Julia has the potential to become a major programming language in economics. In this presentation I will suggest a new way to calibrate models of economic growth. For that purpose I use a Markov-Chain Monte-Carlo algorithm (the Klara package) and I repeatedly solve for the roots of a big system of nonlinear equations using the JuMP and Ipopt packages. With this approach I am able to estimate the distributions of parameter values which drive long-run economic growth and project confidence intervals of macroeconomic variables into the future. For this purpose Julia is the best programming language that I know of, because it combines a great range of functionalities and at the same time it is very fast. To conclude, I will reflect on some challenges that came up during the project.
