Climate resilient development index : theoretical framework, selection criteria and fit-for-purpose indicators.
Date: 2015-04-20
Institutions: Institute for Environment and Sustainability
Subjects: adaptation to climate change, climate change, climate change policy, development policy, environmental indicator, environmental risk prevention, natural hazard, research report

Climate resilient development index: 
theoretical framework, selection criteria and 
fit-for-purpose indicators  

Apollonia Miola, Vania Paccagnan,  
Eleni Papadimitriou, Andrea Mandrici 

2 0 1 5  

Report EUR 27126 EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
European Commission 
Joint Research Centre 
Institute for Environment and Sustainability 

Contact information 
Apollonia Miola 
Address: Joint Research Centre,  
E-mail: apollonia.miola@jrc.ec.europa.eu 
Tel.: +39 0332 786729  

https://ec.europa.eu/jrc 

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service. It aims to provide evidence-based scientific support to the European policy-making process. The scientific output 
expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person 
acting on behalf of the Commission is responsible for the use which might be made of this publication. 

All images © European Union 2015 

JRC94771 

EUR 27126 EN 

ISBN 978-92-79-46012-8 (PDF) 

ISSN 1831-9424 (online) 

doi: 10.2788/07628 

Luxembourg: Publications Office of the European Union, 2015 

© European Union, 2015 

Reproduction is authorised provided the source is acknowledged. 

Abstract 
This report aims to contribute to the debate on climate change policies and their link to development. A climate resilient 
perspective is adopted to understand how climate change policy objectives can be reconciled with development goals. The 
report  reviews  the  main  theoretical  concepts  that  characterise  the  scientific  literature  on  climate  risk  and  vulnerability 
assessments,  and  identifies  climate  resilient  fit-for-purpose  indicators  accordingly.  This  makes  it  possible  to  build  the 
theoretical foundations to improve understanding of the implications of climate aid financing. The novelty of this report lies 
in  the  emphasis  given  to  economic  aspects  of  climate  risk,  most  notably:  the  concepts  of  loss  and  damage,  the 
understanding  of  factors  that  enhance  economic  resilience,  the  links  between  climate  change  policies  and  development 
(besides  economic  growth)  and  the  acknowledgment  of  the  role  of  natural  capital  in  pursuing  development  policies.  By 
reviewing grey and peer-reviewed literature, 102 suitable  indicators are identified and grouped into six components. A case 
study is proposed which involves building three climate resilient development indices. The three indices are built for climate 
resilient  development  using  the  same  components  and  indicators  but  adopting  different  political  perspectives.  Our  case 
study demonstrates that although there is some agreement  on which indicators should be included in an index for climate 
resilient  development,  a  single  approach to  building  a global  index  for  climate  resilient  development  does not  exist.  The 
high  number  of  differences  between  the  scores  of  the  three  indices  indicates  that  a  single  index  in  the  climate  resilient 
development domain  is a sort of chimera. Any index should address a specific policy request with a clear objective. This is a 
first step to building a fit-for-purpose index.  

2 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Executive Summary 

Despite  the  proliferation  of  alternative  indicators,  most  existing  measures  do  not 
capture  the  multidimensional  aspects  of  climate  resilient  development.  Most  climate 
risk indices have some limitations, as their theoretical framework is vaguely (or not at 
all) defined and, as a result, the indicators used are not always relevant and  tend to 
focus  on  current  climate  risk  as  opposed  to  future  hazards.  Moreover,  the  economic 
and  ecological  aspects  are  often  neglected  or  ill  defined.    Most  importantly,  none  of 
the  most  popular  climate  risk  assessment  indices  are  informed  by  the  latest 
developments  in  the  international  policy  debate,  especially  with  respect  to  the  loss 
and  damage  concept  and  climate  resilient  development.  This  report  aims  to  fill  this 
gap. 
Chapter  2  gives  an  account  of  the  main  climate  risk  concepts.  Special  attention  has 
been given to defining resilience and adaptive capacity from an economic perspective, 
and  how  the  preservation  of  natural  capital  contributes  to  adaptation  and 
development.   
The debate on climate resilient development is reviewed and the building blocks of our 
theoretical  framework  are  identified  in  Chapter  3.  Any  approach  taken  to  assess 
climate  risk  depends  on  a  coherent  understanding  of  the  underlying  concept  of  risk 
and the interplay of hazard, exposure, vulnerability and resilience. 
Chapter  4  describes  the  criteria  that  should  be  considered  to  screen  indicators  of 
climate  resilient  development.  Findings  from  the  relevant  literature  are  presented, 
along  with  insights  from  the  use  of  existing  climate  risk  indices  to  understand  how 
indicators can be identified consistently with the theoretical framework we adopt.  
Chapter  5  proposes  relevant  fit-for-purpose  indicators  that  can  be  selected  to 
construct  an  index  for  climate  resilient  development.  In  reviewing  the  relevant  grey 
and  peer-reviewed  literature,  the  impacts  of  climate-related  and  weather-driven 
hazards on the following sectors are considered:  households, livelihood and poverty, 
agriculture  and  fisheries,  industry,  infrastructure,  energy,  trade,  transport,  tourism, 
human health and human security, the economy and ecosystem services.  

The  final  part  of  the  report  proposes  a  case  study.  In  Chapter 6,  three  indices  using 
the  same  components  and  indicators  are  built  for  a  sample  of  countries,  including 
Least Developed Countries (LDC), Small Island Developing States (SIDS), low income 
countries,  lower  middle  income  countries  and  territories  from  the  DAC  list  of  Official 
Development  Assistance  (ODA)  Recipients  (excluding  Tokelau,  Singapore,  and 
Bahamas).  Our  case  study  demonstrates  that  although  there  is  some  agreement  on 
which  indicators  should  be  included  in  an  index  for  climate  resilient  development,  a 
single  approach  to  building  a  global  index  for  climate  resilient  development  does  not 
exist.  The  high  number  of  differences  between  the  scores  of  the  three  indices 
indicates  that  a  single  index  in  the  climate  resilient  development  domain  is  a  sort  of 
chimera.  Any  index  should  address  a  specific  policy  request  with  a  clear  objective. 
This is a first step to building a fit-for-purpose index.  

3 

 
 
 
 
 
 
4 

 
 
 
 
Table of Contents 

Executive Summary ............................................................................. 3 

List of Acronyms .................................................................................. 8 

1.  Introduction .................................................................................. 11 

2.  Defining concepts from a socio-economic perspective:  exposure, 
vulnerability, resilience and adaptive capacity ................................... 12 

2.1 From biophysical hazards to macroeconomic and microeconomic 
impacts ..................................................................................................... 12 
2.2 Vulnerability ....................................................................................... 16 
2.3 Exposure ............................................................................................. 17 
2.3 Resilience ........................................................................................... 18 
2.4 Adaptive capacity ................................................................................ 19 
2.4.1 Adaptation ........................................................................................ 20 
2.4.2 Interface between adaptation and mitigation ........................................ 21 

3. Defining climate resilient development .......................................... 23 
3.1 Understanding the links between climate change and development ... 23 
3.2 Climate Resilient Development ........................................................... 24 

4. Use of metrics and indicators for assessing climate risk, resilience 
and vulnerability ................................................................................ 26 
4.1 Issues in Adaptation and Risk Assessment ......................................... 27 
4.2 Vulnerability Assessment: insights from the literature ....................... 28 

5. Indicators selection ....................................................................... 31 
5.1 Criteria for indicators selection ........................................................... 33 
5.2 Fit-for-purpose indicators: preliminary list ......................................... 35 

6. A Case Study .................................................................................. 38 

7. Open issues .................................................................................... 46 
7.1 Limits of Datasets on Natural Hazards ................................................ 46 
7.2 Including indicators on Monitoring and Evaluation (M&E) .................. 46 
7.3 Indicators from Earth Observation ...................................................... 46 

8.  Conclusion .................................................................................... 48 

References ......................................................................................... 50 

Annex I Fact sheets of the indicators included into the Case study .... 59 
Natural Hazards ........................................................................................ 59 
Drought Events - the past 20 years (cumulative) ........................................... 59 
Flood Events - the past 20 years (cumulative) ............................................... 60 
Storm Events - the past 20 years (cumulative) .............................................. 61 
Exposure ................................................................................................... 62 
Population density (people per sq. km of land area) ....................................... 62 
Internally displaced .................................................................................... 63 
Number of refugees per place of residence .................................................... 64 
Proportion of Population in Low Elevation Coastal Zones (LECZ) ...................... 65 
Gini index ................................................................................................. 66 
Poverty headcount ratio at US$1.25 a day (PPP) (% of population) .................. 67 
Age dependency ratio (% of working-age population) ..................................... 68 

5 

 
 
 
Agriculture, value added (% of GDP) ............................................................ 69 
Forest area (% of land area) ....................................................................... 70 
Water dependency ratio .............................................................................. 71 
Adaptive capacity...................................................................................... 72 
Ecosystem vitality: Agriculture .................................................................... 72 
Manufacturing, value added (% of GDP) ....................................................... 73 
Overall Development Assistance Committee (DAC) aid activities with adaptation 
as principal objective .................................................................................. 74 
Adaptive capacity/Gender ........................................................................ 75 
Access to Literacy ...................................................................................... 75 
Share of female representatives in the National Parliament ............................. 76 
Access to Bank Accounts ............................................................................. 77 

Coping Capacity ................................................................................. 78 
Improved sanitation facilities (% of population with access) ............................ 78 
Hospital beds (per 1 000 people) ................................................................. 79 
Physicians (per 1 000 people) ..................................................................... 80 
Nurses and midwives (per 1 000 people) ...................................................... 81 
Mobile phone subscriptions (per 100 people) ................................................. 82 
Mitigation Capacity ..................................................................................... 83 
CO2 emissions (kg per PPP US$ of GDP) ....................................................... 83 
Participation in UNFCCC fora  - Mitigation actions ........................................... 84 
Development ............................................................................................. 85 
Literacy rate, adult total (% of people ages 15 and above) ............................. 85 
Income Index  - Gross National Income (GNI) ............................................... 86 
Net ODA received per capita (current US$) ................................................... 87 
Personal remittances received (% of GDP) .................................................... 88 
Internet users (per 100 people) ................................................................... 89 

ANNEX II ............................................................................................ 91 
Table I – Sample of  Countries for the case study .......................................... 91 

ANNEX III – Fit-for-purpose indicators by component ....................... 93 
Natural Hazard Indicators  ........................................................................ 93 
Exposure indicators .................................................................................. 96 
Vulnerability Indicators  ......................................................................... 101 
Adaptive capacity indicators ................................................................... 107 
Mitigation capacity indicators  ................................................................ 113 
Development indicators  ......................................................................... 116 

ANNEX IV ......................................................................................... 125 

Table I - Indicators identified by reviewing the relevant literature on 
climate change, development and disaster risk. ..................................... 125 
Table II – Indexes  identified by reviewing the relevant literature on 
climate change, development and disaster risk. ..................................... 187 

6 

 
 
 
 
 
List of Tables 

Table 1 – Climate-related and weather-driven  hazards considered in this report ....... 13 
Table 2 – Examples of direct and indirect impacts of natural hazards ....................... 14 
Table 3 – Main factors affecting economic resilience ............................................... 18 
Table 4 – A comparison of adaptation and mitigation ............................................. 22 
Table 5 – Criteria for selection of indicators .......................................................... 33 
Table 6 – Components and indicators considered to build an index .......................... 39 
Table 7 – Normalisation of indicators and aggregation at component level. ............... 40 
Table 8 – Correlation between components ........................................................... 43 
Table 9 – Examples of Earth-Observation-derived indicators of climate impacts ......... 47 

List of Figures 

Figure 1 – Systematisation of events related to climate change, vulnerability, exposure, risk 
and development ......................................................................................................... 16 
Figure 2 – Building blocks of climate resilient development: summarising a theoretical 
framework .................................................................................................................. 25 
Figure 3 – Correlation Matrix: Plots between overall geometrical index and components ....... 44 
Figure 4 – Correlation Matrix: Plots between overall linear index and components ............... 44 
Figure 5 – Correlation Matrix: Plots between overall mixed index and components .............. 45 

List of Maps 

Map 1 – Index calculated with geometrical formula of aggregation .................................... 41 
Map 2 – Index calculated with linear formula of aggregation ............................................. 41 
Map 3 – Index calculated with mixed formula of aggregation. ........................................... 42 

7 

 
 
 
 
 
 
 
List of Acronyms 

BCR – Benefit Cost Ratio 
COP – Conference of the Parties 
CRI – Germanwatch Global Climate Risk Index 
DEVCO – Directorate-General for International Cooperation and Development 
DFID – Department for International Development (UK) 
EBA – Ecosystem-Based Adaptation 
ECHO – Directorate-General for Humanitarian Aid and Civil Protection (ECHO) 
EEA – European Environment Agency 
EPI – Environmental Performance Index 
EVI – Environmental Vulnerability Index 
FAO – Food and Agriculture Organization of the United Nations 
GCCA – Global Climate Change Alliance 
GDP – Gross Domestic Product 
GHG – Greenhouse Gases  
HDI – Human Development Index 
INFORM - Index for Risk Management 
IPCC – Intergovernmental Panel on Climate Change 
JRC – Joint Research Centre 
LDC – Least Developed Countries 
MDG – Millennium Development Goals 
ND-GAIN – University of Notre Dame Global Adaptation Index 
ODA – Official Development Assistance 
OECD – Organisation for Economic Co-operation and Development 
PPP – Purchasing Power Parity 
REDD – Reducing Emissions from Deforestation and forest Degradation 
SDG – Sustainable Development Goals 
SIDS – Small Island Developing States  
SREX – Special Report on Managing the Risks of Extreme Events and Disasters to 
Advance Climate Change Adaptation 
UN – United Nations 
UNDP – United Nations Development Programme 
UNEP – United Nations Environment Programme  
USAID – United States Agency for International Development 
VA – Vulnerability Assessment 
WHO – World Health Organization 
WRI – World Risk Index 

8 

 
 
 
 
ACKNOWLEDGEMENT 

The authors would like to thank G. Ceddia, G. Mulhern, F. Neher, P. Part, F. Raes, L. 
Salvioni and J. Thielen for their comments and suggestions for this report.  

9 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
10 

 
 
 
 
 
1. Introduction 

Many  initiatives  are  in  place,  or  have  been  announced  by  governments,  companies, 
investors and public-private coalitions to support climate adaptation and resilience for 
the  world’s  most  vulnerable  countries.  Global  efforts  to  set  the  world  on  a  climate 
change  resilient  development  pathway  require  an  understanding  of  the  relationships 
between climate change and development, as well as metrics for the identification of 
the  countries,  groups  of  people  and  sectors  most  seriously  threatened  by  climate 
change. Despite the proliferation of alternative indicators, most existing measures do 
not capture the multidimensional aspects of climate resilient development.  
Most climate risk  indices often show some  limitations, as their  theoretical framework 
is vaguely defined (or even completely missing) and, as a result, the indicators used 
are  not  always  relevant  and  focus  on  current  climate  risk  as  opposed  to  future 
hazards.  Moreover,  the  economic  and  ecological  aspects  are  often  neglected,  or  ill 
defined.   
Most  importantly,  none  of  the  most  popular  climate  risk  assessment  indices  are 
informed by the latest developments in the international policy debate, especially with 
respect to the loss and damage concept and climate resilient development.  

This report aims to fill this gap. It starts by reviewing the key concepts used in climate 
risk assessments, in order to clarify the foundations of our theoretical framework. Any 
approach taken to assess climate-related risk depends on a coherent understanding of 
the underlying concept of risk and the interplay of hazard, exposure, vulnerability and 
resilience.  We  will  then  discuss  how  adaption  can  be  put  into  practice  following  the 
international debate on loss and damage, and how adaptive capacity is dependent on 
development pathways. The main focus will be the identification of criteria and fit-for-
purpose indicators to construct an index that prioritizes the allocation of funding to the 
poorest  developing  countries.  Special  attention  has  been  given  to  defining  resilience 
and  adaptive  capacity  from  an  economic  perspective,  and  how  the  preservation  of 
natural capital contributes to adaptation and development.  
The debate on climate resilient development is then reviewed.  
The  final  part  of  the  report  proposes  relevant  and  fit-for-purpose  indicators  that  can 
be used to construct an index for climate resilient development.  
As a case study, three indices using the same components and indicators are built for 
a sample of countries.  
The  main  outcome  of  this  case  study  is  the  identification  of  the  main  challenges  to 
building an index for climate resilient development, which is fit for purpose. 

11 

 
 
 
 
 
 
 
2. Defining concepts from a socio-economic perspective:  

exposure, vulnerability, resilience and adaptive capacity  

This  section  will  review  the  evidence  currently  available  on  climate  hazards, 
vulnerability  and  exposure,  and  how  adaptation  and  mitigation  policies  can  tackle 
climate  change  impacts.  It  will  clarify  the  conceptual  foundations  for  considering 
exposure, vulnerability and adaptive capacity in risk assessment.  

2.1 From biophysical hazards to macroeconomic and microeconomic 
impacts 

There  is  scientific  evidence  that  the  climate  is  changing.  Observations  of  the  Earth’s 
average surface air temperature indicate evidence of planetary–scale warming (IPCC, 
2013; National Academy and Royal Science, 2014).  
 According  to  the  Intergovernmental  Panel  on  Climate  Change  (IPCC,  2013),  some 
events  are  directly  related  to  climate  change,  namely  ocean  warming,  ice  loss  from 
glaciers, sea-level rise (over the period 1901 to 2010, the global mean sea level rose 
by 0.19 [0.17 to 0.21] m), and change in the global water cycle. The climate-related 
and weather-driven hazards considered  in  this report are flooding, storms,  droughts, 
heat  waves,  sea-level  rise,  and  alpine  hazards  (Table  1).  These  hazards  each  bring 
different risks with different impacts on economic, social and natural systems. 

12 

 
 
 
 
 
 
 
Table 1 - Climate-related and weather-driven hazards considered in this 
report 

Hazards 

Description  

Flooding 

When water covers land that is not normally covered by water, different types of flooding 
might occur depending on the sources of excess water: coastal floods (sea); fluvial floods 
(river), pluvial floods (heavy rain events) and groundwater floods (water collecting below 
the  surface).  Direct  economic  impacts  originate  from  damage  caused  to  buildings, 
infrastructure, transport networks, etc. Flood events can also trigger indirect effects due 
to interruptions to production processes, disruption to businesses, or other ripple effects. 
Finally,  health  impacts  range  from  fatalities  to  psychological  consequences  of  the 
extreme event. The main factors  that determine the severity of losses are water depth, 
flood duration, building/object type, building age, social class of the occupants, warning 
time (Bubeck et al., 2011). 

Storms  

Storms are characterised by strong winds and heavy precipitation. Their economic 
impacts are similar to those of flooding.    

Droughts 

Heat waves 

temperatures,  heat-waves,  high 

Droughts  are  caused  by  a  deficit  in  rainfall.  The  severity  and  duration  of  their  impacts 
can  be  exacerbated  by  high  air 
rates  of 
evapotranspiration  (Bubeck  et  al.,  2011)  and  human  activities.  In  contrast  with  other 
extreme  events,  they  have  mainly  non-structural  consequences.  Droughts  affect  crop 
production  and  ecosystem  services.  If  water  levels become too  low,  this  can  negatively 
impact  navigation  or  the  cooling  of  power  plants.  The  severity  of  economic  impacts 
depends on the length and time of the drought (Bubeck et al., 2011).  
Heat waves are characterised by continuous spells of abnormally hot weather.  They are 
normally  of  shorter  duration  periods  than  droughts.  Heat  waves  are  often  accompanied 
by  droughts,  in  which  case  the  effects  of  the  two  extreme  events  are  difficult  to 
disentangle.  The  main  consequences  of  heat  waves  are  related  to  health.  Whilst  the 
incidence  of  mortality  is  well  documented,  morbidity,  injury  and  illness  associated  with 
heat  waves  and  excessive  heat  are  still  not  well  understood.  Economic  impacts  include 
those  on  human  productivity, 
lift  at  high 
temperatures), livestock and dairy production and ecosystem services, energy and water 
services (due to increased demand). 

transportation  (e.g.  aircrafts 

lose 

Alpine 
hazards 

Sea-level rise  Rising  sea  levels  increase  the  risk  of  coastal  flooding.  Vulnerability  to  coastal  hazards 
may  increase      strongly  due  to  an  accumulation  of people  and  economic  assets  in  risk-
prone coastal areas  (Bubeck et al., 2011).  The severity  of impacts depends on building 
type, flow velocity, wave action and inundation. 
Alpine hazards are caused by the thawing of permafrost at high altitudes, and consist of 
landslides,  avalanches,  rock  falls  and  flooding.  Flood  events  can  occur  as  flash  floods, 
which  are  typically  rapid  and  intense,  or  river  floods  (see  above).  The  economic  risk  of 
alpine hazards has increased in recent years, as the growing demand for land has led to 
the  extension  of  urban  developments  into  areas  that  are  prone  to  alpine  hazards. 
Avalanches  and  flash  floods  can  cause  severe  economic  and  human  losses  due  to  their 
kinetic energy and high pressure (Bubeck et al., 2011).  
Ocean  acidification  is  a  global  problem  that  results  from  the  increase  in  carbon  dioxide 
(CO2) released into the atmosphere, primarily from burning fossil fuels. Excess CO2 in the 
air  dissolves  in  seawater  and  forms  carbonic  acid  which,  through  a  series  of  other 
reactions,  reduces  the  amount  of  carbonate  in  seawater.  Sea  creatures  that  use 
carbonate  and  calcium  to  build  their  shells  or  skeletons  are  affected1.  Acidification  will 
affect  the  production  cycle  of  the  oceans  because  marine  organisms  have  a  very  low 
capacity to deal with changes in pH (acidity or alkalinity). Reproduction is most sensitive, 
and disturbed reproduction will have direct impacts on stocks of fish, shellfish, etc.  

Ocean 
acidification  

1 In seawater containing high levels of CO2, corals have difficulty making new skeletons and their existing skeletons may dissolve 
away, many calcifying plankton struggle, molluscs such as oysters and scallops find it harder to build and maintain shells, and 
juvenile molluscs grow more slowly and have more abnormalities and lower survival rates. Among calcifying organisms, only 
crustaceans such as crabs and lobsters appear to tolerate low carbonate levels; some even make thicker exoskeletons under such 
conditions. 

13 

 
 
 
 
                                                        
The literature on the economics of natural disasters provides different taxonomies that 
can be used to classify the impacts of extreme events and natural hazards.  

The  most  widely  used  taxonomy  is  based  on  the  distinction  between  direct  and 
indirect  economic  effects,  where  the  former  are  economic  losses  that  occur  due  to  a 
direct physical impact of a hazard on humans, economic assets or any other receptor, 
and  the  latter  occur  outside  the  hazard  area,  for  instance,  due  to  a  loss  of  business 
turnover when supplies are disrupted (Hallegatte, 2007; Bubeck and Kreibich, 2011). 
Table  2  shows  some  examples  of  direct  and  indirect  impacts  that  can  be  further 
classified  as  tangible  and  intangible  (Penning-Rowsell  et  al.,  2003),  depending  on 
whether  they  are  traded  in  a  market  and  can  thus  be  easily  expressed  in  monetary 
terms. 

Table 2 - Examples of direct and indirect impacts of natural hazards 

Direct Impacts 
Primary direct impacts 

Indirect Impacts 
Primary indirect impacts 

damage 

Physical 
infrastructure 
Physical damage to production equipment 

buildings 

to 

and 

Physical damage to agricultural land 

Physical damage to raw materials 
Physical damage to products in stock 
Physical damage to semi-finished products 

Loss of production due to direct damage 

Loss  of  production  due  to  infrastructure 
disruptions 
Loss  of  production  due  to  supply-chain 
disruption 

Secondary direct impacts 

Secondary indirect impacts 

Costs of recovery and reconstruction 

Costs  of 
measures 

remediation  and  emergency 

Market  disturbances  (e.g.  price  variations 
of  complementary  and  substitute  products 
or raw materials) 
Damage to the enterprise image 

Reduced short-term competitiveness 

Increased  productivity  and  technological 
development, in the medium- to long-term 

Economic growth for reconstruction 
Increased levels of poverty and inequality 

Source: Andreoni and Miola (2014) 

It often is difficult to clearly distinguish between direct and indirect damage. Errors in 
such  distinctions  can  lead  to  double  counting  (Rose,  2004),  which  can  be  solved  by 
referring to asset losses (i.e. reduction in the stock of assets) and output losses (i.e. 
reduction in an income flow) (Rose, 2007; Hallegatte, 2014). 

Asset  losses  include  impacts  such  as  business  interruptions  (interrupted  production 
during  the  event),  production  losses  directly  attributable  to  asset  losses  (because 
damaged  or  destroyed  assets  are  not  functional  after  the  event),  supply-chain 
14 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
disruptions (when lack of input or reduced demand leads to a reduction in production 
from a site that is not directly affected), macro-economic feedbacks (e.g. the impact 
of reduced demand because consumers and businesses suffer from a reduced income, 
and  the  effect  of  lost  tax  revenue  on  public  demand),    long-term  adverse 
consequences on economic  growth (e.g. due to changes  in risk perception (including 
over-reactions) that can drive investors and entrepreneurs out of the affected area); 
and  increased  production  from  a  subsequent  “reconstruction  boom”  that  acts  as  a 
stimulus for the economy.  

All  these  impacts  have  an  effect  on  gross  domestic  product  (GDP),  but  they  are  not 
completely captured by GDP in cases where impacts are large but localised, or when 
they  affect  household  or  non-market  production  (which  are  not  included  in  GDP 
calculations).  

With regard to output losses, the impacts on households are central.  

According  to  Hallegatte  (2014)  vulnerability  is  higher  where  levels  of  inequality  are 
higher  and  GDP  levels  are  lower.  Considering  the  heterogeneity  of  direct  losses  to 
households,  economic  diversification  decreases  household  vulnerability,  because  if 
households have multiple income sources, they are more likely to lose a smaller share 
of their income if one activity is particularly affected.  

It  is  also  argued  that  those  households  with  a  negative  income  in  the  year  of  the 
hazard  occurrence  and  which  do  not  have  any  smoothing  option  and  assistance  will 
suffer  high  welfare  losses.  Similarly,  social  protection  and  other  government  actions 
may  mitigate  sudden  income  losses  and  can  help  households  to  smooth  income 
shocks over time (Hallegate, 2014).  

Climate  risk  assessments  and  the  identification  of  loss  and  damage  risks  should  not 
only  consider  factors  related  to  climate  change,  but  also  the  development  pathways 
that a country or community takes. According to the IPCC (2013, 2014), the severity 
of disasters depends on weather and climate events, but also on exposure (e.g. urban 
developments  in  low-lying  coastal  areas)  and  vulnerability  (e.g.  poverty,  weak 
economic structures) which arise from non-climatic and  multidimensional  inequalities 
(Figure 1).  
Figure  1  captures  all  the  elements  that  will  be  considered  in  building  our  conceptual 
framework for identifying the indicators that should be used to assess climate resilient 
development, namely: 

-  Exposure to hazards related to climate change; 
-  Vulnerability to these hazards; 
-  Socio-economic pathways; 
-  Adaptation and mitigation options.  

15 

 
 
 
 
 
Figure 1 - Systematization of events related to climate change, vulnerability, 
exposure, risk and development 

Source: IPCC (2014) 

A general discussion on concepts and definitions is far from being the objective of this 
report.  However,  a  clear  definition  of  the  terminology  is  useful  in  order  to 
operationalise  concepts  that  will  be  used  to  identify  indicators  that  for  assessing 
climate change risk components. 

2.2 Vulnerability 

Vulnerability  is  a  central  concept  in  climate  change  research  and  policy.  It 
encompasses a variety of concepts, including sensitivity or susceptibility to harm and 
lack  of  capacity  to  cope  and  adapt  (IPCC,  2014:  chapter  19).  It  is  the  propensity  or 
predisposition to be adversely affected. 

The  dynamic  nature  of  the  concept  is  often  emphasised  by  stressing  its  direct  and 
indirect  relation  to  a  range  of  environmental,  social,  economic  and  political  factors 
(EEA, 2008). 

For  the  purpose  of  this  work,  it  should  be  noted  that  other  authors  adopt  a  static 
vision  of  the  concept  of  vulnerability,  consistent  with  what  is  argued  by  Adger  et  al. 
(2007),  as  a  state  variable,  determined  by  the  internal  property  of  the  system  (i.e. 
the  predisposition  to  be  affected).  From  such  a  perspective  the  frequency  and 
magnitude  of  climate  change  and  extreme  weather  events  are  characteristics  of 
hazards  and  not  of  vulnerability.  Vulnerability  is  an  internal  risk  factor,  while  the 

16 

 
 
 
 
 
 
 
 
hazard  event  is  rather  considered  as  a  factor  external  to  the  exposed  society  or 
system  (Birkmann,  2006).  The  dynamic  component  is  captured  by  the  resilience 
concept (see paragraph 2.4).   

This  way  of  conceptualising  vulnerability  is  consistent  with  that  defined  by  Brooks  et 
al.  (2005)  as  that  “function  of  physically  defined  climate  hazard  and  socially 
constructed  vulnerability”,  which 
to  an  outcome-based 
representation of risk (Adger et al., 2007)2.  

is  related 

turn 

in 

In  this  respect,  it  is  important  to  distinguish  between  generic  and  specific 
determinants  of  vulnerability  (Adger  et  al.,  2007).  Generic  determinants  are  factors 
that  are  likely  to  influence  vulnerability  in  different  geographical  and  socio-political 
contexts  and  for  different  hazards.  Poverty,  health  status,  economic  inequality  and 
elements  of  governance  are  some  examples  (see  below  for  a  discussion  of  poverty 
and economic determinants). Specific determinants are relevant for a given context or 
hazard.  Vulnerability  to  the  same  hazard,  for  example  flooding,  can  be  explained  by 
different  factors,  depending  on  whether  this  hazard  occurs  in  a  least  developed 
country  or  a  developed  one.  In  the  former  case,  income  diversification  will  be 
important,  whilst  in  latter  case  infrastructure  might  be  the  dominant  determinant 
(Adger et al., 2007).  

2.3 Exposure  

Vulnerability is often indicated as a social concept that is intrinsically interrelated with 
exposure, which can be considered as encompassing the spatial and temporal 
distribution of populations and assets. 

According  to  the  IPCC  (2014),  exposure  is  “the  presence  of  people,  livelihoods, 
species  or  ecosystems,  environmental  services  and  resources,  infrastructure,  or 
economic,  social,  or  cultural  assets  in  places  that  could  be  adversely  affected”.  As 
noted  by  Hallegatte  (2014),  in  order  for  an  extreme  event  to  become  a  hazard,  a 
natural  event  should  have  an  impact  on  a  human  system,  leading  to  negative 
consequences.  It  is  the  interaction  between  extreme  weather  events  or  climate 
stressors and the vulnerable conditions that determines disaster risk (Surminski et al., 
2013). Disaster loss and damage is caused by the interaction between hazard events 
and  the  characteristics  of  the  exposed  object  or  subject  that  make  the  latter 
susceptible to damage. 

2 An alternative representation of risk is the probabilistic one, which depicts risk as the probability of occurrence of 
hazardous events or trends multiplied by the consequences of such occurrences. 

17 

 
 
  
 
 
 
                                                        
2.3 Resilience 

There  are  several  definitions  of  the  term  “resilience”,  stemming 
from  the 
conceptualisation  of  the  wealth  of  a  nation  in  terms  of  natural,  environmental  and 
social capital (Bahadur et al., 2010). 

The  term  originates  in  the  natural  sciences.  Ecological  resilience  was  first 
conceptualised  by  Holling  (1973),  who  considered  resilience  to  combine  persistence, 
resistance and transformation. 

Resilience in ecological terms is defined as the magnitude of disturbance that can be 
absorbed  before  the  system  changes  its  structure  by  changing  the  variables  and 
processes  that  control  behaviour  (Gunderson,  2000).  Holling  (1973)  argues  that  a 
certain degree of fluctuation in a system may actually improve the system’s ability to 
persist in the face of change.  

The concept of resilience has been applied in economics by considering generic shocks 
and extreme events that affect the economy. Generally speaking, economic resilience 
can  be  defined  as  the  ability  of  the  economy  or  society  to  cope,  recover,  and 
reconstruct  (macroeconomic  resilience)  and  to  minimise  household  welfare  losses 
(microeconomic resilience) for a disaster of a given magnitude (Hallegatte, 2014).  

The factors affecting economic resilience are summarised in Table 3.   

Table 3 – Main factors affecting economic resilience 

Component 

Factors 

Exposure 

Vulnerability  

Macroeconomic 
resilience 

Microeconomic 
resilience 

-  Total affected capital  
-  Number of affected households  

Total asset losses 

Interest rate and marginal capital productivity  

- 
-  Reconstruction duration in years (𝑁), which depends on the 
ability of the economy to mobilise financial and technical 
resources to rebuild  

-  Ripple effects that amplify (or diminish) instantaneous 

production losses  

- 
- 
- 

level of income in the country  
inequality level  
“poverty bias” of disasters, i.e. the relative exposure of the 
poor, compared with the share of assets owned by the poor  

-  heterogeneity in direct losses across households  
- 
ability of households to smooth income shocks over time  
-  maximum loss of welfare that an household can withstand  
- 

amount of risk-sharing in the economy  

Source: Adapted from Hallegatte (2014)  

18 

 
 
 
 
 
 
 
 
 
 
 
In its application at community level, the social resilience concept can be seen as “the 
ability  of  communities  to  withstand  shocks  to  their  social  infrastructure”  (Adger, 
2000).  A  resilient  system  is  one  in  which  people  are  dependent  upon  a  variety  of 
natural resources (so that a shock to one does not upset the entire system), has a low 
frequency  of  extreme  weather  events  (as  these  can  lead  communities  to  depend  on 
particular natural resources), and where institutions are seen as being legitimate. 

Resilience  can  also  be  considered  as  a  pathway  for  decision-making  strategies  as 
described below: 

1)  The  resistance  of  a  system  or  of  a  component  does  not  require  any  re-
organisation  since  every  component  remains  at  the  same  point  of  equilibrium, 
and policy strategy can focus on mitigation; 

2)  Persistence:  the  system  can  re-organise  its  assets  and  return  to  a  similar 

equilibrium level. The system is maintained in its status quo; 

3)  Transformation  requires  more  significant  structural  changes  that  push  the 

system to a different status quo. 

All of these strategies conceptualise resilience as a dynamic concept (Manyena, 2006). 
In particular, resilience can be increased (and vulnerability reduced) by enhancing the 
strength  of  socio-economic  systems,  reducing  the  intensity  of  the  impact,  or  both. 
Both  options  for  increasing  resilience  are  interlinked  with  humanitarian  and 
development assistance. 

2.4 Adaptive capacity 

The concept of adaptive capacity has its roots in biology, where it was used to indicate 
the  ability  of  species  or  organisms  to  become  adapted  to  a  certain  range  of 
environmental contingencies (Gallopin, 2006).  

Determinants  of  adaptive  capacity,  understood  as  the  main  features  of  communities 
or regions that seem to determine their adaptive capacity, have been widely debated 
in  the  literature  and  can  be  grouped  as  follows  (IPCC,  2014;  EEA,  2008;  Yohe  and 
Moss, 2000): 

  Economic wealth, in terms of the availability of resources and their distribution 
across  the  population.  Resources  include  economic  assets,  capital  resources, 
natural  capital  and  financial  means.  It  is  widely  recognised  that  poverty  is 
directly related to vulnerability.  

  Technology, i.e. the range of technological options available for adaptation. As 
discussed in section 2.4.1, this element is crucial to ensure that a country can 
implement adaptation options.  
Information  and  skills  refer  to  the  stocks  of  human  capital  (i.e.  education  and 
personal  security)  and  the  stocks  of  social  capital  (i.e.  definition  of  property 
rights). 

 

19 

 
 
 
 
 
 
 

Infrastructure  acts  both  as  an  enhancing  factor  in  terms  of  adaptive  capacity 
(see for instance flood defences) and as a limiting factor, as it can increase the 
economic damage following extreme events. 
Institutions  affect  the  ability  to  implement  effective  adaptation  options,  to 
manage information, and the credibility of the decision-makers themselves.  
  Equity  including  the  availability  of  resources  and  their  access  to  vulnerable 

 

subsectors of a population.   

2.4.1 Adaptation  

According  to  the  IPCC  (2014),  although  natural  systems  have  the  potential  to  adapt 
through  multiple  autonomous  processes, 
intervention  is  required  for  human 
adaptation,  to  promote  particular  adjustments  or  to  manage  adaptation  deficits  by 
minimising adverse impacts from existing climate conditions and variability.  

The adoption a policy-driven adaptation strategy approach should answer some high-
level questions, namely (Fankauser and Soare, 2013): (i) Where to adapt? (ii) When 
to adapt? (iii) How to adapt? (iv) Who should adapt? 

In order to give an answer to the first question (where), as well as an understanding 
of  the  main  areas  of  vulnerability  (i),  the  urgency  of  action  (ii),  and  the  ease  with 
which risk may be reduced (iii) should also be considered. Vulnerability should not be 
assessed  by  simply  looking  at  current  socio-economic  structures,  but  also  by 
considering different development pathways.  

Regarding the timing of adaptation (when), although most climate change effects will 
materialise  in  the  future,  adaptation  might  be  brought  forward  in  cases  where 
adapting  now  is  less  expensive  than  adapting  in  the  future  (such  as  retrofitting 
existing buildings or improving spatial planning), and when the benefits of actions do 
not depend on future effects of climate change (the so called “low-regret” adaptation), 
e.g. improving water efficiency or better environmental management.  

Finally the ‘who should adapt’ point raises a series of additional questions, related to 
the  allocation  of  responsibilities  between  the  public  and  private  sectors  such  as  the 
role of public policy in adaptation, the economic nature of adaptation options, and how 
to overcome barriers to adaptation posed by private entities. 

It should be noted that criteria other than economic efficiency include: effectiveness, 
equity, stakeholders’ participation and social acceptance, sustainability, flexibility and 
appropriateness in terms of timeframe and scope. These criteria should be consistent 
with  mitigation  and  integrated  with  wider  social  goals  that  are  likely  to  avoid 
maladaptation  traps  and  to  prove  robust  against  a  wide  range  of  climate  and 
development scenarios (IPCC, 2014). 

