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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){:target="_blank"}
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, vol. 12, Article 8048.
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
models. (Documentation){:target="_blank"}
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){:target="_blank"}
Boehl G. (2022) Efficient Solution and Computation of Models with Occasionally Binding Constraints, Journal of Economic Dynamics and Control, vol. 143, Article 104523. Working paper version.
skillmodels a Python implementation of estimators for skill formation models. (Documentation){:target="_blank"}
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){:target="_blank"}
ruspy is an open-source package for the simulation and estimation of a prototypical infinite-horizon dynamic discrete choice model based on Rust (1987){:target="_blank"}. (Documentation){:target="_blank"}
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){:target="_blank"}