Algorithmic economics is an interdisciplinary field that combines the knowledge of economics, engineering, mathematics and computer science in order to understand and improve complex social markets and networks.
The Internet has produced new service platforms and marketplaces, such as online advertising auctions and social media networks, which involve advanced algorithms, economic exchanges and social systems. Algorithmic economic professionals strive to understand and document these processes.
The science of economic algorithms and computer science have been historically combined for different reasons. There are complex applications that are utilized by large-scale digital markets in popular shopping websites like EBay and Amazon. These websites are now global markets that handle millions of transactions and visitors every day. These applications are gold mines of fascinating data for market researchers and economists. Alternatively, academic researchers seek to understand the computational complexity of things like game theory and the Nash equilibria. In order to productively model and study the Internet’s novel algorithmic phenomena, computer scientists need tools and insights from areas like sociology, game theory and economic theory.
The Purpose of Economic Algorithms
Most economists now feel that a computational point of view is essential to understand the digital world of networked markets and online platforms of economic transactions. The field of computational economics is less than 20 years old, but has already achieved a remarkable degree of collaboration between various fields and made notable progress on many shared research questions related to digital auctions and mechanism design. Thus, the ultimate goal is to further the interactions between theoretical economists and computer scientists in order to identify and understand online financial transactions and relationships. As more information is gleaned from computational economics, businesses will understand consumer behaviors and economists will better understand digital microeconomics.
The research spans a wide variety of topics at the crossroads of economics and computation. Software application areas include online auctions, gaming, polling, advertising, crowd-sourcing and information aggregation. As crowd-sourcing rapidly replaces traditional forms of entrepreneurial funding, business and government organizations need to better understand this unique digital phenomena. Application areas also include prediction engines, digital monetization, market optimization and machine learning in markets. Online service providers and companies now require dual research in social science and computer science. This means that they need integrated information from the social sciences, such as economics, sociology and psychology, and technology areas, like algorithm programming, system interfaces and machine learning.
Economic and computer science researchers combine their expertise to bridge the gap between modeling human behavior and engineering large-scale market systems. For example, researchers often study several problems related to game theory within the frameworks of computer systems, network design and ecommerce applications. When it comes to mechanism design, researchers aim to develop structures that optimize objective functions, such as the seller’s revenue or global inter-connectivity. They apply techniques from machine learning and online algorithms to mechanism design in order to understand and streamline processes.
Those who want to understand this fascinating new field can earn a degree in algorithmic economics.