Finally, adaptation options will not eliminate all climate-change-related impacts. If one 
considers all actions necessary to eliminate all impacts, only a subset will be feasible 
due  to  technical  and  physical  limitations.  Moreover,  there  might  be  some 
implementation constraints that further restrict what can be done.  

20 

 
 
 
 
The awareness that it is impossible to eliminate all impacts of climate change (through 
mitigation),  together  with  the  recognition  of  limits  to  adaptation  measures,  have 
resulted  in  the  emergence  of  the  concept  of  “loss  and  damage”  in  the  policy  debate 
(Dow  and  Berkhout,  2014).  When  it  is  not  possible  to  alleviate  all  effects  of  climate 
change, residual damage will occur. In Cancun in 2010, the Conference of the Parties 
(COP)  of  the  United  Nations  Framework  Convention  on  Climate  Change  (UNFCCC) 
established a work programme on loss and damage. Whilst that discussion on how to 
frame  loss  and  damage  is  still  ongoing,  the  different  dimensions  and  factors  that 
increase  or  reduce  loss  and  damage  are  still  not  completely  understood  (Birkmann, 
2006).  

More  investment  in  ex-ante  risk  reduction  measures  is  needed  to  address  climate 
variability,  together  with  mechanisms  to  share  residual  risk.  It  should  also  be  noted 
that  adaptation  practices  should  not  simply  deal  with  existing  climate  variability,  but 
also help society to cope with extremes and qualitative changes in climate expected in 
the  future  (Brooks  et  al.,  2011).  Most  importantly,  the  impossibility  of  having  zero 
residual damage implies that mitigation actions are needed, together with adaptation, 
to deal with climate-related hazards and climate vulnerability.  

2.4.2 Interface between adaptation and mitigation 

Mitigation  has  traditionally  received  much  greater  attention  than  adaptation  in  the 
climate change community, both from a  scientific and from a  policy perspective. The 
main  reasons  for  this  are  explained  in  Füssel  and  Klein  (2006).  In  fact,  both  are 
essential in dealing with climate change risk as discussed above. On the one hand, as 
claimed  by  Klein  et  al.  (2007),  mitigation  is  crucial  when  a  magnitude  of  climate 
change could be reached that makes adaptation impossible for some natural systems, 
while  for  most  human  systems  such  high  magnitudes  of  change  would  involve  very 
high social and economic costs. On the other hand, even if mitigation was completely 
effective, adaptation  would  be essential to deal with climate change impacts  induced 
by  past  development  patterns  and  with  residual  damage.  In  economic  jargon,  each 
policy option can compensate to some extent for deviations from the efficient outcome 
caused by the non-optimality of the other.  De Bruin et al. (2009) concluded that the 
higher  the  current  value  of  damage,  the  more  important  mitigation  is  as  a  policy 
option in comparison to adaptation.  

Therefore,  mitigation  and  adaptation  are  interlinked.  For  a  start,  mitigation  can 
potentially  reduce  the  magnitude  of  climate  change  to  which  human  and  natural 
systems should adapt (IPCC, 2014). In this respect, they can be considered as partial 
substitutes,  as  stringent  mitigation  efforts  would  also  reduce  climate  damage  and 
therefore  reduce  the need  for  adaptation  investments  over  the long  term  (Agrawala, 
et al., 2010).  

Despite  several  differences  (Table  4),  adaptation  and  mitigation  options  are  often 
seen  as  being  complementary,  since  they  can  deliver  co-benefits,  the  main  reasons 
being: 

21 

 
 
 
 
  Mitigation actions aim to prevent climate change impacts, by stabilising carbon 
concentrations  in  the  atmosphere,  whilst  adaptation  deals  with  the  impacts  of 
climate change once these occur, by reducing the net climate damage and the 
total climate costs   

  Adaptation measures have immediate benefits, as opposed to mitigation actions 
whose effects can be only seen in future decades. Moreover, adaptation can be 
implemented  at  the  local  and  regional  scale,  whilst  mitigation  actions  require 
global cooperation (Füssel and Klein, 2006). 

Table 4 – A comparison of adaptation and mitigation 

Source: Füssel and Klein (2006: 3) 

The  most  compelling  argument  for  combining  mitigation  and  adaptation  measures  is 
given  by  the  World  Bank  (2014),  where  they  emphasise  the  fact  that  adaptation 
strategies  can  compensate  for  some  adverse  effects  of  climate  change  below  2°C 
warming,  but  that  large  negative  impacts  cannot  be  avoided  under  3-4°C  warming, 
e.g.  impacts  on  agricultural  productivity  and  complete  glacier  loss  in  the  Andes. 
Similarly,  limiting  warming  to  2°C  is  projected  to  significantly  reduce  the  risk  of 
drought.  

Although adaptation can be complementary to mitigation and to non-climate policies, 
an  important  concern  is  that  of  determining  the  balance  between  spending  on 
adaptation versus mitigation policies, or other investments.  

In  terms  of  economic  efficiency,  Agrawala  et  al.  (2010)  found  that  the  total  costs  of 
climate  change  are  lowest  when  both  mitigation  and  adaptation  options  are  jointly 
undertaken. They conclude that any least-cost policy response to climate change will 
need  to  involve  substantial  amounts  of  mitigation  efforts,  investments  in  adaptation 
stock, and reactive adaptation measures to limit the remaining damage.  

Finally,  it  is  often  difficult  to  distinguish  between  mitigation  and  adaptation.  A  well-
documented  example  is  given  by  agricultural  management  practices  used  in 
conservation  agriculture.  These  practices  involve  increasing  the  organic  matter  in 
soils,  of  which  carbon  is  a  main  component.  This,  in  turn,  increases  fertility,  water 
retention  and  the  structure  of  soils,  leading  to  better  yields  and  greater  resilience 
22 

 
 
 
 
 
 
(FAO,  2010).  In  soils  lacking  in  carbon,  the  improved  agricultural  management 
practices  required  for  mitigation  are  often  the  same  as  those  needed  to  increase 
productivity,  food  security  and  adaptation.  In  other  cases,  adaptation  options  also 
deliver mitigation co-benefits, such as with the creation of wetlands.  

3. Defining climate resilient development 

3.1 Understanding the links between climate change and development 

The  relationship  between  the  use  of  natural  resources  and  economic  development  is 
complex,  primarily  because  it  is  difficult  to  establish  the  causal  links  between 
economic  growth,  environmental  degradation  and  poverty  alleviation  (Dasgupta, 
2009).  On  one  hand,  economic  growth  has  caused  environmental  degradation,  with 
overexploitation  of  natural  resources  and  the  collapse  of  many  ecosystems.    On  the 
other  hand,  it  has  brought  about  improvements  in  the  quality  of  a  number  of 
environmental resources, such as better access to water and sanitation services.  

The same difficulties apply when analysing the links between climate change (with its 
impacts on natural and socio-economic systems) and development. Nonetheless, it is 
widely  accepted  that  “climate  change  impacts  can  put  development  goals,  such  as 
increasing  the  rate  of  economic  growth,  reducing  poverty,  improving  access  to 
education, bettering child health, combating disease, and sustaining the environment, 
at risk” (USAID, 2014: page 10). 

The impacts of climate change effects on development have been analysed in several 
academic  studies.  A  first  strand  of  literature  focuses  on  the  impacts  on  economic 
growth.  A  number  of  studies  have  found  that  natural  disasters  have  adverse 
macroeconomic  impacts.    Macroeconomic  variables,  particularly  GDP,  are  the  main 
focus  of  this  strand  of  research.  In  particular,  “higher  annual  temperature  and 
declining  rainfall  both  affected  economic  growth.  It  is  estimated  that  a  1°C  warming 
reduces income in the long run between 0.5% and 3.8% “(Dell et al., 2009; Horowitz, 
2009).  Looking  at  extreme  events,  as  opposed  to  slow  changes  in  temperature 
patterns,  similar  conclusions  could  be  drawn.  According  to  Radatz  (2009),  extreme 
climate events are associated with 2% and 4% declines in  GDP in  the year following 
the  event.  The  difference  between  short-  and  long-term  impacts  may  be  due  to 
adaptation measures. 

The  second  strand  of  literature  focuses  on  the  effects  of  climate  change  on  poverty, 
showing  compelling  evidence  that  the  poor  are  most  seriously  affected  by  climate 
shocks.    Empirical  data  from  Munic  RE  (2014)  support  these  conclusions,  indicating 
that  low-income  and  lower-middle-income  countries  account  for  85%  of  all  disaster 
fatalities. Moreover,  many countries  at highest projected future poverty risk are also 
those  with  the  lowest  level  of  risk  preparedness  (Shepherd  et  al.,  2013).  Therefore, 
climate and disaster resilient development has been indicated as central to the global 
goal of ending poverty and promoting shared prosperity (World Bank, 2013; 2014). 

23 

 
 
 
 
Therefore,  there  is  an  urgent  need  to  integrate  climate  considerations  into 
development  policy-making.  This  could  create  a  win-win  outcome,  if  development 
ensures  climate  resilience,  and  improved  resilience  supports  the  achievement  of 
development objectives.  

3.2 Climate Resilient Development 

Mochizuki  et  al.  (2014)  argue  that  the  focus  of  academic  research  should  shift  away 
from  analysing  the  links  between  climate  change  impacts  and  economic  growth  and 
towards  a  wider  perspective.  In  their  estimation,  the  relevant  policy  question 
becomes:  “what  kind  of  development  will  foster  our  ability  to  proactively  manage 
natural  disasters  risk  over  time  and  how  can  we  make  the  most  of  pre-and  post-
disaster  opportunities  for  interventions  so  that  societies  may  build  resilience  and 
adaptive capacity over the long-run?’’ (p. 49). 

In our opinion, this research question can be addressed by referring to the concept of 
climate  resilient  development.  “Climate-resilient  development  is  about  adding 
considerations  of  climate  variability  and  climate  change  to  development  decision-
making  in  order  to  ensure  that  progress  toward  development  goals  now  includes 
consideration of climate impacts” (USAID, 2014). In a recent report, the World Bank 
(2014) notes that, in order to end global poverty, attention should be paid not just to 
growth,  but  to  the  type  of  growth  that  increases  returns  to  assets  held  by  the  poor. 
This  report  also  points  out  that  equity  is  crucial  to  ensuring  that  poverty  reduction 
goals  are  achieved,  as  the  closer  countries  are  to  these  goals  the  more  difficult  it 
becomes to achieve these.  

The consequences of adopting this wider perspective are twofold.  

First of all, from an analytical and policy perspective, the focus should be on the wider 
impacts of climate change, not just economic growth.  

This  is  advocated  by  scholars  who  embrace  development  paradigms  that  focus 
primarily on human wellbeing and freedom.  

From this perspective, climate change is seen as a possible constraint to the rights of 
individuals to enjoy the freedom to meet their needs including energy, food and water 
access,  health  services,  education,  political  rights,  etc.  The  implications  are  that 
climate  change  policies  should  be  embedded  in  development  policies,  not  just  to 
ensure economic growth, but also to include land resource management, and energy 
and  water  access  and  affordability  (Halsnæs  and  Verhagen,  2007).  Moreover,  these 
policies  should  take  future  climate  change  effects  into  account.  From  this  viewpoint, 
climate  resilient  development  (OECD,  2014:  p.  20)  occurs  when  societies  pursue 
economic  growth,  poverty  reduction  and  other  development  objectives,  and 
systematically  integrate  current  and  future  climate  risks  into  strategies  for 
development.  Whilst  vision  and  commitment  are  important,  integrating  climate 
resilience into planning processes is essential (OECD, 2014).  

24 

 
 
 
 
From  an  analytical  perspective,  more  attention  should  be  paid  to  risk,  resilience  and 
adaptive  capacity,  as  opposed  to  disaster  damage.  As  argued  by  Dow  and  Berkhout 
(2014),  “serious  effort  should  be  made  to  reframe  the  problem  of  losses  faced  by 
vulnerable  groups  and  regions  in  order  to  be  able  to  move  forward  to  address 
emerging losses and damages3”. They argue that a better understanding is needed of 
the  limits  to  the  capacity  of  groups,  sectors  and  regions  to  adapt  to  the  impacts  of 
climate variability and change. 

The  diagram  in  Figure  2  shows  the  building  blocks  of  climate  resilient  development. 
This diagram will guide us in setting criteria and selecting indicators. 

Figure 2 – Building blocks of climate resilient development: summarising a 
theoretical framework 

Source: Adapted from OECD, 2014. 

3 In their definition, a loss is what is destroyed, whilst damage refers to something that can be recovered over time. 

25 

 
 
 
 
 
 
 
 
 
                                                        
4. Use of metrics and indicators for assessing climate risk, 

resilience and vulnerability 

As  noted  by  Fünfgeld  and  McEvoy  (2011),  a  variety  of  frameworks  have  been 
developed for the assessment of climate impacts, vulnerability and adaptation.  

According  to  Surminski  et  al  (2013)  any  assessment  of  loss  and  damage  resulting 
from climate change and general climate risk needs to incorporate information about: 

• 

the  climate  hazard,  including  current  climate  variability  and  future,  long-term 
projections;  

•  vulnerability and exposure; 
•  how  adaptation  and  mitigation  policies  can  help  deal  with  climate  change 

impacts.  

Before  discussing  rationale,  issues  and  approaches  to  measure  vulnerability  and 
adaptation,  it  is  worthwhile  to  clarify  the  terms  used  in  this  report.  According  to  the 
IPCC (2014): 

-  A  measure  is  the  amount  or  degree  of  something,  e.g.  a  value  describing  the 
current  state  of  a  variable,  such  as  the  number  of  fatalities  following  a  flood 
event. This is synonymous with an indicator.  

-  The  term  metric  refers  to  a  group  of  values  (measures)  that  taken  together 

give an indication of the progress towards a desired state. 

According  to  this  terminology,  we  use  metrics  to  understand  vulnerability  or 
adaptation, which are made up of several components, captured by indicators.  

In  this  report  we  refer  to  “assessment”  instead  of  “measurement”.  Hinkel  (2011) 
argues  that  since  vulnerability  is  not  an  observable  phenomenon,  it  cannot  be 
measured and should simply be made operational. In order to do that, it is suggested 
providing an operational definition, i.e. a method for linking it to observable concepts 
(he uses the term “methodology of a vulnerability assessment”).   

Box 1- Types of metrics 

Indicators can measure inputs, processes, outputs, and outcomes.  

Input indicators measure resources, both human and financial, devoted to a 
particular programme or intervention (e.g. number of workers). Input indicators can 
also include measures of characteristics of target populations (e.g. number of clients 
eligible for a programme).  

Process indicators measure ways in which services and goods are provided (e.g. 
error rates).  

Output indicators measure the quantity of goods and services produced and the 
efficiency of production (e.g. number of people served, speed of response to reports 
of abuse).  

Outcome indicators measure the broader results achieved through the provision of 
goods and services. 

These indicators can exist at various levels: population, agency, and programme. 
Population-level indicators measure changes in the condition or well-being of 
children, families, or communities (e.g. teen pregnancy rate, infant mortality rate). 

26 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Three  approaches  can  be  followed  for  the  development  of  indicators,  namely  the 
deductive, inductive and normative (expert judgement) approaches (Hinkel, 2011). 

Deduction  uses  available  scientific  knowledge  in  the  form  of  frameworks,  theories  or 
models  about  the  vulnerable  system.  These  give  an  indication  of  variables  that 
potentially determine vulnerability, but cannot be used for aggregation, as they do not 
explain  the  links  between  vulnerability  and  its  causes.  The  only  deductive  argument 
that  can  be  used  for  aggregation  purposes  is  expert  judgement  (see  below).  An 
example  of  this  approach  is  given  by  determinants  of  adaptive  capacity  to  climate 
change determined  by Yohe and Moss (2000), the IPCC (2014) and  the EEA (2008), 
mentioned above. 

“Induction  uses  data  for  building  statistical  models  that  explain  observed  harm 
through  some  indicating  variables”  (Brooks  et  al.,  2005:152).  The  main  limitation  of 
this  approach  is  that  it  works  with  few  variables  and  insufficient  data,  so  they  are 
applicable  to  local  analyses  only.  By  showing  statistical  relationships,  it  does  not 
explain  the  links  between  the causes  and  impact  of  vulnerability.  An  example  of  this 
approach is given by the application of principal component analysis (PCA) to reduce 
the number of causes, for example to define a Social Vulnerability Index (Cutter et al., 
2003).  

Finally,  normative  arguments  use  value  judgement  for  selecting  and  aggregating 
variables.  For  climate  risk  assessment  purposes,  the  normative  approach  is  used  to 
select  exposure  variables  and  for  aggregating  variables  with  equal  weights.  This 
approach is used by, for example, the Human Development Index (HDI).  

4.1 Issues in Adaptation and Risk Assessment 

We briefly analyse here the  main issues and difficulties that analysts face when they 
have to assess climate risk and adaptation strategies. 

As  already  pointed  out,  climate  resilient  development  is  essentially  a  locally  driven 
process,  which  should  take  into  account  global  dynamics.  Climate  change  is  a  global 
problem  that  requires  coordinated  adaptation  strategies  at  the  local  level  (Ayres, 
2011).  

From an analytical point of view, any related analyses need to combine two different 
types  of  information:  the  data  provided  by  global  scenarios  on  climate  risk,  often 
produced  by  expert  knowledge  outside  the  area  impacted  by  hazards,  and  on  the 
other,  evidence  to  inform  the  definition  of  adaptation  strategies  at  national,  regional 
or local level.  

There  are  two  difficulties  arising  from  the  need  to  combine  information  produced  at 
different levels: 

- 

- 

the  conclusions  of  the  analyses  conducted  at  national  level  do  not  hold  once 
these are disaggregated to a different scale; 
local  institutions  often  either  do  not  have  access  to  relevant  information  or  do 
not have the tools to understand and translate it into practical actions.  

27 

 
 
 
 
Even  if  these  difficulties  can  be  overcome,  a  further  complication  is  caused  by  the 
shifting  baseline  (Brooks  et  al.,  2011),  which  arises  due  to  the  fact  that  adaptation 
occurs  under  changing  climatic  conditions.  Any  adaptation  effort  therefore  becomes 
more difficult to assess, and conclusions on the evolution of key indicators over time 
should  be  treated  with  caution.  So,  for  example,  a  stable  exposure  indicator  (e.g. 
fatality  rate)  can  be  interpreted  either  in  a  positive  or  negative  way.  It  will  be  an 
improvement  in  all  cases  where  changing  climate  conditions  might  negatively  affect 
the fatality rate over time, whilst it will signal ineffective practices in the case of stable 
climate change conditions.   

Indicator-based  evaluation  therefore  needs  to  be  supported  by  monitoring  climatic 
and other trends (such as environmental and economic conditions) so that adaptation 
action  can  be  attributed  correctly.  This  requires  the  normalisation  of  evaluation 
metrics with respect to changing climatic and environmental baselines. 

This issue is particularly important given that development pathways can contribute to 
or mitigate climate change impacts.  

Another  important  issue  is  that  of  circular  arguments,  which  is  related  to  the 
application of inductive approaches to identify resilience indicators (Béné, 2013).  

The problem here lies in the fact that this method identifies variables related to social, 
environmental  and  economic  characteristics  as  the  building  blocks  of  resilience,  and 
assumes that these are proxies for measuring resilience.  

Bené concludes that “this inductive process leads to circular analyses where resilience 
indices are first built from an a priori identified combination of […] indicators and then 
used to evaluate the impact of resilience interventions […], leading to circular (or non-
independent analyses)”. 

In order to avoid this potential pitfall, it is suggested that metrics be identified which 
are independent of the system characteristics. One example is given by the total costs 
of extreme events (Béné, 2013; Carter et al., 2007).  

We conclude that vulnerability is one of the inherent factors that should be taken into 
consideration when selecting climate resilience indicators, especially for aid allocation. 

4.2 Vulnerability Assessment: insights from the literature 

Assessments  of  vulnerability  to  climate  change  aim  to  inform  the  development  of 
policies that reduce the risks associated with climate change. All studies reviewed for 
this analysis use an empirical approach to selecting indicators, whereby indicators are 
chosen subjectively by the authors on the basis of “assumptions about the factors and 
processes leading to vulnerability” (Brooks et al., 2005). 

Three broad uses of vulnerability assessments have been identified (IPCC, 2014).The 
first is to understand the need for adaptation. In this respect, Hinkel (2011) identifies 
the reasons for assessing vulnerability, namely: (i) identification of mitigation targets; 
identification  of    particularly  vulnerable  people,  regions  or  sectors  to  allocate 

28 

 
 
 
 
adaptation  funds;  (ii)  raising  awareness  about  climate  change;  (iii)  monitoring  the 
performance  of  adaptation  policy;  and  (iv)  scientific  research.  Within  this  context 
indicators  can  only  be  used  to  identify  particularly  vulnerable  people,  regions  or 
sectors.  

The  second  and  third  uses  are  both  related  to  implementation  of  adaptation  actions, 
i.e.  tracking  their  progress  or  measuring  effectiveness.  The  literature  on  assessing 
vulnerability  has  evolved  over  the  past  30  years.  It  is  thus  possible  to  draw  some 
useful insights, by considering the progress made and the criticism received.  

Vulnerability assessments (VAs) have so far been successful in helping to understand 
the  different  social  and  economic  groups  and  sectors  that  will  be  most  harmed  by 
climate-related hazards (i.e. ‘who is vulnerable’), and provide evidence to support the 
understanding of risks to human and environmental systems posed by climate-related 
hazards. In other words, VAs have been very successful in identifying and describing 
the problem. 

However, while there are agreed indicators to measure the impact of climate change, 
there  are  no  agreed  metrics  to  describe  vulnerability  as  it  is  not  directly  observable 
(e.g. relating to crop yields or agricultural income) (Fellmann, 2012).  

As  already  pointed  out,  vulnerability  is  place-based  and  context-specific,  and 
consequently  the  significance  of  particular  indicators  can  vary  from  region  to  region, 
especially depending on the specific socio-economic context.  

This is reflected by the indicators identified in the grey and peer reviewed literature.  

There are two main criticisms of current VA practices: the limited understanding of the 
dynamic  factors  that  influence  vulnerability  and  adaptive  capacity  (IPCC,  2014),  and 
the  fact  that  the  results  and  conclusions  of  existing  VAs  depend  heavily  on  the  data 
and the analytical framework used.  

First of all, VAs are deemed to be static, i.e. portraying a snapshot of current levels of 
hazards within a given context, without considering future possibilities (Preston et al., 
2011;  Hinkel,  2011).  This  is  a  major  limitation  as  it  is  widely  recognised  that  past 
trends cannot be used to predict future hazards (Royal Society, 2014).  

As  such,  they  cannot  inform  adaptation  processes  to  deliver  actual  change,  and  in 
many cases are unable to provide policy insights. 

Secondly, current VAs focus on the inherent nature of vulnerability (Kahn, 2011), and 
seem  to  neglect  the  dynamic  and  structural  factors  that  shape  the  risks  that  people 
face,  i.e.  what  makes  them  vulnerable.  Therefore,  as  well  as  identifying  vulnerable 
groups,  VAs  should  make  it  possible  to  understand  the  factors  that  produce 
vulnerability, and shed some light on policies needed to reduce vulnerability.  

More  generally,  many  VAs  lack  a  consistent  methodology  (IPCC,  2014),  or  fail  to 
explain their theoretical framework in a satisfactory manner (Eriksen and Kelly, 2007). 

Most importantly, VAs largely rely upon social and economic information at a range of 
geopolitical  scales,  (i.e.  income,  poverty  and  resource  access).  The  evidence  that  is 
used  as  input  into  an  assessment  ultimately  influences  vulnerability  estimates,  their 

29 

 
 
relevance and how they should be interpreted (Preston, 2013). VAs are predominantly 
dependent  upon  secondary  data  sources  for  both  biophysical  and  socio-economic 
dimensions of vulnerability. 

Moreover,  they  cannot  satisfactorily  incorporate  uncertainty.  Analytical  mechanisms 
for dealing with uncertainty are not developed, due to the often qualitative or at least 
semi-quantitative nature of many VAs, as well as the normative judgments they entail 
(Preston,  2012).  Moreover,  input  information  (such  as  projected  climate  related 
hazards impacts) is often highly uncertain.  

Finally, their policy relevance is limited in many cases. As noted by Preston (2012: p. 
47)  “the  tendency  for  vulnerability  assessments  to  be  conducted  as  technical, 
academic exercises rather than participatory, stakeholder-driven exercises means that 
‘success’ is often defined by investigator reputation and academic publications rather 
than  tangible  benefits  for  stakeholders  and  social  return  on  investment”.  It  is  widely 
recognised that stakeholders’ engagement is limited and this obviously limits learning 
possibilities.  

From  the  above,  it  is  clear  that  the  main  analytical  challenge  is  to  include  complex 
socio-ecological  interactions,  and  to  explore  the  use  of  participatory  approaches  and 
factors  in  developing  adaptation  and  mitigation  policies  (Tschakert  et  al.,  2013),  so 
that VAs can support the definition of climate resilient development.  

Moreover,  considering  the  descriptive  focus  on  the  current  level  of  impacts  of  VAs 
carried out so far, it is of critical importance to understand adaptation processes and 
outcomes,  as  many  VA  outcomes  are  used  for  policy  decision-making  or  for  funding 
decisions with regard to adaptation priorities. 

30 

 
 
 
 
5. Indicators selection 

The purpose of this study is to identify and recommend a list of fit-for-purpose climate 
resilient  development 
the  approach 
indicators.  The  methods  used 
recommended by the OECD and the JRC (2008) for building composite indicators. The 
guidance identifies 10 steps to define composite indicators (Box 2). The first section of 
this  report  covers  the  theoretical  framework.  This  second  section  explores  the  main 
issue  related  to  the  definition  and  selection  of  indicators  with  a  case  on  the 
aggregation of such indicators. 

follow 

As already pointed out to select fit-for-purpose climate resilient indicators, we adopted 
the following objectives (OECD and JRC, 2008): 

-  To check the quality of the available indicators. 
-  To discuss the strengths and weaknesses of each selected indicator. 
-  To  create  a  summary  table  of  data  characteristics,  e.g.  availability  (across 

place, time), source, type (hard or soft, input or output, process). 

The quality of indicators has been checked in terms of robustness against the relevant 
literature and criteria. This analysis also made it possible to identify the strengths and 
weaknesses of each indicator. The final list is dependent on data availability. 

31 

 
 
 
 
 
 
Box 2: Index (Composite indicator), definitions 

In general terms, an index (composite indicator) provides an overall assessment of changes in 
the  subject  matter  (be  it  economic,  environmental  or  social  conditions),  which  can  be  easily 
interpreted  and  communicated  to  the  intended  target  audience.  It  is  useful  for  indicating 
progress  in  achieving  goals,  and  for  benchmarking  or  policy-making  purposes  (JRC/OECD, 
2008).  

According  to  JRC/OECD  (2008),  ten  main  issues  should  be  addressed  to  build  a  composite 
indicator: 

1)  The  theoretical  framework  constitutes  the  basis  for  the  selection  and  combination  of 
indicators  under  the  fit-for-purpose  principle.  Ideally,  the  composite  indicator,  as  well  as  the 
choice  of  indicators,  fully  reflects  its  objectives.  Key  elements  of  this  framework  are:  (i) 
definition  of  the  concept,  (ii)  the  subgroups  related  to  multi-dimensional  concepts;  (iii) 
identification of selection criteria. 

2) Variables selection. High-quality data is not always available, so it must be accepted that 
at  times  ‘second-best’  or  'proxy'  indicators  have  to  be  used  as  component  indicators.  This 
should  be  done  on  the  basis  of  relevance,  analytical  soundness,  measurability,  country 
coverage, and underlying relationships. However, the lack or the scarcity of quantitative data 
meeting all the above mentioned requirements can be overcome by the use of qualitative data.  

3)  Imputation  of  missing  data.  Consideration  should  be  given  to  different  approaches  for 
imputing missing values using statistical and technical knowledge about environmental themes 
to  be  combined.  Extreme  values  should  be  examined  as  they  can  become  unintended 
benchmarks. 

4) Multivariate analysis will explain the methodological choices and provide insights into the 
structure  of  the  indicators  and  the  stability  of  the  dataset.  An  exploratory  analysis  should 
investigate  the  overall  structure  of  the  indicators,  assess  the  suitability  of  the  dataset  and 
explain the methodological choices, e.g. weighting, aggregation. 

5)  Normalisation  is  carried  out  to  make  the  indicators  comparable.  Attention  needs  to  be 
paid  to  extreme  values  which  can  influence  subsequent  steps  in  the  process  of  building  a 
composite indicator. Skewed data should also be identified and accounted for. 

6)  Weighting  and  aggregation  is  carried  out  in  line  with  the  theoretical  framework. 
Correlation and compensation among indicators need to be considered and either corrected for 
or treated as features of the phenomenon that needs to remain in the analysis. 

7)  Robustness  and  sensitivity  tests  can  lead  to  decisions  to  exclude  certain  indicators  or 
use another technique for completing the datasets.  The robustness of the composite indicator 
should  be  analysed  in  terms  of,  for  example,  the  mechanism  for  including  or  excluding 
component indicators, the normalisation scheme, the imputation of missing data, the choice of 
weights and the aggregation method. 

8)  Links  to  other  variables.  Links  to  other  composite  or  aggregate  indicators  should  be 
ascertained.  Attempts  should  be  made  to  correlate  the  composite  indicator  with  other 
published indicators, as well as to identify links through regression analyses. 

9)  Back  to  the  real  data. To improve transparency, it should be possible to decompose the 
indicator into its underlying values. 

10) Presentation  and Visualisation. Composite indicators can be visualised or presented in 
a number of different ways, which can influence how they are interpreted and understood. 

32 

 
 
 
 
 
5.1 Criteria for indicators selection 

To identify criteria for indicators selection, we will first present general criteria, which 
are  valid  for  all  indicators  (table  5),  and  then  those  pertinent  mainly  to  resilience 
indicators. 

Table 5 – Criteria for selection of indicators 

Source: IPCC (2014): chapter 14, page 885. 

33 

 
 
 
 
 
 
These general criteria are valid for any assessment study, and are useful for checking 
whether the screened indicators are robust.  

However,  to  ensure  consistency  and  theoretical  robustness  we  first  need  to  consider 
the purposes and aim of the study. Secondly, the specific criteria relevant to selected 
indicators for climate resilient development will be analysed.  

Whilst  we  are  not  interested  in  monitoring  the  implementation  of  adaptation  or 
mitigation  actions,  the  indicators  should  ensure  that  we  identify  the  most  vulnerable 
sectors or social groups - we understand when action  is needed, we target the most 
cost-effective  opportunities  and  we  minimise  losses  and  damages  from  extreme 
events.   

Methods  and  frameworks  for  assessing  vulnerability  should  also  address  the 
determinants  of  adaptive  capacity  in  order  to  examine  the  potential  responses  of  a 
system to climate variability and change.  

In  some  quantitative  approaches,  the  indicators  used  are  related  to  factors  that  are 
deemed  to  increase  adaptive  capacity  (e.g.  national  economic  capacity,  human 
resources, and environmental capacities). 

 Other  studies  include  indicators  that  can  provide  information  related  to  the 
conditions,  processes  and  structures  that  promote  or  constrain  adaptive  capacity 
(EEA, 2008).  

In this respect, we will also refer to the specific criteria identified by Schneider et al. 
(2007) for selecting key impacts.  

They recommend that the following criteria be referred to: 

timing of impacts;  

  magnitude of impacts (scale and  intensity);  
 
  persistence and reversibility of impacts; 
 
  potential for adaptation; 
  distributional aspects of impacts and vulnerabilities across regions and population 

likelihood (estimates of uncertainty) of impacts and vulnerabilities; 

groups; 
importance of the natural systems at risk. 

 

The  main  focus  of  this  exercise  will  not  be  the  selection  of  indicators  based  on 
determinants  of  vulnerability  which,  as  discussed  above,  are  considered  as  given. 
Instead,  we  will  emphasise  the  importance  of  enabling  people  to  become  more 
resilient  to  climate  hazards,  without  jeopardising  development  opportunities  and 
without compromising their natural capital.  

34 

 
 
 
 
 
Therefore, for the purpose of this study, we will also consider these additional criteria, 
more  focused  on  the  processes  (adaptation  and  mitigation  strategies)  and  outcomes 
(climate resilient development and protection of natural capital): 

  mitigation  capacity:  when  adaptation  is  not  feasible  or  future  impacts  will  be 
excessive,  then  it  is  imperative  to  implement  mitigation  actions  immediately. 
Some  adaptation  options  also  present  mitigation  benefits.  Win-win 
opportunities exist, especially in the agricultural sector.  

  environmental  implications:  adaptation  and  mitigation  actions  should  take  into 
account their consequences on the natural environment, and work with natural 
processes as much as possible.  
impacts on development opportunities: adaptation and mitigation actions could 
represent opportunities in term of economic growth and social development, as 
discussed above.  

 

  economic  efficiency:  any  funding  decision  should  consider  effectiveness  and 
efficiency  as  key  criteria  for  allocating  scarce  resources.  As  discussed  above, 
no-  or  low-regret  options  and  other  actions  yielding  net  benefits  are  already 
available. These should be explored and implemented sooner rather than later. 

Finally,  it should be  noted that the  analysis will be carried out  on the national  scale, 
i.e. indicators will be developed at country level. As noted by Füssel (2010), this scale 
is the most appropriate for assessment purposes, when funding is the main objective 
of the study.  

That said, the indicators will be identified in such a way that they can also be applied 
at a smaller scale by local stakeholders, to ensure local participation and involvement. 
In many cases information at the national scale is not available, but can be collected 
for specific detailed case study analyses.  

This is consistent with the goal of developing a platform that stakeholders can use for 
climate resilient assessment purposes.  

We  aim  to  develop  climate  resilient  indicators,  therefore  these  should  be  precise, 
robust,  transparent  and  objective;  they  should  also  be  simple,  clear  and  easy  to 
understand. 

5.2 Fit-for-purpose indicators: preliminary list 

A  list  of  country-level  indicators  with  a  global  coverage  has  been  compiled  by 
reviewing  the  relevant  literature  on  climate  change,  development,  disaster  risk  and 
the application of vulnerability and resilience indicators.  

The  main  focus  has  been  on  peer-reviewed  contributions,  and  on  indicators  used  to 
compute global development, vulnerability and risk indices.  

In  particular,  with  respect  to  human  development,  the  Human  Development  Index 
(HDI)  and  its  indicators,  the  current  Millennium  Development  Goals  (MDGs)  and 
proposed post-2015 Sustainable Development Goals (SDGs) were considered.  

35 

 
 
  
 
 
Other indicators used for international assessment and monitoring purposes,  such as 
those used for the Adaptation Fund and the Hyogo Assessment Framework (both the 
current ones and the post-2015 proposals), have also been included.  

Moreover,  further  indicators  were  identified  by  looking  at  the  relevant  literature  on 
determinants  of  vulnerability  and  adaptive  capacity,  and  on  social  and  economic 
vulnerability.  

Finally, the following global indices were reviewed, and relevant indicators considered: 

1. 

2. 

3. 

4. 

5. 

The  World  Risk  Index  (WRI) 4  -  developed  by  the  UN  University  and  the 
University of Bonn. Its objective is to measure vulnerability to extreme natural 
events.  The  Index  is  composed  of  four  main  indicators:  exposure  to  natural 
hazards  such  as  earthquakes,  cyclones,  floods,  droughts  and  sea  level  rise; 
susceptibility  depending  on  infrastructure,  nutrition,  housing  conditions  and 
economic  framework  conditions;  coping  capacities  determined  by  governance, 
preparedness  and  early  warning,  healthcare,  and  social  and  material  security; 
and adaptive capacities relating to future natural events and climate change. It 
covers 171 countries. The latest update was made in 2014. 
The  Index  for  Risk  Management  (INFORM)  -  developed  by  the  JRC  in 
partnership  with  DG  ECHO  and  several  international  organisations.  The  most 
recent version, from 2015, considers data for 191 countries. Its objectives are 
to  understand  the  drivers  of  humanitarian  risk  and  to  help  rank  countries 
according  to  the  likelihood  of  need  for  international  assistance  in  the  near 
future.  
The  University  of  Notre  Dame’s  Global  Adaptation  Index  (ND-GAIN)  aims  to 
help  businesses  and  the  public  sector  to  better  prioritise  investments  by 
providing  information  on  a  country's  vulnerability  to  climate  change  and  other 
global hazards. In its 2014 version, it considers 178 countries. 
The  Environmental  Vulnerability  Index  (EVI) 5  uses  50  indicators  to  assess 
environmental  vulnerability.  It  was  developed  by  the  United  Nations 
Environment Programme (UNEP). Unfortunately, it was last updated in 2004.  
The  Germanwatch  Global  Climate  Risk  Index  (CRI)  analyses  to  what  extent 
countries  have  been  affected  by  the  impacts  of  weather-related  loss  events 
(storms,  floods,  heat  waves,  etc.),  using  four  indicators.  The  2015  version 
considers information from 1994 to 2013, and for 2013.  

As a source of information, we reviewed the Environmental Performance Index (EPI), 
developed  by  Yale  University,  which  analyses  the  environmental  performance  of  178 
countries  regarding  environmental  health  and  ecosystem  vitality.  Only  pertinent 
indicators were considered.  

4 http://www.ehs.unu.edu/article/read/world-risk-report-2014  
5 http://www.vulnerabilityindex.net/EVI_Indicators.html  

36 

 
 
 
 
 
 
                                                        
By  also  considering  the  relevant  literature,  a  total  of  269  indicators  and  17  indexes 
were  identified  (Table  I  and  Table  II  of  Annex  IV)  and  classified  under  the  following 
headings: 

  Natural  hazards  -  the  occurrence  of  climate-related  and  weather-driven 
hazards, such as flooding, storms, droughts, heat waves, and sea-level rise. 
  Exposure  - the consequences for people and assets of the occurrence of such 

events.  

  Vulnerability  -  the  socio-economic  factors  that  are  likely  to  influence 
vulnerability,  including  indicators  on  sensitivity,  which  cover  sectors  that  are 
dependent on natural resources, such as agriculture.  

