Module also offered within study programmes:
General information:
Name:
Introduction to applied econometrics
Course of study:
2019/2020
Code:
ZZIP-2-306-n
Faculty of:
Management
Study level:
Second-cycle studies
Specialty:
-
Field of study:
Management and Production Engineering
Semester:
3
Profile of education:
Academic (A)
Lecture language:
English
Form and type of study:
Part-time studies
Course homepage:
 
Responsible teacher:
Gurgul Henryk (gurgul@zarz.agh.edu.pl)
Module summary

The course offers introduction to applied econometrics.

Description of learning outcomes for module
MLO code Student after module completion has the knowledge/ knows how to/is able to Connections with FLO Method of learning outcomes verification (form of completion)
Social competence: is able to
M_K001 Knows advantages and weak sides of econometric modelling. ZIP2A_K01 Test
Skills: he can
M_U001 Can build and verify single-equation econometric models. ZIP2A_U01 Test
M_U002 Can interpret econometric models, including time series models. ZIP2A_U05 Test
Knowledge: he knows and understands
M_W001 Knows basic techniques of data analysis. ZIP2A_W05 Test
M_W002 Knows the role of econometrics in scientific analyses. ZIP2A_W03 Test
Number of hours for each form of classes:
Sum (hours)
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Zaj. terenowe
Zaj. warsztatowe
Prace kontr. przejść.
Lektorat
28 14 14 0 0 0 0 0 0 0 0 0
FLO matrix in relation to forms of classes
MLO code Student after module completion has the knowledge/ knows how to/is able to Form of classes
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Zaj. terenowe
Zaj. warsztatowe
Prace kontr. przejść.
Lektorat
Social competence
M_K001 Knows advantages and weak sides of econometric modelling. - + - - - - - - - - -
Skills
M_U001 Can build and verify single-equation econometric models. - + - - - - - - - - -
M_U002 Can interpret econometric models, including time series models. - + - - - - - - - - -
Knowledge
M_W001 Knows basic techniques of data analysis. + - - - - - - - - - -
M_W002 Knows the role of econometrics in scientific analyses. + - - - - - - - - - -
Student workload (ECTS credits balance)
Student activity form Student workload
Summary student workload 128 h
Module ECTS credits 5 ECTS
Udział w zajęciach dydaktycznych/praktyka 28 h
Preparation for classes 40 h
przygotowanie projektu, prezentacji, pracy pisemnej, sprawozdania 20 h
Realization of independently performed tasks 40 h
Module content
Lectures (14h):

Introduction to econometrics

Main goal of the course:

Acquirement of basic knowledge on econometric methods and their applications in quantitative analysis of economic processes as well as possession of skills of exploitation of chosen function of econometric software related to estimation and verification of linear econometric models.

Course Content:

1. Definition and subject of econometrics. Types of statistical regularities. Econometric model
2. Stages of econometric modelling
3. Estimation of structural parameters of econometric models – OLS
4. Verification of econometric models. Chosen challenges of building of econometric models
5. Autocorrelatiom
6. Heteroscedasticity
7. Nonlinear models – building and applications
8. Econometric forecasting – introduction
9. Time series analysis -introduction

Auditorium classes (14h):

Intoduction to econometrics

1. Selection of variables in econometric model. Estimation of single-equation model.
2. Hellwig’s Method. Coefficient of determination.
3. Variables significance verification. Evaluation of the parameters estimation errors.
4. Statistical verification of LSM model.
5. Heteroscedasticity.
6. Autocorrelation.
7. Econometric forecasts. EX ANTE and EX POST prediction errors.
8. Introduction to time series.

Additional information
Teaching methods and techniques:
  • Lectures: Treści prezentowane na wykładzie są przekazywane w formie prezentacji multimedialnej w połączeniu z klasycznym wykładem tablicowym wzbogaconymi o pokazy odnoszące się do prezentowanych zagadnień.
  • Auditorium classes: Podczas zajęć audytoryjnych studenci na tablicy rozwiązują zadane wcześniej problemy. Prowadzący na bieżąco dokonuje stosowanych wyjaśnień i moderuje dyskusję z grupą nad danym problemem.
Warunki i sposób zaliczenia poszczególnych form zajęć, w tym zasady zaliczeń poprawkowych, a także warunki dopuszczenia do egzaminu:

Form and terms of examination:

Students are assessed by means of a test, which verifies of achievement of educational effects of skills (3 assignments) – exercises, and their group project, which verify achievement of educational effects of skills as well as effects in social competences – (during the test students are allowed to use statistical tables and self-prepared lecture notes).

Participation rules in classes:
  • Lectures:
    – Attendance is mandatory: No
    – Participation rules in classes: Studenci uczestniczą w zajęciach poznając kolejne treści nauczania zgodnie z syllabusem przedmiotu. Studenci winni na bieżąco zadawać pytania i wyjaśniać wątpliwości. Rejestracja audiowizualna wykładu wymaga zgody prowadzącego.
  • Auditorium classes:
    – Attendance is mandatory: Yes
    – Participation rules in classes: Studenci przystępując do ćwiczeń są zobowiązani do przygotowania się w zakresie wskazanym każdorazowo przez prowadzącego (np. w formie zestawów zadań). Ocena pracy studenta może bazować na wypowiedziach ustnych lub pisemnych w formie kolokwium, co zgodnie z regulaminem studiów AGH przekłada się na ocenę końcową z tej formy zajęć.
Method of calculating the final grade:

Final grade:

Each student can be granted a satisfactory credit – when she/he is able to discuss problems related to statistical regularities, formulation of model hypothesis, estimation of structural parameters and verification of econometric models, as well as solve assignments related to this issues. The final mark is that from exam.

Sposób i tryb wyrównywania zaległości powstałych wskutek nieobecności studenta na zajęciach:

Catching-up after the absence of a student during classes takes place during office hours.

Prerequisites and additional requirements:

Prerequisites and additional requirements not specified

Recommended literature and teaching resources:

Recommended literature and teaching resources not specified

Scientific publications of module course instructors related to the topic of the module:

Additional scientific publications not specified

Additional information:

None