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Econometric and statistical modelling in R

Informacje ogólne

Kod przedmiotu: 2400-ZEWW817 Kod Erasmus / ISCED: 14.3 / (0311) Ekonomia
Nazwa przedmiotu: Econometric and statistical modelling in R
Jednostka: Wydział Nauk Ekonomicznych
Grupy:
Punkty ECTS i inne: 3.00
zobacz reguły punktacji
Język prowadzenia: angielski
Rodzaj przedmiotu:

nieobowiązkowe

Skrócony opis: (tylko po angielsku)

Course is designed for MA students, who already are on intermediate level in statistics and econometrics. Topics are presented as an overview of methods to solve given problem. Class in is applied form – formulas and formal estimators are limited, while it stresses the proper scientific usage. Reading is based on scientific papers, to understand how scholars use and describe the methods in real research and publications. Class is in R software, students should know the basics of R. Topics cover statistics and econometrics, especially: fitting of statistical distributions, inequality measures, Monte Carlo simulations, Bootstrapping, Survey data analysis, regression and hierarchical linear models as well as propensity score matching, difference in difference and regression discontinuity.

Pełny opis: (tylko po angielsku)

Applied statistical modeling

[1] Statistical distributions – types of probability distributions, generating random variables, testing consistency, differences and similarities, usage of probability distributions

[2] Inequality measures – one-dimensional and two-dimensional measures (e.g. Gini, Herfindahl, entropy, KLD, mutual information)

[3] Monte Carlo simulations – formulating the problem and underlying distributions, aggregation and distributions of results, confidence intervals, sensitivity analysis

[4] Bootstrapping – sampling and replications issues, aggregation of independent and inter-dependent results, confidence intervals, sensitivity analysis, strata sampling

[5] Survey data analysis - discriminant analysis, factor analysis, non-parametric tests, different measurement scales, rand index, mantel test

Applied econometric modelling

[6] Regression and hierarchical linear models - model and variable selection, estimation, testing, forecasting, missing data issues

[8] Propensity score matching, difference in difference, regression discontinuity - model and variable selection, estimation, testing, forecasting, missing data issues, quality of fit

Literatura: (tylko po angielsku)

[1] Damodar, G. (2013). Econometrics by example, The McGraw-Hill/Irwin Series in Economics

[2] James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning. New York: Springer.

http://faculty.marshall.usc.edu/gareth-james/ISL/ISLR%20Seventh%20Printing.pdf

[3:n] Papers selected for classes

Efekty uczenia się: (tylko po angielsku)

- Students know the popular statistical and econometric methods, and their software solutions in R

- students are able to use statistical and econometric methods to solve economic problem

- students understand the scientific approach to statistical and econometric methods, and are able to comment on them after reading the professional research paper

- students discuss and comment on quantitative methods, are able to review and present the paper

Metody i kryteria oceniania: (tylko po angielsku)

Grading scale: 0%-50% - 2 (negative), 50%-60% - 3 (sufficient), 60%-70% - 3+ (more than sufficient), 70%-80% - 4 (good), 80%-90% -4+ (more than good), 90%-95% -5 (very good), 95%-100% - 5! (with honours)

1) Each student is to review (orally) the assigned paper on selected quantitative topic during the class – extra points are given to the audience for discussion

2) Attendance is obligatory – for each absence students write the paper on omitted topic (topics will be given before the class)

3) Students are to find a paper which deals with “their” topic and uses the quantitative methods and to replicate (and possibly develop) the study on similar data (collected or generated)

4) Points collection:

a. max. 20 points review & oral presentation of assigned paper,

b. max. 20 points – activity during classes (esp. discussion of others reviews)

c. max. 60 points – own paper as in 3)

d. 0-1 criteria – attendance or papers for absence

Zajęcia w cyklu "Semestr letni 2020/21" (zakończony)

Okres: 2021-02-22 - 2021-06-13
Wybrany podział planu:


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Typ zajęć: Konwersatorium, 30 godzin więcej informacji
Koordynatorzy: Katarzyna Kopczewska
Prowadzący grup: Katarzyna Kopczewska
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie na ocenę
Konwersatorium - Zaliczenie na ocenę
Tryb prowadzenia:

zdalnie

Przedmiot dedykowany programowi:

4EU+KURSY

Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Warszawski.