Skip to content

REPLICA: PR #355 #382

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.

Sign up for GitHub

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

Closed
wants to merge 4 commits into from
Closed

REPLICA: PR #355 #382

Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
84e7dfc
REPLICA: PR #355
mmcky Dec 19, 2023
a0ab8d3
updates from @oyamad and @jstac
mmcky Dec 19, 2023
d5cb680
revert updates
mmcky Dec 19, 2023
5c2c313
migrate changes
mmcky Dec 19, 2023
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
19 changes: 6 additions & 13 deletions lectures/lake_model.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -218,7 +218,7 @@ This class will
1. store the primitives $\alpha, \lambda, b, d$
1. compute and store the implied objects $g, A, \hat A$
1. provide methods to simulate dynamics of the stocks and rates
1. provide a method to compute the steady state of the rate
2. provide a method to compute the steady state rate using {ref}`a technique <dynamics_workers>` we previously introduced for computing stationary distributions of Markov chains

Please be careful because the implied objects $g, A, \hat A$ will not change
if you only change the primitives.
Expand Down Expand Up @@ -265,12 +265,8 @@ class LakeModel:
--------
xbar : steady state vector of employment and unemployment rates
"""
x = np.full(2, 0.5)
error = tol + 1
while error > tol:
new_x = self.A_hat @ x
error = np.max(np.abs(new_x - x))
x = new_x
x = np.array([self.A_hat[0, 1], self.A_hat[1, 0]])
x /= x.sum()
return x

def simulate_stock_path(self, X0, T):
Expand Down Expand Up @@ -415,6 +411,7 @@ plt.tight_layout()
plt.show()
```

(dynamics_workers)=
## Dynamics of an Individual Worker

An individual worker's employment dynamics are governed by a {doc}`finite state Markov process <finite_markov>`.
Expand Down Expand Up @@ -1016,12 +1013,8 @@ class LakeModelModified:
--------
xbar : steady state vector of employment and unemployment rates
"""
x = np.full(2, 0.5)
error = tol + 1
while error > tol:
new_x = self.A_hat @ x
error = np.max(np.abs(new_x - x))
x = new_x
x = np.array([self.A_hat[0, 1], self.A_hat[1, 0]])
x /= x.sum()
return x

def simulate_stock_path(self, X0, T):
Expand Down