Editing IPCC:AR6/WGII/Chapter-9 (section)

=== 9.11.4 Climate Change Adaptation to Reduce Vulnerability, Poverty and Inequality ===

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High temperature-related income losses have been observed in both low- and high-income countries, suggesting optimistic economic development trajectories may not substantially reduce climate change impacts on aggregate economic performance in Africa ( ''low confidence'' ) ( [[#Burke--2015b|Burke et al., 2015b]] ; [[#Deryugina--2017|Deryugina and Hsiang, 2017]] ; [[#Henseler--2019|Henseler and Schumacher, 2019]] ). Nevertheless, climate change impacts on poverty in Africa will depend on how socioeconomic development unfolds over the coming decades ( ''medium confidence'' ) ( [[#Rozenberg--2015|Rozenberg and Hallegatte, 2015]] ; [[#Hallegatte--2017|Hallegatte and Rozenberg, 2017]] ; [[#Henseler--2019|Henseler and Schumacher, 2019]] ). Climate change by 2030 is projected to push 39.7 million Africans into extreme poverty [[#footnote-000|3]] under a baseline scenario of delayed and non-inclusive growth, with food prices acting as the dominant channel of impact, but this number is cut roughly in half under an inclusive economic growth scenario ( [[#Rozenberg--2015|Rozenberg and Hallegatte, 2015]] ; [[#Hallegatte--2017|Hallegatte and Rozenberg, 2017]] ; [[#Jafino--2020|Jafino et al., 2020]] ).

People in Africa are disproportionately employed in highly climate-sensitive sectors: 55–62% of the sub-Saharan African workforce is employed in agriculture and, although between 90–95% of cropland is rainfed ( [[#Woodhouse--2017|Woodhouse et al., 2017]] ; [[#ILO--2018a|ILO, 2018a]] ; International Institute of Water Management, 2019; [[#World%20Bank--2020c|World Bank, 2020c]] ), there has been an expansion of small-scale ‘farmer-led irrigation’ ( [[#Woodhouse--2017|Woodhouse et al., 2017]] ). Agricultural GDP also appears more strongly affected by increasing temperatures than non-agricultural GDP, implying livelihood diversification out of agriculture may help minimise future economic damage ( [[#Bezabih--2011|Bezabih et al., 2011]] ; [[#Burke--2015b|Burke et al., 2015b]] ; [[#Acevedo--2017|Acevedo et al., 2017]] ; [[#Deryugina--2017|Deryugina and Hsiang, 2017]] ), although such workforce reallocation requires careful management and planning depending on the overall livelihood portfolios, type of farmer and profitability ( [[#Stringer--2020|Stringer et al., 2020]] ). De-agrarianisation can feed urbanisation, which may exacerbate inequality within and between countries ( [[#Stringer--2020|Stringer et al., 2020]] ).

Changes in trade patterns may help mitigate projected aggregate economic losses by reallocating agricultural production abroad and encouraging economic diversification toward less affected sectors. Temperature increases have been shown to lower agriculture and manufacturing exports with especially large declines in poor countries ( [[#Jones--2010|Jones and Olken, 2010]] ; [[#Roberts--2013|Roberts and Schlenker, 2013]] ). Further, imports of agricultural products are projected to rise across most of Africa by 2080–2099 under a high emissions scenario (RCP8.5), with increases ranging from ~30% of GDP in the Central African Republic to ~5% of GDP in South Africa and Nigeria, although some countries will experience increases in net agricultural exports ( [[#Nath--2020|Nath, 2020]] ). While these reallocation effects may be large, current evidence is mixed regarding whether such adjustment of production will dampen or amplify overall social costs of climate change in Africa ( [[#Costinot--2012|Costinot et al., 2012]] ; [[#Bren%20d’Amour--2016|Bren d’Amour et al., 2016]] ; [[#Wenz--2016|Wenz and Levermann, 2016]] ; [[#Nath--2020|Nath, 2020]] ), as food prices are projected to rise by 2080–2099 across all African countries under a scenario with high challenges to mitigation and adaptation (SSP3 and RCP8.5), with the largest price effects (up to 120%) experienced in Chad, Niger and Sudan ( [[#Nath--2020|Nath, 2020]] ). Moreover, reallocating production of agriculture abroad could be maladaptive if it leads to decline or replacement of traditional sectors by industrial and service sectors, which could lead to land abandonment, food insecurity and loss of traditional practices and cultural heritage ( [[#Thorn--2020|Thorn et al., 2020]] ; [[#Gebre--2021|Gebre and Rahut, 2021]] ; [[#Nyiwul--2021|Nyiwul, 2021]] ).

