Get the Government Tax Revenue to GDP Ratio for a variety of countries over time from the Global Macro Database (GMDB). The Government Tax Revenue to GDP Ratio is the ratio of the total amount of money that a government collects from taxes to the Gross Domestic Product (GDP).

Data comes from the Global Macro Database (GMDB), further information about the variable can be found within https://www.globalmacrodata.com/documentation.html

The ratio is expressed as a decimal fraction (0.1022 for 10.22% of GDP).

Changed in v2.2.0: this used to be returned in percentage points. It is now a decimal fraction, matching every other ratio in the Finance Toolkit.

Also known as: tax burden, tax to GDP ratio.

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

Calculate the Tax Revenue to GDP in Python

The Tax Revenue to GDP is available in the Economics module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_government_tax_revenue_to_gdp_ratio as shown below.

from financetoolkit import Economics

economics = Economics(start_date='2015-01-01')

economics.get_government_tax_revenue_to_gdp_ratio(
    countries=['United States', 'Canada', 'Mexico'])

Which returns:

  United States Canada Mexico
2015 0.1994 0.1239 0.1318
2016 0.1958 0.125 0.1386
2017 0.2031 0.1261 0.134
2018 0.1874 0.1306 0.1336
2019 0.1888 0.1274 0.1348
2020 0.1934 0.135 0.1452
2021 0.2065 0.1322 0.1414
2022 0.2156 0.1283 0.1368
2023 0.1022 0.1401 0.1427

Parameters

get_government_tax_revenue_to_gdp_ratio accepts the following parameters:

  • countries (list[str] | str | None, optional): The countries to include in the data. Defaults to None.
  • 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. Defaults to False.
  • lag (int, optional): The number of periods to lag the growth data. Defaults to 1.
  • 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.

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

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