Understanding patterns of climate-resilient economic development: Synthesis report Report prepared...

Understanding patterns of climate-resilient economic development: Synthesis report

Report prepared for DFID

September 2015

2Understanding patterns of climate-resilient economic development: Synthesis report

This work draws from four case studies to answer three key questions:

— what have been the impacts of different development patterns on climate resilience?

— in cases where development trends have had negative impacts on climate resilience, when are these impacts ‘locked in’ (and when are they relatively easy to reverse)?

— how can policy direct development patterns to enhance climate-resilience while still delivering other benefits from development?

This project aims to understand how patterns of development impact climate resilience

The objective of this project is, through the use of case studies, to help better understand how patterns of development influence climate resilience.

The ability of a country to influence how much they are affected by climate change goes beyond adapting to changes as they happen, to considering how broader patterns of economic development have the potential to reduce or avoid some hazards, or dampen their impacts.

This work aims to inform whether and how, developing countries, DFID and the broader development community can help best promote climate resilient economic development.


Cagayan D’Oro (city), The Philippines How has CDO’s rapid growth and transition over the last decade affected its climate resilience, and what lessons has it learned from the devastating effects of 2011 Tropical Storm Washi?

Senegal (country)How has coastal and tourism development affected climate resilience?

Rwanda (country)What are the linkages between agricultural transformation, poverty reduction, and resilience to climate variability in Rwanda?

Maputo (city), Mozambique To what extent has Maputo’s traditional role as the epicentre of the Mozambican economy and hub of economic investment contributed to increases in the city’s climate resilience, in particular of those living in the informal settlements?

The case studies look at both the city and country context from Africa and Asia

All photographs courtesy of case study authors


1. The impact of economic development on climate resilience is ambiguous: it depends on the type of development.

2. More specifically, without deliberate policy intervention, development tends to lead to:― increases in exposure (the likelihood and number of people and assets that may be affected by

a climate shock) → this reduces climate resilience― mixed impacts on sensitivity (the damage done by a climate shock) → this has an uncertain on

climate resilience― in many cases, development tends to lead to more diversified economies where the impact

of a climate shock on the overall economy is smaller; but also more complex economies with denser linkages that allow shocks to ‘ripple’ more extensively through an economy

― improvements in adaptive capacity (the ability to respond to the impacts of a climate shock) → this improves climate resilience

3. Even if overall climate resilience increases, it is easy for the most vulnerable to suffer a deterioration in climate resilience. They often face greater exposure and are excluded from improvements in adaptive capacity than the rest of the population.

4. ‘Decisions’ made today can easily ‘lock in’ positive or negative impacts on climate resilience for many decades:

― this includes decisions where action is being taken e.g. infrastructure development― but also include inaction e.g. where specialisation of labour and supply chains is unchecked or

when informal settlements grow rapidly

Key findings


1. Policies and targeted interventions can have a powerful impact in making development more climate resilient

— Cagoyon D’ Oro (The Philippines) developed rapidly both before and after Washi, but policy interventions e.g. improvements in river basin management, only led to climate resilient development (for many) after the impact of Washi

2. Analysing the implication of a development policy or programme on climate resilience can help identify how any negative impacts on climate resilience might be addressed

— these analyses could be built into country growth diagnostics

3. The results of any such analysis will be context specific:― in some cases it will provide a powerful extra justification for existing policy and development

patterns e.g. in Senegal, diversification to the tertiary sector is good for both development and climate resilience

― in others, it may help identify how changes in policy are important to ensure development is made climate resilient e.g. in Senegal, even though diversification has improved resilience, the development of a land use framework that incorporated climate risks would have aided climate resilience further

― and in some cases it will reveal uncomfortable trade-offs e.g. in Rwanda, the large increases in agricultural productivity have been delivered in part by a specialisation in certain crop varieties that deliver high yields in current climatic conditions, but which may lead to lock-in that maintains high levels of sensitivity to future changes in the climate

Implications for DFID: smart policy making can often improve the climate resilience of development patterns (1 of 2)


4. DFID is developing an increasingly sophisticated toolkit to help evaluate whether it is appropriate and cost effective to take action on the basis of the results of this type of analysis (http://www.vfmadaptation.com/)

5. Any analysis, and resulting actions, need to factor in that climate resilience is a function not just of exposure, but also of sensitivity and adaptive capacity

— relocation programmes in Maputo and CDO reduced vulnerable people’s exposure to climate impacts but placed them a long way from job opportunities, reducing their adaptive capacity → the net impact on resilience, for these people, was ambiguous