  Adaptive  capacity  -  the  features  that  determine  the  ability  of  a  local 
community  (including  ecosystem  services)  to  adapt.  It  includes  also  indicators 
on  coping  capacity,  which  is  considered  as  the  ability  of  a  country  to  cope 
with disasters in terms of formal, organised activities. 

  Mitigation  capacity  -  the  factors  that  ease  the  implementation  of  actions 

taken to reduce greenhouse gases. 

  Development  -  economic  and  social  factors  that  make  an  economy  more 
resilient  to  natural  hazards,  thereby  reducing  the  impacts  of  climate  related 
events.  These  indicators  also  describe  the  socio-economic  conditions  that 
should be met to ensure that development is climate resilient. 

After considering all of the reviewed indicators and checking their compliance with the 
criteria  summarised  in  the  Tables  of  Annex  III,  a  final  list  of  indicators  for  a  web 
knowledge platform for climate resilient development was compiled on the basis of the 
relevance of the proposed indicators as well as of data availability.  

Data sources quoted in the original study  were checked to ensure that  the most up-
to-date information is used.  

74  indicators  were  excluded  due  to  data  availability  issues,  because  data  were  not 
available, or were only available for some countries or only for a few years.  

Ad  hoc  surveys  or  ex  post  project  assessments  would  be  necessary  for  several 
indicators, so they were excluded as data might become available as reporting efforts 
progress,  especially  with  regard  to  the  Hyogo  Framework  for  Action  (HFA)  or  the 
proposed Sustainable Development Goals.  

Many of these indicators may be potentially useful in the future, as more information 
may  become  available  or  be  collected  at  the  local  scale.  As  some  indicators  are 
redundant  (i.e.  they  capture  similar  aspects),  a  second  check  was  carried  out  to 
ensure that there are no duplications.  

On  the  basis  of  indicator  redundancy,  102  indicators  were  shortlisted.  The  criteria 
used  to  choose  between  similar  indicators  included  the  quality  of  available  data  and 
the  fact  that  a  given  indicator  had  already  been  used  for  global  climate  risk 
assessments. 

37 

 
 
 
We have selected a  final  list of  indicators  which satisfy the following criteria: reliable 
and open-source, consistent, with global coverage and based on observed data which 
are in the public domain. 

The  next  section  will  illustrate  the  application  of  the  theoretical  framework  described 
in the first section by building a composite indicator for climate resilient development. 

6. A Case Study 

All  the  issues  highlighted  by  the  theoretical  framework  described  in  this  report  are 
extremely  urgent  and  relevant,  but  integrating  all  of  them  into  a  single  index 
represents  a  major  challenge.    This  section  proposes  a  case  study  for  building  an 
index  to  support  climate  resilient  development  by  identifying  the  countries  that  are 
most  vulnerable  to  climate  change.  The  objective  of  the  index  will  be  to  rank  the 
countries based on the following issues: climate-related and weather-driven hazards, 
vulnerability  to  climate  change,  adaptive  capacity,  climate  change  mitigation  action, 
disaster  risk,  and  a  (political)  commitment  to  respond  to  climate  change  through 
poverty reduction.  

The  sample  of  the  countries  includes  Least  Developed  Countries  (LDC),  Small  Island 
Developing  States  (SIDS),  low-income  countries  and  lower-middle-income  countries, 
and  territories  from  the  OECD’s  Development  Assistance  Committee  (DAC)  list  of 
Official Development Assistance (ODA) Recipients (excluding Tokelau, Singapore, and 
Bahamas) (Table I of Annex II).   

In line with the theoretical framework and the screening process described in the first 
section of this report, we have selected 32 fit-for-purpose country-level indicators that 
cover  social,  economic  and  environmental  aspects  of  each  of  the  components  under 
which they have been classified (Table 6). 

A  specific  focus  on  gender  is  proposed  for  the  adaptive  capacity  component.  This 
approach  is  coherent  with  the  recognised  role  of  the  gender  equality  in  reducing 
poverty  and  fighting  against  climate  change  (Millennium  Development  Goals,  Post-
2015 SDGs, UNFCCC COP 18 and COP19).  

The tables in Annex I provide detailed  information describing each indicator  in terms 
of  relevance,  measuring  unit,  indicator  creation  method,  data  source,  periodicity, 
trend, data type, and  statistics. This information is complemented by maps showing 
the geographical distribution of each indicator in the sample of the countries analysed 
in this case study and for the latest available year. 

38 

 
 
 
 
 
 
Table 6 - Components and indicators considered to build an index 

Component 

N.  Indicator 

Natural Hazards 

Exposure 

Vulnerability 

1 
2 
3 
4 
5 
6 
7 

8 
9 

Drought Events - the past 20 years (cumulative) 
Flood Events - the past 20 years (cumulative) 
Storm Events - the past 20 years (cumulative) 
Population density (people per sq. km of land area) 
Refugees per place of residence (% of population) 
Internally displaced (% of population) 
Proportion of Population in Low Elevation Coastal Zones 
(LECZ) 

Gini index 
Poverty headcount ratio at $1.25 a day (PPP) (% of 
population) 

10  Age dependency ratio (% of working-age population) 
11  Agriculture, value added (% of GDP) 
12  Forest area (% of land area) 
13  Water dependency ratio 

Adaptive   14  Ecosystem vitality: Agriculture 

Adaptive/ 
Gender 

Coping 

15  Manufacturing, value added (% of GDP) 
16  ODA/DAC – Adaptive Capacity as principal 
17  Access to Literacy 
18  Share of female representatives in the national 

parliament 

19  Access to bank accounts 
20 

Improved sanitation facilities (% of population with 
access) 

21  Hospital beds (per 1 000 people) 
22  Physicians (per 1 000 people) 
23  Nurses and midwives (per 1 000 people) 
24  Mobile phone subscriptions (per 100 people)  

Mitigation  25  CO2 emissions (kg per PPP $ of GDP) 

26  Participation in UNFCCC fora  - mitigation actions 

y
t
i
c
a
p
a
C

Development 

27  Life expectancy at birth, total (years) 
28  Literacy rate, adult total (% of people aged 15 and 

above) 
Income Index  -Gross National Income (GNI) 

29 
30  Net ODA received per capita (current US$) 
31  Personal remittances, received (% of GDP) 
32 

Internet users (per 100 people) 

39 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The  treatment  of  missing  data  is  an  important  issue  for  the  calculation  of  the  index. 
However, for this case study we did not treat missing data but, in order to avoid the 0 
value  of  the  final  index  in  relation  to  missing  data,  we  added  0.000001  to  the 
components presenting a null value related to missing data. 

We normalised the data with the max-min formula and aggregated all the indicators of 
each component (hazards, vulnerability and adaptive capacity) by arithmetic average 
at sub component level, as reported in Table 7. 

Table 7 - Normalisation of indicators and aggregation at component level. 

Component 

Indicator 
Normalisation 

Aggregation at sub component level 

Hazards 

Max-Min 

Arithmetic average 

Exposure 

Max-Min 

Arithmetic average 

Vulnerability 

Max-Min 

Arithmetic average 

Capacity 

Development 

Max-Min 

Max-Min 

Arithmetic average 

Arithmetic average 

Subsequently, components were aggregated by applying geometrical (1) and linear 
(2) formulas of aggregation as follows: 

CC-Risk = Hazard * [(Exposure * Vulnerability) / (Capacity * Development)]     (1)  

CC-linear = (Hazard + Exposure + Vulnerability + Capacity + Development) / 5     (2) 

CC Mixed= [(Hazard*Exposure)+ Vulnerability+ Capacity +Development]/4   (3) 

Maps 1, 2 and 3 show the results of these aggregations representing the index scores 
grouped into five categories (very low to very high) by means of the Jenks 
methodology, which consists of minimising the intra-variance group.  

40 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Map 1- Index calculated with geometrical formula of aggregation 

Map2 - Index calculated with linear formula of aggregation 

41 

 
 
 
 
 
 
 
 
 
 
 
 
Map 3 - Index calculated with mixed formula of aggregation. 

The three maps show different results. The geometrical index (Map 1) prioritises the 
countries that apply a climate change risk approach. Countries affected by climate 
and/or weather events receive the highest score (‘very high’).   

The linear aggregation (Map 2) prioritises the countries by attributing the same weight 
to all the components (natural Hazards, exposure, vulnerability, capacity and 
development). The mixed aggregation show results very close the linear aggregation. 

These results are very clear when we analyse the correlation of the scores of the each 
index with their components as reported in the table 8.  
It    shows    the  results  of  correlations  between  the  various  scores  and  components 
measured  using  the  Pearson’s  Correlation  Coefficient  (Pearson’s  Product  Moment 
Correlation Coefficient)6. High significant correlation is yellow marked. 

6 It  shows  the  degree  of  linear  dependence  between  two  variables  and  is  defined  as  the  covariance  of  the  two  variables 
divided by  the product of their standard deviations. It gives a value between  +1 and −1 inclusive, where 1 is total positive 
correlation, 0 is no correlation, and −1 is total negative correlation.  

42 

 
 
 
 
 
 
 
 
 
                                                        
 
Table 8 - Correlation between components 

Hazards  Exposure  Vulnerability  Capacity  Development 

0,81 

0,32 

0,42 

0,07 

0,13 

0,70 

0,54 

0,74 

0,78 

0,87 

0,62 

0,80 

0,85 

0,91 

Geometric 
score 

Linear 
score 

Mixed 
score 

The  main  component  for  the  geometric  aggregation  is  the  hazard,  highlighting  a 
climate risk focus as already pointed out. 

In  the  linear  and  mixed  score  confirm  an  over  –  representation  of  the  development 
component. 

The results of this case study show that, although there is some agreement on which 
indicators  should  be  included  in  an  index  for  climate  resilient  development,  a  single 
approach to building a global index for climate resilient development does not exist. 

In  our  case  study  we  used  the  same  components  and  indicators  for  climate  resilient 
development, but from two different policy perspectives. In the first case we adopted 
a climate risk approach with a geometrical formula of aggregation. In the second and 
third cases we applied a development policy approach. 

The differences in ranking are very high, which indicates that an index should address 
a specific policy request with a clear objective.  

This is a first step to building a fit-for-purpose index.  

43 

 
 
 
 
 
 
 
 
 
 
 
Figure 3 - Correlation Matrix: Plots between overall geometrical index and 
components 

Figure 4 - Correlation Matrix: Plots between overall linear index and 
components 

44 

 
 
 
 
 
 
 
 
 
Figure 5 - Correlation Matrix: Plots between overall mixed index and 
components 

45 

 
 
 
 
 
 
 
 
7  Open issues 

7.1 Limits of Datasets on Natural Hazards 

A key issue highlighted by our analysis is the general concern about data availability, 

in terms of the quality, coverage and time span of data, particularly since information 

is  least  reliable  in  developing  countries.  This  lack  of  data  may  lead  to  a  fragmented 

picture of the key components and spatial extent of climate change risk. International 

efforts  to  compile  new  databases  (including  those  on  losses)  should  be  supported, 

based on which the list of indicators could be updated. 

7.2  Including indicators on Monitoring and Evaluation (M&E) 

Two different types of indicators are used to target adaptation and mitigation funding, 

and to monitor and evaluate adaptation and mitigation programmes.  

In  the  first  case  the  evaluation  is  ex  ante,  as  indicators  should  be  able  to  identify 

priority  areas  and  sectors  for  intervention  on  the  basis  of  risk  and  vulnerability,  and 

anticipate the types of actions that are needed to build climate resilient development.  

On  the  other  hand,  M&E  is  an  ex  post  activity,  and  indicators  are  needed  mainly  to 

capture the progress made against objectives.  

Whilst  indicators  used  for  aid  allocation  focus  on  structural  features  of  vulnerability 

and  promote  equal  opportunities  for  more  vulnerable  countries  and  sectors,  those 

used  for  M&E  purposes  will  mainly  cover  the  dynamic  component  of  climate  resilient 

development.  

7.3  Indicators from Earth Observation  

There  is  currently  a  wide  variety  of  well  established,  operational  applications  for 

assessing and monitoring observed climate change impacts and risk factors, based on 

analysis  of  data  from  Earth  Observation  satellites.  A  variety  of  indicators  of  climate 

impacts and risk factors derived from Earth Observations has been identified (Table 8) 

that are suitable both for the ex ante classification of geographical areas  in terms  of 

exposure and vulnerability to climate change, as well as for assessing and monitoring 

the climate impacts and risk factors. 

46 

 
 
 
 
 
 
 
 
Of  the  indicators  derived  from  Earth  Observation  listed  in  Table  9,  the  first  four  (i.e. 

Exposure  to  flooding;  Vulnerability  to  flooding;  Vulnerability  to  coastal  erosion; 

Vulnerability  to  landslides)  are  suitable  for  ex  ante  assessment  of  areas  in  terms  of 

climate  impacts  and  risk.  The  inclusion  of  these  indicators  could  be  investigated 

further. 

Table 9 - Examples of Earth-Observation-derived indicators of climate 
impacts and risk factors. 

Indicator name  
# 
Exposure to flooding 
1 
2  Vulnerability to flooding 

Thematic basis of indicator 
Proximity of settlements to water bodies 
Soil 
settlements 

sealing 

surface  permeability 

/ 

of 

3  Vulnerability to coastal erosion  Density of mangrove plantations 
4  Vulnerability to landslides 
5 
6 
7 

Land cover, soil type & topography 
Area of natural lakes & riverine swamps 
Landscape fragmentation in conservation areas 
Area of staple agricultural crops (e.g. maize) 

agricultural 

Loss of wetlands 
Loss of biodiversity 
Loss 
productivity 

of 

Landscape degradation 

8  Agricultural drought 
9 
10  Deforestation 
11  Forest fire damage 
12  Forest storm damage 

Vegetation condition & surface temperature 
Area of arable land 
Area of contiguous forest cover 
Area of burnt or fire-damaged forest 
Area of contiguous forest cover 

47 

 
 
 
 
 
 
 
8. Conclusion 

This study aims to contribute to the debate on climate change policies and their link to 
development.  We  adopted  a  climate  resilient  perspective  to  understand  how  climate 
change  policy  objectives  can  be  reconciled  with  development  goals  and  to  explore 
win-win  opportunities  given  by  the  integration  of  climate  change  and  poverty 
reduction policies.  

With  this  aim  in  mind,  the  study  has  been  organised  in  two  sections,  namely  the 
definition  of  a  theoretical  framework  to  select  fit-for-purpose  indicators,  and  a  case 
study which involves building an index for climate resilient development. 

We reviewed the main theoretical concepts that characterise the scientific literature on 
climate  risk  and  vulnerability  assessments,  and  identified  climate  resilient  indicators 
accordingly. 

This made  it possible to build  the theoretical foundations for a  newly designed  index 
to  improve  our  understanding  of  the  implications  of  aid  financing  on  reversing 
unsustainable pathways, reducing vulnerability to climate change related hazards, and 
to obtain more equitable outcomes. 

As highlighted by our analysis, climate risk indices have already been developed. The 
novelty  of  our  contribution  lies  in  its  focus  on  the  economic  aspects  of  climate  risk 
assessment,  most  notably  the  concepts  of  loss  and  damage,  the  understanding  of 
factors  that  enhance  economic  resilience,  the  links  between  climate  change  policies 
and  development  (besides  economic  growth)  and  the  acknowledgment  of  the  role  of 
natural capital in pursuing development policies. 

By reviewing grey and peer-reviewed literature, we identified 102 suitable indicators, 
which  have  been  grouped  under  six  components.  These  were  selected  from  a 
preliminary list of 286 indicators, on the basis of general criteria such as validity, data 
availability  and  their  value  in  terms  of  information  potential.  Other  specific  criteria 
were also considered to ensure that the indicators shortlisted are theoretically robust.  

Finally, although we consider all the issues highlighted in this report to be very urgent 
and relevant, it is extremely difficult to  integrate them all into a single index. This is 
supported  by  the  results  of  our  case  study,  which  involved  building  three  climate 
resilient development indices. 

The three case-study climate resilient development indices were built using the same 
components  and  indicators  but  from  two  different  political  perspectives.  The  results 
demonstrate  that,  although  there  is  some  agreement  on  which  indicators  should  be 
included in an index for climate resilient development, a single approach to building a 
global  index  for  climate  resilient  development  does  not  exist.  The  high  number  of 
differences between the scores of the three indices indicates that a single index in the 
climate resilient development domain is a sort of chimera. Any index should address a 
specific  policy  request  with  a  clear  objective.  This  is  a  first  step  to  building  a  fit-for-
purpose index.  

48 

 
 
 
For this reason, we propose the construction of a scientific platform organising all the 
reviewed indicators and concepts. Such a platform, which is proposed as an interface 
between  science  and  policy  in  the  domain  of  climate  change  risk,  and  disaster  risk 
management  for  humanitarian  aid  and  development  should  provide  transparent, 
objective,  reliable,  accurate,  and  open  source  information  on  the  impacts  of  natural 
hazards  related  to  climate  change,  vulnerability,  adaptive  capacity,  mitigation,  and 
resilience.  The  aim  of  such  a  platform  is  not  just  to  provide  information  needed  to 
rank countries and allocate resources, but also to provide supporting tools consistent 
with  many 
low  carbon 
frameworks  such  as  climate  resilient  development, 
development, green growth and the green economy. The 102 indicators of the Table I 
Annex  II  will  be  included  into  this  platform.  It  will  be  up  to  the  users  to  select 
indicators  and  mathematical  formulas  for  building  their  own  composite  indicators 
consistent  with  their  political  objectives  (such  as  funding  allocation  decisions  on 
climate resilient development policies) and their monitoring and evaluation priorities. 

49 

 
 
 
 
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57 

 
 
 
 
 
 
 
58 

 
 
 
 
 
Annex I Fact sheets of the indicators included into the 
Case study 

Natural Hazards 
Indicator 

Name 

Drought Events - the past 20 years (cumulative) 

Description 

Relevance 

Sum of the number of droughts reported the past 20 years 
(cumulative) 
Climate-related and weather-driven  hazards 

Notes 

Measuring Unit 

Number of events 

Indicator Creation 
Method 

For a disaster to be entered into the database at least one of the 
following criteria must be fulfilled: 
1. 
2. 
3. 
4. 

Ten (10) or more people reported killed. 
Hundred (100) or more people reported affected. 
Declaration of a state of emergency. 
Call for international assistance. 

References 

Source 

Source / Citation 

Hahn et al 2009; Costa (2012), Kellenberg and Mobarak (2008), IPCC 
(2007; 2012; 2014). 
EM-Data 

URL 

http://www.emdat.be 

Original source - if 
different 

Date of Publication 

2015 

Periodicity 

Annual 

Year of reference 

2014 and last available 

Trend 

Data type 

1995-2014 

Tabular (excel) 

Missing data 

36/111 

Drought Events – the past 20 years 1995-2014 (cumulative) 

Source: Authors  elaborations on EM – Data, 2015 

59 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Flood Events - the past 20 years (cumulative) 

Description 

Relevance 

Number of floods reported the past 20 years (cumulative) 

Climate-related and weather-driven  hazards 

Notes 

Measuring Unit 

Number of events 

Indicator Creation 
Method 

For a disaster to be entered into the database at least one of the 
following criteria must be fulfilled: 

Ten (10) or more people reported killed. 

 
  Hundred (100) or more people reported affected. 
  Declaration of a state of emergency. 
  Call for international assistance. 

References 

Hahn et al 2009; Costa (2012), Kellenberg and Mobarak (2008), IPCC 
(2007; 2012; 2014).   

Source 

Source / Citation 

EM-Data 

URL 

http://www.emdat.be 

Original source - if 
different 

Date of Publication 

2015 

Periodicity 

Annual 

Year of reference 

2014 and last available 

Trend 

Data type 

1995-2014 

Tabular (excel) 

Missing data 

14/111 

Flood Events - the past 20 years 1995-2014 (cumulative) 

Source: Authors elaborations on EM – Data, 2015  

60 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator 

Name 

Storm Events - the past 20 years (cumulative) 

Description 

Relevance 

Number of storms reported the last 20 years (cumulative) 

Climate-related and weather-driven hazards 

Notes 

Measuring Unit 

Number of events 

Indicator Creation 
Method 

For a disaster to be entered into the database at least one of 
the following criteria must be fulfilled: 

Ten (10) or more people reported killed. 

 
  Hundred (100) or more people reported affected. 
  Declaration of a state of emergency. 
  Call for international assistance. 

References 

Hahn et al 2009; Costa (2012), Kellenberg and Mobarak 
(2008), IPCC (2007; 2012; 2014).  

Source 

Source / Citation 

EM-Data 

URL 

http://www.emdat.be 

Original source - if 
different 

Date of Publication  2015 

Periodicity 

Annual 

Year of reference 

2014 and last available 

Trend 

Data type 

1995-2014 

Tabular (excel) 

Storm Events - the past 20 years 1995-2014 (cumulative) 

Source: Authors elaborations on EM – Data, 2015 

61 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Exposure  
Indicator  Name 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Source 

Source / Citation 

Population density (people per sq. km of land area) 

Population/m2 

The increasing global population increases pressure on environmental 
resources. Relative flood mortality is higher in less populated than in 
densely populated countries 
people per sq. km  

Population density is midyear population divided by land area in 
square kilometers. Population is based on the current definition of 
population, which counts all residents regardless of legal status or 
citizenship - except for refugees that are not permanently settled in 
the country of asylum, who are generally considered part of the 
population of their country of origin. Land area is a country's total 
area, excluding area under inland water bodies, national claims to 
continental shelf, and exclusive economic zones. In most cases the 
definition of inland water bodies includes major rivers and lakes. 
Birkmann 2007; de Oliveira Mendes (2009), Tate et al. (2010) Khan 
(2012), Lee (2014), Brooks et al., 2005 
Green Growth Knowledge Platform (GGKP) 
World Bank Data 

URL 

http://data.worldbank.org/indicator/EN.POP.DNST 

Original source - if 
different 
Date of Publication 

Food and Agriculture Organization and World Bank population 
estimates. 
2014 

Periodicity 

Annual 

Year of reference 

2013 

Trend 

Data type 

1995-2013 yearly 

Tabular (excel) 

Missing data 

3/111 countries 

Population density (people per sq. km of land area), 2013 

Source: Authors elaborations on World Bank data, 2014 

62 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Internally displaced 

Description 

Relevance 

Measuring Unit 
Indicator Creation 
Method 
Additional Notes 

Pre-Processing 

Notes 

Source 

Internal refugees (1 000s) scale by population 

1 000s scale by population 
The data are generally provided by Governments, based on their own 
definitions and methods of data collection 

References 

Brooks et al., 2006 

Source / Citation 

URL 
Original source - if 
different 
Date of Publication 

Periodicity 

United Nations High Commissioner for Refugees (UNHCR) Population 
Statistics Reference Database,  
http://popstats.unhcr.org/PSQ_TMS.aspx 

2014 

Annual 

Year of reference 

2013 and latest available year 

Internally displaced, 2013  

Source: Authors elaborations on UNHCR data, 2014  

63 

 
 
 
 
 
  
 
 
  
 
  
  
  
 
 
  
  
 
 
 
  
 
 
 
 
 
 
 
 
 
Indicator  Name 

Number of refugees per place of residence 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 
References 

Refugees include individuals recognised under the 1951 Convention 
relating to the Status of Refugees; its 1967 Protocol; the 1969 
Organization of African Unity (OAU) Convention Governing the Specific 
Aspects of Refugee Problems in Africa; those recognised in accordance 
with the UNHCR Statute; individuals granted complementary forms of 
protection; or those enjoying temporary protection. The refugee 
population also includes people in a refugee-like situation. 
Displaced people are normally a particularly at-risk group and are 
more likely to live in vulnerable conditions in hazard-prone areas , 
with less access to basic services than low-income households in 
general 
Count 

Post 2015 HFA (UNISDR, 2014) 

Source 

Source / Citation 

UNHCR Population Statistics Database 

URL 

http://popstats.unhcr.org/PSQ_TMS.aspx 

Original source - if 
different 
Date of Publication 

Periodicity 

Annual 

Year of reference 

2013 and latest year available 

Trend 

Data type 

2000-2013 

Tabular (excel) 

Missing data 

23/111 

Number of refugees per place of residence, 2013 

Source: Authors elaborations on UNHCR data, 2013 

64 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Name 

Proportion of Population in Low Elevation Coastal Zones (LECZ) 

Description  Proportion of Population in Coastal Zones. Low Elevation Coastal Zone (LECZ) is 
defined as the contiguous area along the coast that is less than 10 metres above 
sea level. 
Percentage 

The proportions of populations (urban, rural and total) in low elevation coastal 
zones (LECZ) are calculated for each country or area by UNSD using total and 
LECZ population figures available from CIESIN/SEDAC. Country-level estimates 
of urban, rural and total population and land area in a low elevation coastal 
zones (LECZ) were generated globally using Global Rural-Urban Mapping Project 
(GRUMP) alpha population and land area data products and a Digital Elevation 
Model (DEM) derived from Shuttle Radar Topographic Mission (SRTM) remote 
sensing data. 

The zone was derived from the DEM by selecting all land contiguous with the 
coast that was 10 metres or less in elevation coastal zone . Zonal statistics were 
generated for urban, rural and total population and land area for the country as 
a whole and within the LECZ. 

United Nations Statistics Division, Environmental Indicators: Marine and Coastal 
Areas 
http://unstats.un.org/unsd/environment/Proportion_Population_CoastalZones.ht
m 
2009 

2000 

Indicato
r 

Notes 

Measuring 
Unit 
Indicator 
Creation 
Method 

References 

Source  Source / 

Citation 
URL 

Date of 
Publication 
Periodicity 

Year of 
reference 
Trend 

Data type 

tabular (excel) 

Missing 
data 

0/111 

Proportion of Population in Low Elevation Coastal Zones (LECZ), 2000 

Authors  elaborations on UN data, 2009 

65 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vulnerability 
Indicator  Name 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Source 

Source / Citation 

Gini index 

The Gini index measures the extent to which the distribution of 
income or consumption expenditure among individuals or households 
within an economy deviates from a perfectly equal distribution. A Gini 
index of 0 represents perfect equality, while an index of 100 implies 
perfect inequality. 

The index gives an estimate of inequality as it measures the extent to 
which the actual income distribution differs from an equal distribution. 
Resilience is likely to be lower in countries with a high degree of 
income inequality 
Index [0-100] 

A Lorenz curve plots the cumulative percentages of total income 
received against the cumulative number of recipients, starting with 
the poorest individual or household. The Gini index measures the area 
between the Lorenz curve and a hypothetical line of absolute equality, 
expressed as a percentage of the maximum area under the line. Thus 
a Gini index of 0 represents perfect equality, while an index of 100 
implies perfect inequality. 
Inform: Gini 
World Risk Index:  Income inequality 
Hallegatte 2014; Anbarci et al., 2005; Kahn, 2005;Brooks et al., 
2005; post 2015 HFA (UNISDR, 2014); Green Growth Knowledge 
Platform (GGKP) 
World Bank 

URL 

http://data.worldbank.org/indicator/SI.POV.GINI 

Date of Publication 

20/12/2013 

Periodicity 

annual 

Year of reference 

2012 and latest available year 

Trend 

Data type 

1995- 2012 yearly  

Tabular (excel) 

Missing data 

27/111 

GINI index, 2013  

Source: Authors  elaborations on World Bank data, 2014 

66 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Poverty headcount ratio at US$1.25 a day (PPP) (% of 
population) 
% of population living on US$ 1.25 per day or less (purchasing power 
parity - PPP) 
Poor people are more susceptible to suffer from the impact of natural 
hazards, as they tend to live in hazard-prone areas (e.g. in unsafe 
buildings, on floodplains, etc.) and continuously have to cope with 
various shocks related to hazards, in dire conditions with limited 
assets  
Percentage 

Population below US$1.25 a day is the percentage of the population 
living on less than US$1.25 a day at 2005 international prices. As a 
result of revisions in PPP exchange rates, poverty rates for individual 
countries cannot be compared with poverty rates reported in earlier 
editions (source: World Bank) 
Bjarnadottir er al., 2011;  Sub-indicator of the World Risk Index 2014 
and MDGs (UN 2005) 

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/SI.POV.DDAY 

Original source - if 
different 

Date of Publication 

World Bank, Development Research Group. Data are based on 
primary household survey data obtained from government statistical 
agencies and World Bank country departments. Data for high-income 
economies are from the Luxembourg Income Study database. For 
more information and methodology, please see PovcalNet 
(http://iresearch.worldbank.org/PovcalNet/index.htm). 
2014 

Periodicity 

Annual 

Year of reference 

2013 and latest available year 

Trend 

Data type 

1995-2013 

Tabular (excel) 

Missing data 

29/111 countries 

Poverty headcount ratio at US$1.25 a day (PPP) (% of population), 2013 

Source: Authors  elaborations on World Bank data, 2014 

67 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Age dependency ratio (% of working-age population) 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Age dependency ratio (% of working-age population) is the ratio of 
dependents (people younger than 15 or older than 64) to the 
working-age population (those aged 15-64). Data are shown as the 
proportion of dependents per 100 working-age persons. 

The direct effects of extreme weather may disproportionately affect 
the old and the young. A high age-dependency ratio means a high 
proportion of children and elderly people compared to working age 
population. This lowers resilience, particularly in the case of death or 
injury of a working-age adult. 
Percentage 

World Bank estimates from various sources including census reports, 
the United Nations Population Division's World Population Prospects, 
national statistical offices, household surveys conducted by national 
agencies, and ICF International. 
World Risk Index in Susceptibility:  
ND-GAIN in Sensitivity:  
Post 2015 HFA in Resilience: 

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/SP.POP.DPND 

Original source - if 
different 
Date of Publication 

Periodicity 

2014 

Annual 

Year of reference 

2013 and latest available year 

Trend 

Data type 

1995-2013 yearly 

Tabular (excel) 

Missing data 

7/111 countries 

Age dependency ratio (% of working-age population), 2013  

Source: Authors  elaborations on World Bank data, 2014  

68 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Agriculture, value added (% of GDP) 

Description 

Relevance 

Agriculture corresponds to ISIC divisions 1-5 and includes forestry, 
hunting, and fishing, as well as cultivation of crops and livestock 
production. Value added is the net output of a sector after adding up 
all outputs and subtracting intermediate inputs. 
Climate-sensitive sector 

Notes 

Measuring Unit 

Percentage 

Indicator Creation 
Method 

References 

The indicator is calculated without making deductions for depreciation 
of fabricated assets or depletion and degradation of natural resources. 
The origin of value added is determined by the International Standard 
Industrial Classification (ISIC), revision 3. Note: For VAB countries, 
gross value added at factor cost is used as the denominator. 
Füssel, 2010 
Füssel,and Klein, 2006, (IPCC, 2014a, 2014b)  

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/NV.AGR.TOTL.ZS 

Original source - if 
different 
Date of Publication 

World Bank national accounts data, and OECD National Accounts data 
files. 
Last Updated: 01/30/2015 [World development indicators] 

Periodicity 

Annual 

Year of reference 

2013 and latest available year 

Trend 

Data type 

1995-2013 

Tabular (excel) 

Missing data 

11/111 

Agriculture, value added (% of GDP), 2013  

Source: Authors  elaborations on World Bank data, 2013 

69 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Forest area (% of land area) 

Description 

Relevance 

Forest area as percentage of the total land area 

Notes 

Measuring Unit 

Percentage 

Indicator Creation 
Method 

References 

Forest area is land under natural or planted stands of trees of at least 
5 metres in situ, whether productive or not, and excludes tree stands 
in agricultural production systems (for example, in fruit plantations 
and agroforestry systems) and trees in urban parks and gardens. 
Brooks et al., 2005; MDG 7.1 (UN 2005); WDI 

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/AG.LND.FRST.ZS 

Original source - if 
different 
Date of Publication 

Periodicity 

Food and Agriculture Organization, electronic files and website. 

2014 

Annual 

Year of reference 

2012 

Trend 

Data type 

1995-2012 yearly 

Tabular (excel) 

Missing data 

4/111 countries 

Forest area (% of land area), 2012 

Source: Authors  elaborations on World Bank data, 2014 

70 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Water dependency ratio 

Description 

Relevance 

Indicator expressing the percent of total renewable water resources 
originating outside the country 
High dependency on foreign water resources exacerbates water insecurity 
due to climate change  

Notes 

Measuring Unit  Percentage 

References 

ND GAIN: Sensitivity  

Source 

Source / 
Citation 
URL 

Original source 
- if different 
Date of 
Publication 
Periodicity 

Year of 
reference 
Trend 

Data type 

FAO- AQUASTAT 

http://www.fao.org/nr/water/aquastat/data/query/index.html?lang=en 

2015 

5-year intervals 

2013-2017 and latest available 

1988 - 2013 in 5-year intervals 

Tabular (excel) 

Water dependency ratio, 2014 

Source: Authors  elaborations on FAO- AQUASTAT data, 2015 

71 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Adaptive capacity  

Indicator  Name 

Ecosystem vitality: Agriculture 

Description 

Relevance 

Component of EPI. Indicator aggregated from 2 performance 
indicators: Agricultural Subsidies (AGSUB) and Pesticide Regulation 
(POPs) 
Agriculture is one the economic activities that causes more impacts to 
ecosystems. 

Notes 

Measuring Unit 

Index [0-100] 

Indicator Creation 
Method 

References 

Source 

Source / Citation 

URL 

Original source - if 
different 
Date of Publication 

Periodicity 

Ordinal scale with a range from 0 (very poor environmental 
performance) to 100 (excellent environmental performance), 
aggregated from two performance indicators: Agricultural Subsidies 
(AGSUB) and Pesticide Regulation (POPs) 
WRI 2014: Adaptive Capacity 

Yale Center for Environmental Law & Policy (YCELP) and the Center 
for International Earth Science Information Network (CIESIN) at 
Columbia University 
http://epi.yale.edu/ 

2015 

Annual 

Year of reference 

2012 

Trend 

Data type 

2002-2012 

Tabular (excel) 

Missing data 

8/111 

Ecosystem vitality: Agriculture, 2012  

Source: Authors  elaborations on EPI data, 2015 

72 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Manufacturing, value added (% of GDP) 

Description 

Relevance 

Manufacturing refers to industries belonging to ISIC divisions 15-37. 
Value added is the net output of a sector after adding up all outputs 
and subtracting intermediate inputs.  
Economic diversification. A community with a relatively diverse local 
economy is better able to adjust to changes that have a significant 
impact on a particular sector or sectors of employment 

Notes 

Measuring Unit 

Percentage 

Indicator Creation 
Method 

References 

Manufacturing refers to industries belonging to ISIC divisions 15-37. 
Value added is the net output of a sector after adding up all outputs 
and subtracting intermediate inputs. 
Hallegatte, 2014, IPCC, 2014 a; 2014b  

Source 

Source / Citation 

URL 

Original source - if 
different 
Date of Publication 

Periodicity 

World Bank national accounts data, and OECD National Accounts data 
files. 
http://data.worldbank.org/indicator/NV.IND.MANF.ZS 

2014 

Annual 

Year of reference 

2012 and latest year available 

Trend 

Data type 

1995-2012 

Tabular (excel) 

Missing data 

8/111 

Manufacturing, value added (% of GDP), 2012  

Source: Authors  elaborations on World Bank data, 2014 

73 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Description 

Relevance 
Measuring Unit 

References 

Notes 

Overall Development Assistance Committee (DAC) aid 
activities with adaptation as principal objective 
Overall DAC aid activities with adaptation as their principal 
objective  

USD Million  

Source  Source / Citation  OECD 

http://www.oecd.org/dac/stats/ 

2014 

URL 
Original source - 
if different 
Date of 
Publication 
Periodicity 
Year of reference  2012 
Trend 
Data type 
Missing data 

tabular (excel) 
17/111 

Overall DAC aid activities with adaptation as principal objective 2012  

Source: Authors  elaborations on OECD data, 2014 

74 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Adaptive capacity/Gender  

Indicator  Name 

Description 

Relevance 

Access to Literacy 
Percentage of female population (15+ yrs) who are literate. 

Literacy allows for increased participation and understanding. 
It plays a central role in increasing the ability to participate in 
decision-making and leadership roles  

Notes 

Measuring Unit 

Percentage 

References 

The Environment and Gender Index (EGI) 2013 Pilot 
(http://genderandenvironment.org/) 

Source  Source / 

UNICEF/World Bank 
www.unicef.org 

Citation 
URL 
Original source - 
if different 
Date of 
Publication 
Periodicity 
Year of reference  2013 and latest available year 
1991- 2013 
Trend 
tabular (excel) 
Data type 
 18/111 
Missing data 

Annual 

2014 

Access to Literacy, 2013  

Source: Authors  elaborations on UNICEF data, 2014 

75 

 
 
 
 
 
 
 
  
  
 
 
  
  
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Share of female representatives in the National Parliament 
The number of seats held by women n national parliaments expressed 
as a percentage of all occupied seats 
This indicator shows the progress of female participation in the 
highest levels of society and their access to leadership and decision-
making positions 

Percentage 
The proportion of seats held by women in national parliament is 
derived by dividing the total number of seats occupied by women by 
the total number of seats in parliament. There is no weighting or 
normalising of statistics (source: UN). 
World Risk Index 2014: Adaptive Capacity 
 MDG 3.3 (UN 2005) 
Environment and Gender Index (EGI) 2013 

Source 

Source / Citation 

UN - MDG Indicators 

URL 
Original source - if 
different 
Date of Publication 

Periodicity 

http://mdgs.un.org/unsd/mdg/Data.aspx 

http://www.ipu.org/wmn-e/world.htm 

07/07/14 

Monthly 

Year of reference 

2014 

Trend 

Data type 

1997-2014 

Tabular (excel) 

Missing data 

 5/111 

Share of female representatives in the National Parliament, 2014  

Source: Authors  elaborations on UN data, 2014 

76 

 
 
 
 
 
 
  
  
 
 
 
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Description 

Relevance 

Measuring 
Unit 

Indicator 
Creation 
Method 

Access to Bank Accounts 
This indicator measures the percentage of women (age 15+) with a bank 
account at a formal financial institution 
Proxy for women's ability to access 'formal' institutions, be involved in the 
formalised economy (vs. informal) providing an indication of their abilities to 
participate more widely in 'formal' decision-making capacities. (EGI,2013)  

Percentage 

Denotes the percentage of respondents with an account (alone or jointly 
with someone else) at a bank, credit union, another financial institution (e.g. 
cooperative, microfinance institution), or the post office (if applicable), 
including respondents who reported having a debit card (% female, age 
15+). 

