Jason DeBacker

It would be worth checking the recent calibration by @rickecon and @jdebacker used in [this TPC working paper](https://www.taxpolicycenter.org/publications/detailed-macroeconomic-analysis-president-bidens-2020-campaign-tax-proposals) to see if the levels of wealth (and not just the shares,...

I found a Windows machine, downloaded this repo, and followed the instructions to install using the Anaconda Prompt CLI. ## Findings: * When I tried to create the environment (`conda...

@MaxGhenis Yes, `psid_lifetime_income.pkl` is too big for GH (~124 MB). I haven't run that script on Colab, but runs locally fine (assuming you have all dependencies installed). All columns in...

Yes - that is a good solution!

@rickecon Thanks for raising this issue. Seems like a good solution might be to either add the `run_micro` argument to the `Calibration` class or assume that if `estimate_tax_functions=False` and `tax_func_path...

@prrathi If you are using the a `pandas.groupby`, it will group by all age values, including this indicator for a missing value. Whether you should drop these values might depend...

@prrathi for consistency at this point, let's not include those over 80 and under 20.

Some plots: DEP functions estimated on Tax-Calculator 3.4.1 (each line is a different age- blues for younger, red for older):  GS functions estimated on Tax-Calculator 3.5.1: 

Some key questions: 1. Are these odd functions and artifact of the microsimulation model output or `txfunc.py` (there have been changes to both)? 2. Are these functions "correct" (i.e., do...

Re (2) above, I don't see how these could be the best fit (albeit, the scatter plot dots do not reflect sampling weights): ETRs for 40 year olds, DEP functions...