6. Analysis, and subsequent actions, need to allow for the possibility (probability) that the development patterns experienced by the most vulnerable will be different from those experienced by the rest of the population

― for example, in Maputo, the most vulnerable have been excluded from development gains that have improved the adaptive capacity of others

― dedicated investments in local infrastructure, transport links and public services would help to improve their adaptive capacity

7. Increasing knowledge on how climate impacts may impair development at the local, regional or national level can often be a useful tool for encouraging action to improve climate resilience

— in CDO, action on improving climate resilience only came after the devastating impacts of Tropical Storm Washi which affected around 40 per cent of its population, destroying 20,000 homes and with recovery and restoration costs of around $0.5 billion

Implications for DFID: smart policy making can often improve the climate resilience of development patterns (2 of 2)

http://www.vfmadaptation.com/

http://www.vfmadaptation.com/


Contents

1. Introduction and patterns of development in the case studies

2. What have been the impacts of different development patterns on resilience?

3. When are the impacts of these development patterns on climate resilience ‘locked in’?

i. Physical lock-in

ii. Economic lock-in

iii. Social lock-in

4. How can policy help make development patterns more climate resilient?

5. Appendices

6. References


The methodology involved considering 3 key patterns of development and implications for 3 aspects of climate resilience

Patterns of development

Geographicalthe physical location of people and assets

Sectoralwhich industries are growing and which are declining and the inputs on

which they depend

Distributionalwhether growth has been inclusive or worsened inequality

Impact of each pattern on each component of climate resilience reviewed in 4 case studies:1. Rwanda2. Senegal

3. Cagayan D’Oro, The Philippines 4. Maputo, Mozambique


Quantitative indicators of the impacts of patterns of development on resilience were identified wherever possible

The impact of each of the recent patterns of development on each dimension of climate resilience was considered.

The analysis identified specific sub-indicators to capture the impact that each pattern of development had on the relevant components of climate resilience.

Wherever possible, the change in these sub-indicators was based on quantitative analysis.

A semi-quantitative assessment was made of the impact of the change in each sub-indicator for the relevant component of climate resilience.


Different development patterns were seen in each case study

Cagayan D’Oro (different patterns before and after flood)• a shift of development from the lowlands to the uplands, particularly after the flood;• strong economic growth; and• the expansion of lifeline utilities’ customer base and improvements in service delivery

Maputo• population growth coupled with a lack of urban planning and investment; and• investments earmarked for existing developments; little extension of public and basic

services to informal settlements

Rwanda• agricultural growth, value addition, increased production and productivity, and improved

food security;• investment in agricultural infrastructure; and• population growth and poverty reduction.

Senegal• internal population movements from inland areas to coastal zones;• rural to urban migration; and• development of the tertiary sector with a specific focus on tourism

All photographs courtesy of case study authors


in most cases, there have been significant increases in average incomes e.g. Rwanda, CDO, Senegal

— but not always for the poorest (e.g. Maputo)

migration – typically linked to urbanisation – is a key development trend in Senegal and Maputo

there have been significant changes in the sectoral composition of the economy in both Rwanda and Senegal but in opposite directions:

— in Senegal, there has been significant economic diversification through the growth of the tourism sector

— in Rwanda, there has been a continued dependence on, increasingly productive, agriculture as a way of alleviating rural poverty

— sectoral patterns in city case studies were less easy to discern

more detail on the case studies is available in the Annex

But with some common trends


Contents




i. Physical lock-in


iii. Social lock-in


5. Appendices

6. References


General trends in the impact of development patterns on climate resilience can be discerned

Development patterns have tended to increase exposure- migration and population

growth tends to increase population exposed to climate risks e.g. Maputo

- economic growth increases asset exposure when not adequately protected e.g. CDO

Development patterns have had an ambiguous impact on sensitivity- if urban growth outpaces

service delivery, sensitivity increases e.g. CDO, Maputo

- economic diversification tends to reduce sensitivity e.g. Senegal

Development patterns have strengthened adaptive capacity (in most cases)―increases in income and

reductions in poverty incidence, help to increase individual’s ability and willingness to invest in reactionary adaptation

―stronger economic growth raises tax receipts allowing public sector to do the same

―although women and the most vulnerable do not always benefit


Impacts of development patterns on exposurein some cases, migration patterns change the nature of the climate risk but it is difficult to say whether exposure has increased or decreased— in Senegal, migrants moving from rural areas to coastal urban centres are at a lower risk of

drought but have increased their exposure to floods and coastal erosion — In CDO, efforts to prevent further development on river banks have reduced exposure of both

people and assets to floods however, much of this development has been redirected to upland areas, some of which are exposed to landslides

