Banking Crisis
Get the Banking Crisis dummy for a variety of countries over time from the Global Macro Database (GMDB). Unlike the other indicators in this module, this is a binary (0 = no crisis, 1 = crisis) Reinhart & Rogoff style crisis-dating series rather than a continuous economic series: a value of 1 marks a year in which a country was undergoing a systemic banking crisis (e.g. bank runs, large-scale bank failures or government intervention to prevent them), and 0 marks a year in which it was not.
The crisis dating stops well short of the present – the series currently ends in 2020 – so recent years are NaN rather than 0.
Data comes from the Global Macro Database (GMDB), further information about the variable can be found within https://www.globalmacrodata.com/documentation.html
Also known as: banking panic, financial crisis dummy, systemic banking crisis.
Banking Crisis in Python
get_banking_crisis is part of the Economics module of the open-source Finance Toolkit. Install it with:
pip install financetoolkit -U
Then call get_banking_crisis as shown below.
from financetoolkit import Economics
economics = Economics(start_date='2005-01-01')
economics.get_banking_crisis(countries=['United States', 'United Kingdom'])
Which returns:
| United Kingdom | United States | |
|---|---|---|
| 2016 | 0 | 0 |
| 2017 | 0 | 0 |
| 2018 | 0 | 0 |
| 2019 | 0 | 0 |
| 2020 | 0 | 0 |
Parameters
get_banking_crisis accepts the following parameters:
- countries (list[str] | str | None, optional): A list of countries or a single country to include in the results. 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.
- rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.