Předmět Quantitative Methods in Development Economics (IEI25E)

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Materiál	Typ	Datum	Počet stažení

Osnova

PřednáškaIntroduction: course objectives and requirements, excel, statistical packages and GAMSIntroduction to modelling and to GAMSFarm modelsPartial equilibrium models - sectoral modelsIntroduction in general equilibrium modelling: I/O models, SAM models, CGE modelsScenarios, sensitivity analyses, further trends in economic modellingBasic statistical terms (moments, covariance, correlation, sample and sample statistics); Hypotheses testingLinear model: Analysis of variance (ANOVA)Chi-square methods (contingency tables)Nonparametric statistical methodsQuantitative approaches to qualitative dataPresentation of group worksCvičeníModel applications in GAMS - farm modelModel applications in GAMS - farm and sectoral modelsI/O models in Excel and in GAMSStatistical exercises: Analysis of varianceStatistical exercises: Contingency tables, nonparametric methodsStatistical exercises: nonparametric methodsPresentation of group work

Získané způsobilosti

Znalosti:Graduates have got good orientation in basic quantitative methods in economics and sociology. They understand that analysing economic and sociological issues require building a model representing complex reality; the models ought to be theoretically justifiable. They understand the difference between partial and general equilibrium models. They acquire knowledge of modelling approaches rooted in mathematical programming and mathematical economics. They understand the principles of finding optimums of economic functions subject to constraints and of solving sets of linear and nonlinear equations. They understand that complex models generate computational and numerical problems and that it is important to use appropriate numerical methods and software. Their knowledge also covers the challenges in respect to statistical inference. They understand the idea of hypothesis testing. They also understand the difference between continuous and discrete random variables/ data and their distributions. They understand that one should think about hypotheses testing prior collecting data.Dovednosti:Students are able to construct simple economic models like farm model, agricultural sector model, I-O model), they can define the model structure, collect and process data in model parameters. They are aware of mathematical software suitable for solving these models and they are able to use it in basic manner, in particular in GAMS (general algebraic modelling software). Students can transpose economic problems in scenarios, run scenarios and interpret them. They can run sensitivity analysis. Students are to state statistical hypotheses and to choose adequate models/methods for their testing. In particular, they are able to design a qualitative questionnaire relevant to the economic or sociological problem and suitable for statistical evaluation (testing of hypotheses). Kompetence - komunikace:They are able to correctly formulate economic problems and transpose them in mathematical or statistical models. They are able to work effectively and in partnership with other experts (represented by their colleagues) and they are able effectively communicate their knowledge to clients (represented by teachers). Students also understand that using more advanced quantitative methods might require collaboration with specialists - mathematicians, statisticians on one hand and with natural and social scientists on the other hand and there are able to communicate with the both groups.Kompetence - úsudek:They are able to interpret model solutions and statistical results in the language of economists, other social science experts, entrepreneurs and managers, and policy makers. They are aware of limitations of their competence in the area and of the need to continuously expand their knowledge or skills.

Literatura

ZákladníHazell, P. B. R.. Norton, Roger D. (1986] Mathematical programming for economic analysis in agriculture. Macmillan. http//www.ifpri.org/publication/mathematical-programming-economic-analysis-agricultureSwinton, S.M. and J.R. Black. 2000. Modeling of Agricultural Systems. Staff Paper No. 00-06, Dept. of Agricultural Economics, Michigan State University, East Lansing, MichiganWackerly, D.D., Mendenhall W., Scheaffer, R., L. () Mathematical Statistics with Applications. 7th edition. Thomson Learning, Inc., ISBN-13 978-0-495-38508-0, (also online http//fvela.files.wordpress.com/2012/01/mathematical_statistics_with_applications1.pdf

Požadavky

None

Garant

Dr. RNDr. Tomáš Ratinger, Ph.D.