Corso di laurea magistrale - Area di Economia - Accesso libero con verifica di requisiti e preparazione in ingresso - Classe LM-56 - Erogato in lingua inglese
Lingua: Inglese
Informazioni generali:
Descrizione e obiettivi formativi
Il Corso fornisce strumenti avanzati di conoscenza teorica ed empirica della realtà economica. I laureati acquisiscono qualificate competenze metodologiche e professionali per operare nell'ambito dell'analisi economica e del disegno delle politiche economiche. Particolare attenzione è dedicata ai problemi micro e macro economici nel contesto dell'economia globalizzata.
Il Corso è articolato su due anni con un piano di studi suddiviso in quattro semestri di insegnamenti ed una dissertazione finale. Lo studente ottiene, mediante la dissertazione finale 18 cfu dei 120 cfu complessivi. Gli insegnamenti fondamentali comprendono trattazioni avanzate di microeconomia, macroeconomia, statistica, probabilità, metodi matematici ed econometrici, economia del diritto, economia del lavoro ed economia pubblica. E’ presente una vasta gamma di corsi opzionali che comprendono economia industriale, economia internazionale, microeconometria, economia dello sviluppo, economia dell’ambiente, economia sanitaria, e acquisiti pubblici e regolamentazione.
Sbocchi professionali
Il corso prepara alla professione di economista in istituzioni nazionali ed internazionali, società di consulenza e centri studi, grazie alle competenze acquisite nell'analisi empirica e teorica e nella comprensione del funzionamento del mercato dei beni e dei servizi, nell'individuare soluzioni ai problemi economici, nel programmare e supportare la realizzazione di politiche di sostegno e di regolazione economica. Il corso costituisce inoltre un primo passo per una carriera accademica e per il proseguimento degli studi con un dottorato in economia presso università internazionali. Molti degli ex-studenti sono stati accolti in programmi di dottorato di prestigiose università statunitensi e europee.
Condizione occupazionale (indicatori di efficacia e livello di soddisfazione dei laureandi):
http://statistiche.almalaurea.it/universita/statistiche/trasparenza?CODICIONE=0580207305700003
Valutazione della didattica - Studenti
Anno accademico precedente
Riferimenti web e contatti
Sito Web: http://economia.uniroma2.it/master-science/economics
Coordinatore: Prof. Francesco Sobbrio
Sito Web: http://economia.uniroma2.it/master-science/economics
Email: msc_economics@economia.uniroma2.it
Telefono: +39 06 7259 5645
Le informazioni sulle istruzioni per l'immatricolazione al Corso di Laurea Magistrale sono presenti al seguente link:
https://economia.uniroma2.it/master-science/economics/admissions/
- Firms, consumers, market and market power - Static and dynamic imperfect competition - Product differentation, advertising and consumers inertia - Pricing strategies and market segmentation - Product quality and information - Cartels and tacit collusion - Horizontal mergers - Vertically related markets - Network, standards and systems - Market intermediation
Topics include: random sampling; principles of data reduction; point estimation; hypothesis testing; confidence intervals. In Particular the following topics will be covered:: Brief review of probability: -Random samples and asymptotic methods -Sampling and sums of random variables -Laws of large numbers and central limit theorem Principles of Data Reduction: Sufficiency The Likelihood Principle: the Likelihood Function Point Estimation -Methods of Finding Estimators: Methods of Moments, -Maximum Likelihood Estimators. -Finite Sample Properties: Unbiasedness and Efficiency. -Asymptotic Properties: Asymptotic Unbiasedness, Consistency and Efficiency. Comparison betweene stimators Bayesian estimators -Fisher Information and the Cramer-Rao theorem. Confidence Intervals Hypothesis Testing -Methods of Finding Tests: Neyman Pearson lemma -Large sample tests: Likelihood Ratio Tests, Score Test, Wald Test -Methods of Evaluating Tests: the Power Function, Most Powerful Tests. -The p-value. Nonparametric Inference
R and MATLAB: data import and export, plotting commands, descriptive statistics, functions for random variables, the likelihood approach, the regression model, time series models. Stata: mechanics (do files, data and datasets), programming (macros, scalar, matrice, branching & looping), descriptives (graphs and tables) estimation of the linear regression model using least-squares and instrumental variables approaches. Python: scraping standard websites, extracting usable information and storing it in machine-readable format.
