32 O Hasu and T-K Lehtonen
guide elaborates on the theme and claims that this, in fact, is technically
not a question of ‘basis risk’ because index insurance only makes payouts
for the risk events defined by the coverage level in the policy. As explained
above, in practice, the authors of RM think it would be difficult to sell index
insurance that would cover the base index and that thus would not imply
underinsurance.
Multiple topologies of temporality
The soil on which smallholder farmers live is constituted by complex ecological
processes and shaped by changing weather conditions that cause uncertainty.
Governing such uncertainty has always been part of agricultural practice and
skill. However, commodified risk management brings a new layer to how this
is done. In order to successfully financialise the relation to weather-related
risks, the unknowable future must be made controllable through a mapping
process. The durée of the soil is objectified, or to put this in Henri Bergson’s
(1896) terms, time is rendered spatial. Yet, this objectification comes in many
forms, not just one. Different ways of conceiving and simultaneously spatialising time interact in the development of the insurance index tool. Therefore,
taking into account the observation that time is both spatialised and objectified in multiple forms, it is not out of place to claim that there are different
‘topologies’ of temporality evident in the design of index insurance.
First, in the early stages of the index insurance design process, the history
of the region at which the product will be aimed is mapped (RM: 29–30).
What kind of variance can be seen? What about disruptions to regularities?
Such information is in the background of the product. Yet, if the calculation
of probabilities takes into account past events as discrete variables and no
attention is paid to the temporal dynamics of their occurrence (for example,
by putting more weight on more recent events), time is neutralised and spatialised into a homogeneous field.
Second, the authors acknowledge that regularities could change and that
environmental conditions might vary over periodic cycles, if not be fundamentally transformed in a relatively short period, as is the case with regions
heavily affected by climate change. However, the term ‘climate change’
appears only once (RM: 125) in the more than 300 pages of the entire document. Somewhat surprisingly, according to RM, well-developed index
insurance systematically bypasses the view that risks change:
Weather, and therefore the indexes used in a weather-based index insurance product, may go through multiyear cycles of, for example, dry and
wet years. Dry years may be followed by more dry years, and vice versa.
Such temporal relationships are not taken into account in the model. The
model assumes that any data for the past 30 years are predictive, and more
recent data are not more predictive than data from 25 to 30 years ago.
(RM: 269)
guide elaborates on the theme and claims that this, in fact, is technically
not a question of ‘basis risk’ because index insurance only makes payouts
for the risk events defined by the coverage level in the policy. As explained
above, in practice, the authors of RM think it would be difficult to sell index
insurance that would cover the base index and that thus would not imply
underinsurance.
Multiple topologies of temporality
The soil on which smallholder farmers live is constituted by complex ecological
processes and shaped by changing weather conditions that cause uncertainty.
Governing such uncertainty has always been part of agricultural practice and
skill. However, commodified risk management brings a new layer to how this
is done. In order to successfully financialise the relation to weather-related
risks, the unknowable future must be made controllable through a mapping
process. The durée of the soil is objectified, or to put this in Henri Bergson’s
(1896) terms, time is rendered spatial. Yet, this objectification comes in many
forms, not just one. Different ways of conceiving and simultaneously spatialising time interact in the development of the insurance index tool. Therefore,
taking into account the observation that time is both spatialised and objectified in multiple forms, it is not out of place to claim that there are different
‘topologies’ of temporality evident in the design of index insurance.
First, in the early stages of the index insurance design process, the history
of the region at which the product will be aimed is mapped (RM: 29–30).
What kind of variance can be seen? What about disruptions to regularities?
Such information is in the background of the product. Yet, if the calculation
of probabilities takes into account past events as discrete variables and no
attention is paid to the temporal dynamics of their occurrence (for example,
by putting more weight on more recent events), time is neutralised and spatialised into a homogeneous field.
Second, the authors acknowledge that regularities could change and that
environmental conditions might vary over periodic cycles, if not be fundamentally transformed in a relatively short period, as is the case with regions
heavily affected by climate change. However, the term ‘climate change’
appears only once (RM: 125) in the more than 300 pages of the entire document. Somewhat surprisingly, according to RM, well-developed index
insurance systematically bypasses the view that risks change:
Weather, and therefore the indexes used in a weather-based index insurance product, may go through multiyear cycles of, for example, dry and
wet years. Dry years may be followed by more dry years, and vice versa.
Such temporal relationships are not taken into account in the model. The
model assumes that any data for the past 30 years are predictive, and more
recent data are not more predictive than data from 25 to 30 years ago.
(RM: 269)