causal inference, confounding variables, and realism of the model. Under the proper guidance, machine learning models may accelerate the process of developing accurate, applicable economics through large scale empirical data analysis and computation. Dynamic Stochastic General Equilibrium (DSGE) model Dynamic modeling methods are frequently adopted in macroeconomic research to simulate economic fluctuations and test for the effects of policy changes. The DSGE one class of dynamic models relying heavily on computational techniques and solutions. DSGE models utilize micro-founded economic principles to capture characteristics of the real world economy in an environment with intertemporal uncertainty. Given their inherent complexity, DSGE models are in general analytically intractable, and are usually implemented numerically using computer software. One major advantage of DSGE models is that they facilitate the estimation of agents' dynamic choices with flexibility. However, many scholars have criticized DSGE models for their reliance on reduced-form assumptions that are largely unrealistic. Computational tools and programming languages Utilizing computational tools in economic research has been the norm and foundation for a long time. Computational tools for economics include a variety of computer software that facilitate the execution of various matrix operations (e.g. matrix inversion) and the solution of systems of linear and nonlinear equations. Various programming languages are utilized in economic research for the purpose of data analytics and modeling. Following is a typical listing of programming languages used in computational economics research: C++, MATLAB, Julia (programming language), Python (programming language), R (programming language), Stata Among these programming languages, C++ as a compiled language performs the fastest, while Python as an interpreted language is the slowest. MATLAB, Julia, and R achieve a balance between performance and interpretability. As an early statistical analytics software, Stata was the most conventional programming language option. Economists embraced Stata as one of the most popular statistical analytics programs due to its breadth, accuracy, flexibility, and repeatability. Journals The following journals specialise in computational economics: ACM Transactions on Economics and Computation, Computational Economics, Journal of Applied Econometrics, Journal of Economic Dynamics and Control and the Journal of Economic Interaction and Coordination. References External links Society for Computational Economics Journal of Economic Dynamics and Control - publishes articles on computational economics Agent-Based Computational Economics - maintained by Leigh Tesfatsion The Use of Agent-Based Models in Regional Science - a study on agent-based models to simulate urban agglomeration Computational Economics with Python - a series of lectures Computational Finance and Economic Agents