Download Free Computational And Decision Methods In Economics And Business Book in PDF and EPUB Free Download. You can read online Computational And Decision Methods In Economics And Business and write the review.

This book presents different topics related to innovation, complexity, uncertainty, modeling and simulation, fuzzy logic, decision-making, aggregation operators, business and economic applications, among others. The chapters are the results of research presented at the International Workshop "Innovation, Complexity and Uncertainty in Economics and Business", held in Barcelona, in November 2019, by The Ibero-American Network for Competitiveness, Innovation and Development (REDCID in Spanish) and the Royal Academy of Economic and Financial Sciences (RACEF in Spanish). These papers are useful for junior and senior researchers in the area of economics and business.
Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.
This textbook connects three vibrant areas at the interface between economics and computer science: algorithmic game theory, computational social choice, and fair division. It thus offers an interdisciplinary treatment of collective decision making from an economic and computational perspective. Part I introduces to algorithmic game theory, focusing on both noncooperative and cooperative game theory. Part II introduces to computational social choice, focusing on both preference aggregation (voting) and judgment aggregation. Part III introduces to fair division, focusing on the division of both a single divisible resource ("cake-cutting") and multiple indivisible and unshareable resources ("multiagent resource allocation"). In all these parts, much weight is given to the algorithmic and complexity-theoretic aspects of problems arising in these areas, and the interconnections between the three parts are of central interest.
Handbook of Computational Economics summarizes recent advances in economic thought, revealing some of the potential offered by modern computational methods. With computational power increasing in hardware and algorithms, many economists are closing the gap between economic practice and the frontiers of computational mathematics. In their efforts to accelerate the incorporation of computational power into mainstream research, contributors to this volume update the improvements in algorithms that have sharpened econometric tools, solution methods for dynamic optimization and equilibrium models, and applications to public finance, macroeconomics, and auctions. They also cover the switch to massive parallelism in the creation of more powerful computers, with advances in the development of high-power and high-throughput computing. Much more can be done to expand the value of computational modeling in economics. In conjunction with volume one (1996) and volume two (2006), this volume offers a remarkable picture of the recent development of economics as a science as well as an exciting preview of its future potential. - Samples different styles and approaches, reflecting the breadth of computational economics as practiced today - Focuses on problems with few well-developed solutions in the literature of other disciplines - Emphasizes the potential for increasing the value of computational modeling in economics
An introduction to the use of computational methods to solve problems in economics and finance.
At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational techniques in finance and economics. Examined topics span on issues at the center of the literature debate, with an eye not only on technical and theoretical aspects but also very practical cases.
This book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment. DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds)
Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). · Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. · Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. · Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. · Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
"This book identifies the economic as well as financial problems that may be solved efficiently with computational methods and explains why those problems should best be solved with computational methods"--Provided by publisher.
This book presents different topics related to innovation, complexity, uncertainty, modeling and simulation, fuzzy logic, decision-making, aggregation operators, business and economic applications, among others. The chapters are the results of research presented at the International Workshop "Innovation, Complexity and Uncertainty in Economics and Business", held in Barcelona, in November 2019, by The Ibero-American Network for Competitiveness, Innovation and Development (REDCID in Spanish) and the Royal Academy of Economic and Financial Sciences (RACEF in Spanish). These papers are useful for junior and senior researchers in the area of economics and business.