Exploring the Use of BBAM 2010-2022 Experimental Accounts for Tracking Biodiversity Credit Market Performance

I’m eager to hear everyone’s thoughts on how we can use these accounts to gain new insights and track the biodiversity credit market in fresh and meaningful ways.

I propose the following discussion points:

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I’m eager to hear everyone’s thoughts on how we can use these accounts to gain new insights and track the biodiversity credit market in fresh and meaningful ways.

I propose the following discussion points:

  • New Tracking Ideas: How can we use the BBAM accounts to create better ways to measure how well the market is doing and its impact?
  • Looking Back and Forward: What can we learn from comparing past data with current trends to improve our understanding of the market?
  • Improving the Market: How can the insights from these accounts help us make the biodiversity credit market more efficient and trustworthy?
  • Shaping the Future: How can we use what we learn from these accounts to guide future policies and market changes?

Your input is crucial for advancing our understanding and improving the market. Please share your ideas, ask questions, and let’s work together to make a meaningful impact. I’m excited to see what we can achieve with your insights!

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Natural Capital Accounts
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Interesting discussion points Rogelio. Here are some very initial thoughts/suggestions... New Tracking Ideas: Deveolpment of a composite index from BBAM account data. Combine various mmetrics from the BBAM accounts. This could provide an objective measure of market health over time and also provide

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Interesting discussion points Rogelio. Here are some very initial thoughts/suggestions...  

New Tracking Ideas: 

  • Deveolpment of a composite index from BBAM account data. Combine various mmetrics from the BBAM accounts. This could provide an objective measure of market health over time and also provide more granular detail on market activity and impact. Notably, many governments use various composite indexes to guide their policy making decisions. 
     
  • Another possibility is to use bivariate choropleth maps to show the association between credit metrics and outcomes/impacts and how that varies by location (LGA/IBRA etc). This is more of a new way to visualize data than tracking per se, but could provide new insights. 

Looking Back and Forward: 

  • Use statistical models (or AI/ML algorithms) to make predictions of future market activity. It could be an interesting exercise and give people an idea of what to expect if current trends continue. If developed properly, it could be a sort of early warning system of potential issues in certain areas and where to focus resources. 

Improving the Market: 

  • A major factor in trusting the data is standardization in the underlying storage and data processing. In my opinion, these processes are very important. 
     
  • This might not be super relevant or even sensible... but based on some recent discussions, I wonder if it would be worth applying techniques for identifying fraudulent transactions to market activity? Put another way, it's sort of like saying, "Are all the transactions we are seeing legitimate?".  

Shaping the future:

  • I think whatever we learn from the accounts needs to be communicated effectively in a sort of pithy headline grabbing way. Specifically, it would be good to focus on the WHY of major take home points both to a general audience and to subject matter experts. 
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Hi Andrew, I really like the idea of creating a composite index using BBAM account data (and later, BAM data once it's available). From what I understand, DCCEEW is already developing a new biodiversity credits sales dashboard, which will include a composite index for market prices of credits. It

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Hi Andrew, I really like the idea of creating a composite index using BBAM account data (and later, BAM data once it's available). From what I understand, DCCEEW is already developing a new biodiversity credits sales dashboard, which will include a composite index for market prices of credits. It might be worth considering a similar composite index to track the dynamics of credit generation and retirements as well.

The bivariate choropleth maps sound like an excellent solution. Could you please share an example of what these maps would look like?

It seems many of your ideas could be incorporated into the new biodiversity credits sales dashboard, which will also feature a section with various market performance indicators. I’m looking forward to seeing the public release of the updated dashboard!

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Thanks Rogelio. They were just some initial ideas to hopefully promote thought and facilitate discussion (much like your post!) Interesting. I'd be curious to see what that composite index looks like and how it's calculated and what the dynamics of credit generation and retirements might look like

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Thanks Rogelio.  They were just some initial ideas to hopefully promote thought and facilitate discussion (much like your post!)

Interesting. I'd be curious to see what that composite index looks like and how it's calculated and what the dynamics of credit generation and retirements might look like.  


Sure. Here's a link to an example of a bivariate choropleth map. It shows the level of insurance vs donations for counties across (as categorical variables) the US. You could do something similar with different levels of categorical data https://www.joshuastevens.net/images/js_finalBivariateMap.png  

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BioBanking Assessment Methodology