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We want to refactorize the code related with AMSS including a series of lectures including `opt_tax_recur` and `amss` (and potentially `amss2` and `amss3` in the near future) by a collaboration...

Lecture [chang_credible](https://python-advanced.quantecon.org/chang_credible.html) fails with the following error: I suspect it could have something to do with the following warning: The version of `scipy` and `polytope` packages are: ``` scipy 1.4.1...

Small issues in the math of *Information and Consumption Smoothing*. * It says > which confirms that {a_t} is a **serially uncorrelated** process with variance > σ^2_a=β^{−1}σ^2_ε. when this should...

We are getting reports of issues for `numba=0.49` coming through on the `QuantEcon` package as well as lecture failures. There are some big changes in `numba=0.49` due to restructuring the...

bug

Every lecture should start with an Overview section. Perhaps also review the lecture an break into more subsections.

https://scholar.harvard.edu/files/antras/files/gvc_ag_latest_draft.pdf Uses a Bellman equation. Could be a complement to Coase's theory of the firm lecture.

- [ ] ( line 305 ) `https://python-intro.quantecon.org/finite_markov.html#Marginal-Distributions` → `https://python-intro.quantecon.org/finite_markov.html#mc_fdd` - [ ] ( line 348 ) `https://python-intro.quantecon.org/finite_markov.html#Marginal-Distributions` → `https://python-intro.quantecon.org/finite_markov.html#mc_fddv` - [ ] ( line 671 ) `https://python-intro.quantecon.org/finite_markov.html#Stationary-Distributions` → `https://python-intro.quantecon.org/finite_markov.html#mc_stat_dd`

- [ ] ( line 34 ) `https://python-intro.quantecon.org/markov_asset.html#Risk-Neutral-Pricing` → `https://python-intro.quantecon.org/markov_asset.html#mass_pra`

The execution test for [Credible Government Policies in Chang Model](https://python.quantecon.org/chang_credible.html) and [Competitive Equilibria in the Chang Model](https://python.quantecon.org/chang_ramsey.html) is failing. There is a ValueError triggered when `ch1.solve_sustainable()` is called. It looks...