solvingmicrodsops
Christopher Carroll's Lecture Notes on Solving Microeconomic Dynamic Stochastic Optimization Problems and Indirect Inference
Science Score: 26.0%
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○Scientific vocabulary similarity
Low similarity (8.1%) to scientific vocabulary
Repository
Christopher Carroll's Lecture Notes on Solving Microeconomic Dynamic Stochastic Optimization Problems and Indirect Inference
Basic Info
- Host: GitHub
- Owner: llorracc
- License: apache-2.0
- Language: TeX
- Default Branch: master
- Size: 113 MB
Statistics
- Stars: 18
- Watchers: 4
- Forks: 19
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
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
Owner
- Name: Christopher Llorracc Carroll
- Login: llorracc
- Kind: user
- Repositories: 16
- Profile: https://github.com/llorracc
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Dependencies
- econ-ark 0.14.*
- ipywidgets
- jupyterlab
- matplotlib
- numpy
- pandas
- python 3.9.*
- voila