Econometrics - Proff. Gianmarco Vacca; Conuselo Rubini Navas
The course aims at acquainting doctoral students with the fundamental aspects of econometric methodology. The purpose is to prepare the student to competently handle the basic econometric tools for the measurement, modelling, interpretation, and forecast of economic phenomena. The course introduces several modeling strategies, starting from basic notions of statistics and probability, and delving into regression analysis in its different perspectives. The notion of causality and its declination in different economic contexts will be examined, going further than the simple linear regression, exploring panel data and causal analysis methods. All the econometric tools analyzed during the course will be paired with practical examples using statistical software such as Stata and R, with an emphasis on the economic interpretation of their output.
Technology adoption and firms’ performance -Prof. Maurizio Baussola
The main objectives of the course will be to provide analytical tools and empirical evidence to understand technological adoption and the impact of innovation on firms’ performance. Sectoral patterns will be highlighted together with the determinants of firms’ diversified behaviour. In addition, the role of non-technological innovations (organizational and marketing) will be discussed. In particular, the focus will be on: (i) theoretical and empirical models of technological diffusion and their policy implications; (ii) the impact of technological and non technological innovation on firms’ performance and the analysis of profit and innovation persistence.
Policies sustaining innovation at EU, national and regional level - Prof. Franco Timpano
The main objective of the course will be to provide evidence of the policies sustaining innovation at different level of government. The theoretical rationale behind the policies will be preliminarily provided and then an analysis of a number of policies at EU level and at national/regional level will be proposed. The analysis of policies will be also proposed in terms of impact on economic growth and productivity. Recent orientation towards digitalization and sustainability will be widely considered. Moreover, issues concerning IPR policy tools (i.e. patent box in Italy), infrastructure (i.e. competence centers in 4.0 policy), new startups policies (i.e. Startup Act in different countries) and other practical policies will be examined.
Introduction to the Economics of Innovation - Prof. Marco Vivarelli
This course will provide the students with the basic concepts and theories which are the bases of the Economics of Innovation. Starting from Schumpeter’s framework and definitions, Neo-Schumpeterian advances will be discussed within an evolutionary approach. The analysis will span from the drivers of innovation - including scientific, economic and institutional determinants - to the very nature of the innovation activities - such as R&D, process and product innovation, patents, etc. - and eventually to the consequences of innovation in terms of productivity, competitiveness and employment. Students should be familiar with macroeconomics, microeconomics and statistics
Econometric methods for innovation studies -Dr. Laura Barbieri
This course examines the econometrics tools used to analyze economic time series and to investigate the dynamic and causal impact of macroeconomic shocks on the variables of interest. Both univariate and multivariate models for stationary and non-stationary time series will be explored. Specifically, students will acquire an understanding of both univariate statistical techniques generally used to study the dynamics of a time series, like ARMA and ARIMA models, and of the main techniques for building linear regression models using stationary and non-stationary time series, as in the case of cointegration. Finally, methodologies related to multi-equational models, such as VARs and Structural VARs, will be introduced. The theoretical presentation of econometric tools will be accompanied with practical examples using statistical software (R), paying particular attention to the economic interpretation of their output. Students should be familiar with basic concepts of statistical multiple linear regression.
Panel-data analysis in innovation studies - Prof. Randolph Bruno
The aim of this course is to help students becoming familiar with static and dynamic panel data applications. Indeed, in order to understand, analyse and study relationships in economics of innovation and industrial organization fields, it is necessary to empirically test hypotheses. As long as more disaggregated data are able to provide more accurate analysis (as they are not affected by aggregation bias), micro-data turn out to be very useful. Indeed, in recent years micro-data with a sufficient time-span are becoming more available, panel data techniques turn out to be more relevant. In addition, the lab part will allow students practicing and replicating some published results and grasp the connection between economic theory and panel-data applications.
Microeconometric methodologies for innovation studies - Prof. Gabriele Pellegrino
The objective of this course is for students to learn a set of statistical tools and core methods that are useful in carrying out high-quality empirical research on topics in applied microeconomics. The course illustrates the identification strategies, estimation and other related issues that are relevant for the appraisal of causal effects using observational data. It will examine the most advanced techniques of Diff-in-Diff such as matching, synthetic control, asymmetric/staggered treatments, dynamic treatments, interference, and heterogeneous treatment effects. It will also focus on the methodology of randomization in social science research and discusses different randomized control trials (RCTs) techniques. Finally, it will briefly touch upon the Regression Discontinuity Design (RDD) methods and their main applications. Such methods and techniques will be illustrated both theoretically and by means of empirical economic applications implemented using the statistical software STATA. The course will reinforce student’s aptitude to critically evaluate results from previous literature and to carry out their autonomous research in applied economics.
