to understand the application of the techniques learned in the first part.
During the lessons the students will be involved in discussions that allow them to develop a critical sense and improve communication skills.
The exercises assigned at home can be carried out in groups of up to 4 students and require the preparation of a written paper, this activity will allow you to develop independent judgment and communication skills.
Verification of learning
The final evaluation is based on a written assignment (50%) and the writing of a report (50%)
The exam questions will be formulated in such a way as to be able to assess whether the student has acquired the main knowledge of empirical analysis methods, if he is able to use them to critically evaluate applied studies in the context of the economics of innovation and the localization of activities productive.
In answering the exam questions, the student will therefore be asked to:
- present and discuss theoretical content
- demonstrate the ability to comment in a rigorous, logical and consequential manner on the results of empirical analyzes, comparing, if necessary, alternative economic approaches.
To pass the exam, thus obtaining a grade of not less than 18/30, the student must demonstrate that they have acquired sufficient knowledge of the topics of the first part of the course, a basic knowledge of those of the second part and to be able to use the tools learned in the first part to interpret the results of the analyzes presented in the second part.
The grade of 30/30, with possible honors, will be awarded if in the examination tests the student demonstrates that he has acquired an excellent command of the course topics, both from a theoretical and applied point of view, and is able to respond to the exam questions using rigorous language.
ROBERTA CAPELLO, Economia regionale
Localizzazione, crescita regionale e sviluppo locale, Seconda edizione, Il Mulino
- Audretsch, David B. and Maryann P. Feldman (2004), Knowledge Spillovers and the Geography of Innovation. In Vernon Henderson and Jacque F. Thisse, eds., Handbook of Urban and Regional Economics, Volume IV, Cities and Geography. Amsterdam: Elsevier.
- Boschma R. (2005) Proximity and innovation. A critical assessment, Regional Studies, 39, 6174.
- Breschi S. (2000) La geografia delle innovazioni tecnologiche, in Malerba F. (a cura di) Economia dellinnovazione. Roma: Carocci (cap 12 p. 343-372).
- Breschi S. and F. Lissoni (2001) Knowledge Spillovers and Local Innovation Systems: A Critical Survey, Industrial and Corporate Change, 10, 975-1005, (LIUC working papers).
- Marrocu E., R. Paci (2012), Education or creativity: what matters most for economic performance?, Economic Geography, 88, 369-401.
- Marrocu E., R. Paci, S. Usai (2013), Productivity growth in the Old and New Europe: the role of agglomeration externalities, Journal of Regional Science, 53, 418-442.
- Marrocu E., Paci R. and Usai S. (2013) Proximity, Networks and Knowledge Production in Europe, Technological Forecasting and Social Change, 80, 1484-1498.
- Moreno R., R. Paci e S. Usai (2005) Spatial spillovers and innovation activity in European regions Spatial spillovers and innovation activity in European regions, Environment and Planning A, 37, 17931812.
- Moretti E. (2004), Human capital externalities in cities. In Vernon Henderson and Jacque F. Thisse, eds., Handbook of Urban and Regional Economics, Volume IV, Cities and Geography. Amsterdam: Elsevier.
- Paci R., Usai S. (2008), Agglomeration economies, spatial dependence and local industry growth, Revue dEconomie Industrielle, 123, 3, 87-109.
- Paci R., Usai S. (2009) Knowledge Flows across European Regions, Annals of Regional Science, 43, 669-690.
- Rosenthal S., Strange W. (2004), Evidence on the Nature and Sources of Agglomeration Economies, in Henderson J.V. and J.F. Thisse (eds.) Handbook of Urban and Regional Economics, Volume IV, Cities and Geography. Amsterdam: Elsevier.