QuantEcon / QuantEcon/lecture-python-intro
Add a lecture on wealth dynamics with ideosyncratic shocks
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- Dominant language
- Jupyter Notebook
- Stars
- 65
- Forks
- 32
- Avg merge
- 4d 14h
- Merged PRs (30d)
- 6
Description
Take this lecture and focus on simulation https://python.quantecon.org/wealth_dynamics.html
This lecture should go after #14 , so there is no need to explain what the Lorenz curve and Gini coefficient are.
However, we need to carefully explain that the wealth distribution "becomes stationary" --- just by simulation, not maths
Then we explain that we are looking at inequality at the stationary distribution.
Investigate how it varies with parameters.
Simplify discussion in the last exercise --- remove mention of Kesten Goldie theorem and just ask for a rank-size plot.
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the linked wealth dynamics lecture and the lecture added by issue #14 to identify the notebook location and expected sequence. Add a simulation-focused lecture covering stationary wealth distributions and parameter variation, and simplify the final exercise to request a rank-size plot without the Kesten-Goldie theorem. Verify the notebook renders and the lecture follows #14.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100