Social Protection in the Face of Climate Change: Targeting Principles and Financing Mechanisms

Social Protection in the Face of Climate Change:
Targeting Principles and Financing Mechanisms
Michael R Carter1 & Sarah Janzen2
1University of California, Davis, I4 Index Insurance Innovation Initiative & NBER
2Montana State University
December 2015
Carter & Janzen Social Protection & Climate Change

Summary
Climate shocks are a recognized driver of poverty
Climate change, which increases the frequency & intensity of
climate shocks, threatens to make shocks an ever more
important part of the poverty dynamics
World Bank’s new Shock Waves study estimates that without
policy adaptation, climate change will increase extreme
poverty by 100 million
Against this backdrop, we ask two questions:
1 How should social protection in the face of climate change be
targeted or prioritized between the already destitute and those
who are vulnerable to becoming destitute?
2 Can public budget constraints be relaxed–and impacts on
poverty increased–by having social protection targeted at the
vulnerable ﬁnanced in part by the private social protection
insurance ’premium’ contributions by its beneﬁciaries?

Summary
To gain purchase on these questions, we develop a theoretical
model of risk, accumulation and insurance inspired by pastoral
regions of East Africa where climate shocks drive poverty
Findings from the theoretical analysis are:
Using social protection dollars to issue contingent payments to
the vulnerable reduces the extent and depth of poverty relative
to a conventional cash transfers that targets only the destitute;
But, given a budget constraint, targeting the vulnerable
induces a tradeoff between the short-term and the long-term
well-being of the poor;
Can mitigate this tradeoff if the public budget is stretched by
having the vulnerable fund a portion of the premium load for
an insurance that functions as contingent social protection;
However, the ability of the vulnerable to self-finance their own
social protection is limited and their demand for insurance is
highly price elastic
Climate change-induced increases in risk can be managed–up
to a point–with insurance mechanisms.

Outline
1 A Dynamic Model of Risk, Vulnerability & Chronic Poverty
Core insights from a model with fixed human
capital/capabilities
Endogenous human capital formation & the inter-generational
transmission of poverty
2 Social Protection Tradeoffs: Targeting the Destitute or the
Vulnerable?
Standard social protection via means-tested in-kind transfers
targeted at the destitute
Inter-temporal poverty tradeoffs if prioritize contingent
transfers to the vulnerable over in-kind transfers
3 Reducing Tradeoffs with Partially Self-financed Insurance
Implementing vulnerability-targeted social protection via index
insurance
Budget-stretching through beneficiary co-finance of VSP
Limitations of co-finance

Dynamic Model of Consumption & Accumulation in the
Face of Risk
Consider an infinitely lived household dynasty d, which is
comprised of a sequence of generations g = 1,2,... & each
generation lasts for 25 years (t = 1...25).
Enjoys initial endowments of physical assets (Ad0) and human
capital (Hd0)
Assets and human capital combine to produce income using
either a low or high (fixed cost) technology
Assets are subject to random depreciation (mortality) shocks
Consumption cannot be more than cash on hand (value of
income plus assets) as no borrowing is assumed possible
Initially assume human capital fixed across generations at Hdo
Will then allow human capital to be updated for each new
generation, where updating sensitive to ’childhood’ nutrition in
the prior generation
Mathematically write fixed human capital model as:

Dynamic Model of Consumption & Accumulation in the
Face of Risk
max
c
−→dgt
Eθ
∞
∑
g=1
25
∑
t=1
u(cdgt)
subject to :
cdgt ≤ Adgt +f (Adgt,Hdgt)
f (Adgt,Hdgt) = Hdgt max[A
γh
dgt −F,A
γl
dgt]
Adgt+1 = f (Adgt,Hdgt)+(1−θdgt+1)Adgt −cdgt
Hdgt+1 = Hd0
Adgt ≥ 0

Dynamic Model (ﬁxed human capital)
Model admits 2 possible long-run equilibria:
For each initial endowment pair (Hd0,Ad0), there is some
probability that the dynasty will end up in ’chronic poverty’ at
the low equilibrium
Fixing Hdo at an intermediate level, ¯Hd0, simulation of the
dynamic model reveals the following:
“Micawber threshold,” AM( ¯Hd0) = 14