African countries have high inequality: the average within-country share of income accruing to the top 10% of households was estimated at 50% for 2019 ( [[#Robilliard--2020|Robilliard, 2020]] ). However, analysis of INDCs across 54 African countries suggests current climate policies do not, on average, target social inequality in energy, water and food security; proposed mitigation and adaptation actions fell about 23% for every 1% rise in social inequality across these sectors ( [[#Nyiwul--2021|Nyiwul, 2021]] ). In contrast, adaptation actions can be designed in ways that actively work towards reducing inequality, whether gender, income, employment, education or otherwise ( [[#Andrijevic--2020|Andrijevic et al., 2020]] ).

In rural Africa, poor and female-headed households face greater livelihood risks from climate hazards ( ''high confidence'' ). Women often constitute a high proportion of the informal workforce and are also more ''likely'' to be unemployed than men ( [[#ILO--2018a|ILO, 2018a]] ). These factors leave women, and particularly female-headed households, at greater risk of poverty and food insecurity from climate hazards. Controlling for multiple factors, income of female-headed households in agricultural districts in South Africa is more vulnerable to precipitation variability than those headed by men ( [[#Davidson--2016|Davidson, 2016]] ; [[#Flatø--2017|Flatø et al., 2017]] ). Across nine countries in east and west Africa women tend to control smaller plots of land that is often of poorer quality, have less access to inputs such as fertilizer, tools and improved seeds, have lower educational attainment and benefit less from extension services, government agencies and non-governmental organisations ( [[#Perez--2015|Perez et al., 2015]] ). Gender assessments prior to adaptation programmes can identify disparities in division of labour and income and socio-cultural norms, hindering women from holding leadership positions or determining livelihood and resource-use activities, thereby helping ensure equitable benefits from livelihood diversification and improving women’s working conditions ( [[#ILO--2018a|ILO, 2018a]] ). Gender-responsive policy instruments can measure success using sex-disaggregated data to monitor impact and meaningful participation in decision making ( [[#GCF--2018b|GCF, 2018b]] ).

Exposure to climate hazards can trap poorer households in a cycle of poverty ( [[#Dercon--2011|Dercon and Christiaensen, 2011]] ; [[#Sesmero--2018|Sesmero et al., 2018]] ) and poor people in Africa are often more exposed to climate hazards than non-poor people. For example, poor people live in hotter areas in Nigeria and in multiple African countries, poor households are more exposed to flooding ( [[#9.9.2|Section 9.9.2]] ; [[#Hallegatte--2016|Hallegatte et al., 2016]] ). Daily wage labourers and residents of urban informal settlements are vulnerable to heat stress because of the urban heat island effect combined with congestion, little shade and ventilation ( [[#Bartlett--2008|Bartlett, 2008]] ). Climate change can negatively affect household poverty through price spikes, destroying assets or ability to invest in new assets and reducing productivity ( [[#Hallegatte--2016|Hallegatte et al., 2016]] ) with important impact pathways operating through agriculture, ecosystem functioning and health (Sections 9.6; 9.8; 9.10; Chapters 5; 7; 8). Non-poor people can lose more in absolute terms from climate shocks because of having more assets and higher incomes, but in relative terms, poor people often lose more than the non-poor. These relative losses matter most for livelihoods and welfare ( [[#Hallegatte--2016|Hallegatte et al., 2016]] ).

