Econometrics

Course unit titles

Econometrics

Course unit code

MNK628

Type of course unit (compulsory, optional)

Compulsory

Level of course units (according to

EQF: first cycle Bachelor, second cycle Master)

Master Program of Islamic Economics

Year of study when the course unit is delivered

(if applicable)

Second year

Semester/trimester when the course unit is delivered

3rd semester

Number of ECTS credits allocated

3 credits (4.8 ECTS)

Name of lecturer(s)

Sulistya Rusgianto, SE, M.IF., Ph.D

Dr. Ririn Tri Ratnasari

Learning outcomes of the course unit

After finishing the course, students are expected to be able to explain and choose the right econometric methodology to answer research problems in Islamic economics and finance, apply Multiple Linear Regression modeling to answer research problems in Islamic economics and finance, apply Structural Equation Modeling to answer research problems in economics and finance, applying Panel Data Regression modeling to answer research problems in Islamic economics and finance, applying Time Series modeling to answer research problems in Islamic economics and finance, applying Volatility modeling to answer research problems in Islamic economics and finance, and explain the basics of Big Data analysis and Artificial Intelligence using machine learning.

Mode of delivery (face-to-face, distance learning)

face-to-face, distance learning

Prerequisites and co-requisites (if applicable)

---

Course content

This course studies various econometric models to answer research problems in Islamic economics and finance. The basic methods studied include multiple linear regression, panel data regression, Structural Equations Modeling, time-series and volatility modeling. Also introduced are the basics of Big Data analysis and Artificial Intelligence using machine learning. The basic method is expected to be a provision for independently studying various econometric methods that are rapidly developing. The learning method used is Project-based learning by using econometric software which is popularly used in research. During project implementation, coaching will be conducted to help students apply econometric methods appropriately.

Recommended or required

reading and other learning resources/tools

1. Gujarati, Damodar N. 2003. Basic Econometrics, Fourth Edition. New York: McGraw-Hill International Edition

2. Ghozali, I. and Ratmono, D. 2017. Multivariate and Econometric Analysis. Diponegoro University Publishing Agency, Semarang

3. Asteriou, D. and Hall, S.G. 2007. Applied Econometrics. Palgrave Macmillan, New York

4. Hair, Joseph F., Black, William C., Babin, Barry J., Anderson, Rolph E. 2010. Multivariate Data Analysis, Seventh Edition, New Jersey: Pearson Prentice Hall (MDA)

5. Witten, IH, Frank, E. and Hall, M.A. 2011. Data Mining. Morgan Kaufmann Publishers, Burlington

6. Relevant Similar References

Planned learning activities and teaching methods

Explanation of learning methods and Discussion of teaching materials

Language of instructions

English

Assessment methods and criteria

Projects and Peer Reviews