Chronic Poverty Map (fixed human capital)
Across full endowment space see the following:
For fixed human capital, partitions space into: Always poor
(Hd0 < 1.05); Never poor (Hd0 > 1.35); and, Multiple
equilibrium potentially poor in between
At any point in time, define the Vulnerable as those in the
multi-color band & AM(H) as the ’Micawber Frontier’

Dynamic Model (ﬁxed human capital)
Model has three key implications:
Shocks Can Have Irreversible Consequences for the Vulnerable
A shock that pushes a household below its critical asset level,
AM(Hdgt), has irreversible consequences as the household
becomes mired in chronic poverty.
Shocks Can Induce Asset Smoothing by the Vulnerable
While households near either steady state will smooth
consumption, highly vulnerable households in the
neighborhood of AM(Hdgt) will asset smooth when hit with a
shock (cut consumption to preserve capital and avoid collapse
into chronic poverty).
While asset smoothing is understandable, it potentially has
deleterious long-term consequences as consumption doubles as
investment into future human capital.

Nutritionally Sensitive Inter-generational Transmission of
Human Capital
Know that the ’First 1000 Days’ matter for human potential
Evidence that the poor households asset smooth by cutting
nutritional and educational investments (e.g., Hoddinott &
Kinsey, 2003, Hoddinott, 2006 & Jacoby et al. 1997)
Assume that household decisionmaker myopically ignore the
long-term consequences on children of these cuts:
discounting
information
middle age bias
present bias

Nutritionally Sensitive Inter-generational Transmission of
Human Capital
Consider following equation of motion for human capital:
The first term is curly brackets is the next generation’s genetic
potential expressed as a weighted average of the parent
generation’s human capital endowment and a random draw,
˜H, from the overall population capabilities distribution
(E H = 1.35 in simulations)
The second term in curly brackets is a penalty that pushes an
individual below their genetic potential if they suffered
consumption shortfalls (cdgt < z) in the first critical five years
of life.

Chronic Poverty Map (endogenous human capital)
Again simulate the dynamic model (assuming myopia), but
this time allowing human capital to evolve
Micawber Frontier has moved to the northeast. Initial
endowment positions in the lower right of the diagram, which
used to have some probability of escape from long-term
poverty have seen those prospects drop to zero.

Chronic Poverty Map (endogenous human capital)
Moreover, vulnerability has increased for a broad range of
dynasties that used to be able to rely on rapid accumulation
and asset smoothing to insure a near certain escape from
poverty.
Get further insight into process by looking how human capital
evolves across 4 generations:

Poverty Dynamics under a Conventional In-kind Social
Protection Policy
The inability of poor households to sustain investment in the
human capital of their children has motivated the outpouring
of ’save the children’ CCTs we now see across the world
We begin by considering a stylized social protection program
that offers in-kind transfers τdgt that are:
Means Tested: Eligible households are those for whom
cdgt < z, where z is the consumption poverty line.
Contingent Transfers: Subject to budget constraints, each
household receives the transfer needed to completely close the
poverty gap–i.e., τdgt = z −cdgt.
Government Budget Constraint: Government has a fixed social
protection budget, B, that is initially just large enough to close
the poverty gap for all destitute households. If budget becomes
insufficient, then transfers are adjusted so that all destitute
dynasties receive transfers that close an equal fraction of their
poverty gap.

Protection Policy
Mathematically, deﬁne the total social protection need at each
point in time as:
˜Bgt =
D
∑
d=1
(z −cdgt)1(z > cdgt)
and deﬁne the available budget adequacy as:
λgt =
B
˜Bgt
.
Individual transfers are thus given by:
τdgt =



z −cdgt if λgt ≥ 1
λgt(z −cdgt), otherwise
.

Protection Policy
To explore the effectiveness of these in-kind transfers, we use
our dynamic model to simulate an economy comprised of D
dynasties that are initially spread uniformly across the
physical/human capital endowment space
Assume transfers are ’unanticipated’ in sense of
Barret-Carter-Ikegami (2013)
We can then see how the transfers influence the chronic
poverty map and also gauge its effectiveness via headcount
and poverty gap measures defined as follows:
Hgt =
D
∑
d=1
1(z > cdgt)
D
Ggt =
1
DHgt
D
∑
d=1
(z −cdgt)1(z > ccgt)

Chronic Poverty Map under a Conventional In-kind Social
Protection Policy
Cash transfers have some impact on poverty dynamics as the
area of certain chronic poverty in the southeast corner of the
map shrinks modestly.
Vulnerability, however, remains high in certain portions of the
endowment space.