Impacts of development patterns on sensitivitywhile economic diversification is generally likely to reduce sensitivity, continued reliance on agriculture, such as seen in Rwanda, has mixed effects:

― the large productivity gains attributable to process changes and technology improvements have led to substantial output growth, strengthening food security and providing a buffer against climatic impacts

― although this has been partly supported by the specialisation in relatively more climate sensitive crop varieties

migration patterns have an ambiguous impact on the sensitivity and adaptive capacity of those (often women) that do not migrate― remittances can help reduce the remaining household’s exposure to climate risks, but may be

outweighed by the drain of skilled, young labour and income from the rural area

Although the case studies also reveal subtleties which make overall assessments of impact on climate resilience difficult


Contents




i. Physical lock-in


iii. Social lock-in


5. Appendices

6. References


Physical lock-in has occurred as a result of infrastructure investments, but to varying degrees.

The size of the fixed costs and length of asset lifetimes determine how ‘locked in’ each of the investments are:

(i). Physical lock-in is common among large infrastructure projectsThe cost of relocation or renovation is a determining factor

Incr

easi

ngly

‘loc

ked

in’

— investments in terracing infrastructure in Rwanda have focussed on the North and West which are susceptible to erosion and landslides due to the particularly steep land. While the infrastructure helps to reduce the sensitivity of the sector to climate events, it may also have contributed to some lock-in of exposure. However, because such infrastructure is relatively short-lived and easier to remove or relocate than examples from other case studies the risk of lock in is only small;

— the ports of both Maputo and Dakar (in Senegal) are the most prevalent forms of physical lock-in. In addition to their high construction costs and long lifetimes, they have attracted development in the surrounding area. This has led to a large increase in the value of assets exposed to coastal flooding and erosion which it would be very difficult to relocate.


(i). Carefully designed infrastructure can also reduce sensitivityThe dikes in CDO could plausibly lock in high or low sensitivity

Increase sensitivity• especially if development in flood-prone areas returns to

previous levels• if a larger flood occurs, then there may be more damage

than if the dike was not built at all

Reduce sensitivity• aims to reduce sensitivity by providing an effective flood

defence• proposals suggest it is tall enough to defend against a

flood with a 25-year return period

A proposal to reengineer CDO’s riverbanks with dikes would be difficult to reverse:

— this is due to high fixed costs, their long lifetime, and the multi-stakeholder approvals required for their removal.

The dikes will increase rather than decrease sensitivity, if they are not high enough to protect against the worst flood likely to occur in their lifetime.


Public support for the agricultural sector in Rwanda has prioritised crops that are in demand in the region but that are more climate sensitive than traditional alternatives

— this has facilitated significant increases in food security, economic growth and the expansion of low-skilled employment.

— but considering that there is a high degree of risk aversion for untested seeds and poor certification, this specialisation of the supply chain entrenches Rwanda’s reliance on certain climate sensitive crop types that it may be difficult to reverse

By contrast, recent public support in Senegal has focused on the somewhat less sensitive tertiary sector as well as consciously diversifying across tourism products and locations

— the tertiary sector accounted for 73 per cent of GDP growth between 2006 and 2014 while agriculture declined as a percentage of GDP;

— the Plan Senegal Emergent (PSE) identifies two to six new areas in which to focus tourism development as well as new products addressing demand for ecotourism, culture, history and religion;

— these were chosen in part due to their lower climate sensitivity (relative to traditional beach holiday packages) in an effort to diversify the sector against both climate and demand shocks.

(ii). Economic dependence can lead to specialisation and lock-inBut specialisation can also increase output - pointing to challenging trade-offs


This is typically due to low skills, a lack of social and economic mobility and poor access to finance.

(iii). Informal settlements can lead to social lock-inPoor access to economic opportunities makes it difficult to break this cycle

the poorest are often forced to live in informal settlements where living conditions are cheaper but exposure to climatic

impacts is higher

a lack of social infrastructure and poor

provision of public services in these settlements

creates high sensitivity to climatic impacts

most residents work in the informal sector and do not

benefit from economic growth associated with

sectors that require skilled labour

sectors requiring skilled labour are unlikely to grow in informal settlements as

local education suffers from insufficient resources limiting the poor’s adaptive

capacity

rates of illiteracy, unemployment and

dropping out of school are often higher among

women worsening the lock-in both in terms of impact

and irreversibility

This cycle is seen in Maputo, CDO and Dakar.

Those who live in informal settlements can experience social lock-in of worsened exposure, sensitivity and adaptive capacity.


