Econometrics-2Syllabus

Subject code

IF-2607y

Credits

5

Student workload

120

Semester

Spring semester

Academic year

2025-2026

Subject type

Mandatory

Form of education

Full-time

Language of instruction

English

In-class hours

a) Of these, 15 hours are allocated to lectures and b)30 hours to practical classes

Out-of-class hours

a) 60saat sərbəst iş, b) 45 saat hazırlıq

The teaching of the subject “Econometrics” is planned to include 45 hours of classroom hours. Of these, 15 hours are allocated to lectures and 30 hours to practical classes. Students’ independent work (TSI) is 120 hours. This includes SI – the performance and submission of independent work, preparation for lectures, seminars, laboratory classes, and colloquiums. Students are given 1 to 5 independent tasks or 2-5 students are given 1 independent task in groups. Each of the independent tasks is evaluated on a scale of 1-10, and a total of 10 points are allocated for the semester. If necessary, students may be given 1 independent task of a larger and more scientific nature. At this time, that free assignment is evaluated on a 10-point scale. At the end of the semester, the student's attendance in the subject is evaluated with 10 points, practical classes and colloquiums with 30 points, and free assignments with 10 points. The remaining 50 points in the subject are determined by the exam. The teaching load is planned to be fulfilled in the 2nd semester. The teaching of the subject results in an exam. The educational program provides for 10 credits for the subject.

• lecture
• interactive discussion
• seminar
• case study
• presentations

No learning outcomes have been added.

1. 1.
   Nonlinear regression analysisLecture

   Nonlinear regression analysis

2. 2.
   Panel data analysis. regression equation with panel dataLecture

   Panel data analysis. regression equation with panel data

3. 3.
   Stationarity problems in time seriesLecture

   Stationarity problems in time series

4. 4.
   Preparation of forecastsLecture

   Preparation of forecasts

5. 5.
   Nonlinear regression analysisLecture

   Nonlinear regression analysis

1. G.s. maddala/ introduction to economterics. second edition. 2. jeffrey m. wooldridge. introductory econometrics. a modern approach 3. damodar n. gujarati, dawn c. porter. basic econometrics. fifth edition.