Computational economics is a subfield of economics that uses computational methods to analyze economic problems. Computational economics includes the use of simulation and optimization models to study economic phenomena, design economic experiments, and evaluate economic policies.

Computational economics also takes advantage of newly available data sources, such as administrative data, to answer economic questions that were previously difficult or impossible to analyze. The goal of computational economics is to provide a set of tools that economists can use to answer economic questions.

One of the most important aspects of computational economics is the use of simulations to study economic problems. Simulations allow economists to study how different factors impact the economy without having to conduct real-world experiments. This makes it possible to study a much wider range of economic problems than would be possible with real-world experiments.

Simulations are also useful for studying problems that are too difficult or expensive to study in the real world. For example, economists may use simulations to study the impact of a natural disaster on the economy or the impact of a new economic policy.

Optimization models are another important tool used in computational economics. Optimization models are used to find the best way to allocate resources in order to achieve a specific goal. For example, an optimization model could be used to find the best way to allocate limited resources in order to maximize economic growth.

Computational economics is a relatively new field, and it is constantly evolving as new computational methods are developed and new data sources become available. Computational economics is an important tool for economists, and it is only going to become more important in the future.