The Irving Fisher Committee or IFC report, shared by the BIS, has summarized the results of a survey carried out on sustainable finance statistics among its members.
There were 63 answers, offering extensive information for 28 advanced economies (AEs) and 31 emerging market economies (EMEs).
As noted by the Bank for International Settlements in a blog post, the objective was to identify “related data needs, availability and gaps from the perspective of the central banking community, in close coordination with other international statistical initiatives.”
Sustainable finance is “defined as integrating a wide range of environmental, social and governance (ESG) aspects when making investment decisions.”
A key finding is that statistics on sustainable finance are of “growing interest to central banks in pursuing their core mandates, ie micro- and macro-prudential supervision, asset and reserve management activities, and the conduct of monetary policy.”
Central banks have been “contributing significantly to the establishment of relevant sustainable finance statistical frameworks,” the update noted. Yet there are still “substantial differences across regions with respect to standardized definitions and taxonomies,” the announcement revealed.
The IFC study identified around 80 ESG types of metric “considered of particular relevance by central banks when pursuing their policy objectives.” Information on the key central banks’ ESG metric types may be accessed here.
The data underlying the dashboard, including detailed information for 450 specific metrics is available here.
The exercise was complemented by “a stock take of core references on ESG data issues, as identified by IFC members, which are available here.”
The findings of the survey also point to “three main recommendations” for central banks:
- Intensify the identification of sustainable finance data “needs to pursue their policy objectives”
- Cooperate with traditional and new stakeholders to “close data gaps, especially at the micro level”
- Lead by example by “improving the usage of the new data being collected”