Below I report some of my codes and replications of recent and former models in macroeconomics, relative to inequality, housing and occupational choice.
int C++ // (for discrete time)
- Solve standard housing macroeconomic models (Sommer & Sullivan AER (2018)) with DC-EGM algorithm (Iskhakov et al. (2017)). Useful note here, code available here.
- Solve the Aiyagari model in 0.04 – 0.14 seconds with Endogenous Grid Method (EGM) (Caroll (2006)). Useful note (by Josep Pijoan-Mas) is available here. Download my code (iterate on marginal utilities or value functions with code here).
- Solve the stochastic growth model as in Barillas & Villaverde (2007) using EGM, code here.
- Discretize income process using Tauchen algorithm in C++: code [here].
MatLab % (for continuous time)
- Solve Aiyagari in 0.13 seconds with Envelope Condition Method (ECM), many codes available here: HATC project.
- Aiyagari in Continous Time with Jump-Drift Process. Code is available here: aiyagari.m, note: here.
- Heterogenous Agent New Keynesian (HANK) (Kaplan et al. (2018)) model and the code available here: (not yet available), note: here.
Computational speed - comparison between EGM, DC-EGM and VFI
Comparison of performance and accuracy of EGM, DC-EGM and VFI methods on occupational choice and entrepreneurship models à la Cagetti & De Nardi (2006). The presence of discrete choice (occupational choice) makes EGM inaccurate. DC-EGM encompasses generated kinks very well, while being substantially faster than standard VFI.
||Speed (in s)