Trust in Government
Trust in government refers to the share of people who report having confidence in the national government. The data shown reflect the share of respondents answering “yes” (the other response categories being “no”, and “don’t know”) to the survey question: “In this country, do you have confidence in… national government?”
Due to small sample sizes, country averages for horizontal inequalities (by age, gender and education) are pooled between 2010-18 to improve the accuracy of the estimates.
The sample is ex ante designed to be nationally representative of the population aged 15 and over. The population-wide figure is returned – both sexes, all education levels – as an annual decimal fraction of that population (0.3933 for 39.33%). The breakdowns by sex and education level that the OECD publishes alongside it are not returned here.
See definition: https://data.oecd.org/gga/trust-in-government.htm
Also known as: political trust, institutional trust.
Trust in Government in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_trust_in_government as shown below.
from financetoolkit import Economics
economics = Economics(end_date="2025-12-31")
trust_in_government = economics.get_trust_in_government()
trust_in_government.loc[:, ['United States', 'Greece', 'Japan']]
Or, after setting up the Finance Toolkit MCP, ask:
What share of people trusted their national government in the United States, Greece and Japan from 2006 to 2025?
Which returns:
| United States | Greece | Japan | |
|---|---|---|---|
| 2006 | 0.4756 | 0.4345 | 0.2952 |
| 2007 | 0.4756 | 0.4345 | 0.2952 |
| 2008 | 0.4335 | 0.2764 | 0.2478 |
| 2009 | 0.4335 | 0.2764 | 0.2478 |
| 2010 | 0.4335 | 0.2764 | 0.2478 |
| 2011 | 0.34 | 0.1483 | 0.2528 |
| 2012 | 0.34 | 0.1483 | 0.2528 |
| 2013 | 0.34 | 0.1483 | 0.2528 |
| 2014 | 0.3309 | 0.2527 | 0.3649 |
| 2015 | 0.3309 | 0.2527 | 0.3649 |
| 2016 | 0.3309 | 0.2527 | 0.3649 |
| 2017 | 0.3544 | 0.2311 | 0.4029 |
| 2018 | 0.3544 | 0.2311 | 0.4029 |
| 2019 | 0.3544 | 0.2311 | 0.4029 |
| 2020 | 0.3933 | 0.3518 | 0.3819 |
| 2021 | 0.3933 | 0.3518 | 0.3819 |
| 2022 | 0.3933 | 0.3518 | 0.3819 |
| 2023 | 0.2944 | 0.2732 | 0.3215 |
| 2024 | 0.2944 | 0.2732 | 0.3215 |
| 2025 | 0.2944 | 0.2732 | 0.3215 |
Parameters
get_trust_in_government accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
countries | list[str] | str | None | The countries to include in the data. Defaults to None. | ["United States", "Germany"] |
rolling | int | The rolling window size to use for smoothing the data (simple moving average). Defaults to None. | 4 |
trailing | int | The trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None. | 4 |
growth | bool | Whether to return the growth data or the actual data. Defaults to False. | True |
lag | int | The number of periods to lag the data by. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |
rounding | int | None | The number of decimals to round the results to. Defaults to None. | 2 |