Notes 

Source 

References 

The Environment and Gender Index (EGI) 2013 Pilot 
(http://genderandenvironment.org/) 

Source / 
Citation 
URL 
Original 
source - if 
different 
Date of 
Publication 
Periodicity 
Year of 
reference 
Trend 

World Bank’s Global Financial Inclusion Database (Findex), 2011 
(http://econ.worldbank.org/) 
http://databank.worldbank.org/Data/Views/reports/tableview.aspx 

2014 

Annual 

2011 

Data type 

tabular (excel) 

Missing data 

 43/111 

Access to Bank Accounts, 2011 

Source: Authors  elaborations on World Bank data, 2014 

77 

 
 
 
 
 
 
 
  
  
 
 
  
 
 
 
 
  
 
 
 
 
 
 
 
 
Coping Capacity  

Indicator  Name 

Improved sanitation facilities (% of population with access) 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Source 

Source / Citation 

URL 

Percentage of population using improved sanitation facilities. The 
improved sanitation facilities comprise flush toilets, piped sewer 
systems, septic tanks, flush/pour flush to pit latrines, ventilated 
improved pit latrines, pit latrines with slabs and composting toilets. 
Access to sanitation is particularly crucial to enhance preparedness for 
various natural disasters that are exacerbated by climate change. 
People without good sanitation are susceptible to diseases and can 
become more vulnerable following a natural hazard event. 
Percentage 

Coverage estimates are based on data from household surveys and 
censuses carried out at national level. For each country, survey and 
census data are plotted on a timescale from 1980 to date. A linear 
trend line, based on the least-squares method, is drawn through these 
data points to provide estimates for each year between 1990 and 
2012 (wherever possible). The total estimates are population-
weighted averages of the urban and rural numbers. Countries with 
missing data are assigned regional averages when generating regional 
and global estimates. 
World Risk Index in Susceptibility: Population with access to sanitation 
ND-GAIN in Adaptive capacity: Access to improved sanitation facilities 
INFORM in  Lack of coping capacity: Access to improved sanitation 
facilities 
Green Growth Knowledge Platform (GGKP) 
WHO/UNICEF Joint Monitoring Programme for Water Supply and 
Sanitation 
http://www.wssinfo.org/data-estimates/tables/ 

Date of Publication 

2014 

Periodicity 

Annual 

Year of reference 

2012 and last available year 

Trend 

Data type 

1995-2012 yearly 

Tabular (excel) 

Missing data 

1/111 

Improved sanitation facilities (% of population with access), 2012 

Source: Authors elaborations on WHO/UNICEF data, 201 

78 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Hospital beds (per 1 000 people) 

Description 

Hospital beds include inpatient beds available in public, private, general, and 
specialised hospitals and rehabilitation centres. In most cases, beds for both 
acute and chronic care are included. 

Relevance 

Hospital beds also indicate the capacity of the medical care infrastructure to 
help, support or treat societies in the event of a mass emergency or disaster 
situation 

Notes 

Number of beds 

Measuring 
Unit 
References  World Risk Index 2014: Coping Capacity 

Source 

Source / 
Citation 
URL 

Original 
source - if 
different 
Date of 
Publication 
Periodicity 

Year of 
reference 
Trend 

World Data Bank 

http://data.worldbank.org/indicator/SH.MED.BEDS.ZS 

Data are from the World Health Organization, supplemented by country data. 

2014 

2012 and latest available year 

1995-2012 

Data type 

Tabular (excel) 

Missing data  5/111 

Hospital beds (per 1 000 people), 2012  

Source: Authors elaborations on World Bank data, 2012 

79 

 
 
 
 
 
 
  
  
 
 
  
  
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Physicians (per 1 000 people) 

Description 

Physicians include general and specialist medical practitioners. 

Relevance 

This indicator reflects the capacity of a country to cope with health risks 
caused by climate change 

Notes 

Source 

Measuring 
Unit 
References 

Source / 
Citation 
URL 
Original 
source - if 
different 
Date of 
Publication 
Periodicity 
Year of 
reference 
Trend 

Number of Physicians 

ND GAIN: Adaptive Capacity 

World Bank 

 http://data.worldbank.org/indicator/SH.MED.PHYS.ZS 

World Health Organization, Global Atlas of the Health Workforce. For latest 
updates and metadata, see http://apps.who.int/globalatlas/. 

2014 

2012 and latest available year 

1995-2012 

Data type 

Tabular (excel) 

Missing data  4/111 

Physicians (per 1 000 people), 2012  

Source: Authors elaborations on World Bank data, 2014 

80 

 
 
 
 
 
 
  
  
 
 
  
  
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Indicator  Name 

Nurses and midwives (per 1 000 people) 

Description 

Relevance 

Nurses and midwives include professional nurses, professional midwives, 
auxiliary nurses, auxiliary midwives, enrolled nurses, enrolled midwives and 
other associated personnel, such as dental nurses and primary care nurses.  
This indicator reflects the capacity of a country to cope with health risks 
brought about by climate change 

Notes 

Measuring 
Unit 
Pre-
Processing 

Number of nurses and midwives 

References 

ND GAIN: Adaptive Capacity 

Source 

Source / 
Citation 
URL 

Original 
source - if 
different 
Date of 
Publication 
Periodicity 

Year of 
reference 
Trend 

World Bank 

http://data.worldbank.org/indicator/SH.MED.NUMW.P3 and 

World Health Organization, Global Atlas of the Health Workforce. For latest 
updates and metadata, see http://apps.who.int/globalatlas/. 

2014 

2012 and latest available year 

1995-2012 

Data type 

Tabular (excel) 

Missing data  5/111 

Nurses and midwives (per 1 000 people), 2012  

Source: Authors elaborations on World Bank data, 2014  

81 

 
 
 
 
 
 
  
  
 
  
 
  
  
 
 
  
  
 
 
 
 
  
 
 
 
 
 
 
 
 
Indicator  Name 

Mobile phone subscriptions (per 100 people) 

Description  Mobile telephone subscriptions are subscriptions to a public mobile telephone 

service using cellular technology, which provide access to the public 
telephone network. Post-paid and prepaid subscriptions are included. 

Notes 

Source 

Relevance 

Measuring 
Unit 
Indicator 
Creation 
Method 

Number of subscriptions per 100 people 

References 

INFORM: Lack of coping capacity 

Source / 
Citation 
URL 

Original 
source - if 
different 
Date of 
Publication 
Periodicity 

Year of 
reference 
Trend 

http://data.worldbank.org/indicator/IT.CEL.SETS.P2/countries/1W?display=m
ap 
International Telecommunication Union, World Telecommunication/ICT 
Development Report and database, and World Bank estimates. 

2014 

Annual 

2013 and latest available year 

1995-2013 

Data type 

Tabular (excel) 

Missing data  3/111 countries 

Mobile cellular subscriptions (per 100 people), 2013  

Source: Authors elaborations on Inform, 2015 

82 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mitigation Capacity  

Indicator  Name 

CO2 emissions (kg per PPP US$ of GDP) 

Carbon dioxide emissions are those stemming from the burning of 
fossil fuels and the manufacture of cement. They include carbon 
dioxide produced during consumption of solid, liquid, and gas fuels 
and gas flaring. 
kg per PPP US$ of GDP 

Description 

Notes 

Measuring Unit 

Indicator Creation 
Method 
Additional Notes 

Pre-Processing 

References 

MDG 7.2 (UN 2005) 
Post 2015 HFA (UNISDR, 2014) 

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/EN.ATM.CO2E.PP.GD 

Original source - if 
different 

Carbon Dioxide Information Analysis Center, Environmental Sciences 
Division, Oak Ridge National Laboratory, Tennessee, United States. 

Date of Publication 

2014 

Periodicity 

Annual 

Year of reference 

2011 and latest available year 

Trend 

Data type 

1995-2010 yearly 

Tabular (excel) 

Missing data 

9/111 countries 

CO2 emissions (kg per PPP US$ of GDP), 2011 

Source: Authors elaborations on World Bank data, 2014  

83 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Participation in UNFCCC fora  - Mitigation actions  

As proxy of active participation in the UNFCCC, a specific indicator has 
been built on Submitted National Communications from non Annex I 
Parties 

Description 

Relevance 

Validity/ Limitation 
of Indicator 

Notes 

Measuring Unit 

Score [0-4] 

Indicator Creation 
Method 

References 

Our elaboration giving scores as follows: 
0=no report 
1=Initial national communication 
2= Initial national communication + Second national communication 
3=Initial national communication + Second national communication + 
Third national communication 

Source 

Source / Citation 

UN Framework Convention on Climate Change 

URL 

http://unfccc.int/national_reports/non-
annex_i_natcom/submitted_natcom/items/653.php 

Original source - if 
different 
Date of Publication 

Periodicity 

2015 

Year of reference 

2015 and latest available year 

Trend 

Data type 

tabular (excel) 

Missing data 

6/111 

Participation in UNFCCC fora  - Mitigation action, 2015  

Source: Authors elaborations on UNFCCC data, 2015 

84 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Development  

Indicator  Name 

Literacy rate, adult total (% of people ages 15 and above) 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Population aged 15 years and above who can read and write a short 
simple statement on their everyday life ( source: World Bank) 
Literacy could be an essential indicator, when empowering people on 
hazard risk reduction 
Percentage 

Adult (15+) literacy rate (%). Total is the percentage of the 
population aged 15 and above who can, with understanding, read and 
write a short, simple statement about their everyday life. In general, 
‘literacy’ also encompasses ‘numeracy’, the ability to make simple 
arithmetic calculations. This indicator is calculated by dividing the 
number of literates aged 15 years and over by the corresponding age 
group population and multiplying the result by 100  ( source: World 
Bank) 
Brooks et al., 2005 
World Risk Index 2014 
 MDG 2.3 (UN 2005) 
 post 2015 HFA 
 INFORM 2014 

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/SE.ADT.LITR.ZS 

Original source - if 
different 
Date of Publication 

Periodicity 

2014 

Annual 

Year of reference 

2013 and latest available year 

Trend 

Data type 

1995-2013 

Tabular (excel) 

Missing data 

18/111 

Literacy rate, adult total (% of people ages 15 and above), 2013  

Source: Authors elaborations on World Bank data, 2014 

85 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Income Index  - Gross National Income (GNI) 

Description 

Relevance 

The total value of all final goods and services produced within a nation 
in a particular year, plus income earned by its citizens (including 
income of those located abroad) 

Notes 

Measuring Unit 

Index [min. value of UE$100 max. value US$60,000]  

Indicator Creation 
Method 

References 

GNI per capita (2005 PPP International US$, using natural logarithm) 
expressed as an index using a minimum value of US$100 and a 
maximum value US$60,000. (source UNDP) 
Adger (2003), Cutter et al. (2000, 2003), Dwyer et al. (2004), Brooks 
et al. (2005), Tunstall et al. (2007), Polsky et al. (2007), Ojerio et al. 
(2011), Khan (2012), Lee (2014); Sub-indicator of HDI. 

Source 

Source / Citation 

UNDP - Human Development Reports 

URL 

http://hdr.undp.org/en/content/income-index 

Original source - if 
different 
Date of Publication 

15/11/2013 

Periodicity 

Annual 

Year of reference 

2013 

Trend 

Data type 

1990,2000,2005-2013 

Tabular (excel) 

Missing data 

6/111 

Income Index - Gross National Income (GNI), 2013 

Source: Authors elaborations on UNDP data, 2013 

86 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Net ODA received per capita (current US$) 

Description 

Relevance 

Notes 

Measuring Unit 

Indicator Creation 
Method 

References 

Source 

Source / Citation 

ODA received per person 

Countries heavily dependent of ODA will be more dependent on ODA 
decisions to finance recovery and reconstruction 
Current US$ of ODA 

Net official development assistance (ODA) per capita consists of 
disbursements of loans made on concessional terms (net of 
repayments of principal) and grants by official agencies of the 
members of the Development Assistance Committee (DAC), by 
multilateral institutions, and by non-DAC countries to promote 
economic development and welfare in countries and territories in the 
DAC list of ODA recipients; and is calculated by dividing net ODA 
received by the midyear population estimate. It includes loans with a 
grant element of at least 25% (calculated at a rate of discount of 
10%) (source: World Bank). 
Costa (2012) and Raschky and Schwindt (2008); post 2015 HFA 
(UNISDR, 2014) and sub-indicator of INFORM 2014 
World Bank 

URL 

http://data.worldbank.org/indicator/DT.ODA.ODAT.PC.ZS 

Original source - if 
different 

Date of Publication 

Development Assistance Committee of the Organisation for Economic 
Co-operation and Development, Geographical Distribution of Financial 
Flows to Developing Countries, Development Co-operation Report, 
and International Development Statistics database. Data are available 
online at: www.oecd.org/dac/stats/idsonline.  
World Bank population estimates are used for the denominator. 
2014 

Periodicity 

Annual 

Year of reference 

2011 and latest available year 

Trend 

Data type 

1995-2011 

Tabular (excel) 

Missing data 

2/111 countries 

Net ODA received per capita (current US$), 2011 

Source: Authors elaborations on World Bank data, 2014 

87 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Indicator  Name 

Personal remittances received (% of GDP) 

Description 

Relevance 

Personal remittances comprise personal transfers and compensation 
of employees. (source: World Bank) 
Economies where remittances represent a high proportion of GDP are 
more resilient as risk is geographically spread and a lower proportion 
of household earnings will be affected. 

Notes 

Measuring Unit 

Percentage 

Indicator Creation 
Method 

References 

Personal transfers consist of all current transfers in cash or in kind 
made or received by resident households to or from non-resident 
households. Personal transfers thus include all transfers between 
resident and non-resident individuals. Compensation of employees 
refers to the income of border, seasonal, and other short-term 
workers who are employed in an economy where they are not 
resident, and of residents employed by non-resident entities. Data are 
the sum of the two items defined in the sixth edition of the IMF's 
Balance of Payments Manual: personal transfers and compensation of 
employees (source: World Bank). 
Post 2015 HFA (UNISDR, 2014) 

Source 

Source / Citation 

World Bank 

URL 

http://data.worldbank.org/indicator/BX.TRF.PWKR.DT.GD.ZS 

Original source - if 
different 
Date of Publication 

World Bank staff estimates based on IMF balance of payments data, 
and World Bank and OECD GDP estimates. 
2014 

Periodicity 

Annual 

Year of reference 

2012 and latest available year 

Trend 

Data type 

1995-2012 

Tabular (excel) 

Missing data 

15/111 countries 

Personal remittances received (% of GDP), 2012 

Source: Authors elaborations on World Bank data, 2014 

88 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Name 

Internet users (per 100 people) 

Indicato
r 

Notes 

Source 

Descriptio
n 
Relevance 

Measuring 
Unit 
Indicator 
Creation 
Method 

Reference
s 

Source / 
Citation 
URL 

Internet users are people with access to the worldwide web Internet network. 
(source: World Data Bank) 

Number of users per 100 people 

Perch- Nielsel 2010; Post 2015 HFA; INFORM 2014 

World Bank 

http://data.worldbank.org/indicator/IT.NET.USER.P2/countries/1W?display=def
ault 
International Telecommunication Union, World Telecommunication/ICT 
Development Report and database, and World Bank estimates. 

Original 
source - if 
different 
Date of 
Publication 
Periodicity  Annual 

2014 

Year of 
reference 
Trend 

2013 and latest available year 

1995-2013 

Data type 

Tabular (excel) 

Missing 
data 

4/111 countries 

Internet users (per 100 people), 2013 

Source: Authors elaborations on World Bank data, 2014 

89 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
90 

 
 
 
 
 
ANNEX II  

Table I – Sample of  Countries for the case study 

Country OECD/DAC 

LDCs 

other LIC-
DAC 

LMI-
DAC 

SIDs 

Afghanistan 
Angola 
Antigua and Barbuda 
Armenia 
Bangladesh 
Barbados 
Belize 
Benin 
Bhutan 
Bolivia 
Burkina Faso 
Burundi 
Cambodia 
Cameroon 
Cape Verde 
Central African Rep. 
Chad 
Comoros 
Congo, Dem. Rep. 
Congo, Rep. 
Cook Islands 
Côte d’Ivoire 
Cuba 
Djibouti 
Dominica 
Dominican Republic 
Egypt 
El Salvador 
Equatorial Guinea 
Eritrea 
Ethiopia 
Fiji 
Gambia 
Georgia 
Ghana 
Grenada 
Guatemala 
Guinea 
Guinea-Bissau 
Guyana 
Haiti 
Honduras 
India 
Indonesia 
Iraq 
Jamaica 
Kenya 
Kiribati 
Korea, Dem. Rep. 
Kosovo 
Kyrgyz Rep. 
Laos 
Lesotho 
Liberia 
Madagascar 
Malawi 

1 
1 

1 

1 
1 

1 
1 
1 

1 
1 
1 
1 

1 

1 
1 
1 

1 

1 
1 

1 

1 

1 
1 
1 
1 
1 

1 

1 
1 

1 

1 

1 

1 

1 
1 

1 

1 

1 
1 
1 

1 

1 

1 

1 

1 

1 
1 

1 

1 

1 
1 

1 

1 
1 

1 

1 

1 
1 
1 
1 

1 

91 

1 

1 

1 

World Bank 
Region 
SAS 
SSA 
LCR 
ECA 
SAS 
LCR 
LCR 
SSA 
SAS 
LCR 
SSA 
SSA 
EAP 
SSA 
SSA 
SSA 
SSA 
SSA 
SSA 
SSA 
EAP 
SSA 
LCR 
SSA 
LCR 
LCR 
MNA 
LCR 
SSA 
SSA 
SSA 
EAP 
SSA 
ECA 
SSA 
LCR 
LCR 
SSA 
SSA 
LCR 
LCR 
LCR 
SAS 
EAP 
MNA 
LCR 
SSA 
EAP 
EAP 

ECA 
EAP 
SSA 
SSA 
SSA 
SSA 

ISO3 

AFG 
AGO 
ATG 
ARM 
BGD 
BRB 
BLZ 
BEN 
BTN 
BOL 
BFA 
BDI 
KHM 
CMR 
CPV 
CAF 
TCD 
COM 
COD 
COG 
COK 
CIV 
CUB 
DJI 
DMA 
DOM 
EGY 
SLV 
GNQ 
ERI 
ETH 
FJI 
GMB 
GEO 
GHA 
GRD 
GTM 
GIN 
GNB 
GUY 
HTI 
HND 
IND 
IDN 
IRQ 
JAM 
KEN 
KIR 
PRK 
MNE 
KGZ 
LAO 
LSO 
LBR 
MDG 
MWI 

 
 
 
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
  
  
 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Country OECD/DAC 

LDCs 

other LIC-
DAC 

LMI-
DAC 

SIDs 

Maldives 
Mali 
Marshall Islands 
Mauritania 
Mauritius 
Micronesia, Federated 
States 
Moldova 
Mongolia 
Morocco 
Mozambique 
Myanmar 
Nauru 
Nepal 
Nicaragua 
Niger 
Nigeria 
Pakistan 
Palau 
Papua New Guinea 
Paraguay 
Philippines 
Rwanda 
Samoa 
São Tomé and Príncipe 
Senegal 
Seychelles 
Sierra Leone 
Solomon Islands 
Somalia 
South Sudan 
Sri Lanka 
St. Kitts-Nevis 
St. Lucia 
St. Vincent and 
Grenadines 
Sudan 
Suriname 
Swaziland 
Syria 
Tajikistan 
Tanzania 
Timor-Leste 
Togo 
Tonga 
Trinidad and Tobago 
Turkmenistan 
Tuvalu 
Uganda 
Ukraine 
Uzbekistan 
Vanuatu 
Vietnam 
West Bank and Gaza 
Strip 
Yemen 
Zambia 
Zimbabwe 

1 

1 

1 
1 

1 

1 

1 
1 
1 
1 

1 
1 
1 

1 

1 
1 
1 

1 
1 

1 

1 
1 

1 

1 

1 

1 

1 

1 

1 

1 

1 
1 

1 
1 

1 

1 

1 
1 

1 

1 

1 

1 
1 

1 

1 

1 

1 
1 
1 
1 

1 

1 
1 

1 
1 
1 

1 

1 
1 

1 

1 

1 
1 

1 

1 

92 

World Bank 
Region 
SAS 
SSA 
EAP 
SSA 
SSA 

EAP 
ECA 
EAP 
MNA 
SSA 
EAP 
EAP 
SAS 
LCR 
SSA 
SSA 
SAS 
EAP 
EAP 
LCR 
EAP 
SSA 
EAP 
SSA 
SSA 
SSA 
SSA 
EAP 
SSA 
SSA 
SAS 
LCR 
LCR 

LCR 
SSA 
LCR 
SSA 
MNA 
ECA 
SSA 
EAP 
SSA 
EAP 
LCR 
ECA 
EAP 
SSA 
ECA 
ECA 
EAP 
EAP 

MNA 
MNA 
SSA 
SSA 

ISO3 

MDV 
MLI 
MHL 
MRT 
MUS 

FSM 
MDA 
MNG 
MAR 
MOZ 
MMR 
NRU 
NPL 
NIC 
NER 
NGA 
PAK 
PLW 
PNG 
PRY 
PHL 
RWA 
WSM 
STP 
SEN 
SYC 
SLE 
SLB 
SOM 
SSD 
LKA 
KNA 
LCA 

VCT 
SDN 
SUR 
SWZ 
SYR 
TJK 
TZA 
TLS 
TGO 
TON 
TTO 
TKM 
TUV 
UGA 
UKR 
UZB 
VUT 
VNM 

WBG 
YEM 
ZMB 
ZWE 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
 
 
ANNEX III – Fit-for-purpose indicators by component  

Natural Hazard Indicators (alphabetical order) 

Indicator 
name 
Average annual 
deviation in 
Sea Surface 
Temperatures 

Average annual 
excess heat 
(degrees) over 
the past five 
years 

Average annual 
excess rainfall 
(mm) over the 
past five years 

Definition 

Average annual 
deviation in Sea 
Surface Temperatures 
(SST) in the past five 
years in relation to 
the 30-year monthly 
means (1961-1990). 
The indicator captures 
the total amount of 
the anomalies in SST, 
either as excess or 
deficit (using absolute 
values) 
Average annual 
excess heat (degrees) 
over the past five 
years for all days 
more than 5°C (9˚F) 
hotter than the 30-
year mean monthly 
maximum 
Average annual 
excess rainfall (mm) 
over the past five 
years for all months 
with more than 20% 
higher rainfall than 
the 30-year monthly 
average 

Rationale 

References 

Data Source  

Relevant 
Hazards 
Fluctuations 
in 
productivity,  
currents, 
cyclones & 
storms,  

Sectors 
affected 
Fisheries, 
blooms and 
coral 
bleaching, 
tourism 

Frequent and severe 
deviations from the 30-
year moving average 
could herald shifts in 
currents, upwelling, 
weather patterns and 
climate, and could 
negatively  affect a 
country’s resilience to 
other hazards 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004); 
http://www.vulnerabilityi
ndex.net/; 
The index has not been 
renewed since 2004. 

Waves, 
desertification
, water 
resources, 
temperature 
stress, 
bleaching 

Floods, 
cyclones, wet 
periods, 
stress on land 
surfaces and 
ecosystems 
subject to 
flooding and 
disturbance 

Agriculture,  
society, 
ecosystems 

This indicator captures 
not only the number of 
days with significantly 
higher temperatures, but 
also the amount of the 
excess 

Agriculture, 
industry, 
society, 
ecosystems 

This indicator ensures 
that the amount of rain 
‘in excess’ is recorded. 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004); 
http://www.vulnerabilityi
ndex.net/; 
The index has not been 
renewed since 2004. 
Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 
http://www.vulnerabilityi
ndex.net/; 
The index has not been 
renewed since 2004. 

93 

Original Source: 1. 
Climatic Research Unit, 
University of East Anglia, 
Norwich, UK. 
http://www.cru.uea.ac.u
k/cru/data/temperature/
#datdow 
2. Data masked and 
extracted for EEZs by 
University of British 
Columbia  
Data NOT AVAILABLE in 
the EVI website.  
Original source: NOAA 
DATSAV3 Surface SOD 
1973-2003  
Data NOT AVAILABLE in 
the EVI website.  

Original source: NOAA 
GHCN 
http://www.ncdc.noaa.g
ov/oa/pub/data/ghcn/v2
/ghcnftp_zipd.html;  
 Data NOT AVAILABLE in 
the EVI website.  

 
 
Average annual 
excess wind 
over the past 
five years 

Average annual 
heat deficit 
(degrees) 

Average annual 
rainfall deficit 
(mm) over the 
past five years 

Drought 
frequency 

Summing speeds on 
days during which the 
maximum recorded 
wind speed is more 
than 20% higher than 
the 30-year average 
maximum wind speed 
for that month 

Average annual heat 
deficit (degrees) over 
the past five years for 
all days more than 
5°C (9˚F) cooler than 
the 30-year mean 
monthly minimum 

Average annual 
rainfall deficit (mm) 
over the past five 
years for all months 
with more than 20% 
lower rainfall than the 
30-year monthly 
average 
Drought Frequency 

Number of 
extreme events 
in the past 
years 

Total number of 
floods, droughts, and 
cyclones that were 
reported by 
households over the 
period considered 

Cyclones, 
tornados, 
storms, 
erosion, 
habitat 
damage, 
disturbance. 

Cold snaps, 
unusual 
frosts, effects 
on water 
resources, 
temperature 
stress, 
pollution 
attenuation 
rates 
Drought, dry 
spells, stress 
on surface 
water 
resources 

Ecosystems
, residential 
and 
industry 

Agriculture, 
health, 
households 

This indicator captures 
the likelihood of damage 
from frequent and severe 
wind that can affect 
forests, fan fires, create 
storm surges, dry soils, 
spread air pollution, and 
interact with other 
stressors 
This indicator captures 
not only the number of 
days with significantly 
lower temperatures, but 
also the amount of the 
“heat deficit” 

Agriculture, 
industry, 
society, 
ecosystems 

This indicator ensures 
that the amount of rain 
‘missed’ is taken into 
consideration. 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 
All 

Health and 
Households
, 
agriculture 

All 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 
http://www.vulnerabilityi
ndex.net/; 
The index has not been 
renewed since 2004. 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 
http://www.vulnerabilityi
ndex.net/; 
The index has not been 
renewed since 2004. 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 
http://www.vulnerabilityi
ndex.net/; 
The index has not been 
renewed since 2004. 
Sub-indicator of 
Hazard/exposure - 
INFORM 2014 

Original source: NOAA 
DATSAV3 Surface SOD 
1973-2003 
Data NOT AVAILABLE in 
the EVI website.. 

Original  source NOAA 
DATSAV3 Surface SOD 
1973-2003 
 Data NOT AVAILABLE in 
the EVI website.  

Original source : NOAA 
GHCN  
http://www.ncdc.noaa.g
ov/oa/pub/data/ghcn/v2
/ghcnftp_zipd.html; 
Data NOT AVAILABLE in 
the EVI website.  

EM DAT www.crred.org 

Hahn et al 2009; Costa 
(2012), Kellenberg and 
Mobarak (2008) 

EM DAT www.cred.org  

94 

 
 
  
 
 
 
Number of 
landslides 
recorded in the 
past five years 

Number of landslides 
recorded in the past 
five years (EMDAT 
definitions), divided 
by land area 

Alpine 
hazards 

Number of 
tsunamis or 
storm surges 
with run up 
greater than 
two metres 

Number of tsunamis 
or storm surges with 
run up greater than 
two metres above 
Mean High Water 
Spring tide (MHWS) 
per 1 000 km 
coastline since 1900 

Coastal 
Floods, 
Cyclones and 
Sea level rise 

Habitat 
disturbance 
and 
persistence 
of 
ecosystems 
and  
species 
from 
catastrophi
c shifts in 
the land 
surface 
Severe or 
permanent 
damage to 
biodiversity
, 
productivity 
and the 
ability to 
recover 
from other 
stressors 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Original source: 
1. EMDAT OFDA/CRED 
International Disaster 
Database 2001 
2. In-country 
Data NOT AVAILABLE in 
the EVI website.  

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

This indicator captures 
the potential loss of 
shorelines, coastal 
ecosystems 
and resources, and loss 
of species due to 
catastrophic run up of 
seawater onto coastal 
lands 

Original sources: 
1. NOAA/NESDIS/NGCC 
2. In-country 
3. Land area and length 
maritime coast from WRI 
2000-2001 and 
CIA 2001  
http://www.ngdc.noaa.g
ov/hazard/tsu.shtmlData  
NOT AVAILABLE in the 
EVI website.  

95 

 
 
 
 
 
Exposure indicators (alphabetical order) 
Indicator 
name 

Relevant 
Hazards 

Definition 

Sectors 
affecte
d 
All 

All 

ual Average 
Loss (AAL) 

Coastal 
vulnerable 
population 

Disaster 
mortality per 
100 000 
population 

AAL represents the 
probable annualised 
loss from all hazard 
events occurring over 
different return 
periods. 
Population less than 
5 m above sea level is 
the percentage of the 
total population living 
in areas where the 
elevation is five 
metres or less. 
Disaster mortality per 
100 000 inhabitants 
(five-year moving 
average) 

Coastal floods, 
cyclones and 
sea-level rise 

All 

Households 
and related 
economic 
activities, 
tourism 

Health and 
Households 

Exposed 
population per 
100 000 
inhabitants 

Sum of people 
exposed to extreme 
events/100 000 
inhabitants 

All 

All 

Fiscal AAL per 
inhabitant 

The fiscal AAL is the 
annual risk to publicly 
owned assets 

All 

All 

Rationale 

References 

Data  Source  

Post 2015 HFA (UNISDR, 
2014) 

Sub-indicator of  
Sensitivity in  ND-GAIN 
Index 2014 

Post 2015 HFA (UNISDR, 
2014); Sub-indicator of 
the Global Climate 
Change Index 
(Germanwatch 2014); 
Vulnerability indicator in 
INFORM 
Post 2015 HFA (UNISDR, 
2014); Sub-indicator of 
Sensitivity in ND-GAIN 

UN Global Risk 
Assessment ; 
http://www.preventionw
eb.net/english/hyogo/ga
r/2013/en/home/data-
platform.html  
http://data.worldbank.o
rg/indicator/EN.POP.EL5
M.ZS 

National disaster loss 
databases and  EM DAT 

National disaster loss 
databases and UN 
population statistics 

Post 2015 HFA (UNISDR, 
2014) 

UN Global Risk 
Assessment; 
http://www.preventionw
eb.net/english/hyogo/ga
r/2013/en/home/data-
platform.html 

Large scale mortality is 
an indicator of both high 
levels of risk as well as 
limitations in disaster risk 
management 

Countries with a high 
proportion of their 
population at risk of 
being affected by 
disasters will have high 
degrees of  livelihood 
interruption and threats 
to human development 
The higher the fiscal AAL 
(the annual risk to 
publicly owned assets, or 
for which governments 
are responsible for 
replacing) per inhabitant, 
the higher the sovereign 
disaster risk, for which is 

96 

 
 
 
 
each citizen is 
responsible 

All 

Households  Housing damage affects 

Housing 
damage in 
extensive 
disasters per 
100 000 
population 

Housing damage / 
100 000 population 
(five-year moving 
average) 

Kilometres of 
roads damaged 
as % of road 
network 

Kilometres of roads 
damaged / km road 
network (five-year 
moving average) 

All 

Industry, 
Agriculture 
and Trade 

Number of 
hectares of 
crops lost per 
total crop area  

Number of hectares of 
crops lost / total crop 
area (five-year 
moving average) 

Numbers of 
health facilities 
damaged as % 
of total number 
of health 
facilities  

% of health facilities 
damaged out of total 
number of health 
facilities (five-year 
moving average) 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

All 

Agriculture 

Health and 
Households 

Post 2015 HFA (UNISDR, 
2014) 

National disaster loss 
databases  and EM DAT 

Post 2015 HFA (UNISDR, 
2014) 

National disaster loss 
databases  and EM DAT 

Post 2015 HFA (UNISDR, 
2014) 

National disaster loss 
databases  and EM DAT 

Post 2015 HFA (UNISDR, 
2014) 

National disaster loss 
databases and World 
Bank Development 
Indicators 

both the lives and 
livelihoods of low-income 
urban and rural 
households. Most 
housing damage is 
spread over extensive 
disasters zones and 
occurs in low-income 
areas. 
Roads are critical to the 
functioning of local 
economies and to small 
and medium enterprises. 
This indicator can 
therefore provide a proxy 
of disaster impacts in the 
employment and 
productive sectors 
Loss of agricultural 
production is particularly 
critical for rural 
households and 
contributes to continued 
or worsening rural 
poverty 
Damaged health facilities 
are a proxy for disaster 
impacts in the health 
sector. Low-income 
households in particular 
are dependent on 
publicly provided primary 
health facilities. 

97 

 
 
Numbers of 
schools 
damaged as % 
of total number 
of schools  

% of schools 
damaged out of total 
number of schools 
(five-year moving 
average) 

Percentage of 
population 
below 5-m 
elevation 

Population 
affected by 
droughts 

Proportion of 
population living in 
areas where the 
elevation is 5-m or 
less above sea level 
People affected by 
droughts 1990-2013 - 
average annual 
population affected 
(inhabitants) 

Population 
density 

Population/m2 

Population 
exposed to 
floods 

Population 
exposed to 
hazards 

Physical exposure to 
floods - average 
annual population 
(2010 as the year of 
reference) exposed 
(inhabitants) 
Sum of people 
exposed to all hazards 
over the period 
considered (e.g. a 
year) 

All 

Households  Damaged schools are a 

proxy for disaster 
impacts in education. The 
interruption of schooling 
negatively affects future 
educational and hence 
economic prospects  
Indicates how many 
people are sensitive to 
risks arising from sea-
level rise and storm 
surges 

Coastal 
Floods, 
Cyclones and 
Sea-level rise 

Households 
and related 
economic 
activities 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 
All 

Health and 
Households 

Households  Higher numbers of 

people increase pressure 
on the environment for 
resources. Relative flood 
mortality is higher in less 
populated than in 
densely populated 
countries 

Post 2015 HFA (UNISDR, 
2014) 

National disaster loss 
databases and World 
Bank Development 
Indicators 

Füssel, 2010; Sub-
indicator of sensitivity in 
ND-GAIN Index 2014 

Sub-indicator of Hazard 
Exposure in INFORM 
2014 

http://sedac.ciesin.colu
mbia.edu/data/set/nagd
c-population-landscape-
climate-estimates-v3 

http://www.emdat.be 

Birkmann 2007; de 
Oliveira Mendes (2009), 
Tate et al. (2010) Khan 
(2012), Lee (2014), 
Brooks et al., 2005 

http://data.worldbank.o
rg/indicator/EN.POP.DN
ST 

Floods 

Health and 
Households 

Sub-indicator of Hazard 
Exposure in  INFORM 
2014 

http://preview.grid.unep
.ch/ 

Sub-indicator of 
Exposure in  the World 
Risk Index 2014 

http://preview.grid.unep
.ch/ 

All 

All 

The knowledge of the 
population exposed is 
fundamental to raising 
awareness and 
developing protection 
measures (e.g. 
identification of suitable 
shelters) and evacuation 
strategies (e.g. 
development of 

98 

 
 
 
 
 
evacuation routes). 

Population 
exposed to 
sea-level rise 
(possible from 
1 m to 6 m) 

Percentage of 
population exposed to 
1-m 
sea-level rise 

Coastal floods, 
cyclones and 
sea-level rise 

This indicator gives a 
general overview of the 
number of people living 
within the most exposed 
(low-lying) areas such as 
coastal zones 

Perch- Nielsel, 2010; 
WRI, 2014 
Perch- Nielsel 2010 
(Number of people 
additionally inundated 
once a year with a sea 
level rise of 50 cm) 

Population 
exposed to 
tropical 
cyclones 

Physical exposure to 
surges from tropical 
cyclone - average 
annual population 
(2010 as the year of 
reference) exposed 
(inhabitants) per 
country 

Cyclones, 
tornados, 
storms 

Health and 
Households 

Sub-indicator of INFORM 
2014 and World Risk 
Index 2014 

99 

http://geodata.grid.une
p.ch/mod_download/do
wnload.php and 
https://www.cresis.ku.e
du/data/sea-level-rise-
maps 
Data sources 
GRUMP Population 
data:Columbia 
University, Center for 
International Earth 
Science 
Information Network 
(CIESIN) 
http://geodata.grid.une
p.ch/mod_download/do
wnload.php 
Sea level rise from 1m 
to 6m: University of 
Kansas Center for 
Remote Sensing of Ice 
Sheets (CReSIS) 
https://www.cresis.ku.e
du/data/sea-level-rise-
maps 
http://preview.grid.unep
.ch/ 

 
 
 
 
Population 
growth (Annual 
%) 

Risk adjusted 
public debt 

Population growth 
(annual %) is the 
exponential rate of 
growth of midyear 
population from year 
t-1 to t, expressed as 
a percentage. 
Indicator to be 
constructed from 
Fiscal Annual Average 
Loss and public debt 

All 

All 

All 

All 

Share of 
coastal area 

km of coastline (scale 
by land area) 

Coastal floods, 
cyclones and 
sea-level rise 

Total damages 
relative to GDP  

Damages of past 
events/GDP 

Total economic 
damages 

Sum of total damages 
related to all hazards 
over the period 
considered 

All 

All 

Households 
and related 
economic 
activities, 
tourism 
All 

Possibly all, 
depending 
on hazards 

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/SP.POP.GR
OW 

Post 2015 HFA (UNISDR, 
2014) 

http://www.preventionw
eb.net/english/hyogo/ga
r/2013/en/home/data-
platform.html 

Füssel 2009, Brooks et 
al., 2005 

http://preview.grid.unep
.ch/ 

Birkman 2007; Sub-
indicator of the Global 
Climate Change Index 
2014 
Forgette and Boening 
(2010); Hallegatte 
(2014); Akter and Mallick 
2013 

http://data.worldbank.o
rg/data-catalog/world-
development-indicators 
http://www.emdat.be 
http://www.emdat.be 

High population growth 
may translate into 
rapidly increasing 
exposure of people to 
hazards 

Fiscal AAL represents a 
contingent liability for 
governments, and is 
often invisible when 
accounting for public 
debt. For countries with 
already high or 
unsustainable levels of 
public debt, disaster risk 
represents another 
critical debt layer. 

