The effect of universal basic income on a novel measure of the racial wealth gap

By Will Fedder and Max Ghenis, 2021-02-28

The large racial wealth gap traces its roots to slavery, redlining, and other discriminatory policies, and persists largely due to racial income gaps. In honor of Black History month, we explore how closing part of this income gap with a universal basic income would affect the racial wealth gap, using novel measurements that consider how Black and White families differ across the full wealth distribution.

The two most common measures of the racial wealth gap simply compare mean and median wealth between White and Black families.1 Based on the 2019 Survey of Consumer Finances2, White families have mean wealth 5.7 times that of Black families, and median wealth 6.4 times that of Black families.

import warnings

import numpy as np
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
import plotly.io as pio
import ubicenter
from plotly.subplots import make_subplots

cdfs = pd.read_csv("data/cdfs.csv")
ubi_summary = pd.read_csv("data/ubi_summary.csv")
nw_quant = pd.read_csv("data/deciles.csv")


# Define UBI Center colors
BLUE = "#1976D2"
DARK_BLUE = "#1565C0"
LIGHT_BLUE = "#90CAF9"
GRAY = "#BDBDBD"
DARK_GRAY = "#616161"
BARELY_BLUE = "#E3F2FD"

colors = [BLUE, DARK_BLUE, LIGHT_BLUE, GRAY, BARELY_BLUE]

bl = ubi_summary.iloc[0].round(-2)
params = pd.DataFrame(
    {
        "Mean": {
            "White": bl.white_mean_networth_pa,
            "Black": bl.black_mean_networth_pa,
        },
        "Median": {
            "White": bl.white_median_networth_pa,
            "Black": bl.black_median_networth_pa,
        },
    }
)

fig = go.Figure(
    data=[
        go.Bar(name="White", x=params.T.index, y=params.T["White"], marker_color=GRAY),
        go.Bar(name="Black", x=params.T.index, y=params.T["Black"], marker_color=BLUE),
    ]
)

fig.update_layout(
    title="Traditional measures of the racial wealth gap",
    hovermode="x",
    xaxis_title="",
    yaxis_title="Wealth per adult (2019)",
    yaxis_tickprefix="$",
    legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.75),
)

ubicenter.format_fig(fig)