Programming Analytical Methods 2400-M1IiEPNA

To propose a novel econometric or statistical tool there is a necessity of programming it. More often than not, in academic work or data analysis at work existing programms adjustments appears. Because of atypical data features, econometricians have to propose a novel method to handle them. The purpose off this class is to recollect and combine students' knowledge of statistics, undergraduate econometrics.

Topics list (lista tematow)
(1) Introduction to R, basic calculations, creating vectors and matrices.
(2) Programming basic statistical tests.
(3) Programming the Ordinary Least Squares Method.
(4) Introduction to the Maximum Likelihood Method.
(5) Likelihood plots. Maximizing one parameter log-likelihood functions.
(6) Maximizing multiparameter log-likelihood functions using their gradients and Hessian. 3D plots.
(7) Introduction to the Method of Moments.
(8) Introduction to the Generalised Method of Moments.
(9) The Generalised Method of Moments estimation.
(10) Colloquium
(11) Bootstrap
(12)-(15) Monte Carlo Method and experiments.

Szacunkowy nakład pracy studenta:
Typ aktywności K (kontaktowe) S (samodzielne)
wykład (zajęcia) 30 0
ćwiczenia (zajęcia) 0 0
egzamin 3 0
konsultacje 15 0
przygotowanie do ćwiczeń 0 25
przygotowanie do wykładów 0 0
przygotowanie do kolokwium 0 15
przygotowanie do egzaminu 0 0
… 0 12
Razem 48 52 = 100

1. Materiały przygotowane przez prowadzącego
2. Givens G.H., Hoeting J.A., Computational Statistics, John Wiley & Sons, 2012
3. Laura M. Chihara,Tim C. Hesterberg, Mathematical Statistics with Resampling and R, John Wiley & Sons, 2011
4. Mycielski J., Skrypt do Ekonometrii, Wydział Nauk Ekonomicznych