This course serves as an introduction to statistical inference and econometrics at the graduate level. First, basic concepts in probability theory (i.e., random variables, their distributions, and their moments) are reviewed. Next, we move to statistical inference. Methods for point and interval estimation (least-squares, maximum likelihood, and method of moments) are introduced and criteria for evaluating their performance (bias, efficiency, consistency, and various risk measures) are discussed. Procedures to perform hypothesis testing (t-test, F-test, Wald, Likelihood ratio, and Lagrange multiplier) are also developed. Finally, estimation and testing in the linear regression model is studied in detail.
Jean-Marc ROBIN,Mattis GILBERT
Cours magistral et conférences
English
Aucun
Autumn 2023-2024
Statistical Inference by G.C. Casella and R.L. Berger (2008)