Econometrics (2010/2011)

Learning outcomes

The course gives an overview of the main econometric tools, with particular emphasis on applications. The course is divided in three parts. The first part provides an introduction to econometrics and a refresher on statistics. The second part presents the standard econometric method (ordinary least squares regression, OLS) and discusses how to tackle its limitations (outliers, collinearity, wrong specification of the functional form, heteroskedasticity and autocorrelation). The third part shows more advanced tools, designed to deal with limited dependent variables (probit, logit) and endogeneity of the explanatory variable (simple instrumental variable estimator, SIV, and generalized instrumental variable estimator, GIVE).

A. Introduction and refresher
1) Introduction
2) Refresher of Statistics
Probability theory; Asymptotic theory; Statistical inference

B. Standard econometrics
3) Ordinary Least Squares (OLS) estimator
Model assumptions; Algebra; Forecasts; Goodness of fit; Frisch-Waugh-Lowell theorem; Large-sample properties; Hypothesis testing
4) OLS failures
Outliers; Collinearity; Misspecification of the functional form; Heteroskedasticity; Autocorrelation

C. Advanced tools
5) Limited Dependent Variable (LDV) models
Binary choice models; Linear probability model, Probit, Logit; Algebra of binary choice models; Goodness of fit; Hypothesis testing
6) Instrumental Variable (IV) estimator
Motivation: endogeneity; Simple Instrumental Variable Estimator (SIV); Generalized Instrumental Variable Estimator (GIVE); Algebra of instrumental variable estimators; Large-sample properties; Weak instruments; Tests on the validity and relevance of the instruments; Endogeneity tests

The exam is written, and it includes both theoretical and applied exercises on the topics covered in class.