Total economic damages 
describe the extent of 
economic impacts caused 
by climate-related 
hazards over the period 
considered 

100 

 
 
 
 
 
 
 
 
Definition 

Vulnerability Indicators (alphabetical order) 
Sectors 
Indicator 
affecte
name 
d 
Households 
and related 
economic 
activities 

Age 
dependency 
ratio 

Relevant 
Hazards 

All 

Ratio of the 
population <15 and 
>65 years of age to 
the population 
between 19 and 65 
years of age 

Average annual 
number of 
international 
tourists per 
km2 land over 
the past five 
years 

Average 
number of 
people per 
household 

All 

Average annual 
number of 
international tourists 
per kmq land over the 
past five years 

Average number of 
people per household 

All 

Average ratio 
of productivity: 
fisheries catch 
over the past 
five years 

Rate of extraction / 
the potential for the 
environment to 
replenish those stocks 
(productivity) 

Coastal floods, 
cyclones and 
sea-level rise 

Economic 
impacts on 
tourism 

Households 
and related 
economic 
activities 

Marine 
ecosystems
; economic 
impacts on 
the fishing 
industry 

Rationale 

References 

Data source  

http://data.worldbank.o
rg/indicator/SP.POP.DPN
D 

Cutter et al. (2003); 
Shah 2013; Wolf et al, 
2010; Susceptibility in 
World Risk Index; 
Resilience in post 2015 
HFA; Sensitivity in ND-
GAIN 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Bjarnadottir et al., 2011 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

http://www.vulnerability
index.net/ 
original source- WTO  
http://i-
tip.wto.org/services/(S(
dczrer0x1sb4i3sg1l0i0m
0l))/ChartResults.aspx 

http://unstats.un.org/un
sd/Demographic/sconcer
ns/popsize/default.htm 

http://www.vulnerability
index.net/ 
Data NOT AVAILABLE in 
the EVI website. The 
index has not been 
renewed since 2004 

The direct effects of 
extreme weather may 
disproportionately affect 
the old and the young. A 
high age dependency 
ratio means a high 
proportion of children 
and elderly people 
compared to the working 
age population. This 
lowers resilience, 
particularly in the case of 
death or injury of a 
working-age adult. 

This indicator captures 
the risk of damage to 
fisheries stocks by 
examining rates of 
extraction (C) in relation 
to the potential for the 
environment to replenish 
those stocks 
(productivity - P). A 
small P:C ratio means 

101 

 
 
 
 
Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

Agriculture 
and macro-
economic 
impacts 

All 

Health 

greater vulnerability of 
fisheries 

A high dependency on 
external resources, 
usually on foreign aid, is 
an indicator of weakness 
in internal capacity and 
thus vulnerability to 
climate-related health 
shocks  

Brooks et al., 2005; Sub-
indicator of Sensitivity in 
ND-GAIN 

http://data.worldbank.o
rg/indicator/SL.AGR.EMP
L.ZS 

Sub-indicator of 
Sensitivity in the ND-
GAIN Index 2014 

http://data.worldbank.o
rg/indicator/SH.XPD.EXT
R.ZS 

All 

All 

A higher proportion of 
imported energy implies 
higher sensitivity to price 
increases or supply crises  

Sub-indicator of 
Sensitivity in  the ND-
GAIN Index 2014 

http://data.worldbank.o
rg/indicator/EG.IMP.CO
NS.ZS 
sensitivity to price 
increases/ supply crises 

Dependence on 
agriculture 

Agricultural 
employees (% of total 
population) 

Dependency on 
external 
resources for 
health services 

Dependency on 
imported 
energy 

This indicator 
measures the 
proportion of total 
expenditure on 
expenditure on health 
or related services 
that are provided by 
entities external to 
the country  
Proportion of energy 
use from imports. 
Energy use refers to 
use of primary energy 
before transformation 
to other end - use 
fuels, according to the 
WDI, equal to 
indigenous production 
plus imports and 
stock changes, minus 
exports and fuels 
supplied to ships and 
aircraft engaged in 
international transport 

102 

 
 
 
Post 2015 HFA (UNISDR, 
2014) 

http://popstats.unhcr.or
g/PSQ_TMS.aspx 

Displaced 
people (% of 
population) 

Displaced People 

All 

Ecological 
footprint 

Food import 
dependency 

Freshwater 
withdrawal 
rate 

Difference between 
the number of 
hectares of land and 
water (both within 
and outside the 
country) needed to 
supply the average 
demand of the 
population and the 
country’s supply of 
land and water  

Imports of food/ total 
supply. Dependency 
rate is measured by 
the proportion of 
cereal consumption 
obtained from 
imports. 
Annual freshwater 
withdrawal / the total 
renewable water 
resources (excluding 
desalinated water)  

Groundwater 
recharge per 
capita 

Groundwater recharge 
per capita 

All 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 
Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

Health, 
households 
and related 
economic 
activities 

Ecosystems 
and related 
economic 
activities 

Displaced people are 
normally a particularly 
at-risk group and are 
more likely to live in 
vulnerable conditions in 
hazard-prone areas , 
with less access to basic 
services than low-income 
households in general 
A country with a surplus 
(more supply than 
demand) has the 
capacity to produce more 
from within its 
boundaries and thus is 
likely to have more 
options to adapt to a 
changing climate 

Post 2015 HFA (UNISDR, 
2014), Sub-indicator of 
Sensitivity in the ND-
GAIN Index 2014 

All 

Countries highly 
dependent on food 
imports are susceptible 
to shocks in food prices. 
Climate change will 
accentuate price volatility 

Sub-indicator of 
Sensitivity in the ND-
GAIN Index 2014 

Ecosystems 

It is a Proxy for 
countries’ water stress  

Sub-indicator of 
Sensitivity in the ND-
GAIN Index 2014 

Brooks et al., 2005 

Households 
and water-
dependent 
economic 
activities 

103 

or 
http://www.unhcr.org/p
ages/49c3646c4d6.html 

http://www.footprintnet
work.org/en/index.php/
GFN/page/footprint_dat
a_and_results 
Difficulty to find data. 
Not clear as context 
National Accounts and 
Country Risk Rankings 
data are available under 
license for academic and 
commercial purposes.  

http://faostat3.fao.org/f
aostat-
gateway/go/to/downloa
d/FB/BC/E 

http://www.fao.org/nr/
water/aquastat/data/qu
ery/index.html?lang=en 
Data available in 5 year 
intervals. 

http://www.fao.org/nr/
water/aquastat/data/qu
ery/index.html?lang=en 

 
 
 
 
 
 
 
Industrial 
water 
consumption 

Natural capital 
dependency 

Annual freshwater 
withdrawals refer to 
total water 
withdrawals, not 
counting evaporation 
losses from storage 
basins. Withdrawals 
also include water 
from desalination 
plants in countries 
where they are a 
significant source. 
Withdrawals can 
exceed 100% of total 
renewable resources 
where extraction from 
non-renewable 
aquifers or 
desalination plants is 
considerable or where 
there is significant 
water reuse. 
Withdrawals for 
industry are total 
withdrawals for direct 
industrial use 
(including withdrawals 
for cooling 
thermoelectric 
plants).  
Ratio of natural 
capital to the total 
wealth of one country 

Industry 

Drought, dry 
spells, stress 
on surface 
water 
resources  

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

http://data.worldbank.o
rg/indicator/ER.H2O.FWI
N.ZS/countries/1W?displ
ay=graph, 

original source: 
http://www.fao.org/nr/
water/aquastat/data/qu
ery/index.html?lang=en 

All 

Ecosystems 
and related 
economic 
activities 

Sub-indicator of 
Sensitivity in the ND-
GAIN Index 2014 

http://index.gain.org/ab
out/download  
Based on world bank 
data. Total wealth 
estimates and per capita 
wealth estimates for 
1995, 2000, and 2005. 

104 

 
 
 
 
 
Population 
with access to 
improved 
water supply 

Percentage of 
population with 
reasonable access 
(within one km) to an 
adequate amount of 
water (20 litres per 
person) through a 
household connection, 
public standpipe well 
or spring, or rain 
water system 

Drought, dry 
spells, stress 
on surface 
water 
resources 

Households  People without clean 

water sources are 
vulnerable to diseases 
caused by unclean water 
and could become more 
vulnerable in the 
aftermath of a hazard 

Füssel, 2010; Shah et al 
2013; "Susceptibility in 
the World Risk Index; 
Adaptive capacity in ND-
Gain; Lack of coping 
capacity in INFORM- 
INFORM names it as 
""Improved water source 
(% of population with 
access)"" and suggests 
as data sources: WHO; 
UNICEF 
http://www.wssinfo.org/
data-estimates/table/  
ND-GAIN uses WB data 
http://data.worldbank.or
g/indicator/SH.H2O.SAFE
.ZS " 
Brooks et al., 2005; Sub 
indicator of Susceptibility 
in ND-GAIN 2014 

http://mdgs.un.org/uns
d/mdg/metadata.aspx?i
ndicatorid=30 and 
http://data.worldbank.o
rg/indicator/SH.H2O.SA
FE.ZS and 
www.wssinfo.org/data-
estimates/table/ 

http://data.worldbank.o
rg/indicator/SP.RUR.TOT
L.ZS 

Households 
and 
agriculture 

Health and 
Households 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 
Drought, dry 
spells, stress 
on surface 
water 
resources 

Rural 
population 

Rural population (% 
of total population) 

Rural 
population with 
access to safe 
water (%) 

Access to a safe water 
source refers to the 
percentage of the 
population using an 
improved drinking 
water source. The 
improved drinking 
water source includes 
piped water on 
premises (piped 
household water 
connection located 
inside the user’s 
dwelling, plot or 
yard), and other 
improved drinking 
water sources (public 
taps or standpipes, 
tube wells or 

Brooks et al., 2005 

http://data.worldbank.o
rg/indicator/SH.H2O.SA
FE.RU.ZS 

People without safe 
water sources are 
vulnerable to diseases 
caused by unclean water 
and could become more 
vulnerable in the 
aftermath of a hazard 

105 

 
 
 
Value of 
production 
equipment 

Water stress 

boreholes, protected 
dug wells, protected 
springs, and rainwater 
collection). 
Machinery and 
transport equipment 
(% of value added in 
manufacturing). Value 
added in 
manufacturing is the 
sum of gross output 
minus the value of 
intermediate inputs 
used in production for 
industries classified in 
ISIC major division D. 
Machinery and 
transport equipment 
correspond to ISIC 
divisions 29, 30, 32, 
34, and 35. 
Water stress occurs 
when the demand for 
water exceeds the 
available amount 
during a certain 
period or when poor 
quality restricts its 
use. 

All 

Industry 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

http://data.worldbank.o
rg/indicator/NV.MNF.MT
RN.ZS.UN 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

Health, 
households 
and related 
economic 
activities, 
ecosystems 

An unsustainable 
withdrawal of renewable 
water resources can 
increase land 
degradation and drought 
risk 

Post 2015 HFA (UNISDR, 
2014) 

http://www.fao.org/nr/
water/aquastat/data/qu
ery/index.html?lang=en 

106 

 
 
 
 
 
 
 
Adaptive capacity indicators (alphabetical order) 
Indicator name  Definition 

Rationale 

Relevant 
Hazards 

Sectors 
affected 

References 

Data Source  

Access to 
electricity 

Adoption of 
NAPAs 

Biodiversity 
and habitat 
protection 

Control of 
corruption 

Access to electricity is 
the percentage of 
population with access 
to electricity. 
Electrification data are 
collected from 
industry, national 
surveys and 
international sources. 
National Adaptation 
Plans s are defined 
and adopted (Y/N) 
Ordinal scale with a 
range from 0 (very 
poor environmental 
performance) to 100 
(excellent 
environmental 
performance), 
aggregated from 
three performance 
indicators: Terrestrial 
Protected Areas 
(National Biome 
Weights), Terrestrial 
Protected Areas 
(Global Biome 
Weights), Marine 
Protected Areas and 
Critical Habitat 
Protection 
Reflects perceptions 
of the extent to which 
public power is 
exercised for private 
gain, including both 
petty and grand forms 
of corruption, as well 

All 

All 

This indicator is 
indicative of the capacity 
to delivery energy to a 
country’s citizens and 
businesses  

Sub-indicator of Adaptive 
Capacity in the ND-GAIN 
Index 2014 and Lack of 
coping capacity in 
INFORM 2014 

All 

All 

All 

HFA Reporting 

Sub-indicator of the 
World Risk Index 2014 

Ecosystems 
and species  

Habitat protection is a 
necessary but not 
sufficient condition for 
the conservation of 
biodiversity and 
ecosystem services that 
are critical to sustaining 
human life and well-
being 

http://data.worldbank.o
rg/indicator/EG.ELC.ACC
S.ZS and 
http://www.worldenergy
outlook.org/resources/e
nergydevelopment/ener
gyaccessdatabase/ 

http://www.preventionw
eb.net/english/hyogo/pr
ogress/?pid:228&pil:1 
http://epi.yale.edu/epi/i
ssue-
ranking/biodiversity-
and-habitat 

All 

All 

107 

Post 2015 HFA (UNISDR, 
2014); Exposure 
indicator in ND-GAIN  

http://info.worldbank.or
g/governance/wgi/index
.aspx#home 
Found as part of the 
World Bank Worldwide 
Governance Indicators. 
Scale from -2.5 to 2.5 

 
 
 
 
as "capture" of the 
state by elites and 
private interests. 

Dam Capacity 

Dam Capacity per 
capita 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

Degree of 
economic 
diversification 

Disaster 
preparedness 

Ecosystem 
vitality 

Ecosystem 
vitality: 
Agriculture 

Manufacturing, value 
added (% of GDP). 
Manufacturing refers 
to industries 
belonging to ISIC 
divisions 15-37. Value 
added is the net 
output of a sector 
after adding up all 
outputs and 
subtracting 
intermediate inputs 
Monitoring from HFA 

Ecosystem vitality 
measures ecosystem 
protection and 
resource management 

All 

All 

All 

Ordinal scale with a 
range from 0 (very 
poor environmental 
performance) to 100 
(excellent 
environmental 

Drought, dry 
spells, stress 
on surface 
water 
resources and 
floods 

Water-
related 
economic 
activities, 
electricity 
production 
and 
ecosystems 
Industry 

Dam capacities are an 
appropriate measure of 
the capacity to cope with 
changes brought by 
climate change regarding 
the temporal and 
geographic distribution of 
water resources 
A community with a 
relatively diverse local 
economy is better able to 
adjust to changes that 
have a significant impact 
on a particular sector or 
sectors of employment 

All 

Ecosystems  Healthy ecosystems 
providing regulatory 
ecosystem services 
moderate many weather- 
and climate-related 
hazards 
Agriculture is one the 
economic activities that 
has the greatest impacts 
on ecosystems. 

Agriculture 
and 
ecosystems 

108 

Sub-indicator of Adaptive 
Capacity of the ND-GAIN 
Index 2014 

http://atlas.gwsp.org/in
dex.php?option=com_co
ntent&task=view&id=20
7&Itemid=68 

Hallegatte, 2014 

http://data.worldbank.o
rg/indicator/NV.IND.MA
NF.ZS 

Sub-indicator of Adaptive 
Capacity in the ND-GAIN 
Index 

http://www.preventionw
eb.net/applications/hfa/
qbnhfa/home 

Post 2015 HFA (UNISDR, 
2014);Adaptive capacity 
in  WRI 2014 

http://data.worldbank.o
rg/indicator/NV.IND.MA
NF.ZS 

http://epi.yale.edu/ 

Sub-indicator of Adaptive 
capacity in the World 
Risk Index 2014 

http://epi.yale.edu/ 

 
 
 
Engagement in 
international 
environmental 
conventions 

Forest cover 
change rate (% 
per year) 

performance), 
aggregated from two 
performance 
indicators: 
Agricultural Subsidies 
(AGSUB) and 
Pesticide Regulation 
(POPs) 
Ratio of a country’s 
current status of 
convention 
engagement over the 
maximum 
engagement among 
all countries 
The Forest cover 
change rate indicator 
measures the percent 
change in forest cover 
between 2000 and 
2012 in areas with 
greater than 50% tree 
cover. Ordinal scale 
with a range from 0 
(very poor 
environmental 
performance) to 100 
(excellent 
environmental 
performance), 
aggregated from 
three performance 
indicators: areas of 
deforestation (forest 
loss), reforestation 
(forest restoration or 
replanting) and 
afforestation 
(conversion of bare or 
cultivated land into 
forest) 

Sub-indicator of the ND-
GAIN Index 2014 
http://sedac.ciesin.colum
bia.edu/entri/index.jsp 

http://data.worldbank.o
rg/indicator/NV.IND.MA
NF.ZS 

http://epi.yale.edu 

Sub-indicator of the 
World Risk Index  2014 
and WDIs; post 2015 
HFA (UNISDR, 2014) and 
Environmental 
Vulnerability Index 

This indicates a country’s 
capacity to reach 
agreement on 
appropriate actions 
internally and engage in 
multilateral negotiations 
on environmental issues 
Reduction in the extent 
of forest cover has 
significant negative 
implications for 
ecosystem services and 
habitat protection. 
Forests are carbon sinks 
to combat global climate 
change and in regulating 
the hydrological system 

All 

All 

Ecosystems 
and related 
economic 
activities 

Biodiversity, 
ecosystem 
resilience, the 
capacity of a 
country to 
attenuate 
pollution, 
prevention of 
soil loss and 
ongoing soil 
development, 
reduction of 
runoff, 
recharging of 
ground waters 
and soil 
formation 

109 

 
 
Government 
health 
expenditure 
per capita 

Hyogo 
Framework for 
Action 

Insurance 
penetration 

Per capita total 
expenditure on health 
(TEH) expressed in 
Purchasing Power 
Parities (PPP) 
international dollars. 
The indicator for a 
country’s Disaster 
Risk Reduction (DRR) 
activity comes from 
its score of Hyogo 
Framework for Action 
(HFA) self-assessment 
progress reports. HFA 
progress reports 
assess strategic 
priorities in the 
implementation of 
DRR actions and 
establish baselines on 
levels of progress 
achieved in 
implementing the 
HFA's five priorities 
for action. 
Insurance coverage 
(except life insurance) 

Measles (MCV) 
immunisation 
coverage 
among 1-year-
olds (%) 

The percentage of 
children under one 
year of age who have 
received at least one 
dose of measles-
containing vaccine in 
a given year. 

All 

Health and 
households 

All 

All 

Sub-indicator of lack of 
coping capacity in 
INFORM 2014, Adaptive 
Capacity in WRI 2014 

Sub-indicator of Lack of 
Coping capacity in 
INFORM 2014 

http://apps.who.int/gho
data/ 

http://preventionweb.ne
t/applications/hfa/qbnhf
a/ 

All 

All 

When insurance 
penetration is low, asset 
destruction caused by 
natural disasters could 
severely hamper capital 
accumulation and growth 
potential 

Baritto et al., 2009; Sub-
indicator of coping 
capacity in  the World 
Risk Index 2014; post 
2015 HFA  (UNISDR, 
2014) 

Data not publicly 
available Munich Re, 
Swiss Re 

All 

Health and 
households 

Sub-indicator of lack of 
coping capacity in  
INFORM 2014 

http://apps.who.int/gho
data/ 

110 

 
 
 
 
 
 
Paved Roads 

Per capita net 
savings 

Physician 
density 

The roads surfaced 
with crushed stone 
(macadam) and 
hydrocarbon binder or 
bituminised agents, 
with concrete, or with 
cobblestones, as a 
percentage of all the 
country's roads, 
measured in length  
Gross savings are 
calculated as gross 
national income minus 
total consumption, 
plus net transfers. 
Data are in current US 
dollars. 
Number of physicians 
per 10 000 inhabitants 

All 

All 

Industry, 
agriculture 
and Trade 

Unpaved roads are more 
vulnerable to hazards 
such as floods and 
landslides 

Brooks et al., 2005; Sub-
indicator of the ND-GAIN 
Index; post 2015 HFA  
(UNISDR, 2014) 

http://data.worldbank.o
rg/indicator/IS.ROD.PAV
E.ZS 

All 

All 

Low per capita savings 
implies a lower capacity 
to buffer losses and 
recover, therefore low 
resilience to disaster loss  

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/NY.GNS.ICT
R.CD 

Population 
with access to 
improved 
sanitation  

Drought, dry 
spells, stress 
on surface 
water 
resources 

Improved sanitation 
facilities comprise 
flush toilets, piped 
sewer systems, septic 
tanks, flush/pour flush 
to pit latrines, 
ventilated improved 
pit latrines, pit 
latrines with slab and 
composting toilets 

Households 
and related 
economic 
activities, 
health 

The number of medical 
staff, including 
physicians, nurses and 
midwives, reflects the 
capacity of a country to 
cope with exacerbated 
health risks brought on 
by climate change. 
Physicians, nurses, and 
midwives have similar 
weighting 
Households  Access to sanitation is 

particularly crucial to 
build up preparedness to 
various natural disasters 
exacerbated by climate 
change. People without 
improved sanitation are 
susceptible to diseases 
and can become more 
vulnerable following a 
hazard 

111 

Halsnæs and Verhagen, 
2007; Sub-indicator of 
the World Risk Index 
2014 and the ND-GAIN 
index 2014 and Lack of 
Coping capacity in 
INFORM 2014; post 2015 
HFA (UNISDR, 2014) 

Füssel, 2010; Brooks et 
al., 2005; Sub-indicator 
of Adaptive capacity in  
the ND-GAIN Index 
2014, Sub-indicator of 
Susceptibility in the 
World Risk Index  2014, 
MDG 7.9 (UN 2005) and 
WDIs and sub indicator 
of Lack of coping 
capacity in INFORM 2014 

http://www.who.int/gho
/health_workforce/physi
cians_density/en/ 

http://unstats.un.org/un
sd/mdg/Metadata.aspx?
IndicatorId=31 and 
http://data.worldbank.o
rg/indicator/SH.STA.ACS
N and 
www.wssinfo.org/data-
estimates/table/ 

 
 
Regulation 
quality 

Road density 

Voice and 
accountability 

Reflects perceptions 
of the ability of the 
government to 
formulate and 
implement sound 
policies and 
regulations that 
permit and promote 
private sector 
development 
Road density is the 
ratio of the length of 
the country's total 
road network to the 
country's land area. 
The road network 
includes all roads in 
the country: 
motorways, highways, 
main or national 
roads, secondary or 
regional roads, and 
other urban and rural 
roads. 
Reflects perceptions 
of the extent to which 
a country's citizens 
are able to participate 
in selecting their 
government, as well 
as freedom of 
expression, freedom 
of association, and a 
free media 

All 

All 

The capacity to regulate 
the private sector, 
including households, will 
influence the 
effectiveness of disaster 
risk management 
instruments such as 
building codes and land-
use plans. 

Post 2015 HFA (UNISDR, 
2014) 

http://info.worldbank.or
g/governance/wgi/index
.aspx#home 

All 

Households
, Industry, 
agriculture 
and Trade 

Lack of Coping capacity 
in INFORM 2014 

http://www.irfnet.ch/ 

Keefer et al. (2011), 
Kahn (2005), and 
Raschky and Schwindt 
(2008); Post 2015 HFA 
(UNISDR, 2014) 

http://info.worldbank.or
g/governance/wgi/index
.aspx#home 

All 

All 

The extent to which 
citizens are able to hold 
others, including 
government, to account 
for their actions is critical 
not only to ensure that 
disaster risk 
management plans are 
implemented but also to 
strengthen accountability 
in the case of actions 
that transfer risks from 
one sector to another 

112 

 
 
 
 
 
 
 
Mitigation capacity indicators (alphabetical order) 
Indicator 
name 

Relevant 
Hazards 

Definition 

Rationale 

Sectors 
affecte
d 
All 

All 

% of electricity 
production 
from 
renewable 
sources, 
excluding 
hydroelectric  

Electricity production 
from renewable 
sources, excluding 
hydroelectric, includes 
geothermal, solar, 
tides, wind, biomass, 
and biofuels (% of 
total) 

Countries with a 
significant or growing 
proportion of electricity 
production from 
renewable sources are 
likely to be more 
committed to mitigating 
global climate change 
and its effects as well as 
to environmental 
sustainability 

References 

Data Source  

Development indicator in 
the Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.o
rg/indicator/EG.ELC.RN
WX.ZS 

Carbon 
Emissions per 
unit of GDP 

CO2 intensity 
of the power 
sector, and of 
new power 
generation 
capacity 
installed (gCO2 
per kWh) 

Carbon dioxide 
emissions are those 
stemming from the 
burning of fossil fuels 
and the manufacture 
of cement. They 
include carbon dioxide 
produced during 
consumption of solid, 
liquid, and gas fuels 
and gas flaring. (kg 
per PPP US$ of GDP) 
The amount 
(measured in 
grammes) of CO2 
emissions per unit of 
electricity (measured 
in kilowatt hour) 
generated from the 
power sector as a 
whole (total 
capacities); and from 
new capacities 

All 

All 

MDG 7.2 (UN 2005); Post 
2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/EN.ATM.CO
2E.PC 

Proposed SDG 83 (UN, 
2014) 

http://data.worldbank.o
rg/indicator/EN.ATM.CO
2E.EG.ZS 

All 

All 

Understanding what 
drives the evolution of 
the CO2 intensity of the 
power sector is important 
to define the appropriate 
policies to reduce the 
CO2 emissions of this 
sector 

113 

 
 
 
 
installed (between two 
dates of measurement 
of the indicator) 

The proposed indicator 
is defined as: the 
amount (measured in 
grammes) of CO2 
emissions per vehicle, 
kilometre travelled in 
aggregate; and per 
passenger kilometre 
travelled (pkm) for 
new cars, and per 
tonne kilometre 
travelled (tkm) for new 
trucks (between two 
dates of measurement 
of the indicator) 
Energy use refers to 
use of primary energy 
before transformation 
to other end-use fuels, 
which is equal to 
indigenous production 
plus imports and stock 
changes, minus 
exports and fuels 
supplied to ships and 
aircraft engaged in 
international transport. 
(kg of oil equivalent 
per capita) 
GHG net 
emissions/removals by 
AFOLU refers to 
changes in 
atmospheric levels of 
all greenhouse gases 
attributable to 
agriculture, forest and 

CO2 intensity 
of the 
transport 
sector 
(gCO2/vkm), 
and of new 
cars 
(gCO2/pkm) 
and trucks 
(tCO2tkm) 

Energy 
consumption 
per capita 

Net GHG 
emissions in 
the Agriculture, 
Forest and 
Other Land Use 
(AFOLU) 
sector (tCO2e)  

All 

All 

Understanding what 
drives the evolution of 
the CO2 intensity of the 
transport sector is 
important to define 
appropriate policies to 
reduce the CO2 
emissions of that sector 

Proposed SDG 84 (UN, 
2014) 

http://data.worldbank.o
rg/indicator/EN.CO2.TR
AN.ZS 

All 

All 

Proposed SDG 85 (UN, 
2014) 

http://data.worldbank.o
rg/indicator/EG.USE.PCA
P.KG.OE 

All 

All 

Proposed SDG 85 (UN, 
2014) 

http://data.worldbank.o
rg/indicator/EN.CLC.GH
GR.MT.CE 

114 

 
 
 
 
land-use change 
activities, including but 
not limited to (1) 
emissions and 
removals of CO2 from 
decreases or increases 
in biomass stocks due 
to forest management, 
logging, fuel wood 
collection, etc.; (2) 
conversion of existing 
forests and natural 
grasslands to other 
land uses; (3) removal 
of CO2 from the 
abandonment of 
formerly managed 
lands (e.g. croplands 
and pastures); and (4) 
emissions and 
removals of CO2 in soil 
associated with land-
use change and 
management. 

115 

 
 
 
 
 
Rationale 

References 

Data sources 

Definition 

Development indicators (alphabetical order) 
Sectors 
Indicator 
affecte
name 
d 
Households 
and related 
economic 
activities 

Population aged 15 
years and above who 
can read and write a 
short simple statement 
on their everyday life 

Relevant 
Hazards 

Adult literacy 
rate 

All 

Literacy could be an 
essential indicator, when 
empowering people on 
hazard risk reduction 

All 

Health and 
households 

Removal of economically 
active 
population 

All 

All 

All 

All 

The economies of 
countries with a positive 
balance of payments to 
GDP ratio are likely to be 
more resilient to 
reductions in domestic 
demand following 
disasters, but could be 
less resilient to disasters 
in key export markets 
High existing debt limits 
the capacity of a 
government to recover 

AIDS/HIV 
infection (% of 
adults) 

Balance of 
payments (net 
current 
account % of 
GDP) 

Central 
government 
debt, total (% 
of GDP) 

An HIV/AIDS epidemic 
is defined by the HIV 
prevalence in the 
general population. 
HIV prevalence is the 
percentage of the 
population living with 
HIV 
Current account 
balance is the sum of 
net exports of goods 
and services, net 
primary income, and 
net secondary income 

Debt is the entire stock 
of direct government 
fixed-term contractual 
obligations to others 
outstanding on a 
particular date. It 
includes domestic and 
foreign liabilities such 
as currency and money 
deposits, securities 

116 

Brooks et al., 2005; Sub-
indicator of Adaptive 
Capacity in the World 
Risk Index 2014; MDG 
2.3 (UN 2005); post 
2015 HFA; and Lack of 
Coping capacity in  
INFORM 2014 
Brooks et al., 2005; 
Vulnerability in INFORM 
2014 

http://hdr.undp.org/en/co
ntent/adult-literacy-rate-
both-sexes-ages-15-and-
older and 
http://data.worldbank.org
/indicator/SE.ADT.LITR.Z
S 

http://apps.who.int/gho
/indicatorregistry/App_M
ain/view_indicator.aspx?
iid=334; 
http://www.unaids.org/
en/dataanalysis/datatool
s/aidsinfo 

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/BN.CAB.XO
KA.GD.ZS 

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/GC.DOD.TO
TL.GD.ZS 

 
 
 
 
 
 
other than shares, and 
loans. It is the gross 
amount of government 
liabilities reduced by 
the amount of equity 
and financial 
derivatives held by the 
government. Because 
debt is a stock rather 
than a flow, it is 
measured as of a given 
date, usually the last 
day of the fiscal year 
The proportion of 
children under five 
whose weight for 
height is more than 
two standard 
deviations below the 
median for the 
international reference 
population aged 0-59 
Education expenditure 
as % of GNP 

Clean energy is non-
carbohydrate energy 
that does not produce 
carbon dioxide when 
generated. It includes 
hydropower and 
nuclear, geothermal, 
and solar power, 
among others. 
% of population living 
on US$ 1.25 per day or 
less (purchasing power 
parity) 

All 

All 

All 

All 

Child 
Malnutrition 

Educational 
commitment 1 

Energy source 
diversification 

Extreme 
poverty 

Households 
and  health 

Malnutrition can be a 
product of different 
circumstances relating to 
development policies and 
strategies, such as 
agricultural measures for 
food availability 

Health and 
households 

All 

Households 
and related 
economic 
activities 

The more diversified the 
energy sources, the less 
likelihood of power 
interruption if a given 
source is affected by 
disaster 

Poor people are more 
susceptible to the 
impacts of natural 
hazards, as they tend to 
live in hazard-prone 
areas (e.g. in unsafe 
buildings, on floodplains, 
etc.) and continuously 

117 

ND-GAIN 

http://data.worldbank.o
rg/indicator/SH.STA.WA
ST.ZS 

Brooks et al., 2005 

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/NY.ADJ.AED
U.GN.ZS 
http://data.worldbank.o
rg/indicator/EG.USE.CO
MM.CL.ZS 

Bjarnadottir et al., 2011;  
Sub-indicator of 
Susceptibility in  the 
World Risk Index 2014 
and MDGs (UN 2005) 

http://data.worldbank.o
rg/indicator/SI.POV.DDA
Y 

 
 
 
All 

All 

GDP per capita 
at purchasing 
power parity 
(current US$) 

Gross domestic 
product (GDP) is the 
gross value added by 
all resident producers 
in the economy plus 
any product taxes and 
minus any subsidies 
not included in the 
value of the products. 
GDP per capita is GDP 
divided by the mid-
year population 
converted to US$  
using purchasing 
power parity rates 

have to cope with various 
shocks related to 
hazards, in dire 
conditions with limited 
assets 

The GDP per capita PPP 
can serve as an overall 
measure of economic 
development and has 
often been used as an 
indicator of economic 
development and 
vulnerability. Useful to 
estimate a population’s 
susceptibility to harm, as 
limited monetary 
resources are seen as 
being an important factor 
of vulnerability 

General food 
availability 

Government 
effectiveness 

Food production index 

All 

Health, 
households 

All 

All 

Reflects perceptions of 
the quality of public 
services, the quality of 
the civil service and 
the degree of its 
independence from 
political pressures, the 
quality of policy 
formulation and 

Ineffective government 
undermines 
implementation, for 
example when policies 
and strategies for 
disaster risk 
management are not 
evidence based, clearly 
formulated, integrated 

118 

UNDP, 2014; Füssel 
2010; Ferreira et al. 
(2013), Anbarci et al. 
(2005), Escaleras et al. 
(2007), Keefer et al. 
(2011), Kahn (2005), 
and Raschky (2008) 
Schooling ; X Skidmore 
and Toya (2002), Padli et 
al. (2010), and Padli and 
Habibullah (2009) 
Skidmore and Toya 
(2002), Raschky and 
Schwindt (2008), 
Kellenberg and Mobarak 
(2008), and Padli et al. 
(2010), Padli and 
Habibullah (2009), 
Brooks et al. 2005; 
Bjarnadottir er al., 2011; 
Sub-indicator of 
Susceptibility in the 
World Risk Index 2014; 
post 2015 HFA  
(UNISDR, 2014) 
Brooks et al., 2005; 
Coping capacity in WRI 
2014 
Post 2015 HFA (UNISDR, 
2014);Lack of Coping 
capacity in INFORM 2014 

http://data.worldbank.o
rg/indicator/NY.GDP.PC
AP.CD 

http://data.worldbank.o
rg/indicator/AG.PRD.FO
OD.XD 

 
 
 
 
implementation, and 
the credibility of the 
government's 
commitment to such 
policies 

Gross capital formation 
(formerly gross 
domestic investment) 
consists of outlays in  
addition to the fixed 
assets of the economy 
plus net changes in the 
level of inventories. 
Fixed assets include 
land improvements 
(fences, ditches, 
drains, etc.); plant, 
machinery, and 
equipment purchases; 
and the construction of 
roads, railways, and 
the like, including 
schools, offices, 
hospitals, private 
residential dwellings, 
and commercial and 
industrial buildings. 
Inventories are stocks 
of goods held by firms 
to meet temporary or 
unexpected 
fluctuations in 
production or sales, 
and "work in progress"  
Gini Index 

Gross fixed 
capital 
formation 

Income 
distribution 

All 

All 

into broader policy and 
backed by political 
commitment. 

High rates of Gross Fixed 
Capital Formation are 
likely to be associated 
with rapidly increasing 
hazard exposure of 
economic assets 

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/NE.GDI.TOT
L.KD 

All 

All 

The Gini index gives an 
estimate of inequality as 
it measures the extent to 
which the actual income 
distribution differs from 
an equitable distribution. 
119 

Hallegatte, 2014; Anbarci 
et al. (2005) and Kahn 
2005, Brooks et al., 
2005; Sub-indicator of 
the World Risk Index 
2014; post 2015 HFA 

http://data.worldbank.o
rg/indicator/SI.POV.GIN
I 

 
 
Resilience is likely to be 
lower in countries with a 
high degree of income 
inequality 

(UNISDR, 2014); 
INFORM 2014 

Internet users are 
people with access to 
the worldwide web 
network. Internet 
users per 100 
inhabitants 
Years of individual life 
expectancy 
(procedure: 
0.25*Log(log(85/Years 
of individual life 
expectancy))) 
The number of deaths 
caused by malaria per 
100 000 people per 
year 

Maternal mortality 
ratio is the number of 
women who die during 
pregnancy and 
childbirth, per 100 000 
live births.  
A component of the 
Fraser Index of 
Economic Freedom 

Internet users 

Life expectancy 
at birth 

Malaria 
mortality rate 

Maternal 
mortality per 
100 000 

Microeconomic 
market 
efficiency - 
regulation of 
credit, labour 
and business 
index 

All 

All 

Perch- Nielsel, 2010; 
Post 2015 HFA; INFORM 
2014 

http://data.worldbank.o
rg/indicator/IT.NET.USE
R.P2 

All 

All 

All 

All 

Households 
and related 
economic 
activities 

This indicator also 
reveals the general 
health standards of a 
country 

Health and 
households 

Removal of economically 
active 
population 

Health and 
households 

Macroecon
omic 
impacts 

Briguglio et al., 2008. 
Brooks et al., 2005; Sub-
indicator of HDI and 
World Risk Index 2014 
and post 2015 HFA 
(UNISDR, 2014) 
Sub-indicator of INFORM 
2014; 
WHO Global Health 
Observatory 

Brooks et al., 2005; 
MDG5.1 (UN 2005) 

Briguglio et al., 2008 

http://data.worldbank.o
rg/indicator/SP.DYN.LE0
0.IN 

http://apps.who.int/gho
data/ 

http://data.worldbank.o
rg/indicator/SH.STA.MM
RT 

http://www.fraserinstitu
te.org/research-
news/display.aspx?id=2
0395 

120 

 
 
 
 
 
ODA received 
per person 

Personal 
remittances 
(% of GDP) 

Net official 
development 
assistance (ODA) per 
capita consists of 
disbursements of loans 
made on concessional 
terms (net of 
repayments of 
principal) and grants 
by official agencies of 
the members of the 
OECD’s Development 
Assistance Committee 
(DAC), by multilateral 
institutions, and by 
non-DAC countries to 
promote economic 
development and 
welfare in countries 
and territories in the 
DAC list of ODA 
recipients. It is 
calculated by dividing 
net ODA received by 
the midyear population 
estimate. It includes 
loans with a grant 
element of at least 
25% (calculated at a 
rate of discount of 
10%). 
Personal remittances 
comprise personal 
transfers and 
compensation of 
employees. Personal 
transfers consist of all 
current transfers in 
cash or in kind made 
or received by resident 
households to or from 
non-resident 
households. Personal 

All 

All 

Countries heavily 
dependent on ODA will 
also be more dependent 
on ODA decisions to 
finance recovery and 
reconstruction 

Costa (2012) and 
Raschky and Schwindt 
(2008); post 2015 HFA 
(UNISDR, 2014) and 
sub-indicator of INFORM 
2014 

http://www.oecd.org/da
c/stats/ 

Post 2015 HFA (UNISDR, 
2014) 

http://data.worldbank.o
rg/indicator/BX.TRF.PW
KR.DT.GD.ZS 

All 

All 

Economies where 
remittances represent a 
high proportion of GDP 
are more resilient as risk 
is geographically spread, 
and a lower proportion of 
household earnings will 
be affected. 

