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The use of innovative computational models in political economic research as a complement to traditional analytical methodologies.
How to use nonlinear dynamic models in policy analysis. Policymakers need quantitative as well as qualitative answers to pressing policy questions. Because of advances in computational methods, quantitative estimates are now derived from coherent nonlinear dynamic macroeconomic models embodying measures of risk and calibrated to capture specific characteristics of real-world situations. This text shows how such models can be made accessible and operational for confronting policy issues. The book starts with a simple setting based on market-clearing price flexibility. It gradually incorporates departures from the simple competitive framework in the form of price and wage stickiness, taxes, rigidities in investment, financial frictions, and habit persistence in consumption. Most chapters end with computational exercises; the Matlab code for the base model can be found in the appendix. As the models evolve, readers are encouraged to modify the codes from the first simple model to more complex extensions. Computational Macroeconomics for the Open Economy can be used by graduate students in economics and finance as well as policy-oriented researchers.
Offers an overview of mathematical modeling concentrating on game theory, statistics and computational modeling.
Models of Political Economy will introduce students to the basic methodology of political economics. It covers all core theories as well as new developments including: decision theory game theory mechanism design games of asymmetric information. Hannu Nurmi's text will prove to be invaluable to all students who wish to understand this increasingly technical field.
Most theories of elections assume that voters and political actors are fully rational. This title provides a behavioral theory of elections based on the notion that all actors - politicians as well as voters - are only boundedly rational.
The ability to conceptualize an economic problem verbally, to formulate it as a mathematical model, and then represent the mathematics in software so that the model can be solved on a computer is a crucial skill for economists. Computational Economics contains well-known models--and some brand-new ones--designed to help students move from verbal to mathematical to computational representations in economic modeling. The authors' focus, however, is not just on solving the models, but also on developing the ability to modify them to reflect one's interest and point of view. The result is a book that enables students to be creative in developing models that are relevant to the economic problems of their times. Unlike other computational economics textbooks, this book is organized around economic topics, among them macroeconomics, microeconomics, and finance. The authors employ various software systems--including MATLAB, Mathematica, GAMS, the nonlinear programming solver in Excel, and the database systems in Access--to enable students to use the most advantageous system. The book progresses from relatively simple models to more complex ones, and includes appendices on the ins and outs of running each program. The book is intended for use by advanced undergraduates and professional economists and even, as a first exposure to computational economics, by graduate students. Organized by economic topics Progresses from simple to more complex models Includes instructions on numerous software systems Encourages customization and creativity
This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.
In this book, Federico Sturzenegger and Mariano Tommasi propose formal models to answer some of the questions raised by the recent reform experience of many Latin American and eastern European countries.
Handbook of Computational Economics: Heterogeneous Agent Modeling, Volume Four, focuses on heterogeneous agent models, emphasizing recent advances in macroeconomics (including DSGE), finance, empirical validation and experiments, networks and related applications. Capturing the advances made since the publication of Volume Two (Tesfatsion & Judd, 2006), it provides high-level literature with sections devoted to Macroeconomics, Finance, Empirical Validation and Experiments, Networks, and other applications, including Innovation Diffusion in Heterogeneous Populations, Market Design and Electricity Markets, and a final section on Perspectives on Heterogeneity.
An introductory overview of the methods, models and interdisciplinary links of artificial economics. Addresses the differences between the assumptions and methods of artificial economics and those of mainstream economics. This is one of the first books to fully address, in an intuitive and conceptual form, this new way of doing economics.