Dear all,
I have recently updated a repo on my github to solve Pijoan-Mas model (RED 2006) which is in essence an Aiyagari model with elastic labor supply. I guess it might be interesting for students who want to start from a relatively simple model and then extend it.
Here is the link: GitHub - aledinola/PijoanMasTaxes
It should work well with the latest version of the toolkit. Warning: as usual, my code could be full of bugs! If you find any, please let me know 
Best,
Alessandro
Fantastic!
Exciting milestone, first VFI Toolkit example written by someone other than me 
I added a short pdf with a description of the model.
There seems to be a problem in the computation of some statistics like the earning shares, which is based on the lorenz curve
Some shares are greater than one, which can’t be
Not really sure what’s going on
I’ll take a look at it later this week, let you know what I find (busy teaching until late in the week)
Just pushed to github. Should be fixed now. Somehow the code for Lorenz curve had gotten a typo, this was infecting all the stuff based on lorenz. Thanks for spotting.
You’re welcome! I ran again the code and this time the results make sense. They more or less correspond to the version of Pijoan-Mas model denoted as “Model E0” (see Tables 1 and 2 in the paper).
One question: If I do not specify vfoptions and simoptions, the toolkit automatically selects discretization with refinement for the VFI and the Tan improvement for the distribution, is that right?
MOMENTS
Corr(h,z) : 0.020037
CV(h) : 0.202920
Hours : 0.355203
K/Y : 2.989966
w*L/Y : 0.640020
I/Y : 0.248167CV
CV(Hours) : 0.202920
CV(Earnings): 0.639090
CV(Income) : 0.627450
CV(Wealth) : 1.358534GINI
Gini(Hours) : 0.095844
Gini(Earnings): 0.319153
Gini(Income) : 0.307965
Gini(Wealth) : 0.641633CORR
corr(Hours,z) : 0.020037
corr(Wealth,z): 0.511574SHARES EARNINGS
q1 earnings: 0.074302
q2 earnings: 0.124517
q3 earnings: 0.174612
q4 earnings: 0.228116
q5 earnings: 0.398453SHARES WEALTH
q1 wealth: 0.000907
q2 wealth: 0.023915
q3 wealth: 0.094677
q4 wealth: 0.231797
q5 wealth: 0.648704
I think everything in the toolkit nowadays uses Tan improvement (everything involving agent distributions, only exception I can think of would be a model with semi-exo but no exo shocks as Tan improvement does not apply to semi-exo shocks).
And yes, infinite horizon with a decision variable will use refinement by default for value function (so Aiyagari 1994 codes won’t use it as there is no decision variable to refine, but Pijoan-Mas 2006 has the labor decision so it will use refinement).