Modelling Learning In Economics

Author : Thomas Brenner
Publisher : Springer Science & Business Media
ISBN 13 : 1461550297
Total Pages : 392 pages
Book Rating : 4.97/5 ( download)

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Download or read book Computational Techniques for Modelling Learning in Economics written by Thomas Brenner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Techniques for Modelling Learning in Economics offers a critical overview of the computational techniques that are frequently used for modelling learning in economics. It is a collection of papers, each of which focuses on a different way of modelling learning, including the techniques of evolutionary algorithms, genetic programming, neural networks, classifier systems, local interaction models, least squares learning, Bayesian learning, boundedly rational models and cognitive learning models. Each paper describes the technique it uses, gives an example of its applications, and discusses the advantages and disadvantages of the technique. Hence, the book offers some guidance in the field of modelling learning in computation economics. In addition, the material contains state-of-the-art applications of the learning models in economic contexts such as the learning of preference, the study of bidding behaviour, the development of expectations, the analysis of economic growth, the learning in the repeated prisoner's dilemma, and the changes of cognitive models during economic transition. The work even includes innovative ways of modelling learning that are not common in the literature, for example the study of the decomposition of task or the modelling of cognitive learning.

Author : Thomas Brenner
Publisher : Edward Elgar Publishing
ISBN 13 :
Total Pages : 360 pages
Book Rating : 4.77/5 ( download)

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Download or read book Modelling Learning in Economics written by Thomas Brenner and published by Edward Elgar Publishing. This book was released on 1999 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an investigation into the processes that are involved in economic learning by categorizing different ways of learning, and using mathematical models for their description. Three learning processes are covered: non-cognitive, routine-based and associative learning.

Author : Alessandro Caiani
Publisher : Springer
ISBN 13 : 3319440586
Total Pages : 219 pages
Book Rating : 4.83/5 ( download)

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Download or read book Economics with Heterogeneous Interacting Agents written by Alessandro Caiani and published by Springer. This book was released on 2016-09-21 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical guide to Agent Based economic modeling, adopting a “learning by doing” approach to help the reader master the fundamental tools needed to create and analyze Agent Based models. After providing them with a basic “toolkit” for Agent Based modeling, it present and discusses didactic models of real financial and economic systems in detail. While stressing the main features and advantages of the bottom-up perspective inherent to this approach, the book also highlights the logic and practical steps that characterize the model building procedure. A detailed description of the underlying codes, developed using R and C, is also provided. In addition, each didactic model is accompanied by exercises and applications designed to promote active learning on the part of the reader. Following the same approach, the book also presents several complementary tools required for the analysis and validation of the models, such as sensitivity experiments, calibration exercises, economic network and statistical distributions analysis. By the end of the book, the reader will have gained a deeper understanding of the Agent Based methodology and be prepared to use the fundamental techniques required to start developing their own economic models. Accordingly, “Economics with Heterogeneous Interacting Agents” will be of particular interest to graduate and postgraduate students, as well as to academic institutions and lecturers interested in including an overview of the AB approach to economic modeling in their courses.

Author : Domenico Delli Gatti
Publisher : Cambridge University Press
ISBN 13 : 1108414990
Total Pages : 261 pages
Book Rating : 4.99/5 ( download)

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Download or read book Agent-Based Models in Economics written by Domenico Delli Gatti and published by Cambridge University Press. This book was released on 2018-03-22 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first step-by-step introduction to the methodology of agent-based models in economics, their mathematical and statistical analysis, and real-world applications.

Author : Bent Jesper Christensen
Publisher : Princeton University Press
ISBN 13 : 1400833108
Total Pages : 488 pages
Book Rating : 4.08/5 ( download)

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Download or read book Economic Modeling and Inference written by Bent Jesper Christensen and published by Princeton University Press. This book was released on 2021-07-13 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples

Author : Christophe Chamley
Publisher : Cambridge University Press
ISBN 13 : 9780521530927
Total Pages : 420 pages
Book Rating : 4.2X/5 ( download)

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Download or read book Rational Herds written by Christophe Chamley and published by Cambridge University Press. This book was released on 2004 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description

Author : Martin J. Osborne
Publisher : Open Book Publishers
ISBN 13 : 180511123X
Total Pages : 382 pages
Book Rating : 4.38/5 ( download)

