20295 - MICROECONOMETRICS
CLMG - M - IM - MM - AFC - CLAPI - CLEFIN-FINANCE - CLELI - ACME - DES-ESS - EMIT
Course taught in English
Go to class group/s: 31
The course covers a selection of topics in Microeconometrics, the branch of economics that empirically test the behavioural implications of microeconomic theory using large individual-level datasets, e.g. labour force surveys, population of firm censuses. After an introduction to the problem of identification in econometrics, we will proceed to the discussion of causality and the various methodologies that allow to estimate causal relationships from the data. If time permits, we will also discuss (some or all) of the following topics: panel data (static and dynamic,linear and non-linear models) and duration analysis. The course combines theoreticallectures and applied computer sessions. It is recommended that students are familiar with the mathematical and statistical concepts used in any econometrics class. Previous knowledge of econometrics is preferable but not strictly necessary.
- (a)The identification problem in econometric
- (b)Brief aside on asymptotic theory
- (a)Causality and the potential outcome setting
- (b)Identification on observables:
- Regression and causality
- The curse of dimensionality and the common support problem
- Matching estimators
- (c)Identification on unobservables
- Instrumental variables and causality
- Instrumental variables in non-linear models
- LATE interpretation of instrumental variables
- Fixed effects and differences in differences
- Regression discontinuity design
- Additional topic to be covered only if time permits
- (a)The econometrics of panel data models (static and dynamic, linear and non-linear)
- (b)Duration analysis
The theoretical lectures are combined with applied sessions during which students are introduced to the software STATA.
J.M. Wooldridge, Econometric Analysis of cross section and panel data, MIT Press, 2002.
A. COLIN Cameron, P.K. Trivedi, Microeconometrics. Methods and Applications, Cambridge University Press, New York, 2005.
M. Arellano, Panel Data Econometrics, Oxford University Press: Oxford, 2003.
J.D. ANGRIST, J.S. PISCHKE, Mostly Harmless econometrics: an empiricist's companion, Princeton University Press, 2009.
Additional readings are provided at the beginning of the course.
To deal with the topics covered here it is recommended that students have some knowledge of the contents of basic econometrics and the mathematical and statistical techniques used therein.