Get the Household Debt to Disposable Income Ratio for a variety of countries over time from the OECD’s Household Dashboard. This expresses total household gross debt (loans and debt securities) as a share of household gross disposable income, returned as a decimal ratio (1.0014 means debt equals 100.14% of income).

It is a standard household-leverage indicator used in financial-stability analysis: a high or rapidly rising ratio signals households are more exposed to income shocks or interest rate increases (debt-servicing costs rise directly with rates on variable-rate or refinanced debt), and has historically preceded credit-cycle downturns (e.g. in the lead-up to the 2008 financial crisis). It is the household- sector analogue to government debt (see get_government_debt_to_gdp_ratio) - the two together give a fuller picture of an economy’s overall leverage.

See definition: https://data-explorer.oecd.org/vis?df[ds]=dsDisseminateFinalDMZ&df[id]=DSD_HHDASH%40DF_HHDASH_INDIC

Also known as: household leverage ratio, debt-to-income ratio.

No programming experience? With the Finance Toolkit MCP server, AI assistants such as Claude and ChatGPT can calculate the Household Debt to Income Ratio for you. Just ask in plain English.

Calculate the Household Debt to Income Ratio in Python

The Household Debt to Income Ratio is available in the Economics module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_household_debt_to_income_ratio as shown below.

from financetoolkit import Economics

economics = Economics(start_date='2015-01-01', end_date='2022-12-31')

economics.get_household_debt_to_income_ratio(
    countries=['United States', 'Australia'],
    quarterly=False)

Which returns:

  United States Australia
2018 1.0014 1.9888
2019 0.9955 1.9676
2020 0.9532 1.8811
2021 0.9624 1.9168
2022 1.0162 1.9253

Parameters

get_household_debt_to_income_ratio accepts the following parameters:

  • countries (list[str] | str | None, optional): The countries to include in the data. Defaults to None.
  • quarterly (bool | None, optional): Whether to return the quarterly data or the annual data.
  • rolling (int, optional): The rolling window size to use for smoothing the data (simple moving average). Defaults to None.
  • trailing (int, optional): The trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None.
  • growth (bool, optional): Whether to return the growth data or the actual data.
  • lag (int, optional): The number of periods to lag the data by.
  • standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
  • rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.
Rent Prices Share Prices Exchange Rates Producer Price Index Real Effective Exchange Rate Household Savings Rate Misery Index Retail Sales Industrial Production Index Housing Starts Real Personal Income Commercial Real Estate Prices

The Economics module page introduces the module, and the sidebar lists all of its functions.

Share