Module A (Francesca Giambona): Longitudinal data analysis: definition and benefits for estimation and inference. Fixed and random effects estimators. Testing random effects against fixed effects. Fixed-effects model: Covariance Model, Within Estimator, Individual Dummy Variable Model, Least Squares Dummy Variable Model. Random effects model. Linear mixed regression models with both fixed and random effects. Dynamic panel data estimators. Nonlinear regression models for categorical repeated measurements: binary, categorical and counts data. Techniques for analysing longitudinal data with non-ignorable missing observations. Empirical applications will be provided using statistical software.
Module B (Alessandro Palandri): The second half of the course will introduce simulation based estimators and their properties. While the emphasis will be on Indirect Estimators (Indirect Inference and Efficient Method of Moments), other estimators that will be discussed are: Method of Simulated Moments, Simulated Quasi-Maximum-Likelihood and MCMC. Individual projects will be assigned to apply these new methodologies to practical problems in Economics and Finance.