Poverty Dynamics under Conventional Policy
Measures based on realized post-transfer consumption
As can be seen, cash transfers initially cut into the extent and
depth of poverty.
Over time, the poverty headcount measure drifts upwards as
shocks slowly increase the number of destitute dynasties
Given the ﬁxed budget, this increase in the number of cash
transfer-eligible households in turn pushes up the average
depth of poverty

Poverty Dynamics under Conventional Policy
Measures based on potential earnings
These measures are based on expected income (based on
assets)
More stable, but draw out that in-kind transfers have limited
impact on potential (except via human capital circuit)

Vulnerability-targeted Contingent Social Protection (VSP)
The pernicious eﬀects of the underlying system dynamics
raises the question as to whether there can be a more eﬀective
deployment of the given social protection budget
Consider a VSP scheme as one which is:
Vulnerability Targeted
Issues payments to the “moderately vulnerable” (non-poor
20-80% chance of collapse into destitution) when they are hit
by a shock that could push them into chronic poverty (note
that these are contingent payments)
Follows Triage Rule
Social protection resources are triaged by replacing the assets
lost by the vulnerable who have been hit by shocks, and then
transferring the residual social protection budget to the already
destitute. Analogous to restocking programs in pastoral regions

Vulnerability-targeted Contingent Social Protection
This asset replacement strategy reduces the upward creep
poverty based on earning capacity
But tradeoﬀ in depth of poverty visible in poverty measures
This tradeoﬀ emerges because triage eats up funds for in-kind
transfers
Also note instability in budget for in-kind transfers

Using Insurance Mechanisms to Reduce Targeting Tradeoff
In principal, contingent social protection is essentially a social
insurance contract that pays off in moments of need
As already seen, contingent social protection can break the
descent into poverty for the vulnerable
Given these large private gains from contingent social
protection, and the tradeoff implied for the poverty gap when
budget is redirected from in-kind transfers to a VSP, might it
be possible for the vulnerable to pay for their own social
protection?
To explore the willingness of the vulnerable to pay for this
protection, we explore the pattern of demand for an index
insurance contract set up to mimic a VSP
In particular, will explore an implementable index insurance
contract that pays off any time a covariant shock occurs
(idiosyncratic shocks do not trigger payments, exposing the
vulnerable to ’basis risk’)

Vulnerability & the Demand for Insurance
Cash-on-hand spent on insurance directly competes with
consumption and investment
Despite potential gains from insurance payouts, the
vulnerable’s willingness to purchase insurance at market prices
is modest, because their shadow price of liquidity is high
However, price elasticity of demand is high (see Janzen, Carter
and Ikegami, 2015):

Evaluation of Cash Transfer & Subsidized Insurance Social
Protection Scheme
Taking the same budget constraint, government ﬁrst spends
money oﬀering a 50% insurance subsidy to anyone with less
than 35 units of assets
Residual budget spent on cash transfers as before

Further Insights into Eﬃcacy of Alternative Schemes
Insurance subsidy leads to a smaller & more stable on budget
than does the full cost asset replacement program
Cheaper despite ’sloppier’ targeting
Finally, see growth impacts of insurance (note have assumed
that asset transfers are unanticipated & rule out the kind of
moral hazard equilibrium found in Barret-Carter-Ikegami 2013)

Shocks and Climate Change

Conclusion
Weather & other shocks may be an important driver of poverty
Coping strategies of the vulnerable are partially effective in the
short-term, but may fail in the longer-term as the
consequences of reduced nutrition are transmitted through to
the next generation
Logic of contingent social protection for the vulnerable is clear:
Prevent the growth of the number of destitute (which crowds
the social protection budget & increases the poverty gap)
Reduce the inter-generational transmission of poverty caused
by asset smoothing
Insurance can in principal serve at least a partially self-financed
form of social protection for the vulnerable
However, if climate change & risk become too severe, then
even vulnerability-targeted program lose their efficacy.
There are also challenges to making insurance work, but that
is a topic that merits its own discussion

Social Protection in the Face of Climate Change: Targeting Principles and Financing Mechanisms

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