Course unit title

Advanced Econometrics

Course unit code

EKK805

Type of course unit (compulsory, optional)

Compulsory

Level of course units (according to

EQF: first cycle Bachelor, second cycle Master)

Third cycle Doctor

Year of study when the course unit is delivered

(if applicable)

Year 1

Semester/trimester when the course unit is delivered

Semester 1

Number of ECTS credits allocated

4.8 ECTS

Name of lecturer(s)

Rossanto Dwi Handoyo, Ph.D.

Dyah Wulan Sari, Ph.D.

Learning outcomes of the course unit

Students are expected to be able to: 1) critically evaluate and build a probabilistic economic model (stochastic model); 2) perform data processing and interpret the results; 3) analyze the economy quantitatively. Thus, students are expected to be able to analyze various phenomena and empirical economics into a stochastic economic model.

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

Face to face (offline) and or distance learning (online)

Prerequisites and co-requisites (if applicable)

No

Course content

This course discusses analytical tools in quantitative form based on economics, mathematics, and statistics. The topic discussed in this lecture focuses on regression analysis that captures causality (functional) relationships. In more detail, this course material includes simple regression, multiple regression and several functional forms of regression models. Furthermore, it also examines the problem of violations of classical assumptions which include: multicollinearity, heteroscedasticity, autocorrelation, and specification errors. In addition, this course material also includes time-series models including ARIMA models, bivariate and multivariate (VAR) models, Error Correction Model (ECM) models, Vector Error Correction Model (VECM) models, and continued with models using panel data. , simultaneous equations, and probit/logit models.

Recommended or required

reading and other learning resources/tools
  1. Gujarati, Damodar N. 2008. Basic Econometrics, fifth Edition. New York: McGraw-Hill International Edition. (DNG
  2. Wooldridge, Jeffrey M., 2013, Introduction Econometrics: A Modern Approach, Fifth Edition, Thomson South-Western International Edition. (JMW)
  3. Greene, William H. 2003. Econometric Analysis, Fifth Edition. New Jersey: Prentice Hall, Inc. (WHG)
  4. Pindyck, Robert S. and Rubinfeld, Daniel L. 1998. Econometric Models and Economic Forecasts, Fourth Edition. New York: McGraw-Hill. (PR)
  5. Enders, Walter. 2004. Applied Econometric Time Series, Second Ed. New York: John Wiley & Sons. WE)
  6. Intriligator, Michael D.; Bodkin, Ronald G.; and Hsiao, Cheng. 1996. Econometric Models, Techniques, and Applications. Second Edition. Englewood Cliffs, New Jersey: Prentice-Hall Inc. (IBH)  
  7. Kmenta, Jan, 1986, Elements of Econometrics, Second Edition, New York: Macmillan Publishing. (JK)
  8. Johnston, Jack and Dinardo, John. 1997. Econometric Methods, Forth Edition. New York: McGraw-Hill. (J.D.)
  9. Maddala, G.S. 2001. Introduction to Econometrics, Third Edition, New York: John Wiley & Sons. (GSM)
  10. Maddala, GS and Kim, In-Moo. 1998. Unit Roots, Cointegration, and Structural Change (Themes in Modern Econometrics). Cambridge, UK: Cambridge University Press. (MK)
  11. Hsiao, Cheng, 1995, Analysis of Panel Data (Econometrics Society Monographs No.11), Cambridge, UK: Cambridge Univ. Press. (CH)
  12. Baltagi, Badi H. 2005. Econometric Analysis of Panel Data. Third Edition. New York: John Wiley & Sons. BHB)
  13. Patterson, Kerry. 2000. An Intro. to Applied Econometrics: A Time Series Approach. New York: Palgrave Macmillan. (KP)
  14. Harris, Richard and Sollis, Robert. 2003. Applied Time Series Modeling & Forecasting. West Sussex: John Wiley & Sons.(HS)
  15. Hamilton, James D. 1994. Time Series Analysis. Princeton, New Jersey: Princeton University Press. (JDH)

Planned learning activities and teaching methods

Teaching (Classical Method), Presentation, Discussion, Group based project, case/problem based method

Language of instruction

In Bahasa (Indonesian Language) and English

Assessment methods and criteria

Projects/papers