Code used in paper Jeremy Fox, Vitor Hadad, Stefan Hoderlein, Amil Petrin and Robert Sherman (In progress). Heterogenous Production Functions, Panel Data, and Productivity Dispersion. Our application is called FHHPS, after the authors' initials.
The setup is a linear panel data with two correlated random coefficients. It is assumed that the coefficients follow AR(1) processes where the shocks are assumed to be independent of everything in the previous K periods.
The application we have in mind is the identification and estimation of first and second moments of Cobb Douglas coefficients of a production function. For more details, please contact Vitor Hadad at vitorh@stanford.edu.
To run fhhps, you will need Python 3.7 or newer.
For MAC OSX / Linux
Clone our repo.
git clone https://github.com/halflearned/FHHPS/
cd FHHPS/To install in an existing environment.
python setup.py develop
To create a new environment (recommended).
conda create --name fhhpsenv
conda activate fhhpsenv
python setup.py develop
After that you should be able to import our package like you would any other.