121 

 
 
transfers thus include 
all current transfers 
between resident and 
non-resident 
individuals. 
Compensation of 
employees refers to 
the income of border, 
seasonal, and other 
short-term workers 
who are employed in 
an economy where 
they are not resident 
and of residents 
employed by non-
resident entities. Data 
are the sum of two 
items defined in the 
sixth edition of the 
IMF's Balance of 
Payments Manual: 
personal transfers and 
compensation of 
employees.  
Number of supply 
interruptions 

Quality of 
energy supply 

All 

All 

Swanson et al. 2007; 
Post 2015 HFA (UNISDR, 
2014) 

file:///D:/Dev1/WEF_Glo
balEnergyArchitecturePe
rformance_Index_2015.
pdf 

The quality of utilities 
infrastructure affects the 
impact severity of natural 
hazards. A significant 
proportion of business 
interruption is associated 
with power outages. A 
reliable electricity 
network is therefore a 
key resilience factor for 
business  

122 

 
 
Share (%) of 
population 
undernourishe
d 

Tourism as % 
of GDP 

All 

All 

Population below 
minimum level of 
dietary energy 
consumption (also 
referred to as 
prevalence of 
undernourishment) 
shows the percentage 
of the population 
whose food intake is 
insufficient to meet 
dietary energy 
requirements 
continuously 
International tourism 
receipts are 
expenditures by 
international inbound 
visitors, including 
payments to national 
carriers for 
international transport. 
These receipts include 
any other prepayment 
made for goods or 
services received in 
the destination 
country. They also 
may include receipts 
from same-day 
visitors, except when 
these are important 
enough to justify 
separate classification. 
For some countries, 
they do not include 
receipts for passenger 
transport items 
(current US$) 

Households 
and related 
economic 
activities, 
health 

Malnutrition situation can 
be also a product of 
different circumstances 
having relationship with 
development policies and 
strategies, such as 
agricultural measures for 
food availability 

Sub-indicator of the 
World Risk Index 2014 
and ND-GAIN Index 2014 
and INFORM; MDG1.9 
(UN 2005) 

http://data.worldbank.o
rg/indicator/SN.ITK.DEF
C.ZS 

Tourism 
and macro-
economic 
effects 

Economies which are 
significantly concentrated 
in the tourism sector 
may have lower 
resilience when that 
sector is affected 

Perch- Nielsel, 2010 

http://data.worldbank.o
rg/indicator/ST.INT.RCP
T.CD 

123 

 
 
All 

Health and 
households 

Removal of economically 
active 
population 

Sub-indicator of INFORM 
2014; 
WHO Global Health 
Observatory 

http://apps.who.int/gho
data/ 

Tuberculosis 
prevalence 

The number of cases of 
tuberculosis (all forms) 
in a population at a 
given point in time 
(the middle of the 
calendar year), 
expressed as the rate 
per 100 000 
population. Estimates 
include cases of TB in 
people with HIV. 

124 

 
 
 
 
 
 
ANNEX IV 

Table I - Indicators identified by reviewing the relevant literature on climate change, 
development and disaster risk. (alphabetical order)   

Indicator name  Definition 

Rationale 

Strengths and 
Weaknesses 

References 

Data source 

% forest cover 

% of households 
dependent solely on 
agriculture as a 
source of income 

% of households 
primarily dependent 
on self-farmed food 

% of the national 
budget allocated to 
risk reduction 
Access to education 

Land under natural or 
planted stands of trees of 
at least 5 metres, whether 
productive or not, 
excluding tree stands in 
agricultural production 
systems (% of land area) 
Percentage of households 
dependent solely on 
agriculture as a source of 
income 

Percentage of households 
that get their food 
primarily from their own 
farms 
% of the national budget 
allocated to risk reduction 

Number of students 
enrolled in primary, 
secondary and tertiary 
levels of education, 
regardless of age, as a 

125 

Brooks et al., 2005; 
MDG 7.1 (UN 2005); 
WDI 

http://data.worldbank.
org/indicator/AG.LND.F
RST.ZS 

Hahn et al., 2009; 
Shah et al., 2013; de 
Oliveira Mendes 
(2009), Schmidtlein et 
al. (2011), Khan 
(2012) 
Hahn et al., 2009; 
Shah et al., 2013 

Not Available/ Data to 
be collected locally 

Data can be collected 
locally 

Post 2015 HFA 
(UNISDR, 2014) 

Available in future 

Halsnæs and 
Verhagen, 2007; 
Briguglio et al., 2008 

http://data.uis.unesco.
org/ 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Access to electricity 

Adoption of NAPAs 

Adult literacy rate 

percentage of the school-
age population for each 
level 

The percentage of 
population with access to 
electricity. Electrification 
data are collected from 
industry, national surveys 
and international sources 

National Adaptation Plans 
are defined and adopted 
(Y/N) 

Population aged 15 years 
and over who can read and 
write a short simple 
statement on their 
everyday life 

Age and condition of 
utilities 

Age dependency 
ratio 

Ratio of the population 
<15 and >65 years of age 
to the population between 
19 and 65 years of age 

Indicative of the 
capacity to delivery 
energy to a 
country’s citizens 
and businesses 

Literacy could be 
an essential 
indicator, which 
helps to empower 
people with regard 
to hazard risk 
reduction 

The direct effects 
of extreme weather 
may 
disproportionately 
affect the old and 
the young. A high 
age dependency 
ratio means a high 
proportion of 
children and elderly 
people compared 
to the working age 
population. This 
lowers resilience, 
particularly in the 
case of the death 
or injury of a 

126 

http://data.worldbank.
org/indicator/EG.ELC.A
CCS.ZS and 
http://www.worldenerg
youtlook.org/resources
/energydevelopment/e
nergyaccessdatabase/ 
http://www.prevention
web.net/english/hyogo
/progress/?pid:228&pil
:1 
http://hdr.undp.org/en
/content/adult-literacy-
rate-both-sexes-ages-
15-and-older and 
http://data.worldbank.
org/indicator/SE.ADT.L
ITR.ZS 
Data not available   

http://data.worldbank.
org/indicator/SP.POP.6
5UP.TO.ZS/ 

Sub-indicator of the 
ND-GAIN Index 2014 
and  INFORM 2014 

Brooks et al., 2005; 
Sub-indicator of the 
World Risk Index 
2014; MDG 2.3 (UN 
2005); post 2015 HFA; 
and INFORM 2014 

Swanson et al., 2007 

Cutter et al. (2003); 
Shah 2013; Wolf et al., 
2010; Sub-indicator of 
the World Risk Index 
2014; post 2015 HFA  
(UNISDR, 2014), ND-
GAIN 2014 

 
 
 
 
 
 
 
 
 
 
 
Agricultural capacity  This comprises of four 

working-age adult 

indicators: % of 
agricultural area/land area 
equipped for irrigation, 
Fertiliser use on arable and 
permanent crop areas; 
Tractor use per 100  kmq 
of arable land; and % of 
agricultural area/land area 
equipped for irrigation 
Agricultural production 
index 
An HIV/AIDS epidemic is 
defined by the HIV 
prevalence in the general 
population. HIV prevalence 
is the percentage of the 
population living with HIV 
The probable annualised 
loss from all hazard 
events occurring over 
different return periods. 

Annual average losses 

Annual percentage growth 
rate of GDP at market 
prices based on constant 
local currency. Aggregates 
are based on constant 
2005 US dollars  

Agricultural self-
sufficiency 
AIDS/HIV infection 
(% of adults) 

Annual Average Loss 
(AAL) 

Annual Average Loss 
(AAL) as % of Gross 
Fixed Capital 
Formation 

Annual change in 
GDP 

Removal of 
economically active 
population 

Countries that risk 
losing a significant 
proportion of their 
annual capital 
investment in 
disasters run a 
high risk to their 
economies 
Rapidly increasing 
GDP indicates 
decreasing 
vulnerability and 
mortality for a 
given level of 

127 

Sub-indicator of ND-
GAIN  

Brooks et al., 2005 

Brooks et al., 2005; 
INFORM 2014 

http://apps.who.int/gh
odata/ 

Post 2015 HFA 
(UNISDR, 2014) 

Post-2015 HFA 
(UNISDR, 2014) 

http://www.prevention
web.net/english/hyogo
/gar/2013/en/home/da
ta-platform.html 

http://www.prevention
web.net/english/hyogo
/gar/2013/en/home/da
ta-platform.html 

Post-2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/NY.GDP.
MKTP.KD.ZG 

 
 
 
 
 
 
 
 
 
 
 
 
 
Annual maximum 
five-day 
precipitation 

Availability and 
implementation of a 
transparent and 
detailed deep 
decarbonisation 
strategy 

Where RRkj is the amount 
of precipitation for the 
five-day interval ending k, 
period j, the maximum 
five-day values for period j 
are: Rx5dayj = max (RRkj)  
A decarbonisation strategy 
is in place and 
implemented 

hazard exposure, 
and increasing 
hazard exposure of 
economic assets 

Keeping global 
warming within 2°C 
or less requires 
that countries 
prepare national 
deep 
decarbonisation 
strategies to 2050, 
covering all sources 
of greenhouse gas 
(GHG) emissions 
including from the 
energy, industry, 
agriculture, forest, 
transport, and 
building sectors 

Perch- Nielsel, 2010; 
World Bank, 2014 

Data can be collected 
locally 

Proposed SDG 82 (UN, 
2014) 

http://unsdsn.org/wp-
content/uploads/2014/
07/140724-Indicator-
working-draft1.pdf 

Average agricultural 
Livelihood 
Diversification Index 

The inverse of (the number 
of agricultural activities + 
1) reported by a household 

Average annual 
deviation in Sea-
Surface 
Temperatures 

Average annual deviation 
in Sea-Surface 
Temperatures (SST) in the 
past five years in relation 
to the 30-year monthly 
means (1961-1990). The 
indicator captures the total 
amount of the anomalies in 
SST, either as excess or 

Frequent and 
severe 
deviations from the 
30-year moving 
average could 
herald shifts in 
currents, 
upwelling, weather 
patterns and 

Hahn et al., 2009; 
Shah et al., 2013 

Data to be collected 
locally 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

http://www.vulnerabilit
yindex.net/ and 
Climatic Research Unit, 
University of East 
Anglia, Norwich, UK. 
http://www.cru.uea.ac.
uk/cru/data/temperatu
re/#datdow 

128 

 
 
 
 
 
 
 
 
 
deficit (using absolute 
values) 

climate, and could 
negatively  a 
country’s resilience 
to other hazards 

Average annual 
excess heat 
(degrees) over the 
past five years 

Average annual excess 
heat (degrees) over the 
past five years for all days 
more than 5°C (9˚F) 
hotter than the 30 year 
mean monthly maximum  

This indicator 
captures not only 
the number of days 
with  
significantly higher 
temperatures, but 
also the amount of 
the excess 

Average annual 
excess rainfall (mm) 
over the past five 
years 

Average annual excess 
rainfall (mm) over the past 
five years for all months 
with more than 20% 
higher rainfall than the 30-
year monthly average 

This indicator 
ensures that the 
amount of rain ‘in 
excess’ is 
considered 

Average annual 
excess wind over the 
past five years 

Summing wind speeds on 
days during which the 
maximum recorded wind 
speed is more than 20% 
higher than the 30-year 
average maximum wind 
speed for that month 

This indicator 
captures the 
likelihood of 
damage from 
frequent and 
severe wind that 
can affect forests, 
fan fires, create 
storm surges, dry 
soils, spread air 
pollution, and 
interact with other 
stressors 

129 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

http://www.vulnerabilit
yindex.net/ 

NOAA DATSAV3 
Surface SOD 1973-
2003  
http://gcmd.gsfc.nasa.
gov/records/GCMD_go
v.noaa.ncdc.C00442.ht
ml 
http://www.vulnerabilit
yindex.net/ 
and NOAA GHCN  
http://www.ncdc.noaa.
gov/oa/pub/data/ghcn/
v2/ghcnftp_zipd.html 

http://www.vulnerabilit
yindex.net/ 
NOAA DATSAV3 
Surface SOD 1973-
2003  
http://gcmd.gsfc.nasa.
gov/records/GCMD_go
v.noaa.ncdc.C00442.ht
ml 

 
 
 
 
 
 
 
Average annual heat 
deficit (degrees) 

Average annual heat deficit 
(degrees) over the past 
five years for all days more 
than 5°C (9˚F) cooler than 
the 30-year mean monthly 
minimum 

This indicator 
records not only 
the number of days 
with significantly 
lower 
temperatures, but 
also the amount of 
the “heat deficit” 

This indicator 
ensures that the 
amount of rain 
‘missed’ is 
considered 

Average annual 
number of 
international 
tourists per km2 land 
over the past five 
years 

Average annual 
rainfall deficit (mm) 
over the past five 
years 

Average annual 
water usage as  a 
percentage of 
renewable water 
resources over the 
past five years 
Average crop 
diversity index 

Average days water 
supply stored per 
household 
Average days 
without regular 
water supply per 
month 

Average annual number of 
international tourists per 
km2 land over the past five 
years 

Average annual rainfall defi 
cit (mm) over the past five 
years for all months with 
more than 20% lower 
rainfall than the 30-year 
monthly average 
Average annual number of 
international tourists per 
km2 land over the past five 
years 

The inverse of (the number 
of crops grown by a 
household + 1) 

Average water supply 
security per 
household 
Percentage of households 
reporting that water is not 
available from their 
primary water supply 

130 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Shah, 2013 

Shah et al., 2013 

Shah et al., 2013 

http://www.vulnerabilit
yindex.net/ and  
NOAA DATSAV3 
Surface SOD 1973-
2003  
http://gcmd.gsfc.nasa.
gov/records/GCMD_go
v.noaa.ncdc.C00442.ht
ml 
http://www.vulnerabilit
yindex.net/ 
WTO http://i-
tip.wto.org/services/(S
(dczrer0x1sb4i3sg1l0i0
m0l))/ChartResults.asp
x 
http://www.vulnerabilit
yindex.net/ 
NOAA GHCN  
http://www.ncdc.noaa.
gov/oa/pub/data/ghcn/
v2/ghcnftp_zipd.html; 
http://www.vulnerabilit
yindex.net/ 
NOAA GHCN  
http://www.ncdc.noaa.
gov/oa/pub/data/ghcn/
v2/ghcnftp_zipd.html; 
Data can be collected 
locally 

Data can be collected 
locally 

Data can be collected 
locally 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sub-indicator of 
INFORM 2014 

http://www.fao.org/ec
onomic/ess/ess-fs/ess-
fadata/en/ 

Hahn et al., 2009; 
Shah et al., 2013 

Data can be collected 
locally 

Bjarnadottir et al., 
2011 

Hahn et al., 2009; 
Shah et al 2013 

http://unstats.un.org/u
nsd/Demographic/scon
cerns/popsize/default.h
tm 
Data can be collected 
locally 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

http://www.vulnerabilit
yindex.net/ 

Average dietary 
supply adequacy 

Average help 
received: given ratio 

Average number of 
people per 
household 

Average ratio of 
borrowing to lending 

Average ratio of 
productivity: 
fisheries catch over 
the past five years 

Average dietary energy 
supply as a percentage of 
the average dietary energy 
requirement 

Ratio of (the number of 
types of help received by a 
household in the past 
month +1) to (number of 
types of help given by a 
household to another 
household in the past 
month +1) 
Average number of people 
per household 

Ratio of a household’s 
financial borrowings in the 
past month to a 
household’s financial 
lending in the past month 
Rate of extraction/ the 
potential for the 
environment to replenish 
those stocks (productivity) 

This indicator 
captures the risk of 
damage to fisheries 
stocks by 
examining rates of 
extraction in 
relation to the 
potential for the 
environment to 
replenish those 
stocks 
(productivity). A 
small productivity 
ratio means 
greater 
vulnerability of 
fisheries 

131 

 
 
 
 
 
 
 
 
 
 
 
Average time to 
health facility 

Average time to 
water source 
(minutes) 

Balance of payments 
(current account net 
% of GDP) 

Average time taken to 
travel to the nearest health 
facility 
Average time it takes 
households to 
travel to their primary 
water source 

Current account balance is 
the sum of net exports of 
goods and services, net 
primary income, and net 
secondary income 

Beach length to be 
maintained in order 
to maintain 
important tourist 
resort areas 
Benefit/cost ratios 
of adaptation 
options 
identified/implemen
ted 

Better vulnerability 
Assessments 

Beach length to be 
maintained (km) in order 
to maintain important 
tourist resort areas 

BCR based on the ratio of 
the value of assets and 
productivity made less 
vulnerable to climate 
hazards, to adaptation 
expenditure 
Number of 
projects/interventions that 
conduct and update risk 
and vulnerability 
assessments 

The economies of 
countries with a 
positive balance of 
payments to GDP 
ratio are likely to 
be more resilient to 
reductions in 
domestic demand 
following disasters, 
but could be less 
resilient to 
disasters in key 
export markets 
This highlights the 
dependence of the 
tourism sector on 
the maintenance of 
natural capital 

This indicator cannot 
measure quality of 
generated or updated 
risk and vulnerability 
assessments 

This indicator 
assumes that 
higher numbers of 
projects and 
interventions within 
different sectors 
conducting and 
updating risk and 
vulnerability 

132 

Shah 2013 

Hahn et al., 2009 

Data can be collected 
locally 

Data can be collected 
locally 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/BN.CAB.X
OKA.GD.ZS 

Perch- Nielsel, 2010 

Brooks et al., 2011 

Data to be collected by 
reviewing local projects 

Adaptation Fund 
indicator 1.1  (AF, 
2014) 

Data to be collected by 
reviewing national 
policies 

 
 
 
 
 
 
 
 
 
 
 
Biodiversity and 
habitat 
protection 

Birth rate 

Capacity to 
undertake research 
and 
understand issues 
Carbon Emissions 
per capita 

Ordinal scale with a range 
from 0 (very poor 
environmental 
performance) to 100 
(excellent environmental 
performance), aggregated 
from three performance 
indicators: Terrestrial 
Protected Areas (National 
Biome Weights), Terrestrial 
Protected Areas (Global 
Biome Weights), Marine 
Protected Areas and 
Critical Habitat Protection 
Crude birth rate indicates 
the number of live births 
occurring during the year, 
per 1 000 population 
estimated at mid-year 
Scientists and engineers in 
R&D per million population 

Carbon dioxide emissions 
stemming from the burning 
of fossil fuels and the 
manufacture of cement. 
They include carbon 

assessments would 
provide more 
information on 
specific risk and 
vulnerability 
assessments. This 
information would 
form the basis to 
develop relevant 
and sector-specific 
adaptation 
measures 
Habitat protection 
is a necessary but 
not sufficient 
condition for the 
conservation of 
biodiversity and 
ecosystem services 
that are critical to 
sustain human life 
and well-being 

Controversial in terms 
of development 
opportunities 

Sub-indicator of the 
World Risk Index 2014 

http://epi.yale.edu/  

de Oliveira Mendes 
(2009),  Lee (2014) 

http://data.worldbank.
org/indicator/SP.DYN.C
BRT.IN 

Brooks et al., 2007 

MDG 7.2 (UN 2005); 
Post-2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/EN.ATM.C
O2E.PC  

133 

 
 
 
 
 
 
 
 
 
MDG 7.2 (UN 2005); 
Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/EN.ATM.C
O2E.PP.GD 

High existing debt 
limits the capacity 
of a government to 
recovery 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/GC.DOD.
TOTL.GD.ZS 

Carbon Emissions 
per unit of GDP 

Central government 
debt, total (%of 
GDP) 

dioxide produced during 
consumption of solid, 
liquid, and gas fuels and 
gas flaring (metric tonnes 
per capita) 
Carbon dioxide emissions 
stemming from the burning 
of fossil fuels and the 
manufacture of cement. 
They include carbon 
dioxide produced during 
consumption of solid, 
liquid, and gas fuels and 
gas flaring (kg per PPP US$ 
of GDP) 
Debt is the entire stock of 
direct government fixed-
term contractual 
obligations to others that 
are outstanding on a 
particular date. It includes 
domestic and foreign 
liabilities such as currency 
and money deposits, 
securities other than 
shares, and loans. It is the 
gross amount of 
government liabilities 
reduced by the amount of 
equity and financial 
derivatives held by the 
government. Because debt 
is a stock rather than a 
flow, it is measured as of a 
given date, usually the last 
day of the fiscal year 

134 

 
 
 
 
 
Child Malnutrition 

Child Mortality Rate 

Children Under 
Weight 

The proportion of children 
under five whose weight 
for their height is more 
than two standard 
deviations below the 
median for the 
international reference 
population aged 0-59 

The under-five mortality 
rate is the probability per 
1 000 that a new born child 
will die before reaching the 
age of five 
Children aged <5 years 
Under Weight 

Climate change 
priorities are 
integrated into 
national 
development 
strategy 

This is a measure of the 
existence of a document to 
achieve goals and 
objectives at national 
and/or local levels and a 
group of potential and 
agreed adaptation options 
to be implemented. 
Climate change 
“adaptation priorities” 
depend on: 
• Targeted geographic area 
covered (local, regional, 
national, etc.). For 

Malnutrition can be 
a product of 
different 
circumstances 
related to 
development 
policies and 
strategies, such as 
agricultural 
measures for food 
availability 

Malnutrition can be 
a product of 
different 
circumstances 
related to 
development 
policies and 
strategies, such as 
agricultural 
measures for food 
availability 
Understanding the 
integration of 
climate change 
priorities into 
development 
strategies can help 
determine the level 
of commitment at 
local/municipality, 
regional, and 
national scales, as 
well as the 
effectiveness of 
adaptation 

ND-GAIN 

http://data.worldbank.
org/indicator/SH.STA.
WAST.ZS 

Füssel, 2010; de 
Oliveira Mendes 
(2009),  Lee (2014) 
MDG4.2 (UN 2005); 
INFORM 2014 
INFORM 2014 

http://data.worldbank.
org/indicator/SH.DYN.
MORT 

http://apps.who.int/gh
odata/; 
http://www.unicef.org/
publications/index_pub
s_statistics.html 

Integrating climate 
change priorities into 
development strategies 
does not necessarily 
address their actual 
implementation 

Adaptation Fund 
indicator 7  (AF, 2014) 

Data to be collected by 
reviewing national 
policies 

135 

 
 
 
 
 
 
example, at the national 
level NAPAs include climate 
change adaptation 
priorities. 
• Sectors targeted: 
agriculture, health, energy, 
waste, forestry, etc. 
• Socioeconomic aspects 
covered by policy: physical 
capital; improve 
livelihoods; social, natural 
or human capital 
Industrial clusters are 
groups of firms on the 
same location composing a 
production system with 
spill-overs that can be 
vertical and/or horizontal 

This indicator is defined as 
the amount (measured in 
grammes) of CO2 
emissions per unit of 
electricity (measured in 
kilowatt hour) generated 
from the power sector as a 
whole (total capacities); 
and from new capacities 
installed (between two 
dates of measurement of 
the indicator) 
The amount (measured in 
grammes) of CO2 
emissions per vehicle, 
kilometre travelled in 
aggregate; and per 
passenger kilometre 
travelled (pkm) for new 
cars, and per tonne 
kilometre travelled (tkm) 
for new trucks (between 

responses 

Understanding 
what drives the 
evolution of the 
CO2 intensity of 
the power sector is 
also important to 
define the 
appropriate policies 
to reduce the CO2 
emissions of this 
sector  

Understanding 
what drives the 
evolution of the 
CO2 intensity of 
the transport 
sector is important 
to define 
appropriate policies 
to reduce the CO2 
emissions of that 

136 

Clustering tendency 

CO2 intensity of the 
power sector, and of 
new power 
generation capacity 
installed (gCO2 per 
kWh) 

CO2 intensity of the 
transport sector 
(gCO2/vkm), and of 
new cars 
(gCO2/pkm) 
and trucks 
(tCO2tkm) 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Proposed SDG 83 (UN, 
2014) 

http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
http://data.worldbank.
org/indicator/EN.ATM.C
O2E.EG.ZS 

Proposed SDG 84 (UN, 
2014) 

http://data.worldbank.
org/indicator/EN.CO2.T
RAN.ZS 

 
 
 
 
 
 
two dates of measurement 
of the indicator) 

sector 

A good level of 
education is 
important to 
recover sooner 
from shocks related 
to natural hazards 

Coastal vulnerable 
population 

Combined gross 
school enrolment 

Commitment to and 
resources for 
research 

Community health 
and services 
measure 
Conflict 

Population below 5m is the 
percentage of the total 
population living in areas 
where the elevation is 5 
metres or less above sea 
level 
The number of students 
enrolled in primary, 
secondary and tertiary 
levels of education, 
regardless of age, as a 
percentage of the 
population of theoretical 
school age for the three 
levels 
R&D investment (% GNP) 

Internal refugees (1 000s) 
scale by population 

Control of corruption  Reflects perceptions of the 

extent to which public 
power is exercised for 
private gain, including both 
petty and large forms of 
corruption, as well as 
"capture" of the state by 
elites and private interests 

137 

Sub indicator of ND-
GAIN 

http://data.worldbank.
org/indicator/EN.POP.E
L5M.ZS 

Sub-indicator of the 
World Risk Index 2014 
and HDI 

Brooks et al., 2008 

http://hdr.undp.org/en
/content/combined-
gross-enrolment-
education-both-sexes 
and 
http://www.uis.unesco.
org/Datacentre/Pages/i
nstructions.aspx?SPSL
anguage=EN 
Data not available 

Swanson et al., 2007 

Data not available   

Brooks et al., 2006 

Post 2015 HFA 
(UNISDR, 2014) 

http://info.worldbank.o
rg/governance/wgi/ind
ex.aspx#home 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
http://cpi.transparency
.org/cpi2013/results/ 

Escaleras et al. (2007); 
Sub-indicator of the 
World Risk Index 2014 
and INFORM 2014 and 
Proposed SDG 100 
(UN, 2014) 

Brooks et al., 2011 

Data to be collected by 
reviewing local projects 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Sub-indicator of the 
ND- GAIN Index 2014 

http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
http://www.fao.org/nr/
water/aquastat/data/q
uery/index.html?lang=
en 

Corruption 
Perception Index 

This indicator measures 
the perceived level of 
corruption of national 
governments using 13 
different sources 

Coverage of Climate 
Change 
interventions 
Customer proximity 

Proportion of portfolio that 
includes measures to 
address climate change 
The level of proximity of 
customers 

Dam Capacity 

Dam Capacity per capita 

People living in 
countries with 
higher levels of 
corruption are 
thought to have 
greater difficulty in 
recovering from 
natural hazard 
impacts, due to 
limited 
governmental 
support reaching 
affected population 
compared to states 
with lower levels of 
corruption 

Dam capacities are 
an appropriate 
measure of the 
capacity to cope 
with changes 
brought about by 
climate change 
regarding the 
temporal and 
geographic 
distribution of 
water resources 

138 

 
 
 
 
 
 
 
 
Debt repayments 

Degree of economic 
diversification 

Degree of power self 
supply 

Actual amounts of principal 
(amortization) paid by the 
borrower in currency, 
goods, or services in the 
year specified 
Manufacturing, value 
added (% of GDP). 
Manufacturing refers to 
industries belonging to 
ISIC divisions 15-37. Value 
added is the net output of 
a sector, calculated by 
adding up all outputs and 
subtracting intermediate 
inputs. 
Degree of power self 
supply 

A community with 
a relatively diverse 
local economy is 
better able to 
adjust to changes 
that have a 
significant impact 
on a particular 
sector or sectors of 
employment 

Degree of water self 
supply (industry) 

Degree of water self supply 
(industry) 

Democracy 

Density of people 
living in coastal 
settlements 

Density of people living in 
coastal settlements (within 
100 km of the coast) 

Countries with 
heavy densities of 
human populations 
living in coastal 
areas are likely to 
damage some of 
their most 

139 

Brooks et al., 2005 

http://data.worldbank.
org/indicator/DT.AMT.
DLTF.CD 

Hallegatte, 2014 Füssel 
and Klein, 2006 

http://data.worldbank.
org/indicator/NV.IND.M
ANF.ZS 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Keefer et al. (2011), 
Kahn (2005), and 
Raschky and Schwindt 
(2008) 
UNDP, 2004 ; Perch- 
Nielsel 2010 

http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
Data not available   

http://www.vulnerabilit
yindex.net/ 
Center for 
International Earth 
Science Information 
Network - CIESIN - 
Columbia University 

 
 
 
 
 
 
 
 
 
 
 
 
 
Dependence on 
agriculture 

Agricultural employees (% 
of total population) 

Dependency on 
external resource for 
health services 

This indicator measures 
the proportion of total 
expenditures to health or 
related services that are 
provided by entities 
external to the country  

Dependency on 
imported energy 

Direct benefits 

Proportion of energy use 
from imports. Energy use 
refers to the use of 
primary energy before 
transformation to other 
end-use fuels, according to 
WDI, equal to indigenous 
production plus imports 
and stock changes, minus 
exports and fuels supplied 
to ships and aircraft 
engaged in international 
transport 
Value of assets and 
economic activities 
protected or made less 
vulnerable as a result of 
adaptation interventions 
compared with a business-
as-usual scenario, turnover 

productive and 
diverse areas and 
negatively 
affect the country 
‘s resilience to 
natural disasters 
such as cyclones, 
tsunamis etc. 

A high dependency, 
usually on foreign 
aid, is an indicator 
of weakness in 
internal capacity 
and thus 
vulnerability to 
climate-related 
health shocks  
A higher proportion 
of imported energy 
implies higher 
sensitivity to price 
increases or supply 
crises  

140 

http://sedac.ciesin.colu
mbia.edu/data/sets/br
owse 

Brooks et al., 2005 

Sub-indicator of the 
ND-GAIN Index 2014 

http://data.worldbank.
org/indicator/SL.AGR.E
MPL.ZS 
http://data.worldbank.
org/indicator/SH.XPD.E
XTR.ZS 

Sub-indicator of the 
ND-GAIN Index 2014 

http://index.gain.org/a
bout/download 
http://data.worldbank.
org/indicator/EG.IMP.C
ONS.ZS 

Brooks et al., 2011 

Data to be collected by 
reviewing local 
projects/surveys 

 
 
 
 
 
 
 
 
 
 
of businesses incorporating 
adaptation measures 
resulting from projects, 
etc. 

Disaster mortality 
per 
100 000 population 

Disaster mortality per 
100 000 inhabitants (five-
year moving average) 

Disaster 
preparedness 

Monitoring from Hyogo 
Framework Action  

Displaced people (% 
of population) 

Displaced People 

Large scale 
mortality is an 
indicator of both 
high levels of risk 
as well as 
limitations in 
disaster risk 
management 

Displaced people 
are normally a 
particularly at-risk 
group and are 
more likely to live 
in vulnerable 
conditions in 
hazard-prone 
areas, with less 
access to basic 
services than low-
income households 
in general 

Drought frequency 

Drought Frequency 

Ecological footprint 

Difference between the 
number of hectares of land 
and water (both within and 
outside the country ), 
needed to supply the 
average demand of the 
population and the 
country’s supply of land 

A country with a 
surplus (more 
supply than 
demand) has the 
capacity to produce 
more from within 
its boundaries and 
thus is likely to 

141 

Post 2015 HFA 
(UNISDR, 2014); Sub-
indicator of the Global 
Climate Change Index 
(Germanwatch 2014) 

http://germanwatch.or
g/en/cri 

Sub-indicator of the 
ND-GAIN Index 

http://www.prevention
web.net/applications/hf
a/qbnhfa/home 

Post 2015 HFA 
(UNISDR, 2014) 

http://www.unhcr.org/
pages/49c3646c4d6.ht
ml  

Sub-indicator of 
INFORM 2014 
Post 2015 HFA 
(UNISDR, 2014), Sub-
indicator of ND-GAIN 
Index 

http://www.emdat.be  

http://www.footprintne
twork.org/en/index.ph
p/GFN/page/footprint_
data_and_results 

 
 
 
 
 
 
 
 
 
 
and water  

Economic loss as 
proportion of Gross 
Fixed Capital 
Formation (GFCF) 

Economic loss / Gross 
Fixed Capital Formation 
(GFCF) (five-year moving 
average) 

Ecosystem vitality 

Ecosystem vitality 
measures ecosystem 
protection and resource 
management 

Ecosystem vitality: 
Agriculture 

Educational 
commitment 1 

Educational 
commitment 2 

Ordinal scale with a range 
from 0 (very poor 
environmental 
performance) to 100 
(excellent environmental 
performance), aggregated 
from two performance 
indicators: Agricultural 
Subsidies (AGSUB) and 
Pesticide Regulation (POPs) 
Education expenditure as 
% of GNP 

Education expenditure as 
% of government 
expenditure 

have more options 
to adapt to a 
changing climate 

When a significant 
proportion of public 
and private capital 
investment is lost 
in disasters, social 
and economic 
development is 
eroded 
Healthy 
ecosystems 
providing 
regulatory 
ecosystem services 
moderate many 
weather and 
climate related 
hazards 
Agriculture is one 
the economic 
activities that has 
most impacts on 
ecosystems 

Post-2015 HFA 
(UNISDR, 2014) 

Post 2015 HFA 
(UNISDR, 2014); WRI 
2014 

http://epi.yale.edu/epi
/data-explorer 

It is not is a direct 
measurement of 
agricultural 
environmental 
performance 

Sub-indicator of the 
World Risk Index 2014 

http://epi.yale.edu/ 

Brooks et al., 2005 

Brooks et al., 2005; 
Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/SE.XPD.T
OTL.GB.ZS/countries 

Poverty is closely 
associated with low 
levels of education, 
which in turn limits 
capacities for 
disaster risk 
management 

142 

 
 
 
 
 
 
 
 
 
Emergency plans in 
place 

Emergency plans are in 
place (0-1) 

Energy access 

Energy source 
diversification 

Engagement in 
international 
environmental 
conventions 

Proportion of population 
with access to electricity 

Clean energy is non-
carbohydrate energy that 
does not produce carbon 
dioxide when generated. It 
includes hydropower and 
nuclear, geothermal, and 
solar power, among others 

Ratio of a country’s current 
status of convention 
engagement to the 
maximum engagement 
among all countries 

Expected years of 
schooling (years) 

Number of years of 
schooling that a child of 
school-entrance age can 
expect to receive if 
prevailing patterns of age-
specific enrolment rates 
persist throughout the 
child’s life 

Exposed cropland to 
drought 

Exposed population 
per 100 000 
inhabitants 

Sum of people exposed to 
extreme events/100 000 
inhabitants 

The more 
diversified the 
energy sources, 
the less likelihood 
of power 
interruption if a 
given source is 
affected by disaster 
Indicates a 
country’s capacity 
to reach agreement 
on appropriate 
actions internally 
and thereby 
engage in 
multilateral 
negotiations on 
environmental 
issues 

Countries with a 
high proportion of 
their population at 
risk of being 
affected by 
disasters will have 

143 

Hallegatte, 2014 

Data available for 
some countries 

Sub-indicator of the 
ND-GAIN Index  

Halsnæs and 
Verhagen, 2007 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/EG.USE.C
OMM.CL.ZS 

Sub-indicator of the 
ND-GAIN Index 2014 
http://sedac.ciesin.colu
mbia.edu/entri/index.js
p 

http://sedac.ciesin.colu
mbia.edu/entri/index.js
p 

Sub-indicator of HDI 

http://hdr.undp.org/en
/content/expected-
years-schooling-
children-years 

Sub-indicator of 
INFORM 2014 

Post 2015 HFA 
(UNISDR, 2014) 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Briguglio et al., 2008 

http://data.worldbank.
org/indicator/DT.DOD.
DECT.GN.ZS 

External debt-to-GNI 
ratio 

high degrees of  
livelihood 
interruption and 
threats to human 
development 
A country with a 
high level of 
external debt may 
find it more difficult 
to mobilise 
resources in order 
to offset the effects 
of external shocks 

Total external debt stocks 
to gross national income 
(GNI). Total external debt 
is debt owed to non-
residents that is repayable 
in currency, goods, or 
services. It is the sum of 
public, publicly 
guaranteed, and private 
non-guaranteed long-term 
debt, use of IMF credit, 
and short-term debt. 
Short-term debt includes 
all debt having an original 
maturity of one year or 
less and interest in arrears 
on long-term debt. GNI 
(formerly GNP) is the sum 
of value added by all 
resident producers plus 
any product taxes (less 
subsidies) not included in 
the valuation of output, 
plus net receipts of 
primary income 
(compensation of 
employees and property 
income) from abroad 

144 

 
 
 
Extreme poverty 

Percentage of the 
population living on US$ 
1.25 per day or less 
(purchasing power parity) 

Facilitated access to 
credit in post-
disaster situation 

Financial sector 

Credit is available in post-
disaster situations (0-1) 

Fiscal AAL per 
inhabitant 

The annual risk to publicly 
owned assets 

Fiscal Deficit 

Government's total 
expenditure surpasses the 
revenue generated. Cash 

Poor people are 
more susceptible to 
the impact of 
natural hazards, as 
they tend to live in 
hazard-prone areas 
(e.g. in unsafe 
buildings, on 
floodplains, etc.) 
and continuously 
have to cope with 
various shocks 
related to hazards, 
in dire conditions 
and with limited 
assets 