Contents




i. Physical lock-in


iii. Social lock-in


5. Appendices

6. References


Observed development patterns often reduce some or all aspects of climate resilienceThis is observed across all of the case studies

Increasing climate resilience

Observed pattern of development (and associated policies)

Increasing economic

developmentExposure Sensitivity Adaptive

capacity

CDO and Maputo’s relocation programmes moved people away from areas at high-flood risk but weak government support for these areas and poor access to key markets worsened their poverty

In Senegal, development has concentrated along the coast in the most economically advantageous but risky areas due to limited awareness of, and consideration for, climate risks

~ In Rwanda, policy to support the expansion of the agricultural sector has generated broad-based income rises but caused dependence on the sector and certain crop types that has limited the improvements in sensitivity that would otherwise have been expected

~ ~


In many, but not all, cases, well-designed policy can help mitigate these tensionsMitigating these trade-offs requires explicit consideration of where they exist

Increasing climate resilience

Possible adjusted pattern of development

Increasing economic

developmentExposure Sensitivity Adaptive

capacity

If either CDO or Maputo’s resettlement strategies were accompanied by investments in local infrastructure, transport links and public services, residents may have been less sensitive in the short term and better able to improve their own resilience in the long term

In Senegal, if initial support was targeted at tourism locations or products less exposed or sensitive to climatic impacts, or to a greater diversity of tourism offerings, this may have made urbanisation and development more resilient. The Plan Senegal Emergent is now taking policy forward in this direction

By contrast, in Rwanda, it is difficult to see how agricultural productivity and output could have grown such that it generated the same income rises without greater reliance on the somewhat more climate sensitive crops (although additional R&D in climate resilient crops may provide some longer term benefit)

~ ~


the possible existence of trade-offs between development and climate resilience – and the scope for policy to often help resolve these trade offs – suggests that explicit attention should be given to whether and how development trends are supporting climate resilience

— these could be linked in to existing country growth diagnostics

the outcomes of any such reviews will depend on the context:

― in some cases it will provide a powerful extra justification for existing policy and development patterns e.g. in Senegal, diversification to the tertiary sector is good for development and good for climate resilience

― in others, it may help identify how changes in policy might ensure development is made climate resilient e.g. in Senegal, even though diversification has improved resilience, the development of a land use framework that incorporated climate risks would have aided climate resilience further

― and in some cases it will reveal uncomfortable trade-offs e.g. in Rwanda, it is difficult to see how improvements in agricultural productivity (and subsequent improvements in poverty reduction and food security) would have been as successful if there had not been a focus on certain crop types that are relatively more climate sensitive

Explicit consideration of the links between climate resilience and development patterns can help formulate better responses


There are a number of points that need to be taken into account when undertaking such analysis

Consideration Example

Given the propensity for lock-in, any analysis and associated strategy/actions, needs to take a long-term (~20-30 year) perspective of both the implications of development patterns and possible climate risks

In Rwanda, public support for high-demand yet low-resilience seed varieties might boost productivity and adaptive capacity in the short run. However, if production becomes locked in through specialisation of the supply chain and climate conditions worsen, then the output gain from public support may be outweighed by the output loss from reduced resilience and the policy would become a form of maladaptation

Lock-in risks also place an emphasis on flexibility of any policy response, so as to avoid the risks of maladaptation

No example from case studies but exit strategies based on pre-defined conditions or the result of an evaluation can help retain flexibility

There is a need to adopt a comprehensive view of climate resilience, not just focusing on reducing exposure to climate risks

Relocation programmes in Maputo reduced vulnerable people’s exposure to climate impacts but placed them a long way from job opportunities, reducing their adaptive capacity → the net impact on resilience, for these people, was ambiguous

The development patterns affecting the most vulnerable may be different from those of the rest of the population

In Maputo, the most vulnerable have been excluded from development gains that have improved the adaptive capacity of others. Dedicated investments in local infrastructure, transport links and public services would help to improve their adaptive capacity


‘Opportunism’ refers to how public officials, at least in part, aim to advance their own interests (Persson & Tabellini, 2000). Outcomes, particularly those relating to large infrastructure projects, are skewed away from the most desirable towards the interests of organised and well-resourced lobby groups.

Corruption, bribery and rent-seeking politicians create similar outcomes.

Simple democratic majority voting counts the number of votes but ignores the intensity of people’s preferences and can thus produce outcomes misaligned with the simple aggregation of preferences. Without adaptation, the least resilient in society stand to lose significantly more than other groups.

