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Macroeconometrics

General data

Course ID:	2400-ICU1MAR
Erasmus code / ISCED:	14.3 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0311) Economics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Macroeconometrics
Name in Polish:	Macroeconometrics
Organizational unit:	Faculty of Economic Sciences
Course groups:	English-language course offering of the Faculty of Economics Mandatory courses for 1st year students of International Economics
ECTS credit allocation (and other scores):	6.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	obligatory courses
Short description:	Master's level course. This course provides a survey of empirical research techniques used in modern macroeconomic research. As a graduate course, it demands completion of undergraduate instruction in econometrics. Assessment is based on a written end-term exam. Final grade is 60% exam and 40% problem sessions (estimation of model) Exam questions are given in advance but the exam is closed-book. Remarks: Prerequisites: intermediate courses in econometrics, probability, and statistics.
Full description:	Systems of simultaneous equations [1,2,3] - structural and reduced forms (multipliers and structural parameters) - identification - endogeneity, simultaneity and Haavelmo bias - estimation methods - partial and full information methods (OLS, 2SLS, 3SLS,FIML) Univariate dynamic models [4,5,6] - ADL models - General to specific analysis - Short and long run multipliers, mean lag - Long run equilibrium, steady state - Geometric lags (Koyck transformation), Almon lags - Seasonality - Polynomials of lag operator - Integration and cointegration, ECM and Granger theorem (unit root tests, two step Eagle-Granger procedure) Multivariate dynamic models [7,8,9] - Sims critique of classical structural models - VAR model - definition - Granger causality - Impulse response analysis (unit and orthogonal shocks) - SVAR - structural shock analysis - VECM and Johansen test, identification of cointegrating vectors - Structural breaks (CUSUM, Chow test) Forecasting [10] - Forecasting with ARIMA models - Forecasting with VAR and VECM - Forecast variance decomposition - Forecast tests Estimation of models based on rational expectation assumption [11] - Formulation of moments restrictions - Model based on rational expectations assumption - GMM estimation and testing Real business cycles, general equilibrium and calibration methods [12] - Lucas critique of simultaneous equations models - General equilibrium and real business models - estimation problems - Benchmarking and solving for parameters values - Comparison of calibration vs. econometric techniques Signal extraction, smoothing, filters and state space models [13] - Beveridge-Nelson decomposion - Hodrick-Prescott decomposition - State space models - Kalman filter - Applications of state space models
Bibliography:	Required readings: - W. Charemza, D. Deadman, New Directions in Econometric Practice: General to Specific Modelling, Cointegration and Vector Autoregression, 2nd edition, Edward Elgar, 1997 - William Greene, Econometric Analysis, Prentice Hall 2003 Suggested readings: - W. Enders, Applied Econometric Time Series, John Wiley and Sons, 1995 - J.J. Heckman, E. Leamer, Handbook of Econometrics, Elsavier Science, 2001
Learning outcomes:	KW01, KW02, KW03, KW04, KW05, KU01, KU02, KU03, KU04, KU05, KU06, KU07, KK01, KK02, KK03

Classes in period "Summer semester 2023/24" (in progress)

Time span:	2024-02-19 - 2024-06-16	Selected timetable range: weekly course term Navigate to timetable MO TU WYK CW W TH FR
Type of class:	Classes, 15 hours more information Lecture, 30 hours more information
Coordinators:	Jerzy Mycielski
Group instructors:	Łukasz Goczek, Jerzy Mycielski
Students list:	(inaccessible to you)
Examination:	Course - Examination Classes - Grading Lecture - Examination

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