FMjee, we have a problem: internalisation of uncertainties due to disruptions in Nature in Indian financial system [1]
[1] Author has contributed to the Bioeconomy component of the Detailed Project Report for the ‘National Mission on Biodiversity and Human Well-being’ as a part of a project funded by a grant awarded by the Office of the Principal Scientific Adviser to the Government of India (Project No. SA/PM-STAIC/ATREE/ Biodiversity/2019 (G)). It was executed by and at ATREE on behalf of Biodiversity Collaborative (BC). The author is a member of BC. No one other than the author is responsible for the contents. Neither PSA, nor Government of India, or BC or author’s employers are responsible for the contents in any manner. Released under the Creative Commons Attribution NonCommercial 4.0 International (CC BY-NC 4.0) license.
Biodiversity losses lead to disruptions in climatic attributes. The resulting impacts — including those on economic systems — are gaining visibility across geographical spaces. ‘Extreme Weather’ events are its most dramatic form. It leads to massive out-of-pocket monetary losses even if the other costs are not accounted for. These ‘social costs’ originate from ‘negative externalities’ (as per mainstream economics) or ‘cost shifting’ (as per ecological economics). They are created by Nature’s actions, but are almost always triggered by activities that are anthropogenic in nature. Some of these are large and many are small, but the cumulative impact is huge.
The costs are borne both by the private entities (say, owner-cultivator of the inundated farming field) as well as the State (say, administrative bandobasts for shifting residents, issuing warnings, arranging food and shelter to those expected to be affected by a natural calamity, among others). Compensations, if any, to address the losses owing to ‘natural’ causes and ‘natural’ calamities are mere transfers but even the transactional costs of administering them are increasing day by day. All these impacts are real, and affecting different components of supply chains across real sectors from natural rubber to housing (changes in insulation) to electricity generation (inundated mines).
It is obvious that changes in the real (both production and exchange) affect the financial system per se; at times, with a lag of course. Such uncertainties — owing to disruptions in Nature — are getting recognised by the authorities responsible for governing financial systems across geographical spaces:
“[E]xtreme weather events — which have been steadily increasing over recent decades — can harm borrowers’ ability to repay their debts and thus make the loan portfolios of banks much riskier. These risks can be further heightened if extreme weather events also depreciate the value of the assets used as collateral in those loans.” (link)
“7. […] Uncertainty around the severity and timing of climate and environment related impact is a source of financial risk and may have a bearing on the safety and soundness of individual financial institutions / entities and in turn the stability of the overall financial system. It, therefore, becomes incumbent on financial institutions to manage the risks and opportunities that may arise from environmental degradation and a changing climate.” (link)
More importantly, the challenges — to internalise the uncertainties owing to the disruptions in Nature within the governance of financial systems — have been recognised as well:
“16. Although the physical and transition risk drivers and transmission channels through which climate risks affect financial institutions are increasingly apparent, quantification of those risks remains a challenge for financial firms and their supervisors. Measurement efforts have been hampered by data gaps and methodological hurdles, many of which are unique to climate risk and contribute to elevated uncertainty in estimates of climate-related risks. For instance, assessment of the potential impact of climate change may require precise data on the location of a borrower’s assets and business operations, as well as information on local weather patterns for those locations. It may also require knowledge of a counterparty’s carbon emissions and of policies in different industries and jurisdictions. Data at this level of granularity is often unavailable or difficult to acquire, presenting challenges in calculating the magnitude of climate-related financial risks.
[…]
Hence, there is a clear benefit to acting early and ensuring an orderly transition. While transition costs may be higher in the short term, they are likely to trend much lower in the long run when compared to the costs of unrestrained climate deterioration”. (link; emphasis added)
Let us assume that all these challenges are overcome at a given point of time. Here are a few — but non-exhaustive set of— further challenges:
- Incomplete knowledge: Herman Daly pointed out half a century ago that the then present state of knowledge was mostly limited to the human-human cell of ‘input-output representation of the total economy’ or cell I in table 1 in Daly (1968; link; adapted as table 1 here). There has not been much change meanwhile. We still know only a little about cells II and III, but nothing as such in IV. UN (2014; link) at present is making attempts to account for flows from III to I (‘Source’ function of the Nature to support the economic system) and from I to II (‘Sink’ function) at the level of Nation-states. There has been some distinct progress in this regard, but it is far from definite.
2. System dynamics of and in Nature: Nature evolves over time due to both natural and anthropogenic causes. To understand the relationship between changes in cell IV and those in II and III requires long term studies in numerous locations. Unlike cell I, identifying representative or sample locations for this purpose is not an easy task. After all, ‘input-output relationships’ within Nature (IV) and therefore flows between IV-II and III-IV are neither static nor independent of spatial and temporal (seasonal) dimensions (captured somewhat by the concept of agro-ecological zones, etc.). A few of the pioneers in the valuation of ecosystem services (a subset of Nature’s services to humans) identified the numerous yet-to-be-taken steps towards achieving this objective a few years ago (link).
3. Lack of availability of relevant data in public domain: Much of the data required to make assessments of uncertainty (required for converting it to risks with appropriate probability distributions) are not available in public domain. Whatever little are there, they seldom match in terms of scale and granularity. In short, consistency required for modelling risks to tackle uncertainty is not supported by publicly available data. Many of Nature’s attributes being sensitive in nature (say, endangered species) there exist additional challenges on the part of statutory authorities to reveal data at a micro scale, essential for modelling.
4. Transaction costs: Given the incompleteness of knowledge and uncertainties on the validity of knowledge collated in time(i) for use and application in time(j) (j>i), it is not difficult to imagine contestations between the parties in transactions over assessment of risks and the corresponding collateral, insurance premium, and other such. No financial system can include every such uncertainly under force majure clause. Alternatively, the allocation between ‘ex ante risks’ and ‘ex post losses’ will undergo a change, but it is unlikely for the parties to a given contract agreeing to any particular allocation, i.e. ‘default rules’ (p.292 in link), a necessary requirement for the contract to be operationalised. Even ‘optimal risk allocation’ will be a challenge (chapter 8 in link). Be it the managers at the local branch of a cooperative bank or the hedge fund manager at international financial institutions, there will be substantial costs, even to train everyone in these matters, leave alone the costs of ensuring sanctity of knowledge (observability, repeatability and verifiability tests).
Even ascertaining the transactional costs in 4 above will be an interesting exercise. May be the estimate will help the government to explore other options, say, making real investments in stabilising Nature through ecological restoration. Taking a cue from what a former governor of RBI said recently (link), Government must stop ‘pussyfooting’ on how to restore Nature. The decision on the road-to-be-taken must be based on sound economics, i.e. social cost minimisation, with appropriate weights to different classes.
Bioeconomy program within the soon-to-be-launched “National Mission on Biodiversity and Human Well-being” for India envisages such interventions (see link1; link2):
“The broad aim of this Program is to identify and promote sustainable development pathways that are based on bio-resources, and are both economically viable and ecologically sustainable. […] In the process, the Program will estimate […] (b) cost of stabilising, augmenting and sustaining bio-resource flows in ecosystems faced with a rapid but recent decline in biodiversity and ecosystem services and (c) cost of restoring, stabilising, augmenting and sustaining ecosystems with a rich biodiversity history and/or potential (Fig. 6).” (Fig 6 in link)
Undoubtedly, such restorations has a much higher potential to reach the historically ordinary state (i.e. ‘normal’); without it, there will be a transition to a new ‘normal’, for which costs will be much higher. In fact, the level of certainty in the former case is far higher than the latter one.