The higher the 
fiscal AAL (the 
annual risk to 
publicly owned 
assets, or for which 
governments are 
responsible for 
replacing) per 
inhabitant, the 
higher the 
sovereign disaster 
risk, for which is 
each citizen is 
responsible 
A healthy fiscal 
position would 
allow adjustments 

145 

Bjarnadottir er al., 
2011;  Sub-indicator of 
the World Risk Index 
2014 and MDGs (UN 
2005) 

http://data.worldbank.
org/indicator/SI.POV.D
DAY 

Hallegatte, 2014; 
Forgette and Boening 
(2010); Akter and 
Mallick, 2013 
Skidmore and Toya 
(2002), and Padli et al. 
(2010) 
Post 2015 HFA 
(UNISDR, 2014) 

Data can be collected 
locally 

Data not available   

http://www.prevention
web.net/english/hyogo
/gar/2013/en/home/da
ta-platform.html 

Briguglio et al., 2008; 
Skidmore and Toya 
(2002), and Padli et al. 

http://data.worldbank.
org/indicator/GC.BAL.C
ASH.GD.ZS 

 
 
 
 
 
 
 
 
 
 
Food import 
dependency 

Food imports (% of 
merchandise 
imports) 

Foreign aid 

Foreign direct 
investment (net 
inflows as % of 
Gross Fixed Capital 
Formation (GFCF) 

surplus or deficit is 
revenue (including grants) 
minus expense, minus net 
acquisition of nonfinancial 
assets 
Imports of food/ total 
supply. Dependency rate is 
measured by proportion of 
cereal consumption 
obtained from imports 

Food comprises the 
commodities in SITC 
sections 0 (food and live 
animals), 1 (beverages and 
tobacco), and 4 (animal 
and vegetable oils and 
fats) and SITC division 22 
(oil seeds, oil nuts, and oil 
kernels) 

to taxation and 
expenditure 
policies in the face 
of adverse shocks 

Countries highly 
dependent on food 
imports are 
susceptible to 
shocks in food 
prices. Climate 
change will 
accentuate price 
volatility 
Countries with a 
high food import 
ratio would be 
more resilient to 
the effects of 
disasters in the 
agricultural sector 
in the country, but 
more at risk of the 
impact of food 
price spikes on the 
international 
market 

Foreign direct investment 
are the net inflows of 
investment to acquire a 
management interest (10 
% or more of voting stock) 
in an enterprise operating 
in an economy other than 
that of the investor. It is 
the sum of equity capital, 
reinvestment of earnings, 

Economies with a 
high proportion of 
capital investment 
from overseas may 
be more resilient 
given that parent 
companies of 
damaged facilities 
can quickly invest 
to repair and 

146 

(2010) 

Sub-indicator of the 
ND-GAIN Index 2014 

http://faostat3.fao.org
/faostat-
gateway/go/to/downlo
ad/FB/BC/E 

Post-HFA (UNISDR, 
2014) 

http://data.worldbank.
org/indicator/TM.VAL.F
OOD.ZS.UN 

Costa (2012) and 
Raschky and Schwindt 
(2008) 
Post-2015 HFA 
(UNISDR, 2014) 

Data not available   

http://data.worldbank.
org/indicator/BX.KLT.D
INV.CD.WD 

 
 
 
 
 
 
 
 
other long-term capital, 
and short-term capital as 
shown in the balance of 
payments 

rehabilitate 
damaged facilities 

Reduction in the 
extent of forest 
cover has 
significant negative 
implications for 
ecosystem services 
and habitat 
protection. Forests 
are carbon sinks 
that help combat 
global climate 
change and 
regulate the 
hydrological 
system 

The Forest cover change 
rate indicator measures 
the percent change in 
forest cover between 2000 
and 2012 in areas with 
greater than 50% tree 
cover. Ordinal scale with a 
range from 0 (very poor 
environmental 
performance) to 100 
(excellent environmental 
performance), aggregated 
from three performance 
indicators: areas of 
deforestation (forest loss), 
reforestation (forest 
restoration or replanting) 
and afforestation 
(conversion of bare or 
cultivated land into forest) 
Percentage of households 
that received a warning 
about the most severe 
flood, drought, and cyclone 
event in the past 10 years 

Forest cover change 
rate (% per year) 

Fraction of the 
population covered 
by an early warning 
system and with 
ability to prepare 
and evacuate 

Frequency of water 
contamination  

Frequency of water 
contamination (over a 
defined period) 

147 

http://epi.yale.edu  

Sub-indicator of the 
World Risk Index  2014 
and WDIs; post 2015 
HFA (UNISDR, 2014) 
and Environmental 
Vulnerability Index 

Füssel and Klein, 2006; 
Hahn et al., 2009; 
Hallegatte, 2014, Akter 
and Mallick 2013; 
Forgette and Boening 
(2010); Adaptation 
Fund indicator 2.2.1  
(AF, 2014); post 2015 
HFA (UNISDR, 2014) 
Swanson et al., 2007 

Data available for 
some countries 

Data can be collected 
locally 

 
 
 
 
 
 
 
Freshwater 
withdrawal rate 

GDP per capita at 
purchasing power 
parity (current US$) 

Annual freshwater 
withdrawal / the total 
renewable water resources 
(excluding desalinated 
water)  
GDP is gross value added 
by all resident producers in 
the economy plus any 
product taxes and minus 
any subsidies not included 
in the value of the 
products. The GDP per 
capita is the gross 
domestic product divided 
by mid-year population 
converted to international 
(US)  dollars, using 
purchasing power parity 
rates 

Gender parity in 
primary, secondary 
and tertiary 
education 

Ratio of girls to boys, 
based on UNESCO data on 
school enrolment 
Values: 1 = parity 
> 0 < 1 = disparity in 
favour of males 
>1 = disparity in favour of 
females  

A proxy for 
countries’ water 
stress  

The GDP per capita 
PPP can serve as 
an overall measure 
of economic 
development and 
has often been 
used as an 
indicator for 
economic 
development and 
vulnerability. It can 
be used to 
estimate a 
population’s 
susceptibility to 
negative impacts, 
as limited 
monetary 
resources are seen 
as an important 
factor of 
vulnerability 

In the disaster risk 
context, education 
is an important 
resource for 
adaptation as it 
prepares a 
community to 
understand natural 
hazards and 
disaster 
consequences 

148 

Sub-indicator of the 
ND-GAIN Index 2014 

UNDP, 2014; Füssel 
2010; Ferreira et al. 
(2013), Anbarci et al. 
(2005), Escaleras et al. 
(2007), Keefer et al. 
(2011), Kahn (2005), 
and Raschky (2008) 
Schooling ; X Skidmore 
and Toya (2002), Padli 
et al. (2010), and Padli 
and Habibullah (2009) 
Skidmore and Toya 
(2002), Raschky and 
Schwindt (2008), 
Kellenberg and 
Mobarak (2008), and 
Padli et al. (2010), 
Padli and Habibullah 
(2009), Brooks et al. 
2005; Bjarnadottir er 
al., 2011; Sub-
indicator of the World 
Risk Index 2014; post 
2015 HFA  (UNISDR, 
2014) 
Brooks et al., 2005; 
Sub-indicator of the 
World Risk Index 
2014; MDG 3.1 (UN 
2005) 

http://www.fao.org/nr/
water/aquastat/data/q
uery/index.html?lang=
en 

http://data.worldbank.
org/indicator/NY.GDP.P
CAP.CD 

http://unstats.un.org/u
nsd/mdg/Metadata.asp
x?IndicatorId=9 and 
http://www.uis.unesco.
org/Datacentre/Pages/i
nstructions.aspx?SPSL
anguage=EN 

 
 
 
 
 
Post 2015 HFA 
(UNISDR, 2014); 
INFORM 2014 

http://info.worldbank.o
rg/governance/wgi/ind
ex.aspx#home 

Sub-indicator of 
INFORM 2014, WRI 
2014 

http://apps.who.int/gh
odata/ 

Raschky (2008) 
Post 2015 HFA 
(UNISDR, 2014) 

Data not available   
http://data.worldbank.
org/indicator/NE.GDI.T
OTL.KD 

Government 
effectiveness 

Government health 
expenditure per 
capita 

Government stability 
Gross fixed capital 
formation 

Ineffective 
government 
undermines 
implementation, for 
example when 
policies and 
strategies for 
disaster risk 
management are 
not evidence 
based, clearly 
formulated, 
integrated into 
broader policy and 
backed by political 
commitment. 

High rates of Gross 
Fixed Capital 
Formation are 
likely to be 
associated with 
rapidly increasing 
hazard exposure of 
economic assets 

Reflects perceptions of the 
quality of public services, 
the quality of the civil 
service and the degree of 
its independence from 
political pressures, the 
quality of policy 
formulation and 
implementation, and the 
credibility of the 
government's commitment 
to such policies 

Per capita total 
expenditure on health 
(TEH) expressed in 
international dollar 
Purchasing Power Parities 
(PPP) 

Gross capital formation 
(formerly gross domestic 
investment) consists of 
outlays in addition to the 
fixed assets of the 
economy plus net changes 
in the level of inventories. 
Fixed assets include land 
improvements (fences, 
ditches, drains, etc.); 
plant, machinery, and 
equipment purchases; and 
the construction of roads, 
railways, and the like, 
including schools, offices, 
hospitals, private 
residential dwellings, and 

149 

 
 
 
 
 
 
 
 
 
commercial and industrial 
buildings. Inventories are 
stocks of goods held by 
firms to meet temporary or 
unexpected fluctuations in 
production or sales, and 
"work in progress"  

The total value of all final 
goods and services 
produced within a nation in 
a particular year, plus 
income earned by its 
citizens (including income 
of those located abroad) 

Gross National 
Product/Income 

Groundwater 
recharge per capita 

Groundwater recharge per 
capita 

Hospital beds 

Number of hospital beds 
per 10 000 persons. 
Hospital beds in private, 
general and specialised 
hospitals, including medical 
and rehabilitation centres 

Houses with weak 
storm-resistant 
construction 
materials (wood, 
mud) 

Percentage of houses that 
will be 
unable to withstand a 
severe climatic event (e.g. 
hurricane winds) due to 
the quality of the materials 

Adger (2003), Cutter 
et al. (2000, 2003), 
Dwyer et al. (2004), 
Brooks et al. (2005), 
Tunstall et al. (2007), 
Polsky et al. (2007), 
Ojerio et al. (2011), 
Khan (2012), Lee 
(2014); Sub-indicator 
of HDI. 
Brooks et al., 2005 

Sub-indicator of the 
World Risk Index 2014 

http://hdr.undp.org/en
/content/income-index  

http://preview.grid.une
p.ch/  

http://data.worldbank.
org/indicator/SH.MED.
BEDS.ZS 

Shah et al., 2013; de 
Oliveira Mendes 
(2009), Lee (2014); 
Cutter et al. (2000), 
Adger et al. (2004) 

Data can be collected 
locally 

“hospital beds” is 
rather weak, since it 
only provides 
information on the 
health care capacity  

Hospital beds 
indicate the 
capacity of the 
medical care 
infrastructure to 
help or support 
societies in the 
case of a mass 
emergency or 
disaster with 
respective 
treatment 

150 

 
 
 
 
 
 
 
 
used in their construction 

Housing damage in 
extensive disasters 
per 100 000 
population 

Housing damage / 100 000 
population (five-year 
moving average) 

Human rights 

Hyogo Framework 
for Action 

Implemented NAMA 

The indicator for the 
Disaster Risk Reduction 
(DRR) activity in the 
country comes from its 
score of Hyogo Framework 
for Action (HFA) self-
assessment progress 
reports. HFA progress 
reports assess strategic 
priorities in the 
implementation of DRR 
actions and establish 
baselines on levels of 
progress achieved in 
implementing the HFA's 
five priorities for action 
Nationally Appropriate 
Mitigation Actions (NAMAs) 
are policies, programmes 
and projects that 
developing countries 
undertake to contribute to 

Post 2015 HFA 
(UNISDR, 2014) 

Housing damage 
affects both the 
lives and 
livelihoods of low 
income urban and 
rural households. 
Most housing 
damage is spread 
over extensive 
disaster zones and 
occurs in low-
income areas 

Costa (2012) 

Data not available   

Sub-indicator of 
INFORM 2014 

http://preventionweb.n
et/applications/hfa/qbn
hfa/  

http://www.nama-
database.org/index.ph
p/NAMAs 

151 

 
 
 
 
 
 
 
 
 
 
 
 
the global effort to reduce 
greenhouse gas emissions 

Income distribution 

Gini Index 

Increased income, 
or avoided decrease 
in income in 
Adaptation Projects 

Industrial water 
consumption 

Income sources for 
households generated 
under climate change 
scenario is a measure of 
how individual livelihoods 
(specifically income 
sources and income in 
general) are strengthened 
in relation to climate 
change impacts and 
variability 

Annual freshwater 
withdrawals refer to total 
water withdrawals, not 
counting evaporation 
losses from storage basins. 
Withdrawals also include 
water from desalination 
plants in countries where 
they are a significant 
source. Withdrawals can 

The Gini index 
gives an estimate 
of inequality as it 
measures the 
extent to which the 
actual income 
distribution differs 
from an equitable 
distribution. 
Resilience is likely 
to be lower in 
countries with a 
high degree of 
income inequality 
Household 
livelihoods 
(including income 
sources), which 
include how people 
obtain their income 
and have access to 
and use assets to 
make a living, are 
a key part of 
understanding 
project beneficiary 
characteristics 

152 

http://data.worldbank.
org/indicator/SI.POV.G
INI 

Hallegatte 2014; 
Anbarci et al. (2005) 
and Kahn (2005), 
Brooks et al., 2005; 
Sub-indicator of the 
World Risk Index 
2014; post 2015 HFA 
(UNISDR, 2014); 
INFORM 2014 

Adaptation Fund 
indicator 6.1.2  (AF, 
2014) 

Data to be collected by 
reviewing local 
projects/surveys 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

http://data.worldbank.
org/indicator/ER.H2O.F
WIN.ZS/countries/1W?
display=graph 

 
 
 
 
 
 
exceed 100% of total 
renewable resources where 
extraction from non-
renewable aquifers or 
desalination plants is 
considerable or where 
there is significant water 
reuse. Withdrawals for 
industry are total 
withdrawals for direct 
industrial use (including 
withdrawals for cooling 
thermoelectric plants).  
Insurance coverage 
(except life insurance) 

Insurance 
penetration 

Internet users 

Inverse of the 
average number of 
litres of water stored 
per household 
(range: >0–1) 
Investment climate 
Investment in low -
arbon energy 

Internet users are those 
with access to the 
worldwide network. 
Internet users per 100 
inhabitants 
The inverse of the average 
number of litres 
of water stored by each 
household,  + 1 

% of investment in low 
carbon energy as % of 
GDP 

When insurance 
penetration is low, 
asset destruction 
caused by natural 
disasters could 
severely hamper 
capital 
accumulation and 
growth potential 

Hydropower tends 
to compete very 
favourably with 
carbon-fuel energy 
sources in much of 
Asia and Africa, 
even at current 

153 

Baritto et al., 2009; 
Sub-indicator of the 
World Risk Index 
2014; post 2015 HFA  
(UNISDR, 2014) 

Data not publicly 
available 

Perch- Nielsel 2010; 
Post 2015 HFA; 
INFORM 2014 

Hahn et al., 2009 

http://data.worldbank.
org/indicator/IT.NET.U
SER.P2/countries?displ
ay=graph  

Data can be collected 
locally 

Raschky (2008) 
Dercon, 2014 

Data not available   
Data not available at 
National scale - see 
http://www.worldenerg
youtlook.org/investme
nt/ 

 
 
 
 
 
 
 
 
 
 
 
prices, provided it 
is available 
Roads are critical 
to the functioning 
of local economies 
and to small and 
medium 
enterprises. This 
indicator therefore 
can provide a 
proxy of disaster 
impacts in the 
employment and 
productive sectors 

This indicator also 
reveals the general 
health standards of 
a country 

Removal of 
economically active 
population 

Kilometres of roads 
damaged as % of 
road network 

Kilometres of roads 
damaged / km road 
network (five-year moving 
average) 

Length of low-lying 
coastal zone with 
more than 10 
persons per km2 
Life expectancy at 
birth 

Malaria mortality 
rate 

Maternal mortality 
per 100 000 

Mean standard 
deviation of average 
precipitation by 
month  

Years of individual life 
expectancy 
(procedure: 
0.25*Log(log(85/Years of 
individual life 
expectancy))) 
The death rate associated 
with malaria is the number 
of deaths caused by 
malaria per 100 000 people 
per year 
Maternal mortality ratio is 
the number of women who 
die during pregnancy and 
childbirth, per 100 000 live 
births 
Standard deviation of 
average monthly 
precipitation 

154 

Post 2015 HFA 
(UNISDR, 2014) 

Perch- Nielsel, 2010 

Data not available   

Briguglio et al., 2008. 
Brooks et al., 2005; 
Sub-indicator of HDI 
and World Risk Index 
2014 and post 2015 
HFA (UNISDR, 2014) 
Sub-indicator of 
INFORM 2014 

http://data.worldbank.
org/indicator/SP.DYN.L
E00.IN 

http://apps.who.int/gh
odata/ 

Brooks et al., 2005; 
MDG5.1 (UN 2005) 

http://data.worldbank.
org/indicator/SH.STA.
MMRT  

Hahn et al., 2009; 
Shah et al., 2013 

http://www.worldclim.
org/bioclim 

 
 
 
 
 
 
 
 
 
 
 
 
 
Mean standard 
deviation of the daily 
average maximum 
temperature by 
month 
Mean standard 
deviation of the daily 
average minimum 
temperature by 
month  
Mean years of 
schooling  

Measles (MCV) 
immunisation 
coverage among 1-
year-olds (%) 

Medical staff 

Microeconomic 
market efficiency - 
regulation of credit, 
labour and 
business index 
Mobile Telephone 
Subscriptions 

Standard deviation of the 
average daily 
maximum temperature by 
month 

Standard deviation of the 
average daily 
minimum temperature by 
month 

Average number of years 
of education received by 
people aged 25 and older, 
converted from education 
attainment levels using 
official durations of each 
level 
The percentage of children 
under one year of age who 
have received at least one 
dose of measles-containing 
vaccine in a given year 
Sum of medical staff, 
including physicians, 
nurses and midwifes per 
1 000 inhabitants 

This is a component of the 
Fraser Index of Economic 
Freedom 

Mobile telephone 
subscriptions are 
subscriptions to a public 
mobile telephone service 
using cellular technology, 
which provide access to 
the public switched 

This reflects the 
capacity of a 
country to cope 
with health risks 
brought about by 
climate change 

155 

Hahn et al., 2009; 
Shah et al., 2013 

http://www.worldclim.
org/bioclim 

Hahn et al., 2009; 
Shah et al., 2013 

http://www.worldclim.
org/bioclim 

Briguglio et al., 2008; 
Sub-indicator of HDI 

http://hdr.undp.org/en
/content/mean-years-
schooling-adults-years 

Sub-indicator of 
INFORM 2014 

http://apps.who.int/gh
odata/ 

Sub-indicator of ND-
GAIN  

Briguglio et al., 2008 

 INFORM 2014 

http://data.worldbank.
org/indicator/SH.MED.
NUMW.P3 and 
http://data.worldbank.
org/indicator/SH.MED.
PHYS.ZS 
http://www.fraserinstit
ute.org/research-
news/display.aspx?id=
20395 

http://data.worldbank.
org/indicator/IT.CEL.SE
TS.P2/countries/1W?di
splay=map 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sub-indicator of the 
ND-GAIN Index 2014 

http://index.gain.org/a
bout/download 

Adaptation Fund 
indicator 5  (AF, 2014) 

Data to be collected by 
reviewing local 
projects/surveys 

Proposed SDG 85 (UN, 
2014) 

http://data.worldbank.
org/indicator/EN.CLC.G
HGR.MT.CE 

Effectively 
established, 
improved, or 
created ecosystem 
services and/or 
natural assets 
would give 
information on the 
availability of 
resources for 
human access and 
sustainable use, as 
well as overall 
ecosystem health 

Natural capital 
dependency 

Natural habitats 
protected or 
rehabilitated due to 
Adaptation Projects 

Net GHG emissions 
in the Agriculture, 
Forest and other 
Land Use (AFOLU) 
sector (tCO2e)  

telephone network. Post-
paid and pre-paid 
subscriptions are included. 

Ratio of natural capital 
over the total wealth of the 
country 
The extent to which project 
initiatives aimed at 
maintaining or improving 
natural resources (land, 
water, soil, forests, etc.) 
have reached their 
intended objectives 

 GHG net 
emissions/removals by 
LUCF refers to changes in 
atmospheric levels of all 
greenhouse gases 
attributable to forest and 
land-use change activities, 
including but not limited to 
(1) emissions and 
removals of CO2 from 
decreases or increases in 
biomass stocks due to 
forest management, 
logging, fuelwood 
collection, etc.; (2) 
conversion of existing 
forests and natural 
grasslands to other land 

156 

 
 
 
 
 
 
 
uses; (3) removal of CO2 
from the abandonment of 
formerly managed lands 
(e.g. croplands and 
pastures); and (4) 
emissions and removals of 
CO2 in soil associated with 
land-use change and 
management 

Net official development 
assistance (ODA) consists 
of disbursements of loans 
made on concessional 
terms (net of repayments 
of principal) and grants by 
official agencies of the 
members of the OECD’s 
Development Assistance 
Committee (DAC), by 
multilateral institutions, 
and by non-DAC countries 
to promote economic 
development and welfare 
in countries and territories 
in the DAC list of ODA 
recipients. It includes loans 
with a grant element of at 
least 25% (calculated at a 
rate of discount of 10%) 
Number of materials used 
for production 

Net ODA received 
(% of GNI) 

Number and type of 
materials 

Number of deaths 
per 100 000 
inhabitants 

Countries heavily 
dependent on ODA 
will also be more 
dependent on ODA 
decisions to finance 
recovery and 
reconstruction 

Sub-indicator of 
INFORM 2014 

http://data.worldbank.
org/indicator/DT.ODA.
ODAT.GN.ZS 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Sub-indicator of the 
Global Climate Change 
Index 

http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
Germanwatch 

157 

 
 
 
 
 
 
 
 
This indicator does not 
provide information on 
the effectiveness or 
operational capacity of 
EWS 

Adaptation Fund 
indicator 1.2  (AF, 
2014) 

Data to be collected by 
reviewing local 
projects/surveys 

Number of early 
warnings 

Number of early warnings 

Development of 
early warning 
systems is a 
measure of long-
term knowledge 
generated and 
disseminated in the 
area of 
intervention. This 
indicator assumes 
higher numbers of 
early warning 
systems would 
provide more 
information on 
specific risk and 
vulnerability 
assessments 

Hahn et al., 2009; 
Costa (2012), 
Kellenberg and 
Mobarak (2008) 

Sub-indicator of the 
Global Climate Change 
Index (Germanwatch 
2014) 
Adaptation Fund 
indicator 4.1.1  (AF, 
2014) 

http://www.emdat.be 

http://www.emdat.be 

Data to be collected by 
reviewing local 
projects/surveys 

Number of extreme 
events in the past 10 
years 

Number of fatalities 
due to extreme 
events 

Number of health or 
social 
infrastructures 
developed or 
modified to respond 
to new conditions 
resulting from 
climate change 
variability and 
change 

Total number of floods, 
droughts, and cyclones 
that were reported by 
households over the period 
considered 
Sum of fatalities over the 
period considered 

Health and social 
development projects 
support the reform of 
secondary education, 
control the spread of 
infectious diseases, 
increase the capacity of 
health services, provide 
national-level health policy 
assistance; provide 
expanded and improved 
reproductive health 
services, and improve 
conditions for vulnerable 

Number of 
development 
services addressed 
by the intervention 
provides 
information on 
availability of 
adapted services 
available for 
human use in 
response to climate 
change impacts 

Number of 
development-sector 
services addressed 
during the project does 
not inform on the 
sustainability or 
effectiveness of these 
services against the 
impacts of climate 
variability 

158 

 
 
 
 
 
 
children and youth 

Number of hectares 
of crops lost per 
total crop area  

Number of hectares of 
crops lost / total crop area 
(five-year moving average) 

Number of 
landslides recorded 
in the past  five 
years 
Number of risk 
reduction actions or 
strategies 
introduced at local 
level 

Number of landslides 
recorded in the past five 
years (EMDAT definitions), 
divided by land area 
Risk reduction actions or 
strategies include: 
Monitoring/Forecasting 
capacity (EWS, 
vulnerability mapping 
system); Policy/regulatory 
reform; Capacity 
development; Sustainable 
forest management; 
Strengthening 
infrastructure; Supporting 
livelihoods; Mangrove 
reforestation; Coastal 
drainage and 
infrastructure; Irrigation 
system; Community-based 
adaptation; Erosion 
control; Soil water 
conservation; 
Microfinancing; Special 
programmes for women; 
Livelihoods; Water 

Post 2015 HFA 
(UNISDR, 2014) 

Loss of agricultural 
production is 
particularly critical 
for rural 
households and 
contributes to 
continued or 
worsening rural 
poverty 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 
Adaptation Fund 
indicator 3.1.1  (AF, 
2014) 

http://www.vulnerabilit
yindex.net/ 

Data to be collected by 
reviewing local 
projects/surveys 

This assesses the 
extent to which the 
intervention/projec
t or programme 
helped improve risk 
reduction at the 
local level 

Number of introduced 
risk reduction actions 
and strategies does not 
necessarily equate to 
their effective 
application at local 
level 

159 

 
 
 
 
 
 
storage; ICT and 
information dissemination, 
among others 

Number of targeted 
development 
strategies that 
incorporate climate 
change priorities  

This assesses the extent to 
which project interventions 
have effectively helped 
enforce strategies to 
address/incorporate 
climate change risks in the 
different sectors 

Number of tsunamis 
or storms surges 
with runup greater 
than two metres 

Number of tsunamis or 
storms surges with runup 
greater than two metres 
above Mean High Water 
Spring tide (MHWS) per 
1 000 km coastline since 
1900 

Understanding the 
number of 
elements of 
development 
strategy enforced 
to effectively 
address/incorporat
e climate change 
risks (increase 
adaptive capacity 
or achieve an 
enhanced level of 
protection) makes 
it possible to 
determine and 
ensure that specific 
regulations support 
the policy(ies) and 
are being 
successfully 
implemented 
This indicator 
captures the 
potential loss of 
shorelines, coastal 
ecosystems 
and resources, and 
loss of species due 
to catastrophic run 
up of 
seawater onto 
coastal lands 

160 

Adaptation Fund 
indicator 7.2  (AF, 
2014) 

Data to be collected by 
reviewing local 
projects/surveys 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

http://www.vulnerabilit
yindex.net/ 

 
 
 
 
Number, type, and 
sector of policies 
introduced or 
adjusted to address 
climate change risks 

Policies that introduce or 
adjust climate change risks 
is a measure of how 
countries/sectors can 
adapt to climate change 

Numbers of 
beneficiaries of 
Climate Change 
interventions 

Numbers of health 
facilities damaged as 
% of total number of 
health facilities  

Number of people 
benefiting from projects or 
project components that 
address climate change 
issues, e.g. by integrating 
measures to promote 
resilience or reduce 
climate-change-related 
risks 
% of health facilities 
damaged out of total 
number of health facilities 
(five-year moving average) 

Numbers of people 
experiencing 
reductions in 
vulnerability 

Numbers of schools 
damaged as % of 
total number of 
schools  

People who become less 
vulnerable to extreme 
events 

% of schools damaged out 
of total number of schools 
(five-year moving average) 

Developed or 
adjusted policies do 
not guarantee 
adoption or 
implementation. 
Consider other 
aspects like 
regulation and 
enforcement to 
fully understand 
impact of policies. 

Damaged health 
facilities are a 
proxy for disaster 
impacts in the 
health sector. Low-
income households 
in particular are 
dependent on 
publicly provided 
primary health 
facilities 

Damaged schools 
are a proxy for 
disaster impacts in 
education. The 
interruption of 

161 

Adaptation Fund 
indicator 7.1  (AF, 
2014) 

Data to be collected by 
reviewing national 
policies 

Brooks et al., 2011 

Data to be collected by 
reviewing local 
projects/surveys 

Post 2015 HFA 
(UNISDR, 2014) 

Brooks et al., 2011; 
Adaptation Fund 
Indicator 2.2  (AF, 
2014) 

Post 2015 HFA 
(UNISDR, 2014) 

Data to be collected by 
reviewing local 
projects/surveys 

 
 
 
 
 
 
 
 
 
 
 
Nutritional status 

Calorie intake per capita 

Brooks et al., 2005 

schooling 
negatively affects 
future educational 
and hence 
economic prospects  

Official climate 
financing from 
developed countries 
that is incremental 
to ODA (in US$) 

Official climate financing 
from developed countries 
that is incremental to ODA 
(in US$) 

Paved Roads 

This is quantified by the 
proportion of roads 
surfaced with crushed 
stone (macadam) and 
hydrocarbon binder or 
bituminised agents, with 
concrete, or with 
cobblestones, as a 
percentage of all the 
country's roads, measured 
in length  

Under the 
Conference of 
Parties of the 
UNFCCC, 
developed 
countries have 
pledged to provide 
some US$100 
billion per year in 
climate finance by 
2020. This 
indicator will track 
official (i.e. public) 
climate finance 
provided by each 
developed country 
as a contribution 
towards the overall 
target of at least 
US$100 billion per 
year 
Unpaved roads are 
more vulnerable to 
hazards such as 
floods and 
landslides 

162 

Proposed SDG 86 (UN, 
2014) 

http://www.climatefun
dsupdate.org/data 

Brooks et al., 2005; 
Sub-indicator of the 
ND-GAIN Index; post 
2015 HFA  (UNISDR, 
2014) 

http://data.worldbank.
org/indicator/IS.ROD.P
AVE.ZS 

 
 
 
 
 
 
 
Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/NY.GNS.I
CTR.CD 

Hahn et al., 2009; 
Shah et al., 2013 

Data can be collected 
locally 

Shah, 2013; Cutter et 
al. (2003), Dwyer et al. 
(2004) 

Data to be collected 
locally 

Shah, 2013 

Data can be collected 
locally 

Shah, 2013 

Data to be collected 
locally 

Shah et al., 2013 

Data can be collected 
locally 

Per capita net 
savings 

Percentage 
households utilising 
a natural 
water system 

Percentage 
households with 
dependent members 
needing care 

Gross savings are 
calculated as gross 
national income minus 
total consumption, plus net 
transfers. Data are in 
current US dollars 

Percentage of households 
obtaining water from wells, 
rainwater, springs and 
other means apart from 
the public system 
% of households with at 
least one member 
requiring daily care 
because of age, physical or 
mental condition, illness or 
disability 

Low per capita 
savings implies a 
lower capacity to 
buffer losses and 
recover, therefore 
low resilience to 
disaster loss  

Households with 
disabled people 
increase the total 
cost to government 
of responding to, 
and recovering 
from, a disaster 

Percentage 
households with 
members suffering 
from chronic illness 

Percentage of households 
reporting at least one 
member with a chronic 
illness 

Percentage 
households without 
non-agricultural 
income contribution 

Percentage 
households without 
ownership of the 
lands on which they 
live  

Percentage of households 
reporting livelihoods other 
than 
agriculture/fishing/hunting 
as their main source of 
income 
Percentage of households 
that can 
be removed from the lands 
on which 
they presently reside 

163 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Countries with a 
significant or 
growing proportion 
of electricity 
production from 
renewable sources 
are likely to be 
more committed to 
mitigating global 
climate change and 
its effects, as well 
as to 
environmental 
sustainability 

Percentage of 
electricity 
production from 
renewable sources, 
excluding 
hydroelectric  

Electricity production from 
renewable sources, 
excluding hydroelectric; 
includes geothermal, solar, 
tides, wind, biomass, and 
biofuels (% of total) 

Percentage of 
female-headed 
households 

Percentage of households 
where the head of the 
household is female 

Percentage of heads 
of households that 
did not attend school 

Percentage of households 
where the head reports not 
finishing primary school 

Percentage of 
households 
dependent on family 
farm/hunting/fishin
g for food 

Percentage of 
households from 
which a member 
missed work/school 
in past two weeks 
due to illness 
Percentage of 
households 
reporting water 
conflicts 

Percentage of households 
that get their food 
primarily from their 
personal farms, 
hunting/fishing activity 
food 
Percentage of households 
reporting at least one 
member who missed 
school or work due to 
illness in the past two 
weeks 
Percentage of households 
that report having heard 
about conflicts over water 
in their community 

164 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/EG.ELC.R
NWX.ZS 

Hahn et al., 2009; 
Shah et al., 2013 

Data to be collected 
locally 

Hahn et al., 2009; 
Shah et al., 2013 

Data to be collected 
locally 

Hahn et al., 2009; 
Shah et al., 2013 

Data can be collected 
locally 

Shah, 2013 

Data can be collected 
locally 

Hahn et al., 2009 

Data can be collected 
locally 

 
 
 
 
 
 
 
 
 
 
 
 
 
Percentage of 
households that do 
not save crops 

Percentage of households 
that do not keep reserves 
of crops from each harvest 

Percentage of 
households that do 
not save seeds 
Percentage of 
households that 
have applied for 
government 
assistance in the 
past 12 months 
Percentage of 
households with 
family member 
working in a 
different community 
Percentage of 
households with 
orphans 
Percentage of 
households without 
pipe-borne water 

Percentage of 
houses not elevated 
by posts/high 
ground to avoid 
floods 
Percentage of land 
area below  5-m 
elevation 

Percentage of households 
that do not have 
seeds from year to year 
Percentage of households 
that reported that they 
have asked their local 
government for assistance 
in the past 12 months 

Percentage of households 
with family member 
working in a different 
community 

Percentage of households 
with orphans 

Percentage of households 
not receiving water 
through the public water 
system 
Percentage of houses that 
will be unable to withstand 
storm surges and floods 

Area where the elevation is 
5 m or less  above sea 
level  

Percentage of land 
area less than or 
equal to 50m above 
sea level 

Percentage of land area 
below or at 50m above sea 
level 

A country’s 
resilience to future 
hazards is related 
to risks on lowland 
areas 

165 

Hahn et al., 2009 

Hahn et al., 2009 

Data can be collected 
locally 

Data can be collected 
locally 

Hahn et al., 2009; 
Shah et al., 2013 

Data can be collected 
locally 

Hahn et al., 2009; 
Shah et al., 2013 

Data to be collected 
locally 

Hahn et al., 2009 

Data to be collected 
locally 

Shah et al., 2013 

Data not available   

Shah et al., 2013; de 
Oliveira Mendes 
(2009), Lee (2014); 
Cutter et al. (2000), 
Adger et al. (2004) 
Füssel, 2010 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

Data can be collected 
locally 

http://sedac.ciesin.colu
mbia.edu/data/set/nag
dc-population-
landscape-climate-
estimates-v3 
http://www.vulnerabilit
yindex.net/ 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Percentage of old 
house 

Percentage of 
population 65 years 
old and over 

Percentage of population 
65 years old and over 

Percentage of 
population below 5-
m elevation 

Proportion of population 
living in areas where the 
elevation is 5 m or less 

Percentage of 
population under 5 
years of age 

Percentage of population 
under 5 years of age 

Percentage of 
population with an 
injury or death as a 
result of the most 
severe natural 
disaster in the past 
10 years 
Percentage of 
targeted population 
aware of predicted 
adverse impacts of 
climate change and 
of appropriate 
responses 

Percentage of population 
that reported either an 
injury to or death of one of 
their family members as a 
result of the most severe 
flood, drought, or cyclone 
events in the past 10 years 
% of targeted population 
aware of predicted adverse 
impacts of climate change 
and of appropriate 
responses 

Those at either 
extreme of the age 
spectrum have a 
relatively poor 
capacity for self-
protection during a 
disaster 
This indicates how 
many people are 
sensitive to risks 
arising from sea 
level rise and 
storm surges 
Those at either 
extreme of the age 
spectrum have a 
relatively poor 
capacity for self-
protection during a 
disaster 

Measures the level 
of knowledge and 
capacity of the 
targeted population 
to respond to 
adverse effects 

Population aware of 
climate change and 
appropriate response 
measures does not 
necessarily translate to 
the application of 
response measures at 
the household level. 
Population perceptions 
are difficult parameters 
to assess 

166 

de Oliveira Mendes 
(2009), Lee (2014) 

Bjarnadottir er al., 
2011; Khan 2012 

Data not available   

http://data.worldbank.
org/indicator/SP.POP.6
5UP.TO.ZS 

Füssel, 2010; Sub-
indicator of the ND-
GAIN Index 2014 

Bjarnadottir er al., 
2011; Khan 2012 

http://sedac.ciesin.colu
mbia.edu/data/set/nag
dc-population-
landscape-climate-
estimates-v3 

http://data.worldbank.
org/indicator/SP.POP.0
014.TO.ZS 

Hahn et al., 2009 

http://www.emdat.be/
database 

Adaptation Fund 
indicator 3.1 (AF, 
2014) 

Data to be collected by 
reviewing local 
projects/surveys 

 
 
 
 
 
 
 
 
 
 
Personal 
remittances (% of 
GDP) 

Physical exposure  

Physical 
infrastructure 
improved to 
withstand climate 
change and 
variability-induced 
stress 

Personal remittances 
comprise personal 
transfers and 
compensation of 
employees. Personal 
transfers consist of all 
current transfers in cash or 
in kind made or received 
by resident households to 
or from non-resident 
households. Personal 
transfers thus include all 
current transfers between 
resident and non-resident 
individuals. Compensation 
of employees refers to the 
income of border, 
seasonal, and other short-
term workers who are 
employed in an economy 
where they are not 
resident and of residents 
employed by non-resident 
entities. Data are the sum 
of two items defined in the 
sixth edition of the IMF's 
Balance of Payments 
Manual: personal transfers 
and compensation of 
employees  
Number of people located 
in the area in which the 
disaster occurred * 
frequency of the hazard  
Physical infrastructure 
includes: Roads, 
Government Buildings, 
Causeways, Airports, 
Schools, Training Centres, 
Hospitals, other 

Economies where 
remittances 
represent a high 
proportion of GDP 
are more resilient 
as risk is 
geographically 
spread and a lower 
proportion of 
household earnings 
will be affected 

This assesses the 
extent to which 
project/programme 
interventions of 
improvement and 
adaptation of 
physical assets 

167 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/BX.TRF.P
WKR.DT.GD.ZS 

UNDP, 2004 

http://www.vulnerabilit
yindex.net/ 

Adaptation Fund 
indicator 4.2  (AF, 
2014) 

Data to be collected by 
reviewing local 
projects/surveys 

 
 
 
 
 
 
Physician density 

Number of physicians per 
10 000 inhabitants 

Policies for 
preventing future 
risk 

Policies for reducing 
existing risk 

Policies for risk 
governance 

Policies for risk 
knowledge 

Index built from the 
checklist included in HFA 
post-2015 (every item 0-1, 
then simple average) -  
Y/N questions 
Index built from the 
checklist included in HFA 
post 2015 (every item 0-1, 
then simple average) - Y/N 
questions 
Index built from the 
checklist included on HFA 
post 2015 (every item 0-1, 
then simple average) - Y/N 
questions 
Index built from the 
checklist included on HFA 
post 2015 (every item 0-1, 
then simple average) - Y/N 
questions 

achieved their 
intended 
results/objectives 

The number of 
medical staff, 
including 
physicians, nurses 
and midwives, 
reflects the 
capacity that a 
country has to cope 
with exacerbated 
health risks 
brought on by 
climate change. 
Physicians, nurses, 
and midwives are 
weighted the same  

168 

http://www.who.int/gh
o/health_workforce/ph
ysicians_density/en/ 

Halsnæs and 
Verhagen, 2007; Sub-
indicator of the World 
Risk Index 2014 and 
the ND-GAIN index 
2014 and INFORM 
2014; post 2015 HFA 
(UNISDR, 2014) 

Derived from proposed 
post-2015 HFA 
Indicator  (UNISDR, 
2014) 

Derived from proposed 
post-2015 HFA 
Indicator (UNISDR, 
2014) 

Derived from proposed 
post-2015 HFA 
Indicator (UNISDR, 
2014) 

Derived from proposed 
post-2015 HFA 
Indicator (UNISDR, 
2014) 

Available in future 

Available in future 

Available in future 

Available in future 

 
 
 
 
 
 
 
 
 
 
 
Policies for 
strengthening 
resilience 

Poor population 
living in hazards 
plains 

Index built from the 
checklist included in the 
HFA post 2015 (every item 
0-1, then simple average) 
-  Y/N questions 
The percentage of poor 
living in areas subject to 
significant risk of death or 
damage caused by 
prominent hazards: 
cyclones, drought, floods, 
and landslides. The 
indicator maybe calculated 
separately for each 
relevant prominent hazard.  