In Malawi, wealthier households were able to maintain more diversified livelihoods, buffering them from extreme weather-related income losses ( [[#Sesmero--2018|Sesmero et al., 2018]] ). Poorer households have limited access to resources such as savings, credit, irrigation technologies and insurance, which can lead to larger crop and other income losses from climate hazards, preventing investments to improve resilience to future climate shocks ( [[#Castells-Quintana--2018|Castells-Quintana et al., 2018]] ). Poor households may reduce risk or aid recovery by cooperating with other households in their community to adapt collectively to climate change, for example, through informal insurance networks ( [[#Paul--2016|Paul et al., 2016]] ; [[#Wuepper--2018|Wuepper et al., 2018]] ). Prioritising poor households for interventions including social protection, EbA, universal healthcare, climate-smart buildings and agriculture, flexible work hours under extreme heat and early warning systems will increase adaptation to climate shocks ( [[#9.6.4|Section 9.6.4]] ; Chapter 6; [[#Angula--2014|Angula and Menjono, 2014]] ; [[#Moosa--2014|Moosa and Tuana, 2014]] ; [[#Hallegatte--2016|Hallegatte et al., 2016]] ; [[#Day--2019|Day et al., 2019]] ). Pro-poor policies that link mitigation and adaptation, such as using renewable energy to increase rural electrification or using revenues from a carbon tax, combined with international financial support to increase social assistance, could support sustainable eradication of poverty under near-term climate change ( [[#Hallegatte--2016|Hallegatte et al., 2016]] ; [[#Aklin--2018|Aklin et al., 2018]] ; [[#Simpson--2021c|Simpson et al., 2021c]] ). Integrating urban green infrastructure into adaptation planning in informal settlements can simultaneously unlock pathways for inclusivity and social justice ( [[#9.9.5|Section 9.9.5]] ; [[#Tozer--2020|Tozer et al., 2020]] ; [[#Wijesinghe--2021|Wijesinghe and Thorn, 2021]] ).

Social protection has been used for decades, particularly in eastern and southern Africa, to safeguard poor and vulnerable populations from poverty and food insecurity ( [[#Niño-Zarazúa--2012|Niño-Zarazúa et al., 2012]] ). Instruments of social protection include public works programmes, cash transfers, in-kind transfers, social insurance and microinsurance schemes that assist individuals and households to cope during times of crisis and minimise social inequality. Evidence from Ethiopia, Kenya and Uganda indicates national social protection programmes are effective in improving individual and household resilience to climate-related shocks, regardless of whether they aim specifically to address climate risks ( [[#Ulrichs--2019|Ulrichs et al., 2019]] ). Strengthening social protection and better integrating climate risk management into design of social protection programmes can help build long-term resilience to climate change ( [[#Hallegatte--2016|Hallegatte et al., 2016]] ; [[#Agrawal--2019|Agrawal et al., 2019]] ). For example, public works programmes can build climate resilience by targeting soil, water and ecosystem conservation and carbon sequestration, such as South Africa’s Working for Water Programme that restores river catchments to reduce fire risk and increase water supplies ( [[#Turpie--2008|Turpie et al., 2008]] ; [[#Norton--2020|Norton et al., 2020]] ).

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==== 9.11.4.1 Climate Insurance ====

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African countries and communities are inadequately insured against climate risk. Insurance penetration is less than 2% of GDP ( [[#Swis%20Re--2019|Swis Re, 2019]] ) and 90% of natural catastrophe losses were uninsured in Africa in 2018 ( [[#Swis%20Re--2019|Swis Re, 2019]] ) leaving a large risk protection gap. The cost of reinsurance in Africa’s most mature insurance market—South Africa—has increased since 2017 due to climate-related payouts ( [[#SAIA--2018|SAIA, 2018]] ; [[#Simpson--2020|Simpson, 2020]] ), ''which is expected'' to further reduce the extent of insurance coverage. Emerging trends that seek to address this gap include innovative weather and drought index-based insurance schemes to transfer risk, forward-looking climate data and models to manage risk and insurers transitioning from risk transfer providers to proactive risk managers.