Too little weight may be placed on the interests of future generations who lack the ability to vote such that there is insufficient adaptation to future climate change. This argument has been made more widely in the context of sustainable resource management (Folke et al., 1998; Young, 2003).

Even when possible changes to policies have been identified, political economy barriers can prevent implementationWith particular relevance to adaptation measures

Several of these issues can be seen within the current political dynamic in CDO:

— the City Council has repeatedly voted down, delayed or neutered many of the recently elected Mayor’s policies - especially those forming part of his resilience agenda – through loyalty to the previous Mayor;

— this could be seen as a form of ‘opportunism’ as members of the City Council choose to maintain their relationship with the previous Mayor as opposed to passing those policies that are in the public’s best interest;

— it may also be that the City Council is placing too little weight may be placed on the interests of future generations


Contents




i. Physical lock-inii. Economic lock-iniii. Social lock-in


5. Appendicesi. Rationaleii. Methodologyiii. Case study topicsiv. Detailed scorecardsv. Analytical reflections

6. References


While there is recognition that the effect of economic development on climate resilience depends on the specific development pathway (IPCC, 2014), a previous report by Oxford Policy Management (OPM) found there is relatively little evidence on the subject (Tarazona, Chiappe, & Hearle, 2014). Indeed, a number of reports identify that economic development is not sufficient by itself to build climate resilience (Blythe, Pye, Savage, & Watkiss, 2010; The World Bank, 2010) yet it is unclear in which circumstances it does and how.

This provides an entry point for DFID to incorporate climate resilience concerns in its broader economic development policies. As development policy inherently aims to direct and strengthen economic development, it is important that DFID ensures that such development builds and does not diminish climate resilience. This has been an increasing area of interest for DFID over the past few years.

Building on the OPM report, the objective of this project is to develop case studies, under a common conceptual frame, that examine whether different patterns of development in the recent past have reduced, enhanced or had negligible effects on climate resilience. This aims to inform whether and how DFID - and, indeed, the broader development community - can help best promote economic development in a changing climate.

It is not fully understood how development impacts resilienceThis project contributes to closing the evidence gap


Contents






5. Appendicesi. Rationaleii. Methodologyiii. Case study topicsiv. Detailed score-cardsv. Analytical reflections

6. References


A conceptual framework was devised to guide and ensure coherence across the case studies so as to facilitate as many general findings from the synthesis as possible. Following the previous work by Oxford Policy Management on the interaction between patterns of development and climate resilience, the framework considers three specific patterns: geographical, sectoral and distributional.

As indicated in the figure below, while the first two were considered in detail, distributional patterns were considered to the extent that data were available. Where it was not, recent distributional patterns were considered qualitatively or by using proxies as appropriate.

Analysis focussed on three patterns of economic development

Geographical patterns

• the physical location of people and assets

Sectoral patterns

• which industries are growing and which are declining

• the inputs they depend on

Distributional patterns

• whether growth has been inclusive or worsened inequality


Resilience is conceived within the IPCC-recognised framework of exposure and vulnerability to climate-related hazards in which (IPCC, 2001; IPCC, 2014):

— exposure is the presence of people or assets in places or settings at risk of climate shock or stress; and— vulnerability is the degree to which a system is susceptible to or unable to cope with adverse climate

impacts.

However, for the analysis to achieve sufficient granularity, vulnerability is disaggregated as a function of sensitivity and adaptive capacity where (IPCC, 2014):

— sensitivity is the degree to which a system is affected by positive or negative climate shocks or stresses; and

— adaptive capacity measures a system’s potential to to adapt to, or alter to better suit, climate shock or stress, or their effects or impacts.

Exposure, sensitivity and adaptive capacity were considered

Exposure

Vulnerability

Risk

Adaptive capacity

Hazard

Sensitivity

Pat

tern

s of

de

velo

pmen

t

Decomposition for this work

IPCC AR5 framework

For our analysis, we consider exposure,

sensitivity and adaptive capacity determining

climate resilience


Quantitative indicators of the impacts of patterns of development on resilience were identified wherever possible

A semi-quantitative assessment was made of the impact of the change in each sub-indicator for the relevant component of climate resilience. This assessment drew from the quantitative and qualitative data collected on the sub-indicator, taking into consideration the direction of specific impacts, their severity and their relative importance to the case study (and area of focus).


