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Christopher Carroll's Lecture Notes on Solving Microeconomic Dynamic Stochastic Optimization Problems and Indirect Inference

License: Apache License 2.0

TeX 66.21% Stata 1.52% PostScript 13.82% Shell 0.15% Roff 0.01% Jupyter Notebook 15.93% Python 2.09% Perl 0.01% Emacs Lisp 0.27%

solvingmicrodsops's Introduction

SolvingMicroDSOPs

Installation

See the instructions at https://econ-ark.org/materials/SolvingMicroDSOPs

Structure

Jupyter notebook corresponding to the SolvingMicroDSOPs lecture notes
Python Code that does the structual estimation

Replication

To reproduces all the results in the repository first clone this repository locally:

# Clone this repository
$ git clone https://github.com/econ-ark/SolvingMicroDSOPs

# Change working directory to SolvingMicroDSOPs
$ cd SolvingMicroDSOPs

Then you can either use a local virtual env(conda) or nbreproduce to reproduce to the results.

A local conda environment and execute the do_all.py file.

$ conda env create -f environment.yml
$ conda activate solvingmicrodsops
# execute the script, select the appropriate option and use it to reproduce the data and figures.
$ python do_all.py

Local conda environment to execute the notebooks

$ conda env create -f environment.yml
$ conda activate solvingmicrodsops
# open jupyter lab, browse through the notebooks and execute them.
$ jupyter lab

nbreproduce (requires Docker to be installed on the machine).

# Install nbreproduce
$ pip install nbreproduce

# Reproduce all results using nbreproduce
$ nbreproduce

References

solvingmicrodsops's People

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lnsongxf jovansam anhnguyendepocen macrofinancehub dynamicprogramming-structuralestimation amonninger naiyang97 yupeiliuxiang lucasandlevinandjadon jiaecon alanlujan91 econ-ark shizelong1985 sbyeuva tudorschlanger dedwar65

solvingmicrodsops's Issues

Replication issues with gothic_class.ipynb

Thank you for putting together the lecture notes and corresponding codes, they have been clear and instructive!

I have been trying to replicate the figures in the lecture notes (e.g. Figure 2) using the gothic_class.ipynb codes - which seems to be the right set of codes to replicate such figures, please correct me if I'm wrong.

However, when I try to define the arguments needed to run the function Gothic.C_Tminus1 (i.e. a_grid, self_a_min), the code throws errors that I am unable to resolve just by looking at the Gothic class alone.

Would you be able to provide more code or comments that allow users (with limited object oriented programming in Python) to run this replication successfully?

That would be much appreciated,
Tudor

Python/Code/snippets does not actually contain Python code

Not sure what happened here, but @llorracc can you take a look?

The Python/Code/snippets/*.py files are either empty (with a comment or two) or contain pseudocode that is not valid Python.
For a direct link see: https://github.com/llorracc/SolvingMicroDSOPs/tree/604970acb909a95fae70743757b9155c324bea61/Code/Python/snippets

Should the entire snippets folder be removed?

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