The most significant area of climate risk insurance innovation has occurred in weather and drought index-based insurance schemes that pay out fixed amounts based on the occurrence of an event instead of full indemnification against assessed losses (Table 9.12). However, despite the relatively low cost, uptake remains low due to affordability constraints, lack of awareness, access to and trust in products, distribution challenges, basis risk, poor transparency, challenges regarding the integration of complementary interventions (e.g., access to improved inputs or informal savings/credit) and poor perceptions/norms of insurance and risk transfer. Lack of data and models further hinders insurers’ ability to price risk correctly, which reduces value to clients ( [[#Greatrex--2015|Greatrex et al., 2015]] ; [[#Di%20Marcantonio--2017|Di Marcantonio and Kayitakire, 2017]] ; [[#WEF--2021|WEF, 2021]] ). Impact assessments point to potential but remain context-specific ( [[#Awondo--2019|Awondo, 2019]] ; [[#Hansen--2019b|Hansen et al., 2019b]] ; [[#Noritomo--2020|Noritomo and Takahashi, 2020]] ). In addition, there is no comprehensive overview of the number of people covered by such schemes, nor of the value they provide in terms of actual claims payouts. Lastly, donor and/or public funds still play an outsized role in launching and/or sustaining these schemes and schemes beyond weather and drought remain limited (Table 9.12).

'''Table 9.12 |''' Insurance opportunities to mitigate climate risk.

{| class="wikitable"
|-
! '''Initiatives'''

! '''Drought/'''

'''heatwave'''

! '''Flood'''

! '''Cyclone'''

! '''Fire'''

! '''Example'''

! '''Policyholders/ beneficiaries'''

! '''Reference'''

|-
| ''Index and parametric schemes— smallholder farmer''

| X

| X

|
| ACRE Africa, Pula, R4 Rural Resilience Initiative, KLIP, FISP, Ghana Agricultural Insurance Pool, Oko Crop Assurance

| Smallholder farmers

| [[#Greatrex--2015|Greatrex et al. (2015)]] ; [[#CTA--2019|CTA (2019)]] ; [[#Global%20Index%20Insurance%20Facility--2019|Global Index Insurance Facility (2019)]] ; [[#WFP--2020|WFP (2020)]] ; [[#Fava--2021|Fava et al. (2021)]] ; [[#OKO%20Finance--2021|OKO Finance (2021)]] ; [[#Pula--2021|Pula (2021)]] ; [[#Tsan--2021|Tsan et al. (2021)]]

|-
| ''Index and parametric schemes – sovereign and sub-sovereign''

| X

| X

| X

|
| African Risk Capacity

| Governments

| ARC (2019)

|-
| ''Index and parametric schemes – global''

| X

| X

|
| African and Asian Resilience in Disaster Insurance Scheme (ARDIS)

| Individuals and smallholder farmers

| Global Parametrics (2018)

|-
| ''Risk management and data collaboration''

| X

| X

| X

| X

| UNEP PSI

Santam

Tripartite Agreement

| Insurers and reinsurers, local municipalities, governments

| [[#Santam--2018|Santam (2018)]] ; [[#Forsyth--2019|Forsyth et al. (2019)]] ; [[#UNEP-FI--2019a|UNEP-FI (2019a)]] ; InsurResilience (2020); [[#Simpson--2020|Simpson (2020)]]

|-
| ''FinTech''

| X

| X

|
| X

| Lumkani, WorldCover, Econet, PlaNet Guarantee

| Individuals, smallholder farmers

| [[#Greatrex--2015|Greatrex et al. (2015)]] ; Hunter et al. (2018); [[#CTA--2019|CTA (2019)]] ; [[#UK%20Space%20Agency--2020|UK Space Agency (2020)]] ; [[#Tsan--2021|Tsan et al. (2021)]]

|}

Insurers and their clients are often unaware of their risk exposure, partly due to data and modelling gaps. Climate information services and related collaborations are increasingly helping to address this problem (see [[#9.4.5|Section 9.4.5]] ). Climate change attribution methods to estimate the contribution of human-casued climate change to the cost of parametric insurance offers possibilities for a sharing of the premium between the impacted African country and a global climate fund, such as the GCF ( [[#New--2020|New et al., 2020]] ). Technology companies and start-ups (including FinTechs) are also emerging as solutions to fill risk gaps, leveraging new approaches to data and technology through the use of sensors, drones and satellite imaging to speak to mainly agricultural risks, but also urban risks such as informal settlement fires, exacerbated by heat and drought (Table 9.12).

Ten African insurers formally committed to help manage climate risk on the continent through the Nairobi Declaration of the UNEP Principles for Sustainable Insurance (PSI) in 2021 ( [[#UNEP%20PSI--2021|UNEP PSI, 2021]] ). Some early examples of public–private partnerships with municipalities and governments to better manage climate risk are also emerging (Table 9.12).

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