The assessments were presented as a scorecardThe example of Maputo is given below

EXPOSUREPeople

Risk of inland floodingPopulation at risk of inland flooding

AssetsDevelopment in high-risk areasHomes in high-risk areas

SENSITIVITYSocietal resilience

Access to waterAccess to sanitationPopulation density in high-risk areasAccess to health careQuality of low-income housingDRRM activities

ADAPTIVE CAPACITYWealthDRRM planningEducation and trainingPoverty incidenceDepth of povertyInequality

City-wide access to public amenities such as water, sanitation and health slightly improved alongisde the quality of low-income housing, as indicated by a decrease in the percentage of informal structures. However, this was not true for the

most vulnerable bairros which experienced rapid increases in population density. This worsened sensitivity to floods both in terms of the number of people affected and the severity of the damage due to the additional strain on public services

and the spread of disease. Disaster risk reducation and management (DRRM) activities included the distribution of emergency readiness kits though only to a small number of bairros and not those at the highest risk of flooding.

Wealth rose across the period, as reflected by an increase in the home ownership rate, while the high level of inequality remained relatively constant suggesting the rich benefitted the most from GDP growth. That said, both the poverty rate and the average income gap to the poverty line fell indicating a moderate increase in adaptive capacity across the city.

Education and training improved as the secondary enrolment rate rose and climate change awareness programmes were established. DRRM committees in vulnerable bairros were also established to provide structure to DRRM activities.

Informal settlements built in the marshlands experienced rapid population growth, construction of houses and informal infrastructure. As a result, these communities and structures are highly exposed to the risk of inland flooding. Average

annual rainfall rose increasing the risk of inland flooding, though this is not attributable to economic development.

Impact of change in indicator on resilience

Semi-quantitative scores

Sub-indicators

Summary of overall impact on component of resilience

Red or green summary indicates negative or positive

impact


1. Introduction

2 Historic economic patterns

— 2.1 Context— 2.2 Historical geographic and sectoral patterns— 2.3 Summary

3. Analysis: impacts on resilience

— 3.1 Geographical patterns— 3.2 Sectoral patterns— 3.3 Summary

4. Discussion

— 4.1 Distributional impacts of economic change on resilience— 4.2 Policy drivers of economic patterns— 4.3 Vulnerability lock-in

5. Conclusions— 5.1 Key findings— 5.2 Policy implications

Each case study followed the structure below


Contents







6. References


Increasing urbanisation has changed Senegal’s vulnerability to climatic impacts. As in many West-African countries, seasonal internal migration (accompanying seasonal agricultural production) characterises traditional population movements in Senegal. In the last decade, these movements have been coupled with permanent internal migration from rural to urban areas. In urban centres, this has led to an increase in both economic activity and vulnerability to climate change.

Senegal is also experiencing a shift of economic activity from rain-fed agriculture to the tertiary sector. This diversification of income sources has improved climate resilience.

The key patterns of development investigated were as follows:

1. Urbanisation drove migration and sectoral change in Senegal

1. Internal population movements from inland areas to coastal zones;2. Rural to urban migration; and3. Development of the tertiary sector with a specific focus on tourism.


Development in Rwanda is considered to have been relatively robust and inclusive. Effective governance, prudent macro-economic policies, targeted public spending and substantial aid inflows have supported robust growth and significant poverty reduction. This has been primarily driven by transformation of the agricultural sector.

However, development levels remain low. Poverty levels are still high, Rwanda’s Human Development Index is low, the population of young and unskilled workers is growing rapidly coupled with unplanned urban growth.

Reliance on primary commodities and extractives, underdeveloped markets, and limited sectoral diversification means that sensitivity remains high. This is exacerbated by credit constraints and insufficient infrastructure restricting private sector growth.

Together, these factors make Rwanda particularly vulnerable to climatic impacts. Climate change, particularly increased variability and extreme events, represents an emerging threat with the potential to amplify existing pressures and risks in the economy.


2. Strong growth has not yet fully translated into resilience in Rwanda

1. Agricultural growth, value addition, increased production and productivity, and improved food security;

2. Investment in agricultural infrastructure; and3. Population growth and poverty reduction.


Maputo – the economic hub of Mozambique – has experienced strong yet uneven growth. Although affected by multiple flooding episodes Maputo has continued to grow both spatially and economically. Its economic growth has however been tainted by uneven deployment and distribution of population, assets and services leading to a reinforcement of social inequalities and vulnerabilities, especially amongst those in the informal settlements living in flood-prone areas.

Despite initial adaptation efforts, the city remains highly vulnerable to climatic impacts. Maputo is slightly more resilient now than it was following the floods of 2000, due to the development of an overarching climate adaptation national strategy, implementation of local early warning systems and resettlement programmes. However, significant risk still remains as 16 per cent of the administrative territory is categorised as flood prone (due to heavy rainfall and sea level rise) and 82,000 residents are at risk.


