Personal Independence Payment (PIP)#
Personal Independence Payment (PIP) is a benefit payment administered by the Department for Work and Pensions (DWP) in the United Kingdom. It is designed to provide financial support to individuals with long-term health conditions or disabilities. PIP helps recipients with the extra costs associated with their condition and is not means-tested. PIP is divided into two main components:
Daily Living Component: This component provides support to individuals who need help with daily living activities due to their health condition or disability. The level of support is based on an assessment of the individual’s needs and can include assistance with tasks like cooking, dressing, and personal hygiene.
Mobility Component: The mobility component is aimed at individuals who face mobility challenges due to their condition. It can cover costs related to mobility aids, transportation, and other expenses associated with getting around.
More information could be found on the GOV.UK (Personal Independence Payment) website.
PIP components are awarded at different rates, depending on the extent of the individual’s needs and the impact of their health condition or disability.
Pension Credit parameters can be found in policyengine_uk/parameters/gov/dwp/pip and logic in policyengine_uk/variables/dwp/pip.py.
Legislation#
The legal framework for Personal Independence Payment is primarily defined in the legislation provided on the The Social Security (Personal Independence Payment) Regulations 2013 legislation website.
PIP Rate Changes#
The Daily Living component of Personal Independence Payment (PIP) can be further divided into two rates: the Enhanced Rate and the Standard Rate. These rates are determined based on the level of assistance an individual requires with daily living activities due to their health condition or disability.
Enhanced Rate for Daily Living: This is the higher rate of the Daily Living component. Individuals who receive the Enhanced Rate need more substantial help and support to perform daily living activities. They may have more severe health conditions or disabilities that significantly affect their ability to independently carry out tasks such as cooking, dressing, bathing, managing medications, and handling finances. The Enhanced Rate provides a higher level of financial support to help cover the additional costs associated with these substantial care needs.
Standard Rate for Daily Living: The Standard Rate is the lower rate of the Daily Living component. Individuals who receive the Standard Rate still require assistance with daily living activities, but their needs are not as extensive or severe as those who qualify for the Enhanced Rate. This rate is for individuals with moderate care needs who may need some help with daily tasks but can manage many activities independently. The Standard Rate provides a lower level of financial support compared to the Enhanced Rate.
The table below shows the rates changes covered by PolicyEngine-UK.
Show code cell source
from policyengine_uk.system import system
parameters = system.parameters
enhanced_daily = parameters.gov.dwp.pip.daily_living.enhanced
standard_daily = parameters.gov.dwp.pip.daily_living.standard
elements = [enhanced_daily, standard_daily] # [...]
dates = ["2016-01-01","2017-01-01","2018-01-01","2019-01-01","2020-01-01", "2021-01-01", "2022-01-01","2023-01-01"]
names = ["enhanced", "standard"]
import pandas as pd
df = pd.DataFrame()
for date in dates:
for element, name in zip(elements, names):
# Append to a dataframe: row = date, column = element, value = amount
new_row = {
"date": date,
"element": name,
"amount": element(date)
}
# Append row to the dataframe
df = pd.concat([df, pd.DataFrame([new_row])])
# merge element cells
pivot_df = df.pivot(index="date", columns="element", values="amount")
pivot_df.fillna("")
| element | enhanced | standard |
|---|---|---|
| date | ||
| 2016-01-01 | 82.30 | 55.10 |
| 2017-01-01 | 82.30 | 55.10 |
| 2018-01-01 | 83.10 | 55.65 |
| 2019-01-01 | 85.60 | 57.30 |
| 2020-01-01 | 87.65 | 58.70 |
| 2021-01-01 | 89.15 | 59.70 |
| 2022-01-01 | 89.60 | 60.00 |
| 2023-01-01 | 92.40 | 61.85 |
Show code cell source
import plotly.express as px
from policyengine_core.charts import format_fig
fig = px.line(
df,
title="Daily living elements over time",
x="date",
y="amount",
color="element",
).update_layout(
yaxis_range=[0, 100],
yaxis_tickformat=",.0f",
yaxis_tickprefix="£",
yaxis_title = "Amount(£m)",
xaxis_title = "Year",
legend_title = "Element"
)
fig = format_fig(fig)
fig
The Mobility Component of PIP is divided into two rates:
Enhanced Rate for Mobility: This is the higher rate of the Mobility Component. Individuals who qualify for the Enhanced Rate face significant mobility challenges due to their health condition or disability. They may require substantial support and assistance for mobility-related activities. This can include covering expenses for mobility aids, adaptive transportation, and other costs associated with their condition. The Enhanced Rate offers a higher level of financial support to address these more severe mobility needs.
Standard Rate for Mobility: The Standard Rate is the lower rate of the Mobility Component. Individuals who receive the Standard Rate have less severe mobility challenges compared to those eligible for the Enhanced Rate. They may still face mobility difficulties but do not require the same level of support as those at the Enhanced Rate. The Standard Rate provides a lower level of financial assistance compared to the Enhanced Rate to help individuals manage their mobility-related expenses.
Show code cell source
from policyengine_uk.system import system
parameters = system.parameters
enhanced_mobility = parameters.gov.dwp.pip.mobility.enhanced
standard_mobility = parameters.gov.dwp.pip.mobility.standard
elements = [enhanced_mobility, standard_mobility] # [...]
dates = ["2016-01-01","2017-01-01","2018-01-01","2019-01-01","2020-01-01", "2021-01-01", "2022-01-01","2023-01-01"]
names = ["enhanced", "standard"]
import pandas as pd
df = pd.DataFrame()
for date in dates:
for element, name in zip(elements, names):
# Append to a dataframe: row = date, column = element, value = amount
new_row = {
"date": date,
"element": name,
"amount": element(date)
}
# Append row to the dataframe
df = pd.concat([df, pd.DataFrame([new_row])])
# merge element cells
pivot_df = df.pivot(index="date", columns="element", values="amount")
pivot_df.fillna("")
| element | enhanced | standard |
|---|---|---|
| date | ||
| 2016-01-01 | 55.10 | 21.80 |
| 2017-01-01 | 55.10 | 21.80 |
| 2018-01-01 | 55.65 | 22.00 |
| 2019-01-01 | 57.30 | 22.65 |
| 2020-01-01 | 58.70 | 23.20 |
| 2021-01-01 | 59.70 | 23.60 |
| 2022-01-01 | 60.00 | 23.70 |
| 2023-01-01 | 61.85 | 24.45 |
Show code cell source
import plotly.express as px
from policyengine_core.charts import format_fig
fig = px.line(
df,
title="Mobility elements over time",
x="date",
y="amount",
color="element",
).update_layout(
yaxis_range=[0, 100],
yaxis_tickformat=",.0f",
yaxis_tickprefix="£",
yaxis_title = "Amount(£m)",
xaxis_title = "Year",
legend_title = "Element"
)
fig = format_fig(fig)
fig