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Download or read book Models in Microeconomic Theory written by Martin J. Osborne and published by Open Book Publishers. This book was released on 2023-06-26 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models in Microeconomic Theory covers basic models in current microeconomic theory. Part I (Chapters 1-7) presents models of an economic agent, discussing abstract models of preferences, choice, and decision making under uncertainty, before turning to models of the consumer, the producer, and monopoly. Part II (Chapters 8-14) introduces the concept of equilibrium, beginning, unconventionally, with the models of the jungle and an economy with indivisible goods, and continuing with models of an exchange economy, equilibrium with rational expectations, and an economy with asymmetric information. Part III (Chapters 15-16) provides an introduction to game theory, covering strategic and extensive games and the concepts of Nash equilibrium and subgame perfect equilibrium. Part IV (Chapters 17-20) gives a taste of the topics of mechanism design, matching, the axiomatic analysis of economic systems, and social choice. The book focuses on the concepts of model and equilibrium. It states models and results precisely, and provides proofs for all results. It uses only elementary mathematics (with almost no calculus), although many of the proofs involve sustained logical arguments. It includes about 150 exercises. With its formal but accessible style, this textbook is designed for undergraduate students of microeconomics at intermediate and advanced levels.

Author : Songsak Sriboonchitta
Publisher : Springer Nature
ISBN 13 : 3030497283
Total Pages : 445 pages
Book Rating : 4.86/5 ( download)

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Download or read book Behavioral Predictive Modeling in Economics written by Songsak Sriboonchitta and published by Springer Nature. This book was released on 2020-08-05 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents both methodological papers on and examples of applying behavioral predictive models to specific economic problems, with a focus on how to take into account people's behavior when making economic predictions. This is an important issue, since traditional economic models assumed that people make wise economic decisions based on a detailed rational analysis of all the relevant aspects. However, in reality – as Nobel Prize-winning research has shown – people have a limited ability to process information and, as a result, their decisions are not always optimal. Discussing the need for prediction-oriented statistical techniques, since many statistical methods currently used in economics focus more on model fitting and do not always lead to good predictions, the book is a valuable resource for researchers and students interested in the latest results and challenges and for practitioners wanting to learn how to use state-of-the-art techniques.

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
ISBN 13 : 1447150104
Total Pages : 271 pages
Book Rating : 4.07/5 ( download)

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Download or read book Economic Modeling Using Artificial Intelligence Methods written by Tshilidzi Marwala and published by Springer Science & Business Media. This book was released on 2013-04-02 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Isaiah Hull
Publisher : Apress
ISBN 13 : 9781484263723
Total Pages : 368 pages
Book Rating : 4.23/5 ( download)

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Download or read book Machine Learning for Economics and Finance in TensorFlow 2 written by Isaiah Hull and published by Apress. This book was released on 2020-11-26 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work in economics is concentrated on the identification of causal relationships in parsimonious statistical models; whereas machine learning is oriented towards prediction and is generally uninterested in either causality or parsimony. That leaves a gap for both students and professionals in the economics industry without a standard reference. This book focuses on economic problems with an empirical dimension, where machine learning methods may offer something of value. This includes coverage of a variety of discriminative deep learning models (DNNs, CNNs, RNNs, LSTMs, the Transformer Model, etc.), generative machine learning models, random forests, gradient boosting, clustering, and feature extraction. You'll also learn about the intersection of empirical methods in economics and machine learning, including regression analysis, text analysis, and dimensionality reduction methods, such as principal components analysis. TensorFlow offers a toolset that can be used to setup and solve any mathematical model, including those commonly used in economics. This book is structured to teach through a sequence of complete examples, each framed in terms of a specific economic problem of interest or topic. Otherwise complicated content is then distilled into accessible examples, so you can use TensorFlow to solve workhorse models in economics and finance. What You'll Learn Define, train, and evaluate machine learning models in TensorFlow 2 Apply fundamental concepts in machine learning, such as deep learning and natural language processing, to economic and financial problems Solve workhorse models in economics and finance Who This Book Is For Students and data scientists working in the economics industry. Academic economists and social scientists who have an interest in machine learning are also likely to find this book useful.