Green Economy Policy Monitoring: Expert exchange on connecting three monitoring domains

The first session will explore the current digital frontier in green economy policy monitoring and discuss how technologies including AI, ML could be used to further to address bottlenecks.

• The strengths and limitations of current green economy policy monitoring (5 minutes – Simon Evenett and UNEP Team)
• Challenges and opportunities for applying digital technologies in green economy policy monitoring (5 minutes – Michal Nachmany)

Open Discussion (25 minutes)

Data collection:

• In a perfect world, what data on green economy policies would be available for evidence-based decision-making? How far is green economy policy monitoring from providing that quality of data?
• What is the best practice in the collection of green economy policy data? How has the problem of siloes in green economy policy data been addressed?
• How can digital technologies be used to collect more up-to-date data on green economy policies? Can policy changes be monitored in real-time, as announced by countries?
• What information is being extracted from green economy policies? Is this done manually or is there a technology application for data extraction? How can digital technologies be used to extract more information from policy documents and policy releases?

Data analysis:

• What are best practices in the classification of policies? How are policies classified in terms of their relevance to a) economic actors and b) impacts on the environment?
• What digital technologies could be used to classify green economy policies at a greater scale? How could methodologies for classifying policies be automated? Including those observed in green recovery trackers
• What attempts are being made to forecast the expected outcomes of green economy policies on the environment? What attributes of green economy policies may be operationalised to forecast outcomes? What about contextual factors (i.e. macro-economic conditions, popular support, historical investment)?
• What efforts are being made to measure the outcomes of green economy policies on the economy and the environment? For example – have changes in deforestation rates been connected to green economy policies on the food and agricultural sectors? How could digital tools be used to advance the measurement of policy outcomes, and what non-policy data would be needed?
• To begin to introduce effects-based analysis, what improvement in data would be needed from environmental monitoring? Including interoperability, timeframe, scope, reliability

The second session will discuss the technological readiness for a more responsive compliance mechanism with green economy policies, drawing on insights from the RegTech field. The aim is to identify the technologies and supply chain data necessary for a more responsive regime of green economy policies.

• The growth of RegTech, underlying technologies and what can be learned from RegTech in the finance industry (Douglas Arner – 5 minutes)
• The application of RegTech to ESG regulations, focusing on compliance with environmental regulations; the challenges of data availability and compliance (Inna Amesheva  - 5 minutes)

Open Discussion (25 minutes)

• What’s the market need among economic operators for technology solutions of complying with green economy policy measures? Is there a sector of RegTech or Compliance Technology for green economic measures in the rising? How different is it from the traditional scope of RegTech?

• What policy data is required for digitally enabled compliance? How could advances in data availability from green economy policy monitoring lead to enhanced compliance? How do RegTech solutions react to and adapt to changes in policies and regulations?
• How can green economy policies be made operable for digital compliance? How far can digital technologies (i.e. NLP, ML) extract key information and match green economy policies with business data? How do RegTech tools determine the relevance of a policy to a business’s activities?
• What are the specific challenges for using digital technologies to streamline compliance with green economy policies? What are the challenges of using RegTech approaches for environmental compliance compared to more established fields, such as financial regulations? (to be explored further in use case examples)

• For more responsive, digitally enabled compliance with green economy policies, what proprietary data would be needed from businesses? What data infrastructure would be necessary for a responsive, real-time compliance mechanism? Both for businesses and policymakers
• For public monitoring and investors, do transparency practices such as the sustainability reporting requirements and climate-related financial disclosures provide reliable data for evaluating the regulatory effect of green economy policies over supply chains?
  • In your observation, what level of data access are supply chain operators willing to grant to technology solution/services providers for regulatory compliance?
  • In addition to transparency requirements, how could business be incentivised for public private data sharing to allow policy innovations such as the EU digital product passport?
  • What is the maturity of digital solutions for data sharing, such as tokenisation, anonymisation?

The effectiveness of green economy policy monitoring ultimately depends on the uptake of  intelligence by economic operators and by policymakers. The context of successful application of RegTech in the financial sector is the level of digitalization of the whole sector.  Below, use cases provide examples of green economy policy issues in the agri-food sector, which cover the interest of public and private actors in improved policy regimes. Building on technical questions as listed below, the discussion helps to build an understanding on the transformation from machine-readable economic policies to machine-enforceable policies, in the context of environmental governance.

Note that the use cases might require some prior knowledge of thematic areas. Experts are encouraged to raise alternative examples with explanations prior to the meeting.

Case 1: administering EU regulation on ‘deforestation-free’ products

Case outline:

• A new EU regulation states that commodities and products may only be placed on the Union’s market if they are ‘deforestation-free’.
• ‘Deforestation-free’ is defined such that “the relevant commodities and products… were produced on land that has not been subject to deforestation after 31 Dec 2020”.
• For operators, the compliance challenge is to store required information (such as geo-location data for products), conduct due diligence on goods, and produce specific reports based on the product and its origin
• For responsible authorities in member states, the compliance challenge is to check the compliance of operators and traders
• Article 9 outlines the information requirements for operators, Article 25, 26 and Chapter 7 provide an explanation on the digital infrastructure of operationalizing the regulation.
• In this article by trase.earth, the authors suggest a more effective implementation strategy would be to target action on higher risk areas for deforestation. This would require connecting compliance requirements with a robust and regularly updated benchmarking system for forest areas

Key Questions:

• How could digital tools automate the compliance of agri-food products with new deforestation requirements? What technologies could be employed to connect business data with policy?
• How could digital tools improve the responsiveness of this policy?
  • E.g. allowing operators to respond to changes in reporting requirements, and changes in geographic locations identified as ‘hotspots’
  • E.g. improving the capacity of authorities to implement responsive regulations and measure changes connected to implementation

Case 2: subsidies for green technology uptake in agriculture

Case outline:

• Subsidies are a common green economy policy used to promote the uptake of green technologies.
• This example from Canada subsidises green technology adoption in agriculture, including tech for green energy, precision agriculture and bioeconomy (e.g. waste).
• Under this policy, organisations (profit and non-profit), individuals, or indigenous groups can apply for non-repayable contributions for up to 75% of green technology costs on an agricultural project.
• For applicants, the challenge is to prepare a project that aligns with program criteria and requirements. Also, applicants must provide project-related financial, progress, and performance reports for monitoring.
• For responsible authorities, the challenge is to identify and administer funds to eligible green projects that are likely to be effective. Also, authorities must analyse a large amount of data to monitor the outcome of subsidies, at the project and policy level.
• The application guideline provides an application and review process in a manual manner, i.e. through the submit of paper/PDF forms and documents to emails or physical address. It’s unclear how the selection and monitoring process take place.

Key questions:

• How could digital tools be used to improve the process of administering subsidies? E.g. in the application process for businesses, and the assessment process for authorities
• How could digital tools improve the monitoring of green tech subsidies? E.g. ensuring subsidies are used for the allocated purpose, or monitor progress and performance

In the first part of the conclusions, speakers are invited to make concluding suggestions for technology solutions that would advance green economy policy through digitally enabled monitoring and compliance. These suggestions could note a specific sector, taking into account data availability in that sector.

Secondly, following short interventions by two members of the project team to recap the discussion of other two expert groups, the expert is invited to outline questions to experts of supply chain monitoring and environmental monitoring that would facilitate a redesign of green economy policies that convert ambition at the macroeconomy level to actions of supply chain players and economic operators in a realistic manner.