JAN GAJDA EKONOMETRIA PDF

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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Additional information registration calendar, class conductors, localization and schedules of classesmight be available in the USOSweb system:. Input-output models – input-output table in terms ekonojetria quantity and value – technical factors and basket factors – Leontief’s model and its solutions in terms of quantity and value – price model. Almon, The Craft of Economic Modeling. Non-measurable factors in econometric models. Descriptive jna models – selection of variables for the model and approximation function, construction, estimation of MNK, interpretation, evaluation and application in logistic decisions.

Definition of forecasts and simulation. Faculty of Economics and Sociology.

Skills of building and estimating econometric models and using them in practice. You are not logged in log in. You are not logged in log in. Metody i ich zastosowanie, wyd. Gsjda is based on tutorial exercises and individually prepared project at the end of the semester. Sampling from probability distributions — inverse transform method. On-line services of the University of Warsaw. Showing them examples of practical use of econometric methods.

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Gajda, Jan Bogusław

An example of the seasonality of economic phenomena. Verification of the econometric model, economic interpretation of the estimation results.

Beck, Warszawa 2. Deterministic and stochastic simulation. Part I by Clopper Almon A. Generalized least squares method. On-line services jab the University of Warsaw You are not logged in log in. Stages of econometric analysis. Time series decomposition seasonality, trend, error. Structural and non-structural models. The project requires the theory, described during classes, to be applied to a specific problem in finance or economics. Placet, Warszawa 5.

Measurement of forecasting error ex ante and ex post. Introduction to econometrics goals of econometrics, the concept of an econometric model, classification of econometric models. Stationary and non stationary time series.

Business Forecasting – University of Warsaw

Time series forecasting rules. 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. Additional information registration calendar, class conductors, localization and schedules of classesmight ekonometfia available in the USOSweb system: Jzn i zastosowania, PWN, Warszawa 3. Written report should be submitted.

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An analysis of ex post and ex ante forecasting errors.

Descriptive econometric models – general characteristics and examples of applications. Metody i ich zastosowanie, PWE, Warszawa Forecasting based on an econometric model. There will be oral presentation of the project made during the last week of classes.

Using dynamic simulation to improve production. Discrete event simulation — dynamic simulations model changes in a system in response to input signals. Time series analysis — deterministic and stochastic trends in the time series models.

Introduction to optimization with the Excel Solver tool. The subject learning outcomes for the form of lecture and exercises: Total for the subject: There will be also theoretical written exam.

Classification of econometric models 1. Record of the linear and power model 2.