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Some of these areas are unique, while others established areas of economics by allowing robust data analytics and solutions of problems that would be arduous to research without computers and associated numerical methods. [2] Computational methods have been applied in various fields of economics research, including but not limiting to:
Computational finance is a branch of applied computer science that deals with problems of practical interest in finance. [1] Some slightly different definitions are the study of data and algorithms currently used in finance [ 2 ] and the mathematics of computer programs that realize financial models or systems .
Econometrics is a branch of economics that applies statistical methods to the empirical study of economic theories and relationships. Environmental statistics is the application of statistical methods to environmental science. Weather, climate, air and water quality are included, as are studies of plant and animal populations.
Business informatics centers around creating programming and equipment frameworks which ultimately provide the organization with effective operation based on information technology application. [1] The focus on programming and equipment boosts the value of the analysis of economics and information technology.
The use of AI in applications such as online trading and decision-making has changed major economic theories. [66] For example, AI-based buying and selling platforms estimate personalized demand and supply curves, thus enabling individualized pricing.
Computational statistics, or statistical computing, is the study which is the intersection of statistics and computer science, and refers to the statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is ...
A proposal for a "New Socialism" was outlined by the computer scientists Paul Cockshott and Allin Cottrell in 1995 (Towards a New Socialism), where computers determine and manage the flows and allocation of resources among socially owned enterprises. [9]
It has been applied in areas such as computational economics, computational sociology, computational media analysis, cliodynamics, culturomics, nonprofit studies. [1] It focuses on investigating social and behavioral relationships and interactions using data science approaches (such as machine learning or rule-based analysis), network analysis ...