Szeptember - 2018
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Tantárgy adatlap

Econometrics I.

Tantárgy adatlap letöltése: Letöltés

A tantárgy kódja: 4ST14NAK30B
A tantárgy megnevezése (magyarul): Econometrics I.
A tantárgy neve (angolul): Econometrics I.
A tanóra száma (Előadás + szeminárium + gyakorlat + egyéb): 14 lectures + 14 seminars
Kreditérték: 6
A tantárgy meghirdetésének gyakorisága: once every spring semester
Az oktatás nyelve: English
Előtanulmányi kötelezettségek: Statistics I., Statistics II.
A tantárgy típusa: core
Tantárgyfelelős tanszék: Statisztika Tanszék
A tantárgyfelelős neve: Keresztély Tibor

A tantárgy szakmai tartalma: The course covers standard topics in multiple linear regression analysis and some of its extensions and departures. The general linear model and the ordinary least squares (OLS) estimation method are considered a starting point for the course. Core issues of model selection, model specification, hypothesis testing, model diagnostics, multicollinearity, and heteroskedasticity are covered in sufficient detail. Additional topics include non-linear models, limited dependent variable models, quantile regression, generalized least squares (GLS) estimation and Maximum Likelihood estimation. The course intends to place a strong emphasis on discussing the criteria for unbiased and statistically consistent quantification of causal effects.

Évközi tanulmányi követelmények: Rregular attendance of lectures and seminars is strongly recommended.

Vizsgakövetelmény: final exam for 50 points

Az értékelés módszere: End-term grade is based on the total score obtained on (1) the final exam, (2) three out of four mid-term quizzes, (3) research paper prepared by the student.

Tananyag leírása: (1) Nature of Econometrics and Economic Data. (2) Introduction to multiple regression analysis. (3) Ordinary Least Squares arithmetics. (4) Linear variable transformations:
rescaling and standardization. (5) Measures of relationship in the multiple regression
model. (6) Statistical properties of the OLS estimator. (7) Inference in the multiple linear regression model. (8) Regression model building. (9) General Linear Model. (10) Qualitative Variables in the Regression Model. (11) Heteroscedasticity. (12) Quantile Regression. (13) Maximum Likelihood Estimation. (14) Models with discrete valued dependent variable.

Órarendi beosztás: 

Kompetencia leírása: By the end of the course, students will have gained competence in formulating and applying econometric models for various types of analyses in business and economics; selecting among alternative model versions; selecting the set of variables significantly related to the phenomenon of interest; choosing appropriate estimation methods for different types of econometric models; exploring statistical relationships among multiple variables; quantifying the partial effect of changes in regressor values on the value of the dependent variable; formulating and testing research hypothesis within a regression model; providing out-of sample estimates for dependent variable values.

Félévközi ellenőrzések: 4 mid-term quizzes for 10 points each

A hallgató egyéni munkával megoldandó feladatai: empirical research paper for 20 points

Szak neve: Applied Economics

Kötelező irodalom:

  • Detailed lecture notes will be provided on-line.

Ajánlott irodalom:

  • Jeffrey M. Wooldridge: Introductory Econometrics – A Modern Approach (4th Edition)
Ajánlott irodalmak:
Jeffrey M. Wooldridge: Introductory Econometrics – A Modern Approach (4th Edition)
Kötelező irodalmak:

A tantárgy oktatói:

Utolsó módosítás: 2018-09-11 11:00:53


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