Population affected 
by droughts 

Population affected 
by natural disasters 

Population density 

People affected by 
droughts 1990-2013 - 
average annual population 
affected (inhabitants) 
Relative number of 
affected population by 
natural disasters in the 
past three years 
Population/m2 

Smallholder 
farming is 
dependent on land, 
water and climate. 
But also the urban 
poor tend to 
depend on 
environmental 
capital for their 
livelihoods and 
living conditions, 
being more 
affected by 
pollution of air and 
water, and often 
living in floodplains 
in cities, with huge 
consequences for 
health and 
wellbeing. 

Greater numbers of 
people increase 
pressure on the 
environment for 
resources. Relative 
flood mortality is 
higher in less 

169 

Derived from proposed 
post 2015 HFA 
Indicator (UNISDR, 
2014) 

Dercon 2014; Cutter et 
al. (2003), Schmidtlein 
et al. (2011), Khan 
(2012), Lee (2014) 

Available in future 

Data are not available   

Sub-indicator of 
INFORM 2014 

Sub-indicator of 
INFORM 2014  

http://www.emdat.be  

http://www.emdat.be  

Birkmann, 2007; de 
Oliveira Mendes, 2009; 
Tate et al., 2010; 
Khan, 2012; Lee. 
2014; Brooks et al., 
2005 

http://data.worldbank.
org/indicator/EN.POP.D
NST 

 
 
 
 
 
 
 
 
 
 
Population exposed 
to floods 

Population exposed 
to hazards 

Physical exposure to flood 
- average annual 
population (2010 as the 
year of reference) exposed 
(inhabitants) 
Sum of people exposed to 
all hazards over the period 
considered (e.g. a year) 

Population exposed 
to sea level rise 
(possible from 1m to 
6m) 

Percentage of population 
exposed to 1-m 
sea level rise 

Population exposed 
to storm surges 

Population exposed 
to tropical cyclones 

Inundated area based on 
historical records from 
1975-2009 
Physical exposure to 
tropical cyclone surges - 
average annual population 
(2010 as the year of 
reference) exposed 

populated than in 
densely populated 
countries 

The knowledge of 
the population 
exposed is 
fundamental for 
raising awareness 
and the 
development of 
protection 
measures (e.g. 
identification of 
suitable shelters) 
and evacuation 
strategies (e.g. 
development of 
evacuation routes) 
This indicator gives 
a general overview 
of the number of 
people living within 
exposed (low - 
lying) areas such 
as coastal zones 

170 

Sub-indicator of 
INFORM 2014 

http://preview.grid.une
p.ch/  

Sub-indicator of the 
World Risk Index 2014 

http://preview.grid.une
p.ch/  

Perch- Nielsel, 2010; 
WRI, 2014 

http://geodata.grid.un
ep.ch/mod_download/d
ownload.php and 
https://www.cresis.ku.
edu/data/sea-level-
rise-maps 

Sub-indicator of 
INFORM 2014  

Sub-indicator of 
INFORM 2014 and 
World Risk Index 2014 

http://preview.grid.une
p.ch/  

 
 
 
 
 
 
 
 
 
 
 
Population exposed 
to tsunamis 

Population growth 
(Annual %) 

Population with 
access to improved 
sanitation  

(inhabitants) per country 

Average annual population 
(2010 as the year of 
reference) physically 
exposed to tsunamis  
(inhabitants) 
The exponential rate of 
growth of mid-year 
population from year t-1 to 
t, expressed as a 
percentage. 

Improved sanitation 
facilities comprise flush 
toilets, piped sewage 
systems, septic tanks, 
flush/pour flush to pit 
latrines, ventilated 
improved pit latrines, pit 
latrines with slabs and 
composting toilets 

Population with 
access to improved 
water supply 

Percentage of the 
population with reasonable 
access (within one km) to 
an adequate amount of 
water (20 litres per 
person) through a 
household connection, 
public standpipe well or 

High population 
growth may 
translate into 
rapidly increasing 
hazard exposure of 
people 
Access to 
sanitation is 
particularly crucial 
to build up 
preparedness to 
various natural 
disasters that are 
exacerbated by 
climate change. 
People without 
access to improved 
sanitation facilities 
are susceptible to 
diseases and can 
become more 
vulnerable 
following a hazard 
event 
People without 
improved water 
supply sources are 
vulnerable to 
diseases caused by 
unclean water and 
could become more 
vulnerable in the 

171 

Sub-indicator of 
INFORM 2014 

http://preview.grid.une
p.ch/  

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/SP.POP.G
ROW 

Füssel, 2010; Brooks 
et al., 2005; Sub-
indicator of the ND-
GAIN Index 2014, the 
World Risk Index  
2014, MDG 7.9 (UN 
2005) and WDIs and 
INFORM 2014 

http://unstats.un.org/u
nsd/mdg/Metadata.asp
x?IndicatorId=31 and 
http://data.worldbank.
org/indicator/SH.STA.A
CSN and 
www.wssinfo.org/data-
estimates/table/ 

Füssel, 2010; Shah et 
al 2013; Sub-indicator 
of the World Risk Index 
2014, MDG 7.8  (UN 
2005) and WDIs and 
INFORM 2014; Sub-
indicator of the ND-
GAIN Index 2014 

http://mdgs.un.org/un
sd/mdg/metadata.aspx
?indicatorid=30 and 
http://data.worldbank.
org/indicator/SH.H2O.
SAFE.ZS and 
www.wssinfo.org/data-
estimates/table/ 

 
 
 
 
 
 
 
Poverty bias 

Poverty gap 

Power consumption 

spring, or rain water 
system 
The relative exposure of 
the poor, compared with 
the share of assets owned 
by the poor 
Poverty gap is the mean 
shortfall from the poverty 
line (counting the non-poor 
as having zero shortfall), 
expressed as a percentage 
of the poverty line. This 
measure reflects the depth 
of poverty as well as its 
incidence 
Electricity consumption for 
industrial uses 

aftermath of a 
hazard event 

Households in 
extreme poverty 
have greater 
difficulty to access 
the assets required 
to buffer disaster 
losses and are 
therefore likely to 
be less resilient  

Power essentiality 

Essentiality of energy 
availability for industry 

Private per capita 
expenditure on 
health  

Private per capita 
expenditure on health (as 
a percentage of total 
health expenditure) 

Public expenditure 
as % of GDP 

General government final 
consumption expenditure 
(formerly general 
government consumption) 
includes all current 
expenditures by 
government for purchasing 
goods and services 

Low levels of public 
expenditure are 
reflected in 
deficiencies in 
public services and 
social welfare 
systems. Low-
income households 

172 

Hallegatte, 2014 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/SI.POV.G
APS 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Sub-indicator of the 
World Risk Index 2014 

Post 2015 HFA 
(UNISDR, 2014) 

http://www.iea.org/Sa
nkey/index.html or 
http://www.iea.org/sta
ts/prodresult.asp?PRO
DUCT=Electricity/Heat 
http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
World Health Statistics, 
Health Expenditure 
Ratios: 
http://apps.who.int/gh
odata/ 
http://data.worldbank.
org/indicator/NE.CON.
GOVT.ZS 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
are particularly 
dependent on 
public expenditure 
to manage their 
risks  

(including compensation of 
employees). It also 
includes most expenditures 
on national defence and 
security, but excludes 
government military 
expenditures that form 
part of government capital 
Number of hospital beds 
per 1 000 inhabitants 

Pure Prime Risk represents 
the proportion of the value 
of exposed assets that is at 
risk each year 

The higher the Pure 
Prime Risk, the 
higher the risk to 
the country’s 
economy 

Public infrastructure 
and resources that 
belong to 
inhabitants 

Pure Prime Risk 

Quality and price of 
house 

Quality of energy 
supply 

Number of supply 
interruptions 

The quality of 
utilities 
infrastructure 
affects severity of 
impact. A 
significant 
proportion of 
business 
interruption is 
associated with 
power outages. A 
reliable electricity 
network is 
therefore a key 
resilience factor for 
business  

173 

Polsky et al. (2007), de 
Oliveira Mendes 
(2009), Menoni et al. 
(2012), Lee (2014) 

Post 2015 HFA 
(UNISDR, 2014) 

Cutter et al. (2000), 
Adger et al. (2004), 
Lee (2014) 
Swanson et al., 2007; 
Post 2015 HFA 
(UNISDR, 2014) 

Data can be collected 
locally 

http://www.prevention
web.net/english/hyogo
/gar/2013/en/home/da
ta-platform.html 

Data not available   

file:///D:/Dev1/WEF_G
lobalEnergyArchitectur
ePerformance_Index_2
015.pdf 

 
 
 
 
 
 
 
 
 
Quality of port 
infrastructure  

The Quality of port 
infrastructure measures 
business executives' 
perception of their 
country's port facilities 

Quality of trade and 
transport 
infrastructure 

Data are from Logistics 
Performance Index surveys 
conducted by the World 
Bank in partnership with 
academic and international 
institutions and private 
companies and individuals 
engaged in international 
logistics. (1=low to 
5=high)  

Rate of 
unemployment 

Unemployment refers to 
the share of the labour 
force that is without work 
but available for and 
seeking employment (% of 
total labour force)  

Poor quality 
infrastructure is 
likely to be more 
vulnerable to 
hazards. Damaged 
and destroyed 
infrastructure is 
responsible for 
business and 
livelihood 
interruption and is 
therefore a major 
risk driver 
Quality of trade 
and transport 
infrastructure 
shows the capacity 
to effectively 
supply and manage 
essential 
infrastructure by 
the public and 
private sectors, 
and is indicative of 
capacity to sustain 
that infrastructure 
in the face of 
future changes, 
including climate 
change  
Diverse 
employment 
opportunities. As 
with poverty, the 
level of 
unemployment will 
have a direct 
influence on the 
capacity of 
households to 
buffer disaster 

174 

Post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/IQ.WEF.P
ORT.XQ 

ND-GAIN Index 2014  

http://data.worldbank.
org/indicator/LP.LPI.IN
FR.XQ?display=graph 

Dwyer et al. (2004), de 
Oliveira Mendes 
(2009), Khan (2012), 
Lee 2014 Post 2015 
HFA (UNISDR, 2014) 

http://data.worldbank.
org/indicator/SL.UEM.T
OTL.ZS 

 
 
 
 
 
Ratio of length of 
borders (land and 
maritime) to total 
land area 

Ratio of length of borders 
(land and maritime) to 
total land area 

Regulation quality 

Reflects perceptions of the 
ability of the government 
to formulate and 
implement sound policies 
and regulations that permit 
and promote private sector 
development 

Relative 
vulnerability 

Number of people 
killed/the number of 
people exposed 

losses and recover 
or 
provide more 
options if climate 
affects a particular 
type of occupation 

This indicator 
captures the 
degree to which a 
country’s land area 
is fragmented and 
‘thin’ 
The capacity to 
regulate the 
private sector, 
including 
households, will 
influence the 
effectiveness of 
disaster risk 
management 
instruments such 
as building codes 
and land-use plans 
A higher relative 
mortality, 
expressed as the 
average annual 
deaths as a 
proportion of the 
average population 
exposed, indicates 
a higher 
vulnerability for a 
particular country 

175 

Sub-indicator of the 
Environmental 
Vulnerability Index 
(UNDP, 2004) 

http://www.vulnerabilit
yindex.net/ 

Post 2015 HFA 
(UNISDR, 2014) 

http://info.worldbank.o
rg/governance/wgi/ind
ex.aspx#home 

UNDP, 2004 

http://www.vulnerabilit
yindex.net/ 

 
 
 
 
 
Füssel, 2010 

http://data.worldbank.
org/indicator/ER.H2O.I
NTR.PC  

Perch- Nielsel, 2010 

Data can be collected 
locally 

Post 2015 HFA 
(UNISDR, 2014) 

http://www.prevention
web.net/english/hyogo
/gar/2013/en/home/da
ta-platform.html 

INFORM 2014 

http://www.irfnet.ch/  

Renewable water 
resources per person 

m3capita = (internal river 
flows + groundwater from 
rainfall)/population 

Required adaptation 
of corals to 
increased thermal 
stress 

Risk-adjusted public 
debt 

Frequency of coral 
bleaching 

Indicator to be constructed 
from Fiscal AAL and public 
debt 

Road density 

Road density is the ratio of 
the length of the country's 
total road network to the 
country's land area. The 
road network includes all 
roads in the country: 
motorways, highways, 
main or national roads, 
secondary or regional 
roads, and other urban and 
rural roads 

The greater the 
resource 
availability per 
person, the greater 
the resilience of 
society to droughts 
and heat waves 

This highlights the 
dependence of the 
tourism sector on 
the maintenance of 
natural capital 
Fiscal AAL 
represents a 
contingent liability 
of governments, 
and is often 
invisible when 
accounting for 
public debt. For 
countries with 
already high or 
unsustainable 
levels of public 
debt, disaster risk 
represents another 
critical debt layer 

176 

 
 
 
 
 
 
 
 
Costa (2012); Post 
2015 HFA (UNISDR, 
2014) 

http://info.worldbank.o
rg/governance/wgi/ind
ex.aspx#home 

Brooks et al., 2005; 
ND-GAIN 2014 

Brooks et al., 2005 

http://data.worldbank.
org/indicator/SP.RUR.T
OTL.ZS 

http://data.worldbank.
org/indicator/SH.H2O.
SAFE.RU.ZS 

Plans related to 
disaster risk 
management, 
including land use 
plans, building 
codes and 
environmental 
regulations, are 
unlikely to be 
implemented in 
countries where 
there is 
only weak 
compliance with 
laws and 
regulations 

People without 
improved water 
sources are 
vulnerable to 
diseases caused by 
unclean water and 
could become more 
vulnerable in the 
aftermath of a 
hazard 

Rule of law 

Reflects the extent to 
which agents have 
confidence in and abide by 
the rules of society, and in 
particular the quality of 
contract enforcement, 
property rights, the police, 
and the courts, as well as 
the likelihood of crime and 
violence 

Rural population 

Rural population (% of 
total population) 

Rural population 
with access to safe 
water (%) 

Access to a safe  water 
source refers to the 
percentage of the 
population using an 
improved drinking water 
source. The improved 
drinking water source 
includes piped water on 
premises (piped household 
water connection located 
inside the user’s dwelling, 
plot or yard), and other 
improved drinking water 
sources (public taps or 
standpipes, tube wells or 
boreholes, protected dug 
wells, protected springs, 
and rainwater collection). 

177 

 
 
 
 
 
 
Sector - specific 
greenhouse gas 
emission intensity 

Share (%) of 
population 
undernourished 

Share of agricultural 
value added in GDP 

CO2 emissions from 
manufacturing industries 
and construction include 
emissions from the 
combustion of fuels in 
industry 
Population below minimum 
level of dietary energy 
consumption (also referred 
to as prevalence of 
undernourishment) shows 
the percentage of the 
population whose food 
intake is insufficient to 
meet dietary energy 
requirements continuously 

Agriculture corresponds to 
ISIC divisions 1-5 and 
includes forestry, hunting, 
and fishing, as well as 
cultivation of crops and 
livestock production. Value 
added is the net output of 
a sector calculated by 
adding up all outputs and 
subtracting intermediate 
inputs. 

Malnutrition can be 
a product of 
different 
circumstances 
related to 
development 
policies and 
strategies, such as 
agricultural 
measures for food 
availability 

Sub-indicator of the 
ND-GAIN Index 2014 

http://data.worldbank.
org/indicator/EN.CO2.
MANF.ZS 

Sub-indicator of the 
World Risk Index 2014 
and ND-GAIN Index 
2014 and INFORM; 
MDG1.9 (UN 2005) 

http://data.worldbank.
org/indicator/SN.ITK.D
EFC.ZS 

Füssel, 2010; Füssel 
and Klein, 2006 

http://data.worldbank.
org/indicator/NV.AGR.T
OTL.ZS 

Share of arrivals for 
leisure, recreation 
and holidays 
Share of coastal area  km of coastline (scale by 

Share of female 
representatives in 
the National 
Parliament 

land area) 
The number of seats held 
by women in national 
parliament expressed as a 
percentage of all occupied 
seats 

This indicator gives 
an idea of the 
progress of female 
participation in the 
highest levels of 
society 

Low relevance to 
adaptive capacity 

Perch- Nielsel, 2010 

Data not available   

Füssel 2009, Brooks et 
al., 2005 
Sub-indicator of the 
World Risk Index 
2014; MDG 3.3 (UN 
2005) 

http://preview.grid.une
p.ch/  
http://data.worldbank.
org/indicator/SG.GEN.P
ARL.ZS and 
http://mdgs.un.org/un
sd/mdg/Data.aspx 

178 

 
 
 
 
 
 
 
 
 
 
 
 
Slum populations 

Strength of social 
networks  

Subsidised insurance 
for the poor 

Sum of losses in US$ 
purchasing power 
parity (PPP) 

The proportion of urban 
population living in slum 
households, defined by the 
Millennium Development 
Goals as a group of 
individuals living under the 
same roof lacking one or 
more life-supporting 
facilities, namely access to 
safe water, access to good 
sanitation, sufficient living 
area and durability of 
housing 

Availability of Subsidised 
insurance for the poor (0-
1) 
Sum of total damages over 
the period considered in 
US$ purchasing power 
parity (PPP) 

Total affected capital  Capital losses due to 

extreme events  

Total damages 
relative to GDP  

Damages of past 
events/GDP 

This describes the 
extent of loss of 
the productive 
capacity of a 
country following 
an extreme event 

Total economic 
damages 

Sum of total damages 
related to all hazards over 
the period considered 

Total economic 
damages describe 
the extent of 
economic impacts 
caused by climate-

179 

Urban populations 
living in slum-like 
conditions are 
vulnerable to 
climate change and 
poor health  

Sub-indicator of the 
World Risk Index 2014 
and ND-GAIN Index 
2014; MDG 7.10 (UN 
2005); post 2015 HFA 
(UNISDR, 2014) 

http://mdgs.un.org/un
sd/mdg/SeriesDetail.as
px?srid=710 

Füssel and Klein, 2006;   Data not available   

Hallegatte, 2014 

Sub-indicator of the 
Global Climate Change 
Index (Germanwatch 
2014) 
Hallegatte, 2014 

Data can be collected 
locally 

http://germanwatch.or
g/en/cri 

Birkman, 2007; Sub-
indicator of the Global 
Climate Change Index 
2014 

http://data.worldbank.
org/data-
catalog/world-
development-indicators 
http://www.emdat.be  

Forgette and Boening 
(2010); Hallegatte 
(2014); Akter and 
Mallick 2013 

http://www.emdat.be  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Brooks et al., 2005; 
Cutter et al. 2003; 
Sub-indicator of the 
World Risk Index 2014 

http://data.worldbank.
org/indicator/SH.XPD.P
CAP 

Sub-indicator of 
INFORM 2014 and 
Proposed SDG 94 (UN, 
2014) 

http://www.unhcr.org/
pages/49c3646c4d6.ht
ml  

Total health 
expenditure 

Total health expenditure is 
the sum of public and 
private health expenditure 
as a ratio of the total 
population. It covers the 
provision of health services 
(preventive and curative), 
family planning activities, 
nutrition activities, and 
emergency aid designated 
for health, but does not 
include the provision of 
water and sanitation 

Total refugees and 
people in refugee-
like situations  

Total refugees and people 
in refugee-like situations 

related hazards 
over a certain 
period  

High levels of 
government 
expenditure on 
health are 
understood to be 
an indicator for the 
quality of the 
health system, 
which is an 
important factor of 
adaptive capacity 
because medical 
services represent 
important sources 
of post-disaster 
relief. 
Displaced people 
are normally a 
particularly at-risk 
group and are 
more likely to live 
in vulnerable 
conditions in 
hazard-prone 
areas, with less 
access to basic 
services than low-
income households 
in general 

180 

 
 
 
 
Tourism as % of 
exports 

Tourism as % of 
GDP 

International tourism 
receipts are expenditures 
by international inbound 
visitors, including 
payments to national 
carriers for international 
transport. These receipts 
include any other 
prepayment made for 
goods or services received 
in the destination country. 
They may also include 
receipts from same-day 
visitors, except when these 
are important enough to 
justify separate 
classification. For some 
countries they do not 
include receipts for 
passenger transport items. 
Their share in exports is 
calculated as a ratio to 
exports of goods and 
services, which comprise 
all transactions between 
residents of a country and 
the rest of the world 
involving a change of 
ownership from residents 
to non-residents of general 
merchandise, goods sent 
for processing and repairs, 
non-monetary gold, and 
services. 
International tourism 
receipts are expenditures 
by international inbound 
visitors, including 
payments to national 
carriers for international 
transport. These receipts 

Economies which 
are significantly 
concentrated in the 
tourism sector may 
have lower 
resilience when 
that sector is 
affected 

Perch- Nielsel 2010; 
post 2015 HFA 
(UNISDR, 2014) 

http://data.worldbank.
org/indicator/ST.INT.R
CPT.XP.ZS 

Perch- Nielsel, 2010 

http://data.worldbank.
org/indicator/ST.INT.R
CPT.CD 

Economies which 
are significantly 
concentrated in the 
tourism sector may 
have lower 
resilience when 
that sector is 

181 

 
 
 
 
include any other 
prepayment made for 
goods or services received 
in the destination country. 
They also may include 
receipts from same-day 
visitors, except when these 
are important enough to 
justify separate 
classification. For some 
countries they do not 
include receipts for 
passenger transport items 
(current US$). 
The number of wheel and 
crawler tractors (excluding 
garden tractors) in use in 
agriculture at the end of 
the calendar year or during 
the first quarter of the 
following year. Arable land 
includes land defined by 
the FAO as land under 
temporary crops (double-
cropped areas are counted 
once), temporary meadows 
for mowing or for pasture, 
land under market or 
kitchen gardens, and 
temporarily fallow land. 
Land abandoned as a 
result of shifting cultivation 
is excluded. 
This indicator is calculated 
for each country as the 
simple average (i.e. the 
mean) of total trade (i.e. 
the sum of exports and 
imports of goods and 
services) relative to GDP 

Tractor use per 100 
sq. km of arable land 

Trade openness 

affected 

Sub-indicator of the 
ND-GAIN Index 2014 

http://data.worldbank.
org/indicator/AG.LND.T
RAC.ZS 

The more open an 
economy the more 
resilient it is to 
disasters affecting 
any one sector 

Skidmore and Toya 
(2002) and Raschky 
and Schwindt (2008) 

http://data.worldbank.
org/indicator/BX.GSR.
GNFS.CD and 
http://data.worldbank.
org/indicator/BM.GSR.
GNFS.CD 

182 

 
 
 
 
 
 
 
 
Transport volume 

Industry 

Tuberculosis 
prevalence 

Removal of 
economically active 
population 

The number of cases of 
tuberculosis (all forms) in 
a population at a given 
point in time (the middle of 
the calendar year), 
expressed as the rate per 
100 000 population. 
Estimates include cases of 
TB in people with HIV 

Type of materials 

Industry 

Unpopulated land 
area 

Unpopulated land area 

Urban Concentration  % of total population. 

Urban population refers to 
people living in urban 
areas as defined by 
national statistical offices 

The percentage of people 
who have received a 
vaccine in a given year 

Machinery and transport 
equipment (% of value 
added in manufacturing). 
Value added in 
manufacturing is the sum 
of gross output minus the 

Vaccination against 
climate-sensitive 
vector-borne 
diseases 

Value of production 
equipment 

Countries in which 
urban populations 
are concentrated in 
a single or a small 
number of urban 
areas are 
considered to be 
more sensitive to 
climate change 

183 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 
Sub-indicator of 
INFORM 2014 

Data not available   

http://apps.who.int/gh
odata/ 

Data not available   

http://preview.grid.une
p.ch/  

http://index.gain.org/a
bout/download 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Brooks et al., 2005 

Kellenberg and 
Mobarak (2008); Sub-
indicator of the ND-
GAIN Index 2014 and 
WDIs and post HFA 
(UNISDR, 2014) 

Füssel and Klein, 2006  Data are not available 
for vaccination against 
climate sensitive vector 
borne disease 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

http://data.worldbank.
org/indicator/NV.MNF.
MTRN.ZS.UN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Keefer et al. (2011), 
Kahn (2005), and 
Raschky and Schwindt 
(2008); Post 2015 HFA 
(UNISDR, 2014) 

http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
http://info.worldbank.o
rg/governance/wgi/ind
ex.aspx#home 

Vertical integration 

Voice and 
accountability 

value of intermediate 
inputs used in production 
for industries classified in 
ISIC major division D. 
Machinery and transport 
equipment correspond to 
ISIC divisions 29, 30, 32, 
34, and 35 
Degree of vertical 
integration 

Reflects perceptions of the 
extent to which a country's 
citizens are able to 
participate in selecting 
their government, as well 
as freedom of expression, 
freedom of association, 
and a free media 

The extent to 
which citizens are 
able to hold others, 
including 
government, to 
account for their 
actions is critical 
not only to ensure 
that disaster risk 
management plans 
are implemented 
but also to 
strengthen 
accountability in 
the case of actions 
that transfer risks 
from one sector to 
another 

184 

 
 
 
 
 
Wastewater 
treatment 

This tracks the 
performance of basic 
wastewater management  
on an ordinal scale with a 
range from 0 (very poor 
environmental 
performance) to 100 
(excellent environmental 
performance) 

Water dependency 
ratio 

Water essentiality 

Indicator expressing the 
percentage of total 
renewable water resources 
originating outside the 
country. 

Extent to which water is 
essential to industrial 
processes 

Untreated sewage 
can disrupt the 
functioning of 
downstream 
ecosystems. Good 
wastewater 
management is 
especially relevant 
for areas facing 
more significant 
impacts of climate 
change and rapid 
population growth, 
since such areas 
may face more 
constrained water 
resources in the 
future 
High dependency 
on foreign water 
resources 
exacerbates water 
insecurity due to 
climate change  

Water stress 

Water stress occurs when 
the demand for water 
exceeds the available 
amount during a certain 
period or when poor 
quality restricts its use 

An unsustainable 
withdrawal of 
renewable water 
resources can 
increase land 
degradation and 
drought risk 

185 

Sub-indicator of the 
World Risk Index 2014 

http://epi.yale.edu/  

Sub-indicator of the 
ND-GAIN Index 2014 

Sub-indicator of the 
Industrial Vulnerability 
Index (Hiete and Merz, 
2009) 

Post 2015 HFA 
(UNISDR, 2014) 

http://www.fao.org/nr/
water/aquastat/data/q
uery/index.html?lang=
en 

http://www.iscramlive.
org/ISCRAM2009/pape
rs/Contributions/131_A
n%20Indicator%20Fra
mework%20to%20Ass
ess%20the%20Vulnera
bility_Merz2009.pdf 
http://www.fao.org/cli
matechange/asis/en/ 

 
 
 
 
 
 
 
Water use ratio 

Litres /capita/day 

Wealth of Nations 

This provides country-level 
data on comprehensive 
wealth, adjusted net 
savings, and non-
renewable resource 
indicators 

A country’s ability 
to maintain high-
level access to 
improved drinking 
water indicates its 
capacity to adapt 
to water shortage 
in general  

Halsnæs and 
Verhagen, 2007; 
Füssel, 2010; Brooks 
et al., 2005 

http://www.grida.no/gr
aphicslib/detail/water-
availability-in-
africa_3368 

Füssel, 2010 

http://data.worldbank.
org/sites/default/files/t
otal_and_per_capita_w
ealth_of_nations.xls  

186 

 
 
 
 
 
 
 
 
Table II – Indexes  identified by reviewing the relevant literature on climate change, 
development and disaster risk. (alphabetical order)   
Index name 

Reference  

Definition 

Rational  

Data source  

Agriculture 
Stress Index  

Disaster Deficit 
Index 100 

Disaster Deficit 
Index 50 

ASI is based on 10-day satellite data of 
vegetation and land surface 
temperature from the METOP-AVHRR 
sensor at 1-km resolution. Agricultural 
drought: 30% of cropland under stress 
for more than 10 days 

The DDI captures the relationship 
between the demand for contingent 
resources to cover the losses caused 
by the Maximum Considered Event 
(MCE) and the public sector’s 
economic resilience (that is, the 
availability of internal and external 
funds for restoring affected 
inventories). Probable max. loss in 100 
years 

The DDI captures the relationship 
between the demand for contingent 
resources to cover the losses caused 
by the Maximum Considered Event 
(MCE) and the public sector’s 
economic resilience (that is, the 
availability of internal and external 
funds for restoring affected 
inventories). Probable max. loss in 50 
years 

Sub-indicator of INFORM 
2014 

Countries with a high DDI and a low 
capacity to mobilise financial resources 
(through insurance, credits, taxation, 
debt, etc.) will have a low resilience to 
intensive disasters 

Adapted from post 2015 
HFA (UNISDR, 2014) 

http://www.fao.org
/giews/earthobserv
ation/asis/index_1.j
sp?lang=en 

http://www.iadb.or
g/exr/disaster/ddi.c
fm?language=EN&p
arid=2 

Countries with a high DDI and a low 
capacity to mobilise financial resources 
(through insurance, credits, taxation, 
debt, etc.) will have a low resilience to 
intensive disasters 

Adapted from post 2015 
HFA (UNISDR, 2014) 

http://www.iadb.or
g/exr/disaster/ddi.c
fm?language=EN&p
arid=2 

187 

 
 
 
 
 
 
Countries with a high DDI and a low 
capacity to mobilise financial resources 
(through insurance, credits, taxation, 
debt, etc.) will have a low resilience to 
intensive disasters 

Adapted from post 2015 
HFA (UNISDR, 2014) 

http://www.iadb.or
g/exr/disaster/ddi.c
fm?language=EN&p
arid=2 

Sub-indicator of INFORM 
2014 

Briguglio et al., 2008 

If an economy already has high levels of 
unemployment and inflation, it is likely 
that adverse shocks would impose 
significant costs on it 

Vulnerable states may have difficulties 
recovering from the impacts of natural 
hazard, owing to their critical inherent 
characteristics 
Disadvantaged women, in terms of 
reproductive health, empowerment and 
the labour market, are likely to be less 
resilient to disaster loss 

Füssel, 2010; Sub-indicator 
of the World Risk Index 
2014 

Post 2015 HFA (UNISDR, 
2014); INFORM 2014 

http://www.fao.org
/economic/ess/ess-
fs/ess-fadata/en/ 

http://data.worldba
nk.org/indicator/SL.
UEM.TOTL.NE.ZS 
and 
http://data.worldba
nk.org/indicator/SL.
UEM.TOTL.NE.ZS 
http://ffp.statesind
ex.org/rankings-
2013-sortable 

http://hdr.undp.org
/en/content/gender
-inequality-index-gii 

Disaster Deficit 
Index 500 

Domestic Food 
Price Volatility 
Index 

Economic 
discomfort 
index 

The DDI captures the relationship 
between the demand for contingent 
resources to cover the losses caused 
by the Maximum Considered Event 
(MCE) and the public sector’s 
economic resilience (that is, the 
availability of internal and external 
funds for restoring affected 
inventories). Probable max. loss in 500 
years 

This compares the variations of 
monthly change in international prices 
of a basket of food commodities across 
countries and time 
The sum of unemployment and 
inflation rates 

Failed States Index This captures a state’s vulnerability 

Gender 
Inequality 
Index 

based on 12 variables that can be 
divided into social, economic and 
political indicators 
The GII measures gender inequalities 
in three important aspects of human 
development—reproductive health 
measured by maternal mortality ratio 
and adolescent birth rates; 
empowerment, measured by 
proportion of parliamentary seats 
occupied by females and proportion of 
adult females and males aged 25 
years and above with at least some 
secondary education; and economic 
status expressed as labour market 
participation and measured by labour 
force participation rate of female and 

188 

 
 
 
 
male populations aged 15 years and 
above 

General food 
availability 

Gini index 

Food production index 

Brooks et al., 2005 

The Gini index gives an estimate of 
inequality as it measures the extent to 
which 

Income distribution All 

the actual income 
distribution differs from an 
equitable distribution. 
Resilience is likely to be 
lower in countries with a 
high degree of income 
inequality 

Global Aridity 
Index 

The ratio of the annual precipitation 
sum in mm to the annual mean 
temperature in °C +10 

World Bank, 2014 

Global Hunger 
Index 

The GHI combines three equally 
weighted indicators in one index 
number:  
1) Undernourishment - the proportion 
of undernourished as a percentage of 
the population (reflecting the share of 
the population with insufficient calorie 
intake); 
2) Child underweight - the proportion 
of children under the age of five who 
are underweight (low weight for age 
reflecting wasting, stunted growth, or 

Households and communities with high 
levels of malnutrition are likely to have a 
very low capacity to buffer disaster 
losses, such as failed harvests 

Füssel, 2010; Post 2015 
HFA (UNISDR, 2014) 

189 

http://data.worldba
nk.org/indicator/AG
.PRD.FOOD.XD 
Hallegatte, 2014; 
Anbarci et al. 
(2005) and Kahn 
2005, Brooks et al., 
2005; Sub-indicator 
of the World Risk 
Index 2014; post 
2015 HFA (UNISDR, 
2014); INFORM 
2014 
http://data.worldba
nk.org/indicator/SI.
POV.GINI 
http://www.cgiar-
csi.org/data/global-
aridity-and-pet-
database 
http://www.ifpri.org
/book-
8018/ourwork/rese
archarea/global-
hunger-index 

 
 
 
 
 
HDI  

Human Asset 
Index 

Multidimension
al poverty index 

Trade 
concentration 
Index 

both), which is one indicator of child 
malnutrition; and 
3) Child mortality - the mortality rate 
of children under the age of five 
(partially reflecting the fatal synergy of 
inadequate dietary intake and 
unhealthy environments). 
The Human Development Index 
measures development by combining 
indicators of life expectancy, 
educational attainment and income 
into a composite index 
Based on indicators of: (a) nutrition: 
percentage of population 
undernourished; (b) health: mortality 
rate of children aged five years or 
under; (c) education: the gross 
secondary school enrolment ratio; and 
(d) adult literacy rate 
The Multidimensional Poverty Index 
(MPI) identifies overlapping 
deprivations at the household level 
across the same three dimensions as 
the Human Development Index (living 
standards, health, and education) and 
shows the average number of poor 
people and deprivations with which 
poor households contend 
Calculated using the shares of all 
three-digit products in a country’s 
exports: 

Hj = sqrt [ sum (xi / Xt)2] 

where xi is country j’s exports of 
product i (at the three-digit SITC 
classification) and Xt is country j’s 
total exports 

UNDP, 2014; Füssel, 2010; 
and INFORM 

Füssel, 2010 

http://hdr.undp.org
/en/content/table-
1-human-
development-index-
and-its-components 
http://www.ferdi.fr/
en/indicator/human
-assets-index 

Sub-indicator of INFORM 
2014 

http://hdr.undp.org
/en/content/table-
6-multidimensional-
poverty-index-mpi 

The more diversified an economy, the 
more it is resilient to disasters affecting 
any one sector. Export diversification is 
deemed to be important for developing 
countries because many developing 
countries are often highly dependent on 
relatively few primary commodities for 
their export earnings 

Post 2015 HFA (UNISDR, 
2014) 

190 

 
 
 
 
 
 
 
 
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European Commission 
EUR 27126 EN – Joint Research Centre – Institute for Environment and Sustainability 

Title: Climate resilient development index: theoretical framework, selection criteria and fit-for-purpose indicators. 

Authors: Apollonia Miola, Vania Paccagnan, Eleni Papadimitriou, Andrea Mandrici 

Luxembourg: Publications Office of the European Union 

2015 –191 pp. – 21.0 x 29.7 cm 

EUR – Scientific and Technical Research series –ISSN 1831-9424 (online) 

ISBN 978-92-79-46012-8 (PDF) 

doi: 10.2788/07628 

191 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
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doi 10.2788/07628 

ISBN 978-92-79-46012-8 

192