Dynamic linear panel data models Estimating Average Treatment Effects: - Setup and main assumptions: treatment effects and selection bias - Matching and propensity score estimators - Differences-in-differences estimators - Instrumental variables estimators - Regression discontinuity Cross-sectional and panel data models for discrete and limited dependent variables: - Binary outcomes models - Multinomial outcomes models - Count data models - Models for truncated/censored data and sample selection models
1. Consumer theory 2. Choice under uncertainty 3. Firm theory 4. General equilibrium
"Man is by nature a social animal... He who lives without society is either a beast or God" (Aristotle - Politics, Book I, Part II). In economics, the importance of social interactions outside the market is now widely recognized. Individuals share information, learn from each other, and influence one another in various contexts. The course introduces the game-theoretical foundations of social interaction models and focuses on identifying and structurally estimating model parameters. Social interaction models are a specific case of simultaneous equations models, i.e., statistical models in which dependent variables are jointly determined by other dependent variables along with independent ones. Many economic models are simultaneous in nature as a result of the underlying equilibrium mechanism. A prime example is the estimation of utility parameters within the equilibrium equation system in the economy under social interactions. Module 1: Description of Networks - Centrality Measures Bonacich, P. (1987), Power and centrality: A family of measures, American Journal of Sociology, 92(5): 1170-1182. Katz L., "A new index derived from sociometric data analysis," Psychometrika, 18: 39-43. Module 2: Social Interaction Models - Microfoundations and Transition from Model to Data Bramoullé, Y., Djebbari, H., and Fortin, B., 2020. Peer effects in networks: A survey. Annual Review of Economics, 12, pp.603-629. De Paula, A., January 2017. Econometrics of network models. In Advances in Economics and Econometrics: Theory and Applications: Eleventh World Congress (Vol. 1, pp. 268-323). Cambridge: Cambridge University Press. Blume, L.E., Brock, W.A., Durlauf, S.N., and Jayaraman, R., 2015. Linear social interaction models. Journal of Political Economy, 123(2), pp.444-496. Calvó-Arkmengol, A., Patacchini, E., and Zenou, Y., 2009. Peer effects and social networks in education. The Review of Economic Studies, 76(4), pp.1239-1267. Module 3: Identification and Estimation - Statistical Model, Reduced Form, Identification, Estimation, and Specification Tests Manski, C.F., 1993. Identification of endogenous social effects: The reflection problem. The Review of Economic Studies, 60(3), pp.531-542. Lee, L.F., 2007. Identification and estimation of econometric models with group interactions, contextual factors, and fixed effects. Journal of Econometrics, 140(2), pp.333-374. Bramoullé, Y., Djebbari, H., and Fortin, B., 2009. Identification of peer effects through social networks. Journal of Econometrics, 150(1), pp.41-55. Lee, L.F., Liu, X., and Lin, X., 2010. "Specification and estimation of social interaction models with network structures." The Econometrics Journal, 13(2), pp.145-176. Liu, X., and Lee, L.F., 2010. GMM estimation of social interaction models with centrality. Journal of Econometrics, 159(1), pp.99-115. Module 4: Model Extensions - Endogeneity, Quasi-Random Variations, Heterogeneity, and Treatment Effects Angrist, J.D., 2014. The perils of peer effects. Labour Economics, 30, pp.98-108. Arduini, T., Patacchini, E., and Rainone, E., 2020. Identification and estimation of network models with heterogeneous interactions. In The Econometrics of Networks. Emerald Publishing Limited. Arduini, T., Patacchini, E., and Rainone, E., 2020. Treatment effects with heterogeneous externalities. Journal of Business & Economic Statistics, 38(4), pp.826-838. Bifulco, Robert, Jason M. Fletcher, and Stephen L. Ross. The effect of classmate characteristics on post-secondary outcomes: Evidence from the Add Health. American Economic Journal: Economic Policy 3.1 (2011): 25-53. Johnsson, I., and Moon, H.R., 2021. Estimation of peer effects in endogenous social networks: Control function approach. Review of Economics and Statistics, 103(2), pp.328-345. For a complete list of references, please refer to the slides.
