Advanced Econometrics Course unit title Advanced Econometrics Course unit code EKK805 Type of course unit (compulsory, optional) Compulsory Level of course unit (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 model models. Recommended or required reading and other learning resources/tools Gujarati, Damodar N. 2008. Basic Econometrics, fifth Edition. New York: McGraw-Hill International Edition. (DNG Wooldridge, Jeffrey M., 2013, Introduction Econometrics: A Modern Approach, Fifth Edition, Thomson South-Western International Edition. (JMW) Greene, William H. 2003. Econometric Analysis, Fifth Edition. New Jersey: Prentice Hall, Inc. (WHG) Pindyck, Robert S. dan Rubinfeld, Daniel L. 1998. Econometric Models and Economic Forecasts, Fourth Edition. New York: McGraw-Hill. (PR) Enders, Walter. 2004. Applied Econometric Time Series, Second Ed. New York: John Wiley & Sons. WE) Intriligator, Michael D.; Bodkin, Ronald G.; dan Hsiao, Cheng. 1996. Econometric Models, Techniques, and Applications. Second Edition. Englewood Cliffs, New Jersey: Prentice-Hall Inc. (IBH) Kmenta, Jan, 1986, Elements of Econometrics, Second Edition, New Yor: Macmillan Publishing. (JK) Johnston, Jack dan Dinardo, John. 1997. Econometric Methods, Forth Edition. New York: McGraw-Hill. (JD) Maddala, GS. 2001. Introduction to Econometrics, Third Edition, New York: John Wiley & Sons. (GSM) Maddala, G.S. dan Kim, In-Moo. 1998. Unit Roots, Cointegration, and Structural Change (Themes in Modern Econometrics). Cambridge,UK: Cambridge University Press. (MK) Hsiao, Cheng, 1995, Analysis of Panel Data (Econometrics Society Monographs No.11), Cambridge, UK: Cambridge Univ. Press. (CH) Baltagi, Badi H. 2005. Econometric Analysis of Panel Data. Third Edition. New York: John Wiley & Sons. BHB) Patterson, Kerry. 2000. An Intro. to Applied Econometrics: A Time Series Approach. New York: Palgrave Macmillan. (KP) Harris, Richard dan Sollis, Robert. 2003. Applied Time Series Modelling & Forecasting. West Sussex: John Wiley & Sons.(HS) 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 Project/paper