MODELS FOR ECONOMICS AND FINANCE
I candidati ammessi dopo la valutazione dei titoli verranno ascoltati dalla commissione attraverso un colloquio Il colloquio si basa sul progetto di ricerca presentato e sull'accertamento del background del candidato in relazione al curriculum di dottorato prescelto Bibliografia essenziale: Economics. Microeconomics: Consumer theory. Production theory. Market structures and externalities Macroeconomics: The IS-LM model. The AD-AS model. Phillips curve. Ramsey model. Economic Policy: The normative model of economic policy. Fiscal policy. Monetary policy. Books: • Varian H. R., Microeconomic Analysis, Norton & Company. • Blanchard, O.J., Macroeconomics, Pearson 5th edition • Acocella, N. Fondamenti di Politica Economica, Carocci (Eng. Ed.: The Foundations of Economic Policy, Cambridge University Press) • Stiglitz, J. , Economics of the Public Sector, Norton & Company Development Economics. Basics principles of development economics; impact evaluation of development policies and programs; poverty and vulnerability analysis; international trade, economic growth and inequality; international finance and development; labor and migration: sustainable development and environment; common property resources and determinants of cooperation; agriculture for development and the economics of farm households. Books: De Janvry and E. Sadoulet (2016), Development Economics: Theory and Practice, Routledge, UK. Economic Geography Regional development theories; the spatial behavior of firms; spatial agglomeration, regional disparities and regional specialization; local and global production networks; sustainable development, the environment and the climate crisis; innovation, technology and space; the geography of development; urban and regional policies; basics in digital cartography; foundations of statistical methods for geography and spatial analysis. Books: • Sheppard E., Barnes T.J., A Companion to Economic Geography, Wiley-Blackwell, 2017. • Cumbers A., MacKinnon D., An Introduction to Economic Geography: Globalization, Uneven Development and Place, Routledge, 2019 (3rd edition). • Martin R., Economy: critical essays in human geography, Routledge, 2018. • Rogerson P.A., Statistical methods for geography: a student’s guide, Sage, 2020 (fifth edition). • Clark G.L. et al., The New Oxford Handbook of Economic Geography, Oxford University Press, 2018. Mathematics Basic notions of calculus. Implicit functions, homogeneous functions. Free or constrained maxima and minima. Elements of utility theory. Pareto problems. Linear algebra. Ordinary Differential Equations, systems of linear differential equations. Dynamic systems: equilibrium and stability. Probability Set theory, Random Variables; Conditioning, Convergence Theorems, Central Limit Theorem, Law of Large Numbers, Markov Chains. Books: • Guerraggio, A., Salsa, S., Metodi matematici per l’economia e le scienze sociali, Giappichelli, 1997. • Simon, C. – Blume, L.E., Matematica per l’Economia e le Scienze Sociali, Università Bocconi Editore, 2002. • Ross, S., Calcolo delle probabilità, Apogeo 2004. • Chang, A., Wainwright, A. (1967) Fundamental Methods of Math-ematical Economics (available on-line). • Peccati, L., Salsa, S. and Squellati, M. Mathematics for Economics and Business, EGEA, 2008 • Intriligator, M.D. (1971) Mathematical Optimization and Economic Theory, Prentice Hall Series in Mathematical Economics . • Takayama, A., (1985) Mathematical Economics, Cambridge Univ. Press. • Blitzstein, J.K., Hwang, J. (2019) Introduction to Probability, CRC Press. • Liseo, B., Appunti per il corso di probabilità e processi stocastici, on line at https://sites.google.com/a/uniroma1.it/brulis/probabilita-e-processi-sto... Statistics Sampling distributions, estimators, sufficient statistics. Linear and generalized linear models, OLS theory. Multivariate analysis. Index numbers, national income models, income, consumption and productivity measurement. Time series analysis, panel data analysis, regression and causality. Books: • Wood, S. Core Statistics, CRC Press, 2014. • Azzalini A. Inferenza Statistica, Springer Italia, 2001. • Di Ciaccio A., Borra S., Statistica: metodologie per le scienze economiche e sociali, Mc Graw Hill 2007. • Stock J., Watson M., Introduction to Econometrics, Pearson 3rd edition. • Guarini R., Tassinari F., Statistica Economica, Il Mulino, 2000. • Angrist J., Pischke J.S., Mostly Harmless Econometrics, Princeton University Press, 2009. • Dekking, F.M., Kraaikamp, C., Lopuha H.P., Meester L.E , A Modern Introduction to Probability and Statistics: Understanding Why and How, Springer 2005
The Ph.D. program in Models for Economics and Finance aims to provide a solid methodological background in the fields of economics, statistics, econometrics, geography, mathematical finance, oriented to the analysis of relevant economic and social issues. This Ph.D. program differs from others in economics and in statistics as it offers analytical sophisticated tools as well as skills for empirical application. It participates in the Doctoral School of Economics. Curriculum in MATHEMATICS FOR ECONOMIC-FINANCIAL APPLICATIONS: it trains students in quantitative techniques and mathematical modelling of relevant problems arising in economics, finance and actuarial sectors, including risk management. Thanks to the mixture of theoretical and business-specific skills, the program prepares mathematical scientists with knowledge of financial economics for careers in academia, business, and government, enabling them to take research leadership positions. Curriculum in ECONOMIC GEOGRAPHY: the aim is to provide participants with theoretical, methodological and practical skills that are needed to conduct high quality research, both within and beyond the Academia, in the fields of urban and regional planning, local economic development, firms location and geomarketing, and in the statistical and spatial analysis of geographic information. The curriculum promotes researches that are in line with the most recent advances in the disciplines of human geography, spatial statistics, regional economics and urban studies. Curriculum in ECONOMIC STATISTICS: it is solidly based on modern and quantitative methods to analyze relevant economic problems. Emphasis is placed on empirical applications to analysis and solutions of practical problems in the field of applied economic and social sciences. It is designed to form research scientists with robust expertise in applied economics and statistics for careers in academia, business, and government in a leadership position. A solid competence in the field of statistics, econometrics, and applied economic methods is integrated with a focus on empirical applications.
Giorno: 23/9/2020 Ora: da definire Aula: da definire in seguito Indirizzo: da definire in seguito
a) GEOGRAFIA ECONOMICA
b) MATEMATICA PER LE APPLICAZIONI ECONOMICO FINANZIARIE
c) STATISTICA ECONOMICA