Intellectual Property Rights and their data analysis -Dr. Jacopo Staccioli
The course aims at providing comprehensive knowledge to the students regarding the general principles of intellectual property rights and the empirical analysis of relevant data sources. The students will acquire theoretical and methodological skills which will prove useful in addressing research questions relative to the economics of innovation and beyond. After a broad introduction of the main intellectual property instruments, namely patents, trademarks, and copyrights, the course proceeds with a more hands-on approach which covers the leading providers of patents’ data, including ORBIS IP (Bureau van Dijk), PATSTAT (EPO), PatentsView (USPTO), and OECD patent quality indicators. To this purpose, the theory and best practices behind relational database management systems (RDBMS) and the SQL language are briefly touched upon. The course concludes with some introductory computational aspects of text mining and natural language processing applied to the analysis of patents’ full texts.
Economics of Patents -Prof. Fabio Montobbio
The course focuses on the analysis of technology and innovation using patent data.
First the course examines the economic justification for intellectual property and how the institutional design can stimulate or hinder innovation. It addresses the efficiency of the international regulation of intellectual property with a specific regard to developing countries.
Secondly the course brings together the recent empirical literature in economics of innovation with the practical use of a complex database. Patent data provide a very rich set of information on the technological activities of individual inventors and companies. They are increasingly used to map technologies and monitor markets for business intelligence. They can also be used as indicators of innovation in regions and countries. Together with the delivery and explanation of the database, different exercises are proposed to stimulate the development of curiosity-driven research questions.
Strategic management and international business - Prof. Daniele Cerrato
The course deals with some topics related to strategic management and international business with the aim of: (i) Introducing doctoral students to representative conceptual research and empirical research in the fields of strategic management and international business; (ii) Discussing fundamental issues debated in the literature and provide students with a thorough understanding of major theories, issues and methods; (iii) Developing the skills necessary to analyze and evaluate both conceptual and methodological aspects of the literature; (iv) Enabling students to develop at least one creative idea into a research proposal or a literature review on one of the topics covered in class as a basis to develop a full paper to be presented at upcoming professional meetings or for thesis development.
The topics dealt with in module I (Strategic Management) are: (i) Introduction to strategic management; (ii) Diversification: drivers, measures, outcomes; (iii) Mergers & Acquisitions and Strategic Alliances; (iv) Entrepreneurship and SMEs; (v) Corporate governance and ownership structure.
The topics dealt with in module II (International Business) are: (i) Theories of the Multinational Enterprises; (ii) Frameworks of international strategies; (iii) Measuring internationalization and the internationalization-performance relationship; (iv) The internationalization process and the role of distance in international business; (v) International business across different research contexts: small and medium-sized enterprises, international new ventures, family firms.
Industrial dynamics and innovation -Prof.sa Elena Cefis
Changes in the technological paradigm as well as successful radical innovations have the potential to exert a disruptive impact in the life-cycle of industries, sometimes even leading to the creation of new industries. As a result, innovators and early adopters will enjoy an enduring advantage and sustained growth, which could also act as a barrier to new entries. Innovations can also thoroughly change the demand for labor in adopters as well as in other firms in the industry. Further, the impact of innovation are likely to cross the boundaries of countries in ways that are related to the nature of the goods/ services and the different institutional context, for instance, the different levels of enforcement in intellectual property rights. In addressing the broad research questions outlined above, the class will outline, among the others, what factors can be associated to the emergence of a new technology; what determines who will be adopting it; how to assess the impact on different occupational categories; how to estimate the value of an innovation.
Green innovation and environmental sustainability -Dr. Claudia Ghisetti
Green innovation plays a crucial role in the transition towards an environmentally sustainable economy. Green innovation involves a variety of aspects: the development of new technologies which directly or indirectly address climate change mitigation; the introduction of green products which carry environmental benefits; or the improvement in industrial processes, including digitalisation and green information and communication technologies. This PhD course will explore these various facets of green innovation and use an evolutionary economics lens. After the course, students will be able to proficiently discuss questions, such as: what are green technologies and green products? What technological or productive capabilities are necessary for green innovation? Is there a relationship between green innovation and environmental performance? What are the economic implications? Is there a window of opportunity for emerging countries or peripheral regions?
Networks and Geography in the Economics of Innovation - Proff. Mario A. Maggioni; T.Erika Uberti
Any economic activity benefits from clustering in the production activities. However, the innovation studies literature has stressed the role of knowledge spillovers and intentional knowledge exchange networks as the driving engines of successful firms, industries and clusters. The aim of this course is to make students familiar with the main concepts and analytical tools which can be used to look at how knowledge is created, exchanged and diffused in order to provide the basis of an innovation-based process of economic growth at the individual firms and the local system level. The course will draw upon different disciplines and methods such as Economic geography, Network Analysis, Spatial Statistics and Econometrics and will allow students to interact with the current literature on the topic with a hands-on approach.
Innovation and the international arena - Prof. Marco Grazzi
This course will provide students an understanding of the relationship between innovation, globalization and economic development. The main topics of the course will include a description about the stylized facts of globalization and the recent phenomenon of possible de-globalization, an overview about theory of international trade and economic growth, the relationship between international knowledge and technology flows, the relationship between foreign direct investment and innovation, the role of multinational corporations and innovation, foreign direct investment to and from emerging economies, international aspect of intellectual property rights, the relationship between global value chain and the technological upgrading (or not) of emerging economies.
