Stamp Duty Land Tax

Stamp Duty Land Tax (SDLT) is a tax imposed on the purchase and rental of properties or land with values over a certain threshold in England and Northern Ireland. It applies to both residential and non-residential (commercial) properties.

Stamp Duty Land Tax parameters can be found in policyengine_uk/parameters/gov/hmrc/stamp_duty and logic in policyengine_uk/variables/gov/hmrc/stamp_duty_land_tax.py.

Legislation

The regulation of SDLT is defined in part 4 of the Finance Act 2003.

Rates

The rates of SDLT depend on various factors, including the purchase price of the property, property type, and whether it is an additional property or a purchase by a first-time buyer. Generally, SDLT rates are higher for properties or land with a purchase price exceeding a specific threshold, often referred to as “stamp duty bands” or “stamp duty brackets.” The rules and thresholds for SDLT may change over time due to government policy adjustments. First-time buyers may be eligible for reduced SDLT rates if the purchase price of the property is not more than £500,000.

Here we show current rates and thresholds for SDLT under different situations in 2023 below:

Residential

• Rent

  Up to £125,000: 0%

  Over £125,000: 1%

• Purchase

  • Main property

    • First-time

      Up to £300,000: 0%

      £300,000 to £500,000: 5%

      Over £500,000: Ineligible for relief, follow standard rates

    • Subsequent (standard rates):

      Up to £125,000: 0%

      £125,000 to £250,000: 2%

      £250,000 to £925,000: 5%

      £925,000 to £1,500,000: 10%

      Over £1,500,000: 12%

  • Additional property

    An additional 3% on top of the standard rates for each band. However, a secondary property or land with a purchase price or market value less than £40,000 will be exempt from SDLT.

    Less than £40,000: 0%

    £40,000 to £125,000: 3%

    £125,000 to £250,000: 5%

    £250,000 to £925,000: 8%

    £925,000 to £1,500,000: 13%

    Over £1,500,000: 15%

Non-residential

• Rent

  Up to £150,000: 0%

  £150,000 to £5,000,000: 1%

  Over £5,000,000: 2%

• Purchase

  Up to £150,000: 0%

  £150,000 to £250,000: 2%

  Over £250,000: 5%

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import pandas as pd
import plotly.express as px
from policyengine_core.charts import format_fig

residential_rent = pd.DataFrame(
    {
        "Threshold": [0, 125000, 5200000],
        "Rate": [0, 0.01, 0.01],
        "Label": ["Residential rent"] * 3,
    }
)
residential_purchase_main_first = pd.DataFrame(
    {
        "Threshold": [0, 300000, 500000, 925000, 1500000, 5200000],
        "Rate": [0, 0.05, 0.05, 0.1, 0.12, 0.12],
        "Label": ["Residential purchase main (first home)"] * 6,
    }
)
residential_purchase_main_standard = pd.DataFrame(
    {
        "Threshold": [0, 125000, 250000, 925000, 1500000, 5200000],
        "Rate": [0, 0.02, 0.05, 0.1, 0.12, 0.12],
        "Label": ["Residential purchase main standard"] * 6,
    }
)
residential_purchase_additional = pd.DataFrame(
    {
        "Threshold": [0, 40000, 125000, 250000, 925000, 1500000, 5200000],
        "Rate": [0, 0.03, 0.05, 0.08, 0.13, 0.15, 0.15],
        "Label": ["Residential purchase additional"] * 7,
    }
)
non_residential_rent = pd.DataFrame(
    {
        "Threshold": [0, 150000, 5000000, 5200000],
        "Rate": [0, 0.01, 0.02, 0.02],
        "Label": ["Non-residential rent"] * 4,
    }
)
non_residential_purchase = pd.DataFrame(
    {
        "Threshold": [0, 150000, 250000, 5200000],
        "Rate": [0, 0.02, 0.05, 0.05],
        "Label": ["Non-residential purchase"] * 4,
    }
)
df_list = [
    residential_rent,
    residential_purchase_main_first,
    residential_purchase_main_standard,
    residential_purchase_additional,
    non_residential_rent,
    non_residential_purchase,
]
df = pd.concat(df_list)
# plot
fig = (
    px.line(
        df,
        x="Threshold",
        y="Rate",
        color="Label",
        title="Stamp duty land tax rates over property price thresholds",
    )
    .update_layout(
        yaxis_tickformat=",.0%",
        xaxis_tickprefix="£",
        legend=dict(
            orientation="h",
            yanchor="bottom",
            y=-0.3,
            xanchor="right",
            x=0.9,
            title="",
        ),
    )
    .update_traces(line_shape="hv")
)
fig = format_fig(fig)
fig