Models and Methods Władysław Welfe Welfe A., , Ekonometria. Welfe W., Welfe A., , Ekonometria stosowana, (Applied Econometrics), II edition. Welfe, W., & Welfe, A. (). Ekonometria stosowana (Applied econometrics) ( 2nd ed.). Warszawa: PWE. Whitley, J. (). A course in macroeconomic. Welfe A., Welfe W. () Ekonometria stosowana (Applied Econometrics). PWE, Warsaw. Macroeconomic Forecasts in Transition – Polish Projections in the.
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You are not logged in log in. Additional information registration calendar, class conductors, localization and schedules of classesmight be available in the USOSweb system: Metody i ich zastosowanie, PWE, Warszawa Record of the linear stoxowana power model 2. The main aim of the laboratory is to familiarize students with practice of econometric modelling.
An example of the seasonality of economic phenomena. Wide using of computer programs to built econometric models e. Structure of links and multi-equation classification 3. Factors of material consumption, labor consumption and their stosowxna. Almon, The Craft of Economic Modeling.
Single-equation descriptive models 2. Assumptions of the stochastic structure of the model. Statistical evaluation of the econometric model verification of appropriate statistical hypotheses, methods for assessing the goodness of model estimation.
Modeling factors and objectives 2. Descriptive econometric models – general characteristics and examples of applications.
Forecasting based on an econometric model. The subject learning outcomes for the form of lecture and exercises: Input-output models – input-output table in terms of quantity and value – technical factors and basket factors – Leontief’s model and its solutions in terms of quantity and value – price model.
Stosowaan is able to: Showing them examples of practical use of econometric methods. Non-measurable factors in econometric models. Assumptions of the stochastic structure of the model, examination of the properties of the random component, selection of estimators, selection of the ekonomeetria method. Stages of econometric analysis. Descriptive econometric models – selection of variables for the model and approximation function, construction, estimation of MNK, interpretation, evaluation and application in logistic decisions.
Classification of econometric models 1. Methods of estimation of econometric models, conditions of their applicability. Ability of analysing input-output models. Variables and parameters in the descriptive model.
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Skills of building and estimating econometric models and using them in practice. Intermediate flows and balance models. Beck, Warszawa, Welfe A. Heteroscedasticity and autocorrelation of a random component, testing of appropriate hypotheses. Passing exercises based on the project, a written work consisting of a task test and activity in class – participation in solving practical problems classes 15h, current work 15h, preparation for passing 30h – 60h. Input-output table in static approach and balance equations.
Introduction to econometrics ewlfe of econometrics, the concept of an econometric model, classification of econometric models. Generalized least squares method. Verification of the econometric model, economic interpretation of the estimation results.
Concept and classification of multipliers 3.
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Part I by Clopper Almon A. The least-squares method in the matrix notation, properties of the MNK estimators. Total for the subject: Faculty of Economics and Sociology. Modeling of economic phenomena – introductory issues 1.
Additional information registration calendar, class conductors, localization and schedules of classesmight be available in the USOSweb system:.