Editing Computational economics (section)

== History ==
Computational economics developed concurrently with the mathematization of the field. During the early 20th century, pioneers such as [[Jan Tinbergen]] and [[Ragnar Frisch]] advanced the computerization of economics and the growth of econometrics. As a result of advancements in Econometrics, [[Regression analysis|regression models]], [[Statistical hypothesis testing|hypothesis testing]], and other computational statistical methods became widely adopted in economic research. On the theoretical front, complex [[Macroeconomics|macroeconomic]] models, including the [[Real business-cycle theory|real business cycle]] (RBC) model and [[dynamic stochastic general equilibrium]] (DSGE) models have propelled the development and application of numerical solution methods that rely heavily on computation. In the 21st century, the development of computational algorithms created new means for computational methods to interact with economic research. Innovative approaches such as machine learning models and agent-based modeling have been actively explored in different areas of economic research, offering economists an expanded toolkit that frequently differs in character from traditional methods.