What is PyMacLab?

At this point in time, PyMacLab is a simple-to-use library enabling users to calibrate and solve DSGE models based on a number of well-known and efficient solution algorithms. It works in the tradition of real business cycle analysis and thus permits users to simulate and analyze artificial economies build from micro foundations. It is very convenient to use and emphasizes intuition, ease-of-use and extensibility. It is also free and does not depend on any other proprietary software.

What PyMacLab is not yet is an estimation framework for DSGE models in which data can be used to estimate deep structure parameters. But it is only a small step away from possessing that ability. For instance, implementing a limited-information estimation method minimizing the distance between theoretical impulse responses and those obtained from a corresponding SVAR would barely take a couple of days or so to program. Bayesian estimation is not on the todo-list yet and may take somewhat longer to implement. Professional users are welcome to use the existing functionality of PyMacLab as a convenient starting point relying on a robust code base in order to implement some of these as of yet missing features.