Slope parameter of regression models

Methods
1

Hi,
The SBTi provides 2352 regression models (in the file SBTi\inputs\regression_model_summary.xlsx), that is 392 for each slope (there are 6 slopes possible, slope5, 10, 15, 20, 25, 30). When associating a regression model to a target, we use this dictionary (see image) to determine the slope parameter of the regression model. My concern is that there are 3 time frames possible for 6 slopes : indeed, slope10, slope 20 and slope25 do not have a time frame associated. Hence, the corresponding model are not used by the tool, that is half of the data provided.
Is there any reason to use the time frame in order to match a target to its slope ? If not, a solution to avoid this data loss would be to use the ‘lifetime’ of the target and map the target to the slope that minimize the value abs(lifetime - slope) : for example, a target which lives for 21 years would get a slope20 (20 is the closest value to 21 among 5,10,15,20,25,30). Note that a target like this has a LONG time frame, hence the current version of the tool associates it to slope30.

Capture_tf

2

This question has been answered in a separate discussion. But in summary, the finance tool implements SBTi’s application of the Temperature Rating method and the time frames reflect the periods used in corporate and FI target setting, where 5-15 year targets is the mid term range (later changed to 5-10 years). Targets beyond 15 years are seen as long term.