Economic Models Methods Theory And Applications
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Economic Models: Methods, Theory And Applications
Model Building is the most fruitful area of economics, designed to solve real-world problems using all available methods such as mathematical, computational and analytical, without distinction. Wherever necessary, we should not be reluctant to develop new techniques, whether mathematical or computational. That is the philosophy of this volume.The volume is divided into three distinct parts: Methods, Theory and Applications. The Methods section is in turn subdivided into Mathematical Programming and Econometrics and Adaptive Control System, which are widely used in econometric analysis. The impacts of fiscal policy in a regime with independent monetary authority and dynamic models of environmental taxation are considered.In the section on “Modelling Business Organization”, a model of a Japanese organization is presented. Furthermore, a model suitable for an efficient budget management of a health service unit by applying goal programming method is analyzed, taking into account various socio-economic factors. This is followed by a section on “Modelling National Economies”, in which macroeconometric models for the EU member countries are analyzed, to find instruments that stabilize inflation with coordinated action.
Economic Models
Model Building is the most fruitful area of economics, designed to solve real-world problems using all available methods such as mathematical, computational and analytical, without distinction. Wherever necessary, we should not be reluctant to develop new techniques, whether mathematical or computational. That is the philosophy of this volume. The volume is divided into three distinct parts: Methods, Theory and Applications. The Methods section is in turn subdivided into Mathematical Programming and Econometrics and Adaptive Control System, which are widely used in econometric analysis. The impacts of fiscal policy in a regime with independent monetary authority and dynamic models of environmental taxation are considered. In the section on "Modelling Business Organization," a model of a Japanese organization is presented. Furthermore, a model suitable for an efficient budget management of a health service unit by applying goal programming method is analyzed, taking into account various socio-economic factors. This is followed by a section on "Modelling National Economies," in which macroeconometric models for the EU member countries are analyzed, to find instruments that stabilize inflation with coordinated action.
Economic Modeling Using Artificial Intelligence Methods
Author: Tshilidzi Marwala
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-04-02
Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace – and vice versa – is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners.