Most widely held works by Jan Bogusław Gajda. Ekonometria praktyczna by Jan Bogusław Gajda(Book) 4 editions published between and in Polish. Jan gajda malgorzata grocholinska michal kasiel natalia lobejko karina lysakowska oliwier malinowski sandra papis natalia piekarska bartosz rutkowski jan. Course coordinators. Jan Gajda Gajda J., Prognozowanie i symulacje a decyzje gospodarcze, wyd. C. H. Beck, Warszawa Ekonometria. Prognozowanie.
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Intermediate flows and balance models. Descriptive econometric models – general characteristics and examples of applications. Neural networks in forecasting.
Additional information registration calendar, class conductors, localization and schedules of classesmight be available in the USOSweb system:. Forecasting based on an econometric model. Introduction to optimization with the Excel Solver tool.
Assumptions of the stochastic structure of the model, examination of the properties of the random component, selection of estimators, selection of the estimation method. Classification of econometric models 1. The project requires the theory, described during classes, to be applied to a specific problem in finance or economics.
Discrete event simulation — dynamic simulations model changes in a system in response to input signals. Measurement of forecasting error ex ante and ex post. 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. Sampling from probability distributions — inverse transform method. Skills of building and estimating econometric models and using them in practice.
Generalized least squares method. Student is able to: Discrete event simulation — dynamic simulation and simulation of the next event. Part I by Clopper Almon A. Stages of econometric analysis. Structure of links and multi-equation classification 3.
Verification of the econometric model, economic interpretation of the estimation results.
Descriptive econometric models – selection of variables for the model and approximation function, construction, estimation of MNK, interpretation, evaluation and application in logistic decisions. Written report should be submitted.
Faculty of Economics and Sociology. Additional information registration calendar, class conductors, localization and schedules of classesmight be available in the USOSweb system: Concept and classification of multipliers 3.
Beck, Warszawa, Welfe A. Introduction to econometrics goals of econometrics, the concept of an econometric model, classification of econometric models.
Using formulas in Excel — overview. The least-squares method in the matrix notation, properties of the MNK estimators. Input-output table in static approach and balance equations. You are not logged in log in. Almon, The Craft of Economic Modeling.
Time series forecasting rules. Stationary and non stationary time series. The main aim of the laboratory ekonoketria to familiarize students with practice of econometric modelling. 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.
The implementations and limitations of naive models. Introduction to discrete event simulation — simple simulation, simulation on the crate. Building a worksheet-based simple simulation.
Placet, Warszawa 5. Factors of material consumption, labor consumption and their interpretation. Time series decomposition seasonality, trend, error. Discrete event simulation — steady-state models.
Beck, Warszawa 2. Variables and parameters in the descriptive model.
Non-measurable factors in econometric models. Moving average forecasting method. The main objective of the course is acquainting students with the simulation and forecasts methods.
Students will gain an overview of the concepts and practicalities of simulation and forecasts.