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Econometrics

Informacje ogólne

Kod przedmiotu: WZ-ER.047 Kod Erasmus / ISCED: (brak danych) / (brak danych)
Nazwa przedmiotu: Econometrics
Jednostka: Wydział Zarządzania i Komunikacji Społecznej
Grupy:
Punkty ECTS i inne: 5.00 (zmienne w czasie)
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Język prowadzenia: angielski

Zajęcia w cyklu "Semestr zimowy 2019/2020" (zakończony)

Okres: 2019-10-01 - 2020-01-28
Wybrany podział planu:


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Typ zajęć: Wykład, 30 godzin więcej informacji
Koordynatorzy: Yanfei Shu
Prowadzący grup: Yanfei Shu
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Egzamin lub zaliczenie
Ocena wliczana do średniej:

tak

Cele kształcenia:

Econometrics introduces you the regression methods for analyzing data in economics. This course emphasizes both the theoretical and the practical aspects of statistical analysis, focusing on techniques for estimating econometric models of various kinds and for conducting tests of hypotheses of interest to economists. The goal is to help you develop a solid theoretical background in introductory level econometrics, the ability to implement the techniques and to critique empirical studies in economics.

Wymagania wstępne:

Prerequisite


1 course with a minimum grade of C- from microeconomics or relevant courses

Forma i warunki zaliczenia:

There will be no make-up for exams unless you have a valid excuse per University policy (e.g. medical emergency). In these cases you must notify the instructor and present a formal documentation.

Actively engaging in class is an essential part in your learning process. There are 5points as a bonus to encourage your class participation. Your grades for this part will be determined on the basis of your class attendance rate and your contribution to class discussion. Throughout the semester, I may give unannounced in class quiz to check your attendance. Taking these quizzes are necessary, although may not be sufficient, to receive full bonus points.


Classroom Courtesy Coming late to class or/and leaving the classroom during the lecture will inevitably create an unnecessary disturbance for all your fellow classmates. Being late once or twice due to unforeseen reasons is understandable, but if this happens constantly, there will be actions. If your class schedule prevents you from fulfilling these requirements, you may consider enrolling in a different session. I count on your judgement and discipline regarding the uses of electronic devices in the classroom. Exercise your discipline and respect other students and the instructor.


Grades for the course will be based on:


• Homework : 30%


• software practice: 30%


• Final: 40%


• Class participation/quizzes: 5% (bonus)

Bilans punktów ECTS:

Participation in interactive lectures: 30 hours

Participation in the exam (including consultations after the exam): 3 hours

Preparation for tasks, group work assignments: 80 hours

Preparation for the final exam: 35 hours


Total student workload is 148 hours, which is equivalent to 5 ECTS

Grupa treści kształcenia:

Grupa treści kształcenia do wyboru

Skrócony opis:

Econometrics introduces you the regression methods for analyzing data in economics. This course emphasizes both the theoretical and the practical aspects of statistical analysis, focusing on techniques for estimating econometric models of various kinds and for conducting tests of hypotheses of interest to economists. The goal is to help you develop a solid theoretical background in introductory level econometrics, the ability to implement the techniques and to critique empirical studies in economics.

This course will use STATA or Eviews as our main statistical software. The latest version is STATA 13 or Eviews 10, but any version later than STATA 6 or Eviews 6 suffices for the purpose of this course

Pełny opis:

Part I

· A. Review of probability and statistics

o 1. Probability and distribution

o 2. Expectation and moments

· B. Review of statistical inference

o 3. Sampling distributions and inference

o 4. The Central Limit theorem (Asymptotic distribution of the sample mean)

o 5. Confidence intervals

· C. Regression basics

o 6. Conditional expectation functions, bivariate regression

o 7. Sampling distribution of regression estimates; Gauss-Markov theorem

o 8. How classical assumptions are used; asymptotic distribution of the sample slope

o 9. Residuals, fitted values, and goodness of fit

Part II

· D. Multivariate regression

o 10. Regression, causality, and control; anatomy of multivariate regression coefficients

o 11. Omitted variables formula, short vs. long regressions

o 12a. Dummy variables and interactions; testing linear restrictions using F-tests

o 12b. Regression analysis of natural experiments, differences-in-differences

· E. Inference problems - heteroscedasticity and autocorrelation

o 13a. Heteroscedasticity, consequences of; weighted least squares; the linear probability model

o 13b. Serial correlation in time series, consequences of; quasi-differencing; common-factor restriction; Durbin-Watson test for serial correlation

· F. Instrumental variables, simultaneous equations models, measurement error

o 14a. Using IV to solve omitted-variables problems

o 14b. Measurement error (Time-permitting)

o 14c. Regression-discontinuity designs (Time-permitting)

· G. Simultaneous equation models

o 15. Simultaneous equations models I

§ a. The use of structural models

§ b. Simultaneous equations bias

§ c. The identification problem

§ d. The structure and the reduced form

§ e. Indirect least squares

o 16. Simultaneous equations models II

§ a. IV for the SEM

§ b. Two-stage least squares

§ c. Sampling variance of 2SLS estimates

Literatura:

Textbook Required Textbook:

• [W] Jeffrey M. Wooldridge, “Introductory Econometrics: A Modern Approach”, 5th edition, South-Western College Pub. - This textbook contains required exercises/readings. Earlier editions are acceptable, while page numbers may differ.

Other references:

• [SW] James H. Stock and Mark W. Watson, “Introduction to Econometrics”, 3rd edition, Prentice Hall. - Lectures in time series part will follow more closely on this textbook.

Uwagi:

The final exam will take place on Friday, December 13 2019.

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