Economics

This is a graduate level course that is part of the Laurea Magistrale program. The course is intended for advanced level students only. Enrollment is by consent of the instructor. The course focuses on the main tools used by economists and statisticians in machine learning and statistical learning to analyze large/huge data sets coming from several domains. The course highlights how to apply key aspects of machine and statistical learning, such as out-of-sample cross-validation, regularization, and scalability. Special attention is placed on the concepts of supervised and unsupervised learning, classification, regression, and clustering analysis as well as the detection of association rules. The course also focuses on the main learning tools such as lasso and ridge regression, regression trees, boosting, bagging and random forests, principal components, mixture models and the k-means algorithm. The course places emphasis on the application of the techniques discussed using dedicated open-source software packages on training datasets. Course topics: introduction and overview of statistical learning; linear regression as a prediction tool; binary and multinomial classification: logistic regression, linear discriminant analysis and k-nearest neighbors; resampling methods: cross-validation and the bootstrap; linear model selection and regularization: ridge regression, the lasso, and principal components; moving beyond linearity: regression splines, smoothing splines and general additive models; tree-based methods: CART, bagging, boosting, and random forests; support vector machines and neural networks; unsupervised learning: hierarchical and k-means clustering. The relevant theory will be applied to each topic and subsequently the analysis will move to its empirical application in the R language. Special emphasis is placed on the economic interpretation of the results. The course focuses in several empirical analyses and replicates the results of a few case studies using the statistical software R and several of its packages.

The course uses all the skills that students have developed as economists to try and answer important economic questions. Providing an answer is hard because solving the problem of world poverty is not as simple as reallocating income. The course uses rigorous impact evaluation to find out whether the intervention implied by theory works. 

This course provides an introduction to the statistical and econometric theory underlying surveys and counterfactual policy evaluations. Doing so, it sharpens critical appraisal of the very many surveys and policy evaluations found in public discourse, as data-driven evaluations of public policies are becoming commonly used to help societies choose how to organize unemployment insurance, the provisions of health care and education, etc. This course uses mathematical notation and proofs and engages with mathematically formalized material.

This course provides a study of the basic concepts of the urban and regional economy. It examines the economics of cities and problems of urbanism by means of understanding decision-making processes on the part of individuals and firms regarding geographic location. 

This course answers the fundamental set of questions all entrepreneurs should ask themselves: When do we raise money? How much? From whom? Under what terms? What are the longer‐term implications of the chosen financing strategy? The course further considers the investor’s viewpoint as well, since understanding the motivations and incentives faced by ones counterpart is critical to avoiding financing pitfalls and successfully negotiating the best financing outcome for ones venture. Several cases concern technology‐based businesses, though the emphasis is on gaining insights into entrepreneurial finance.

Please note that there are different sections of this course at UNIBO, both at the LM and LT levels. The LM sections require special permission as they are part of the Laurea Magistrale in Direzione aziendale degree.This description applies to the LM course with Prof. Bolatto. This course analyzes the regulatory framework for trade and the regulatory issues relating to international markets and regional markets, such as U.S. and EU markets, and emerging markets in Africa and Asia. Topics include Institutional structures (GATT/WTO, NAFTA, EU, APEC, SADEC, CEDEAO) and Regulatory authorities; International dimensions of market regulation (tariffs and customs regulations, product safety and environmental restrictions, trademark and patent regulations); and settlement of disputes. The course discusses topics including multinational firms and foreign direct investments, global value chains, firm strategies in global value chains, and international princes and exchange rates.

This course analyzes industrialization, focusing on the roles of public policy and other roles of public and private producers and consumers. The course’s empirical focus is on the causes and effects of industrialization in Asia’s advanced (e.g., Japan, Korea, Taiwan) and developing economies (e.g., China, India, Indonesia, Malaysia, Thailand, Vietnam).