[inequality] Compare Labour Income and Wealth

[mmcky]

Previously we had compared labour income and income (from the World bank) Gini coefficients but they exibit different trends.
Further research into explaining these differences is required.

Looking at each data series we see an outlier in Gini coefficient computed for 1965 for `labour income`. 

We will smooth our data and take an average of the data either side of it for the time being.

```{code-cell} ipython3
ginis["l_income"][1965] = (ginis["l_income"][1962] + ginis["l_income"][1968]) / 2
```

Now we can compare net wealth and labour income.

```{code-cell} ipython3
---
mystnb:
  figure:
    caption: Gini coefficients of US net wealth and labour income
    name: gini_wealth_us2
---
fig, ax = plt.subplots()
ax.plot(years, ginis["n_wealth"], marker='o', label="net wealth")
ax.plot(years, ginis["l_income"], marker='o', label="labour income")
ax.set_xlabel("year")
ax.set_ylabel("Gini coefficient")
ax.legend()
plt.show()
```

We see that, by this measure, inequality in both wealth and income has risen
substantially since 1980.

[mmcky]

@jstac I have been thinking about this distinction. Given the tell similar overall stories (just differences in degree) I think it could be a good simplification to leave this out.

What do you think?

[jstac]

@mmcky , what does "leave this out" mean here? Drop one of the measures of income?

[mmcky]

@mmcky , what does "leave this out" mean here? Drop one of the measures of income?

@jstac The above snippet of text was removed when we edited the lecture. I am suggesting we don't add it back in.

[jstac]

Agree. Thanks @mmcky

[mmcky]

thanks @jstac