|
Mutua da
|
8012040 STRUCTURAL ECONOMETRIC MODELLING in Economics - Economia LM-56 ARDUINI TIZIANO
(programma)
"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.
 Materiali di studio relativo alle lezioni frontali e reading list predisposta dal docente verrà pubblicata sulla pagina TEAMs del corso.
|