The aim of the course is to provide a hint of the potential usefulness of behavioral models, in which agents are assumed to be irrational. The course will start with a review of the classic “Thinking Fas and Thinking Slow” by Daniel Kahneman. The main focus will be on one kind of irrationality and discuss implications in the context of the simplest available macroeconomics models. This (main) section is based largely on the work of Paul De Grauwe. In addition (and briefly) Gabaix’s explanation of apparent myopia based on limited attention and finite processing capacity will be discussed. Also the application of Kahnemen and Twersky to economics by Genaiolo and Shleifer will be discussed. Finally examples of apparent bubbles described by Robert Shiller will be discussed. The three additional topics will not be stressed on the exam which will focus on the main topic of the course (deGrauwe’s approach). Robert Waldmann Robert.waldmann@gmail.com Office 46a 06-72595741. Office hours e-mail me for an appointment Textbook: “Lectures on Behavioral Macroeconomics” Paul De Grauwe
The course is organized in two modules of equal length: 1. Static Regression: Conditional expectations and best linear predictors The classical linear model and the OLS estimator Sampling properties of OLS Generalized least squares (GLS) and feasible GLS Diagnostic procedures Hypothesis testing and model selection. 2. Instrumental Variables: The instrumental variables (IV) method Estimation of causal effects Properties of conventional IV estimators under weak instruments Robust inference under weak instruments The generalized method of moments (GMM) Weak identification and robust inference in GMM.
Human capital, migration and development The aim of the course is to provide students with a theoretical framework and empirical evidence to frame questions relative to how migration (or the lack thereof) has been shaping the economy and the society at large. The course will focus on migration and its effects on sending and receiving countries. Interaction of migration decisions with human capital accumulation will help to understand the (self) selection of migrants and its implication for growth and development. The main topics covered by the course will be: Basic models of Human Capital accumulation Migration and Refugees: data and myths Determinants of migration: main theoretical framework and available evidence Impact of migration on countries of origin Impact of migration on countries of destination Demography and migration The fiscal impact of migration Migration and development Remittances Refugees and Asylum seekers Students are expected to actively participate to the course through readings, discussions and presentations. These activities will be an integral part of the final evaluation. Data sets are available for students willing to gain experience with hands on analyses. A detailed reading list will be distributed at the beginning of the course.
The first objective of this course is to make students familiar with strategic thinking. The second one is to introduce them to the theoretical analysis of incentive problems, and on their implications for our understanding of competitive markets. The course is based on standard textbooks, but I will also refer to a few journal articles. No background beyond undergraduate microeconomics is required, although familiarity with analytical reasoning is assumed.
Labor supply (retirement, family), labor demand, labor market equilibrium (minimum wages, payroll taxes, immigration, wage distribution), education (human capital, signaling, quality of education), discrimination (race, gender), pay based on performance (piece-rate, team)
The course focuses on three main topics: the law and economics of antitrust policy; the law and economics of procurement of public services and in particular Public Private Partnerships and the law and economics of corruption. All the topics will be studied from both a theoretical perspective and an applied one. Microeconomic theory models will be used to explain incentives of firms and politicians. Case studies will allow to understand real world applications.
The course will be articulated in two parts: the first one will focus on some selected textbook topics on public economics, the second part will focus on the political economy of news media with class discussion of recent academic papers on this topic.