3. Unplanned growth in Maputo is worsening resilience

1. Population growth coupled with a lack of urban planning and investment; and

2. Investments earmarked for existing developments at the expense of extending public and basic services to informal settlements.


The City of Cagayan de Oro (CDO), among the best prospects in the Philippines for diversifying the country’s growth outside of Metro Manila, experienced a particularly damaging flood disaster in 2011. This was caused by Tropical Storm Washi and a defining moment in the City’s history. It affected around 40 per cent of its population, destroying 20,000 homes and killing at least 674 people.

The City appears to be relatively more resilient today than it was a decade ago and in late 2011 (prior to Washi). This decadal period first saw the decline in elements of the City’s resilience up to 2011, such as increases in exposed population, followed by its rapid increase after the ‘wake-up call’ from Washi. Since 2011, the City has progressed well on developing advanced early warning systems and evacuation protocols, relocating exposed residents to upland areas and proposing hard flood defences to reduce the sensitivity of those that remain.


4. Since severe flooding in 2011, CDO has made substantial progress in building climate resilience

1. A shift of development from the lowlands to the uplands, particularly for those affected by the flooding that were relocated;

2. Changes (or lack thereof) in the rates of forest coverage in the upland areas of the CDO River Basin;

3. Strong economic growth and investor confidence; and4. The expansion of lifeline utilities’ customer base and improvements in service

delivery.


Contents







6. References


Recent development patterns in almost all case studies have worsened exposure to climate risks:

Natural population growth and migration increase the number of people exposed to risk of specific climatic hazards, particularly in Maputo;

the increased likelihood of climatic impacts such as drought, floods and landslides has also worsened exposure (though this is not a result of development);

the only improvement in exposure was due to a decrease in the population at risk of floods in CDO as a result of no-build zones and relocation programmes.

i. Exposure has almost always worsenedIncreases in both population and assets located in high-risk areas reduced resilience


ii. Impacts on sensitivity vary across indicatorsPopulation growth led to the biggest increases in sensitivity

RwandaSocietal resilience

Human Development IndexFood securityDRRM activities

Economic resilienceDependency on agricultureDiversification of exports

SenegalSocietal resilience

DRRM activitiesPressure on water resources

Economic resilienceEconomic diversificationDependence on agricultureDevelopment of flood-sensitive activities

MaputoSocietal resilience

Access to waterAccess to sanitationPopulation density in high-risk areasAccess to health careQuality of low-income housingDRRM activities

CDO - Period 1Societal resilience

Population growthDRRM activitiesSensitivity to floods and landslides

CDO - Period 2Societal resilience

Population growthDRRM activitiesSensitivity to floods and landslides


While some development patterns increased sensitivity, and thereby reduced resilience, others had the opposite effect:

strong growth in absolute levels of population or population density was responsible for worsening sensitivity in all the case studies by increasing pressure on limited social infrastructure and public service provision in already strained areas;

O̴ cases (e.g Rwanda) where specialisation (in this in certain crop types that drove productivity increases) limited the decline in sensitivity that would otherwise have been expected

whereas cases where there was economic diversification reduced sensitivity (e.g Senegal);

broad-based development improvements such as increased access to improved water sources, sanitation facilities and health care reduced sensitivity and thus, increased resilience;

climate-specific disaster risk reduction and management (DRRM) activities, such as flood defences and irrigation, help reduce the damage a climatic impact causes, improving sensitivity.


iii. Adaptive capacity has increased in all case studiesDRRM planning generated the largest improvements

RwandaPolitical stabilityEducation and trainingDRRM planningPoverty incidenceInequality

SenegalPoverty incidenceDepth of povertyEducation and trainingInequality

MaputoWealthDRRM planningEducation and trainingPoverty incidenceDepth of povertyInequality

CDO - Period 1Public fundsBusiness environmentIncome levelsDRRM planning

CDO - Period 2Public fundsBusiness environmentIncome levelsDRRM planning


However, increases in income can mask distributional variation. Women and the poorest often do not benefit from the same rises in income, education or adaptive capacity as the rest of the population.

The largest gains observed were due to:

the creation of disaster risk reduction and management (DRRM) infrastructure such as early warning systems, evacuation protocols and the organisation of communities and government to plan adaptation efforts;

improvements in education and training, especially those focussing on climate resilience.

Other factors enhancing adaptive capacity:

moderate increases in income and reductions in poverty incidence, poverty gaps and inequality helped to increase individual’s ability and willingness to invest in adaptation;

improvements in the business environment and in levels of tax collection led to increases in retained profits and tax receipts for business and government and had a similar effect.


