probabilities.

```{code-cell} python

class Arellano_Economy:

class ArellanoEconomy:

" Stores data and creates primitives for the Arellano economy. "

def __init__(self,

return new_v_c, new_v_d

```

We can now write a function that will use the `Arellano_Economy` class and the

We can now write a function that will use the `ArellanoEconomy` class and the

functions defined above to compute the solution to our model.

We do not need to JIT compile this function since it only consists of outer

loops (and JIT compiling makes almost zero difference).

In fact, one of the jobs of this function is to take an instance of

`Arellano_Economy`, which is hard for the JIT compiler to handle, and strip it

`ArellanoEconomy`, which is hard for the JIT compiler to handle, and strip it

down to more basic objects, which are then passed out to jitted functions.

```{code-cell} python

def solve(model, tol=1e-8, max_iter=10_000):

"""

Given an instance of Arellano_Economy, this function computes the optimal

Given an instance of ArellanoEconomy, this function computes the optimal

policy and value functions.

"""

# Unpack

"""

Simulates the Arellano 2008 model of sovereign debt

Here `model` is an instance of `Arellano_Economy` and `T` is the length of

Here `model` is an instance of `ArellanoEconomy` and `T` is the length of

the simulation. Endogenous objects `v_c`, `v_d`, `q` and `B_star` are

assumed to come from a solution to `model`.

B_grid, y_grid, P = model.B_grid, model.y_grid, model.P

# Set initial conditions to middle of grids

if y_idx == None:

if y_idx is None:

y_idx = np.searchsorted(y_grid, y_grid.mean())

if B_idx == None:

if B_idx is None:

B_idx = B0_idx

in_default = False

In what follows, all results are computed using Arellano's parameter values.

The values can be seen in the `__init__` method of the `Arellano_Economy`

The values can be seen in the `__init__` method of the `ArellanoEconomy`

shown above.

For example, `r=0.017` matches the average quarterly rate on a 5 year US treasury over the period 1983--2001.

To the extent that you can, replicate the figures shown above

* Use the parameter values listed as defaults in `Arellano_Economy`.

* Use the parameter values listed as defaults in `ArellanoEconomy`.

* The time series will of course vary depending on the shock draws.

```{exercise-end}

Compute the value function, policy and equilibrium prices

```{code-cell} python

ae = Arellano_Economy()

ae = ArellanoEconomy()

```

```{code-cell} python