Calculation of footprint for finance

Calculate the footprint of a person’s financial transactions, adjusted with personal habit data. This can be used to nudge people towards more sustainable consumption practices.

All inputs, outputs and defaults can be seen in the Calculate finance technical API docs.

Inputs

This endpoint receives as required input:

• A list of categorised transactions (as documented under Convert finance) along with amounts per transaction
• A transaction ID (for your own reference, to know which user/transaction the data belongs to)

This endpoint receives as optional input:

• Which data source (country) you want to make calculations for - the local currency is then used in calculations
• A date for each transaction
• Answers to questions about habits that greatly affect the footprint of transactions:
  • Dietary habits (meat, dairy and seafood consumption) as documented under Calculate food and drink
  • Habits related to the consumption of goods and services (choosing quality products, repairing, ethical alternatives) as documented under Calculate goods and services

The more questions a user answers the better we understand the user’s behaviour, giving a more accurate footprint estimation. If no input date is given, the current date is used as default. If no habits are provided, the calculation will assume default answers i.e. that the user’s behaviour is similar to an average person from the data source you have specified.

Outputs

This endpoint returns the footprint of each transaction in kilos of CO2e, along with the transaction ID.

Calculations

Each financial transaction is categorised as belonging to one of Ducky’s categories. We currently operate with more than 50 categories, based on the COICOP hierarchy. We principally operate with level 2 categories, but some level 3 categories are used where data of higher resolution is relevant to the footprint.

Ducky maintains a set of time-dependent multipliers describing the amount of CO2e emissions associated with money spent in a given sector (see Methodology for more on this topic). We further adjust our multipliers with habit input using the following logic:

• Answers to dietary questions are used to calculate your estimated dietary footprint, which we then use to normalise any food spending relative to the average diet.
• Quality consumer: We assume here that quality goods are more expensive, but that the CO2e emissions for comparable products (e.g. a cheap and expensive t-shirt) are about the same. That means that the emissions intensity (g CO2e/monetary unit) is lower for the quality item, and the multipliers related to goods categories are scaled by a factor depending on the habit input.
• Repair consumer: We assume here that some spending in goods categories is related to repair, rather than purchasing new items. Repairing has a much lower emissions intensity (g CO2e/monetary unit) than buying new items, so the multipliers related to goods categories are scaled by a factor of up to 20% depending on the habit input.
• Ethical consumer: We assume that individuals who purchase ethical and environmentally conscious goods and services both pay slightly more for them, and that these goods in themselves are less emissions intensive. Multipliers associated with all categories are scaled by a factor of up to 15% depending on the habit input. 

Please refer to Convert Finance for sources related to multipliers.