Economic Models and Applications
lcm (life-cycle models) aims to generalize and facilitate the specification, solving, and estimation of dynamic choice models. (GitHub)
sid is an agent-based simulation model for infectious diseases like COVID-19. It scales from simple examples to complex models which makes it an ideal tool for prototyping, educational purposes, and research. (Documentation)
Gabler J., Raabe T., Röhrl K. & von Gaudecker H. (2022) The Effectiveness of Strategies to Contain SARS-CoV-2: Testing, Vaccinations, and NPIs, Scientific Reports, 2022.
respy is an open-source framework written in Python for the simulation and
estimation of some finite-horizon discrete choice dynamic programming models. The group
of models which can be currently represented in
respy are called Eckstein–Keane–Wolpin
Eisenhauer P., Gabler J. & Janys L. (2021) Structural models for policy-making: Coping with parametric uncertainty, arXiv preprint arXiv:2103.01115, submitted.
pydsge is a Python package that allows to simulate, filter, and estimate DSGE models with occasionally binding constraints. As such, it allows to conduct full-blown Bayesian estimations (including Bayesian filtering) of macroeconomic models featuring an endogenous zero lower bound on nominal interest rates. (Documentation)
Boehl G. (2022) Efficient Solution and Computation of Models with Occasionally Binding Constraints, working paper.
skillmodels a Python implementation of estimators for skill formation models. (Documentation)
econsive is a collection of nonlinear Bayesian filters, in particular for high dimensional models. The filters are implemented in python. It provides the Transposed-Ensemble Kalman Filter (TEnKF) for state and likelihood inference, and the Nonlinear Path-Adjusting Smoother (NPAS) for exact smoothed states. (Documentation)
ruspy is an open-source package for the simulation and estimation of a prototypical infinite-horizon dynamic discrete choice model based on Rust (1987). (Documentation)
Blesch M. & Eisenhauer P. (2021) Robust decision-making under risk and ambiguity, arXiv preprint arXiv:2104.12573, submitted
grmpy is an open-source Python package for the simulation and estimation of the generalized Roy model. It serves as a teaching tool to promote the conceptual framework of the generalized Roy model, illustrate a variety of issues in the econometrics of policy evaluation, and showcases basic software engineering practices. (Documentation)