Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Tom's July 25 edits of calvo_machine_learning lecture #169

Merged
merged 1 commit into from
Jul 27, 2024
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
23 changes: 14 additions & 9 deletions lectures/calvo_machine_learn.md
Original file line number Diff line number Diff line change
Expand Up @@ -156,12 +156,6 @@ the linear difference equation {eq}`eq_grad_old2` can be solved forward to get:
\theta_t = \frac{1}{1+\alpha} \sum_{j=0}^\infty \left(\frac{\alpha}{1+\alpha}\right)^j \mu_{t+j}, \quad t \geq 0
```

```{note}
Equation {eq}`eq_grad_old3` shows that an equivalence class of continuation money growth sequences $\{\mu_{t+j}\}_{j=0}^\infty$ deliver the same $\theta_t$. Consequently, equations {eq}`eq_grad_old1` and {eq}`eq_grad_old3` show that $\theta_t$ intermediates
how choices of $\mu_{t+j}, \ j=0, 1, \ldots$ impinge on time $t$
real balances $m_t - p_t = -\alpha \theta_t$. Chang {cite}`chang1998credible` exploits this
fact extensively.
```



Expand Down Expand Up @@ -1189,9 +1183,9 @@ For example, we could have regressed $\theta_t$ on $\mu_t$ and obtained the same

Actually, wouldn't that direction of fit have made more sense?

After all, the Ramsey planner is **choosing** $\vec \mu$ while $\vec \theta$ is the outcome.
After all, the Ramsey planner chooses $\vec \mu$, while $\vec \theta$ is an outcome that reflects the represenative agent's response to the Ramsey planner's choice of $\vec \mu$.

Which is **cause** and which is **effect**?
Isn't it more natural then to expect that we'd learn more about the structure of the Ramsey problem from a regression of components of $\vec \theta$ on components of $\vec \mu$?

To answer such questions, we'll have to deploy more economic theory.

Expand Down Expand Up @@ -1231,4 +1225,15 @@ print(f'(d_0, d_1) = ({clq.d0:.6f}, {clq.d1:.6f})')

Evidently, these agree with the relationships that we discovered by running regressions on the Ramsey outcomes $\vec \mu^R, \vec \theta^R$ that we constructed with either of our machine learning algorithms.

We have set the stage for diving into this quantecon lecture {doc}`calvo`.
We have set the stage for this quantecon lecture {doc}`calvo`.

We close this lecture by giving a hint about an insight of Chang {cite}`chang1998credible` that
underlies much of quantecon lecture {doc}`calvo`.

Chang noticed how equation {eq}`eq_grad_old3` shows that an equivalence class of continuation money growth sequences $\{\mu_{t+j}\}_{j=0}^\infty$ deliver the same $\theta_t$.

Consequently, equations {eq}`eq_grad_old1` and {eq}`eq_grad_old3` indicate that $\theta_t$ intermediates how the government's choices of $\mu_{t+j}, \ j=0, 1, \ldots$ impinge on time $t$
real balances $m_t - p_t = -\alpha \theta_t$.

In lecture {doc}`calvo`, we'll see how Chang {cite}`chang1998credible` exploits this
insight.
Loading