COMPUTABLE SIMULATION OF MARKETS OR PUBLIC POLICIES

General data

Course ID:	2400-SU2TS52
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:	COMPUTABLE SIMULATION OF MARKETS OR PUBLIC POLICIES
Name in Polish:	COMPUTABLE SIMULATION OF MARKETS OR PUBLIC POLICIES
Organizational unit:	Faculty of Economic Sciences
Course groups:	(in Polish) Przedmioty 4EU+ (z oferty jednostek dydaktycznych)
ECTS credit allocation (and other scores):	(not available) 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:	Master's seminars
Short description:	The course aim is to learn market analysis using available data and to make a simulation of market distortions based on existing nonlinear optimization models.
Full description:	How to define a market? There is no single definition, because it depends on the type of analysis. The goal of the seminar is to show how markets can be analyzed from the general perspective. Statistical offices publish an input-output table that shows a relationship between production sectors. It can be interpreted as a relationship between markets. When more detailed data are available, the markets can be defined in a different way. In order to provide a computable simulation of selected market or economy, we will use a mathematical software GAMS. Students will have an opportunity to learn simple modeling of markets and how to make a simulation of government policies. The course aim is to help students to prepare a Master thesis. Students will be expected to select a topic, read an appropriate literature, to make a class presentation of the work progress, and to prepare a final paper. Papers will be graded based on their clarity and academic quality. The most welcome topics are market research, econometric analysis, general equilibrium modeling, environmental economics. Students may offer their own topic.
Bibliography:	GAMS documentation, http://www.gams.com/docs/document.htm. The free version is enough to provide simple simulations A. Brook, D.Kendrick, A.Meeraus (1988), GAMS a User’s Guide, The Scientific Press E. J. Chambers and D. F. Gordon (1966), "Primary products and economic growth: an empirical measurement", Journal of Political Economy 74, 315-332. R. W. Fogel (1967), "The specification problem in economic history", Journal of Economic History 27, 283-308. R. W. Jones (1965), "The structure of simple general equilibrium models", Journal of Political Economy 73, 557-572. Z.Wang, J.Slagle (1996), “An Object-oriented Knowledge-based Approach for formulating applied general equilibrium models”, Journal of Economic Dynamics and Control 20, 209-236 I.S.Wing (2004), Computable general equilibrium models and their use in economy-wide policy analysis: Everything you ever wanted to know (but were afraid to ask), MIT Technical Note 6
Learning outcomes:	Upon the seminar completion, students will be able to provide simple simulations of economic activities, to use a software GAMS (general algebraic modeling system), to analyze input-output flows and other statistical data, to provide market analysis.
Assessment methods and assessment criteria:	Literature review, programing language MPSGE, simple computable simulations, results interpretation. Applied tools - video platforms for remote learning approved by the University of Warsaw. Attendance verification – the attendance is not necessary, but the thesis progress is required. The final evaluation will be based on the completed thesis.

This course is not currently offered.

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Copyright by University of Warsaw.