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Zagrebačka škola ekonomije i managementa Syllabus: Econometrics SYLLABUS Econometrics (ECTS 8) LECTURERS Lecturers Ivo Krznar Davor Kunovac Contact E-mail: ivo.krznar@hnb.hr davor.kunovac@hnb.hr COURSE DESCRIPTION The Econometric course introduces students to classical theory of econometrics. Student will become familiar with classical regression theory, estimation using ordinary least square methods as well as theory behind maximum likelihood methods and generalized method of moments. Different methods of hypothesis testing will be introduced, specific for each of the stated estimation methods. Apart from elaboration of theory of each of the mentioned concepts, a computer practicum will be an integral part of this course where students will familiarize themselves with applications of theoretical constructions. HOURS Theoretical classes PC lab Total 30 hours (15 weeks * 2 hours) 30 hours (15 weeks * 2 hours) 60 hours PREREQUISITES Students are also expected to be familiar with statistics and maths course from the prep semester as well as Eviews 6 (or higher) basics. GRADING Your grade will be determined based on 2 midterms each of which will carry 25% of the total grade and the exam at the end of classes (with the weight of 50%). Midterms will either require in-depth literature reviews or problem solving. One should expect the following percentage performance/grade schedule: 90-100% = excellent (5), 80-89% = very good (4), 1 Syllabus: Econometrics Zagrebačka škola ekonomije i managementa 70-79% = good (3), 55-69% = pass (2). PRELIMINARY COURSE OUTLINE 1) Introduction to econometrics, a historical overview of development of econometrics, classical regression model and OLS method, descriptive properties of OLS estimators 2) Statistical properties of OLS estimators, Gauss-Markov theorem 3) Hypothesis testing I (D-method, least sum of residuals method, ANOVA method) 4) Hypothesis testing II (D-method, least sum of residuals method, ANOVA method) 5) Asymptotic theory I , modes of convergence, central limit theorem 6) Asymptotic theory II , modes of convergence, central limit theorem 7) Maximum likelihood theory (ML), ML estimator and its properties, information matrix, Cramer-Rao theorem 8) Asymptotic properties of ML estimators 9) ML tests (Likelihood ratio, Wald test) 10) Qualitative variables (logit, probit, tobit) 11) QML and generalized linear model 12) Heteroskedasticity , White estimator, White test, Soldfeld-Quandt test, Gleisjer test, 13) Autocorellation, Newey-West estimator, FGLS, Durbin-Watson test, Godfrey test, Box-Pierce test 14) Exogenity and simultaneity I (simultaneous equations and exogenity) 15) Exogenity and simultaneity II (instrumental variables, Hausman test) READING LIST R. Davidson i James G. MacKinnon (1993), Estimation and Inference in Econometrics, Oxford University Press R. Davidson i James G. MacKinnon (2004), Econometric theory and methods, Oxford University Press M. Creel (2008), Econometrics, Universitat Automona de Barcelona W. Greene (2003), Econometric Analysis, Prentice Hall, 5th Edition F. Hayashi (2000), Econometrics, Princeton University Press J.D. Hamilton (1994), Time series analysis, Princeton University Press 2