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[geom_series] Add an exercise #524

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[geom_series] Add an exercise
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Merge branch 'update_geom_series' of https://github.com/QuantEcon/lec…
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101 changes: 81 additions & 20 deletions lectures/geom_series.md
Original file line number Diff line number Diff line change
Expand Up @@ -743,7 +743,7 @@ the value of a lease of duration $T$ approaches the value of a
perpetual lease.

Now we consider two different views of what happens as $r$ and
$g$ covary
$g$ covary.

```{code-cell} ipython3
---
Expand Down Expand Up @@ -852,17 +852,40 @@ so $\frac{\partial p_0}{\partial r}$ will always be negative.
Similarly, $\frac{\partial p_0}{\partial g}>0$ as long as $r>g$, $r>0$ and $g>0$ and $x_0$ is positive, so $\frac{\partial p_0}{\partial g}$
will always be positive.

## Back to the Keynesian multiplier
## Exercises

We will now go back to the case of the Keynesian multiplier and plot the
time path of $y_t$, given that consumption is a constant fraction
of national income, and investment is fixed.
```{exercise-start}
:label: geom_ex1
```
Consider a dynamic Keynesian multiplier model

$$
y_t = c_t + i_t + g_t \ \ \textrm { and } \ \ c_t = b y_{t-1}.
$$

Assume that $i_t=i_0$ and $g_t=g_0$ for all $t \geq 0$.

Plot the time path of $y_t$ with the following initial values:

```{code-cell} ipython3
i_0 = 0.3
g_0 = 0.3
b = 2/3
y_init = 0
T = 100
```

```{exercise-end}
```

```{solution-start} geom_ex1
:class: dropdown
```
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```{code-cell} ipython3
---
mystnb:
figure:
caption: "Path of aggregate output tver time"
caption: "Path of aggregate output over time"
name: path_of_aggregate_output_over_time
---
# Function that calculates a path of y
Expand All @@ -873,14 +896,6 @@ def calculate_y(i, b, g, T, y_init):
y[t] = b * y[t-1] + i + g
return y

# Initial values
i_0 = 0.3
g_0 = 0.3
# 2/3 of income goes towards consumption
b = 2/3
y_init = 0
T = 100

fig, ax = plt.subplots()
ax.set_xlabel('$t$')
ax.set_ylabel('$y_t$')
Expand All @@ -893,9 +908,29 @@ plt.show()
In this model, income grows over time, until it gradually converges to
the infinite geometric series sum of income.

We now examine what will
happen if we vary the so-called **marginal propensity to consume**,
i.e., the fraction of income that is consumed
```{solution-end}
```

```{exercise-start}
:label: geom_ex2
```

As an extension to {ref}`geom_ex1`.

Plot the time paths of $y_t$ with the same initial values but varying $b$ values:

```{code-cell} ipython3
bs = (1/3, 2/3, 5/6, 0.9)
```

Interpret the economic effect on $y_t$ of increasing $b$.

```{exercise-end}
```

```{solution-start} geom_ex2
:class: dropdown
```

```{code-cell} ipython3
---
Expand All @@ -904,7 +939,6 @@ mystnb:
caption: "Changing consumption as a fraction of income"
name: changing_consumption_as_fraction_of_income
---
bs = (1/3, 2/3, 5/6, 0.9)

fig,ax = plt.subplots()
ax.set_ylabel('$y_t$')
Expand All @@ -920,7 +954,32 @@ plt.show()
Increasing the marginal propensity to consume $b$ increases the
path of output over time.

Now we will compare the effects on output of increases in investment and government spending.
```{solution-end}
```


```{exercise-start}
:label: geom_ex3
```
Continue from {ref}`geom_ex1` with the following values
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```{code-cell} ipython3
values = [0.3, 0.4]
```

First, plot the time paths of $y_t$ using the same initial values but with $i$
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taking the values mentioned above.
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Next, plot the time paths of $y_t$ with the same initial values but let $g$ take
the values abovementioned.
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@SylviaZhaooo not 100% sure which values abovementioned is referring to. Would it be possible to clarify?


Are the effects on $y_t$ of increasing $i$ and $g$ in these plots the same?
```{exercise-end}
```

```{solution-start} geom_ex3
:class: dropdown
```

```{code-cell} ipython3
---
Expand All @@ -933,7 +992,6 @@ fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(6, 10))
fig.subplots_adjust(hspace=0.3)

x = np.arange(0, T+1)
values = [0.3, 0.4]

for i in values:
y = calculate_y(i, b, g_0, T, y_init)
Expand All @@ -955,3 +1013,6 @@ plt.show()
Notice here, whether government spending increases from 0.3 to 0.4 or
investment increases from 0.3 to 0.4, the shifts in the graphs are
identical.

```{solution-end}
```