The 1451 Review (Volume 1) 2021

List of Variables
Variable definition
Total Annual Adaptation
aid per capita
Vulnerability to Climate
Change
Sensitivity to Climate
Change
Variable
name
Specification
Source
AidCapita In constant 2016 USD, logged OECD-DAC
Vulnerab
Sen
1-100 where higher values signal
higher vulnerability, lagged
1-100 where higher values signal
higher sensitivity, lagged
ND-GAIN
ND-GAIN sub-index
under vulnerability
The index has been constructed by measuring exposure, sensitivity and
adaptive capacity across six life-supporting sectors; food, water, health, ecosystem
services, human habitat and infrastructure (see Appendix 3). With regards to
interpretation, a lower score indicates a better outcome. All the measures are weighted
equally within the indices and the focus is on the long-term vulnerability to climate
change. The entire vulnerability index is used in the main model, and the sub-indices
on adaptive capacity and sensitivity are used in a partial model to assess the
differences between physical and structural vulnerability. Indices have been scaled by
Adaptive Capacity Capa 1-100 where lower values signal
greater adaptive capacity, lagged
Readiness Ready 1-100 where higher values signal
higher readiness
Global Climate Risk
Index
CRI
0-126.17 where lower values
indicate higher losses from
extreme weather events
ND-GAIN sub-index
under vulnerability
ND-GAIN
Germanwatch
100 in order to assist with the interpretation of the regression results. As Saunders
(2019) found a concave relationship between vulnerability and the share of adaptation
aid budget received, I also include vulnerability in the squared form to see if the
relationship is nonlinear.
Since the ND-GAIN focuses on long-term vulnerability, a complementing
measure, the Global Climate Risk Index, will be used to represent short-term losses
from climate variability (Germanwatch 2020). Although it is hard to attribute single
Population pop Logged World Bank
GNI per capita PPP GNIcap In current USD, logged and
lagged
Total ODA
Disbursements
ODA
In constant 2017 USD, lagged
and logged
World Bank
OECD-DAC
weather events to climate change, it increases the likelihood of extreme weather events
(Germanwatch 2019). Moreover, decision-makers may take recent weather events
calling for adaptation into account when allocating adaptation aid, and the CRI is a
well-known index to policymakers (Betzold and Weiler 2018). The data reflects the
direct socioeconomic costs of extreme weather events including the economic losses
Table 1.
Independent Variables: Recipient Need and Implementation Capacity
Two complementing indices are used to measure recipient need. As discussed
previously, vulnerability is hard to measure and including all the relevant components
may lead to issues of multicollinearity (Betzold and Weiler 2018). The ND-GAIN index
attempts to quantify the vulnerability to climate change each country experiences over
time (ND-GAIN 2015). The Vulnerability sub-index will be used to capture a coherent
view of vulnerability, including all the components identified by the UNFCCC:
exposure, sensitivity, and adaptive capacity (ND-GAIN; n.d.). To the best of my
knowledge, this measurement is the only one including all these components, while
recognising the multidimensional and dynamic nature of vulnerability. Moreover, it
has been widely used in measuring vulnerability to climate change (Saunders; 2019;
Weiler et al. 2018).
in USD PPP and per unit of GDP as well as the number of deaths per 100,000 people.
I will include the long-term index utilising data from the past 20 years for each
year in my analysis where lower values will indicate a higher degree of vulnerability.
Hence consecutive years will have 19 years of overlapping data and therefore there is
not a great deal of variability within individual countries. The data is from the Munich
Re, one of the most robust and reliable sets of data on this matter (Germanwatch
2019). Correlation between the CRI and the other variables measuring recipient need
is low (see Appendix 1), hence it is included in all models measuring the effect of
vulnerability.
Additionally, GNI per capita is included as a rough proxy for the financial
adaptive capacity the country has, and to complement the measures on vulnerability
and readiness. GNI is chosen over GDP as it reflects the resources available
domestically better since it includes net income from overseas investments and
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