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6. References


Data availability and quality were one of the binding constraints throughout the development of the case studies:

— as adaptation is context specific, the degree of geographical resolution must be high to arrive at meaningful, evidence-based conclusions. However, the data relevant to both adaptation efforts and impacts are generally difficult or costly to find or unavailable;

— similarly, analysis concerning distributional patterns of development requires highly disaggregated household data which are generally rare;

— issues surrounding data availability worsen when looking at a municipal- or city-scale as opposed to a national scale. Statistical agencies often do not collect the wide range of indicators required and, even when they do, they are subject to differences in exact geographical boundaries, gaps and opaque methodologies.

Even where data are available, quantitative attribution of effects and issues around causality are challenging. While this project produced a number of findings about the relationship between economic development and climate resilience, these are based on the synthesis of four case studies. The data gathered were not sufficient to perform robust data-driven analysis in each individual case study to gain a more accurate perception of correlation and causality. Likewise, general equilibrium modelling of climate impacts remains analytically challenging.

Data availability limits how robust the conclusions can be


— research is typically either detailed at a narrow case study level, such as an individual village, or high-level at a global or country level, such as the ‘Economics of Adaptation to Climate Change (EACC)’ studies. There is a dearth of evidence regarding the middle ground. While our case studies of Maputo and CDO go a small way to address this, a much wider body of research and analysis is required. In particular, research is required on the likely outcomes of large investments in major transport and economic development corridors, which have the potential to transform economies and climate resilience;

— understanding distributional issues of patterns of development and climate resilience is equally an area in which there a need for further evidence and analysis. The analysis presented as part of this project was unable to look at distributional patterns of development in as much detail as geographical or sectoral patterns due to data constraints. Further research, including data collection, should focus on such distributional issues.

— changes in resilience require an understanding both of the situation as it is now and as it has been historically. Especially in cases where there has been significant migration (e.g. Senegal), it is not always easy to understand the historic situation and hence the net change in resilience.

Recommendations for future research


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6. References


Arndt, C., Chinowsky, P., Robinson, S., Strzepek, K., Tarp, F., & Thurlow, J. (2012). Economic Development under Climate Change. Review of Development Economics, 16(3), 369–377. Retrieved from http://doi.wiley.com/10.1111/j.1467-9361.2012.00668.x

Blythe, W., Pye, S., Savage, M., & Watkiss, P. (2010). The Economics of Low Carbon, Climate Resilient Patterns of Growth in Developing Countries: A Review of the Evidence. Final Report., 126 pp. Retrieved from http://r4d.dfid.gov.uk/Output/188740/Default.aspx

Fankhauser, S., & McDermott, T. K. J. (2014). Understanding the adaptation deficit: Why are poor countries more vulnerable to climate events than rich countries? Global Environmental Change, 27(1), 9–18. doi:10.1016/j.gloenvcha.2014.04.014

Folke, C., L. Pritchard, F. Berkes, J. Colding, and U. Svedin. 1998. The problem of fit between ecosystems and institutions. International Human Dimensions Programme on Global Environmental Change, Bonn, Germany.

IPCC. (2014). Climate Change 2014: Impacts, Adaptation and Vulnerability.

Persson, T., & Tabellini, G. (2000). Political Economics: Explaining Economic Policy. Cambridge, Mass: MIT press.

Schelling, T. C. (1992). Some Economics of Global Warming. American Economic Association, 82(1), 1–14.

Schelling, T. C. (1997). The cost of combatting global warming: facing the tradeoffs. Foreign Affairs, 76(6), 8–14.

Tarazona, M., Chiappe, F., & Hearle, C. (2014). Understanding the Patterns of Climate-Resilient Development : A Literature Review Summary Report (Vol. 1257).

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The World Bank. (2010). World Development Report 2010: Development and Climate Change. Washington D.C.

Tol, R. S. J., & Yohe, G. (2002). Indicators for social and economic coping capacity - Moving toward a working definition of adaptive capacity. Global Environmental Change, 12(1), 25–40. doi:10.1016/S0959-3780(01)00026-7

Tol, R. S. J., & Yohe, G. W. (2007). The weakest link hypothesis for adaptive capacity: An empirical test. Global Environmental Change, 17(2), 218–227. doi:10.1016/j.gloenvcha.2006.08.001

Waldinger, M. (2015). The effects of climate change on internal and international migration : implications for developing countries (No. 217).

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World Bank. (2012). Climate Change, Disaster Risk, and the Urban Poor. doi:10.1596/978-0-8213-8845-7

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