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Author: Mario Arturo Ruiz Estrada
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper is interested to evaluate how artificial intelligence (AI) can help in the economic modeling. The fast development of AI, big data, data sciences, neural networks, and graphical models is opening opportunities to Economists and Academics to a new era under the uses of these alternative technologies. However, AI can replace the traditional way how we analyze and solve economic problems. In our case, this research presents an alternative economic method under the presentation of an application (theoretical framework) that is using AI, big data, data sciences, neural networks, and Econographicology simultaneously. The new electronic application is called “The Autonomous Economic Decision Maker Simulator (AEDM-Simulator). Finally, we introduce the AEDM-Simulator theoretical framework and a few examples of how to use the AEDM-Simulator to solve any economic issue(s). The AEDM-Simulator is used as a main database based on the uses of all volumes (39) and issues (250) from the Journal of Economic Modelling (JEM) published by Elsevier in the last past thirt-nine years (1984-2023).
Author: Mario Arturo Ruiz Estrada
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper is interested to evaluate how artificial intelligence (AI) can help in the economic modeling. The fast development of AI, big data, data sciences, neural networks, and graphical models is opening opportunities to Economists and Academics to a new era under the uses of these alternative technologies. However, AI can replace the traditional way how we analyze and solve economic problems. In our case, this research presents an alternative economic method under the presentation of an application (theoretical framework) that is using AI, big data, data sciences, neural networks, and Econographicology simultaneously. The new electronic application is called “The Autonomous Economic Decision Maker Simulator (AEDM-Simulator). Finally, we introduce the AEDM-Simulator theoretical framework and a few examples of how to use the AEDM-Simulator to solve any economic issue(s). The AEDM-Simulator is used as a main database based on the uses of all volumes (39) and issues (250) from the Journal of Economic Modelling (JEM) published by Elsevier in the last past thirt-nine years (1984-2023).
Author: Tshilidzi Marwala
Publisher: Springer Science & Business Media
ISBN: 1447150104
Category : Computers
Languages : en
Pages : 271
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Book Description
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: El Bachir Boukherouaa
Publisher: International Monetary Fund
ISBN: 1589063953
Category : Business & Economics
Languages : en
Pages : 35
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Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Author: Ajay Agrawal
Publisher: University of Chicago Press
ISBN: 0226833127
Category : Business & Economics
Languages : en
Pages : 172
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Book Description
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Author: Scott J. Moss
Publisher: Edward Elgar Publishing
ISBN: 9781782541769
Category : Business & Economics
Languages : en
Pages : 216
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Book Description
This important book presents new and original work at the frontiers of economics, namely the interface between artificial intelligence (AI) and neoclassical economics. Artificial Intelligence and Economic Analysis focuses on three quite distinct lines of AI orientated research in economics: applications intended to extend neoclassical theory, applications intended to undermine neoclassical theory and applications which ignore neoclassical theory in the quest for new modelling techniques and fields of analysis. The contributors - all of whom are well established in the field - do not simply report established results but seek to identify those areas where the science of artificial intelligence could enrich standard economic analysis. It includes material from mainstream economists who are willing to express their own views about the limits of mainstream economic modelling and AI based economic modelling. The book makes an important contribution to a new and exciting area of economics which holds much hope for the future.
Author: Tankiso Moloi
Publisher: Springer Nature
ISBN: 3030429628
Category : Computers
Languages : en
Pages : 131
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Book Description
As Artificial Intelligence (AI) seizes all aspects of human life, there is a fundamental shift in the way in which humans are thinking of and doing things. Ordinarily, humans have relied on economics and finance theories to make sense of, and predict concepts such as comparative advantage, long run economic growth, lack or distortion of information and failures, role of labour as a factor of production and the decision making process for the purpose of allocating resources among other theories. Of interest though is that literature has not attempted to utilize these advances in technology in order to modernize economic and finance theories that are fundamental in the decision making process for the purpose of allocating scarce resources among other things. With the simulated intelligence in machines, which allows machines to act like humans and to some extent even anticipate events better than humans, thanks to their ability to handle massive data sets, this book will use artificial intelligence to explain what these economic and finance theories mean in the context of the agent wanting to make a decision. The main feature of finance and economic theories is that they try to eliminate the effects of uncertainties by attempting to bring the future to the present. The fundamentals of this statement is deeply rooted in risk and risk management. In behavioural sciences, economics as a discipline has always provided a well-established foundation for understanding uncertainties and what this means for decision making. Finance and economics have done this through different models which attempt to predict the future. On its part, risk management attempts to hedge or mitigate these uncertainties in order for “the planner” to reach the favourable outcome. This book focuses on how AI is to redefine certain important economic and financial theories that are specifically used for the purpose of eliminating uncertainties so as to allow agents to make informed decisions. In effect, certain aspects of finance and economic theories cannot be understood in their entirety without the incorporation of AI.
Author: OECD
Publisher: OECD Publishing
ISBN: 9264545190
Category :
Languages : en
Pages : 152
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Book Description
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
Author: Tshilidzi Marwala
Publisher: Springer
ISBN: 3319661043
Category : Computers
Languages : en
Pages : 206
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Book Description
This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models.
Author: Federico Cecconi
Publisher: Springer
ISBN: 3030226050
Category : Business & Economics
Languages : en
Pages : 198
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Book Description
This book presents the effects of integrating information and communication technologies (ICT) and economic processes in macroeconomic dynamics, finance, marketing, industrial policies, and in government economic strategy. The text explores modeling and applications in these fields and also describes, in a clear and accessible manner, the theories that guide the integration among information technology (IT), telecommunications, and the economy, while presenting examples of their applications. Current trends such as artificial intelligence, machine learning, and big data technologies used in economics are also included. This volume is suitable for researchers, practitioners, and students working in economic theory and the computational social sciences.
Author: Scott J. Moss
Publisher: Edward Elgar Publishing
ISBN: 9781852786854
Category : Business & Economics
Languages : en
Pages : 193
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Book Description
'It provides interesting reading and a source of speculation for those who hope to find uses for AI techniques in economic research.' - Kent D. Wall, Journal of Economic Behavior & Organization This important book presents new and original work at the frontiers of economics - namely the interface between artificial intelligence (AI) and neoclassical economics. Artificial Intelligence and Economic Analysis focuses on three quite distinct lines of AI orientated research in economics: applications intended to extend neoclassical theory, applications intended to undermine neoclassical theory and applications which ignore neoclassical theory in the quest for new modelling techniques and fields of analysis. the contributors - all of whom are well established in the field - seek to identify those areas where the science of artificial intelligence could enrich standard economic analysis. It includes material from mainstream economists who are willing to express their own views about the limits of mainstream economic modelling and AI based economic modelling.
