(in Polish) Programowanie narzędzi analitycznych II

optional courses

The main aim of this class is to develop students' abilities to create their own computer procedures, functions, and programms for statistical and econometric purposes. The course is thought to deepen students' knowledge gathered during their graduate studies. To create computer procedures and functions students will have to refer to their knowledge from courses: Statistics and Econometrics for undergraduates and Advanced Econometrics I.

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 of this class is to recollect and combine students' knowledge of statistics, undergraduate econometrics, and Advanced Econometrics. To strengthen students' self reliance some modifications of widely used models will be presented.

Topics list (lista tematow)

(1)-(2) Illustrating basic statistical notions with Monte Carlo Method (type-I and type-2 errors, control for type-I error -- Bonferroni correction and alike)

(3) Law of Large Numbers and Central Limit Theorem, Convergence in Distribution, Convergence in Probability, Convergence Almost Surely -- all with computer illustrations

(4)-(7) Programming interesting econometric models based on Maximum Likelihood Method, and other such as Cochrane-Orcutt estimator, and Seemingly Unrelated Regressions. Programming alternative versions of typical econometric models with non-standard link functions.

(8) Panel data models and their properties illustrated with Monte Carlo experiments.

(9) Programming M-estimators and alike

(10)-(11) Kernel density functions estimator and introduction to non-parametric regression.

(12)-(13) Programming Fourier Transform

(14)-(15) Programming instrumental variables method

Literatura

1. Owen Jones, Robert Millardet i Andrew Robison, Introduction to Scientific Programming and Simulation Using R, CRC Press, 2009

2. Vance Martin, Stan Hurn i David Harris, Econometric Modelling with Time Series. Specification, Estimation and Testing, Cambridge University Press, 2013

3. Badi H. Baltagi, Econometric analysis of panel data 3rd ed., John Wiley & Sons, 2005

4. Jerzy Mycielski, Skrypt do Ekonometrii, WNE UW

5. Materiały przygotowane przez prowadzącego

A) Knowledge

Student has basic knowledge of creating novel computer functions and programms for statistical and econometric purposes.

1. Student knows advantages and disadvantages of using computer programms for data analysis.

2. Students knows basic techniques and information technology tools.

3. Student knows selected analytical and computational tools out of econometrician's toolbox.

B) Abilities

Student can use statistical and econometric environments, create their own functions and programms, and adapt procedures created by other scientists and co-workers.

1. Student can perform data analysis with basic statistical software.

2. Student is able to create their own computer functions and scripts.

3. Student can prepare a function or a programm that executes nonclassical data analysis.

4. Student is prepared to work with basic data formats and structures.

5. Student can apply analytical methods for problem solving.

6. Student can make use of computer procedures created by other parties.

7. Student can adequately choose analytical tool for an economic, financial, or related problems.

8. Student has the ability of executing a series of computational and analytical operations.

9. Student is prepared to analyse critically results, interpret their economic sense, and create clear reports.

C) Social competences

Student is aware of necessity of self-improvement and life-long-learning.

1. Student can present data in a clear and understandable way.

2. Student is prepared to extend their knowledge single-handedly.

3. Student can make use of programms prepared by others and create functions understandable and useful for their team-members.

4. Student can assess usefulness of a selected tool for a given problem solving.

5. Student understands limitations of computer techniques in analysing complicated economic phenomenons.

SU05, SU06, SK01, SK03, SU04, SU03, SU02, SU01, SW03, SW02, SW01, SW04, SW05, SK02, SK04

Final grade is a weighted average of fully announced quizzes (40%), class work (20%), and final project (40%).