This Section summarises the main findings of the study. Section 6.1 discusses findings based on DEA and Section 6.2 discusses findings based on dominance analysis. Section 6.3 summarises the findings on the inequity of the global distribution of adaptation performance and reinforces the assertions of Stern and the IPCC concerning the double inequity of global adaptation to climate change.
6.1 DEA results
DEA is used to aggregate the nine adaptive capacity indicators into an adaptive capacity index ACI for each nation and to aggregate the seven adaptation readiness indicators into an adaptation readiness index ARI for each nation. This procedure identifies leading and lagging nations in adaptive capacity and adaptation readiness, respectively. The two indices are then combined to generate a composite adaptation index CAI for each nation in two ways, by calculating the geometric mean of ACI and ARI, and by applying DEA to aggregate ACI and ARI. Both procedures identify leaders and laggards in composite adaptation performance, or the ability to enhance adaptive capacity with a supportive institutional environment. The first has the virtue of simplicity, but implicitly treats the two components as being equally important. The second yields information on nations’ comparative advantage in adaptation and readiness. The rank correlation between the two composite adaptation indices is calculated to test the concordance of the two strategies.
Results of using DEA to construct ACI and ARI are not reported because of the emphasis the IPCC places on complementarity between capability and readiness. The majority of the most capable and most ready nations are European nations and their Western Offshoots, while most of the least capable and least ready nations are LDCs. For these nations the advantage of having the freedom to choose weights is offset by the disadvantage of having relatively small values of adaptive capacity and adaptation readiness indicators to which weights are attached. The mean adaptive capacity of laggard nations is barely 65% that of leader nations, and their mean adaptation readiness is even lower, at 47% that of leader nations.
Table 1 combines adaptive capacity and adaptation readiness by reporting 21 leading nations and 20 lagging nations in composite adaptation, using the geometric mean of adaptive capacity and adaptation readiness indices to generate CAI. The curse of dimensionality appears for the most capable nations, 19 of which are European nations or their Western Offshoots. Most of the least capable nations are LDCs, primarily sub-Saharan African, South Asian, and SIDS. The laggards’ mean CAI value is barely half, 57%, the mean CAI value of the leaders. The picture that emerges is one of European nations and their Western Offshoots being institutionally prepared to exploit their relatively abundant adaptive capacities, and LDCs lacking the economic, governance and social readiness to exploit their limited adaptive capacities. All 134 nations are mapped according to their composite adaptive capacity index CAI in Figure 2. The leaders are located at higher latitudes in the northern and southern hemispheres, and the laggards are located at lower latitudes closer to the equator. White areas indicate nations not among the 134 nations in the data set due to insufficient data.
Results of using DEA to construct a CAI and to identify leaders and laggards are not reported because they are very similar to those using the geometric mean to construct a CAI, with a rank correlation between the two composite adaptation indices of 0.843. A virtue of using DEA to construct a CAI is that, unlike the geometric mean, which weights the two component indices equally, DEA assigns endogenous weights to nations that vary with their circumstances and their relative endowments of adaptive capacity and adaptation readiness in constructing their CAI. A huge majority, 128 of 134 nations, assign zero weights to adaptation readiness, suggesting that most nations, rich and poor, lack the institutional framework that constitutes adaptation readiness, to complement their adaptive capacities. Adom and Amoani (2021) and Arezki (2021) have emphasised the lack of adaptation readiness in Africa, whose nations dominate the CAI laggards, citing limited climate finance absorptive capacity stemming from relatively weak state capacity, inadequate economic governance, weak financial systems, and inefficient transport systems.
6.2 Dominance analysis results
Findings from the application of dominance analysis are collected in Table 2 for adaptive capacity and in Table 3 for adaptation readiness. The dominance relationship is demanding, requiring a nation to dominate, or be dominated, by another nation for every indicator, nine for adaptive capacity and seven for adaptation readiness. Nonetheless, empirical dominance relationships are numerous, particularly for adaptation readiness. As with the results in Table 1, the majority of the most dominating nations in Tables 2 and 3 are European nations and their Western Offshoots, and the majority of the most frequently dominated nations are LDCs.
Twelve of the most dominating nations in adaptive capacity and 17 of the most dominating nations in adaptation readiness appear among the leaders in composite adaptation, and 11 of the least dominating nations in adaptive capacity and 15 of the least dominating nations in adaptation readiness appear among the laggards in composite adaptation. These findings suggest a concordance between capacity and dominance, particularly among leaders, and also demonstrate that frequently dominating nations are not necessarily composite adaptation leaders (e.g., Portugal), and frequently dominated nations are not necessarily composite adaptation laggards (e.g., Angola).
It is worth noting that New Zealand is a high performer, ranking among the leaders in composite adaptation and the leading nation in both types of dominance. This strong showing is consistent with the findings of King and Jones (2021), who augmented the ND-GAIN data with three additional indicators: arable land availability, renewable energy availability, and isolation. They found New Zealand to have the most favourable “starting conditions” to form a “node of increasing complexity”, followed by Iceland, the United Kingdom, Australia, and Ireland. It should be noted that their third additional indicator, isolation, favours island nations.
6.3 Inequity results
Table 4 highlights one dimension of the inequity of global composite adaptation, by listing the GDP per capita of the most and least capable nations ranked by CAI. The most capable nations have mean CAI 75% greater than that of the least capable nations and have mean GDP per capita nearly 15 times that of the least capable nations. This finding is consistent with assertions in IPCC Assessment Reports that adaptive capacity is a function of several factors, the first being wealth, and developing nations cannot afford to invest in composite adaptation. It strongly supports calls for an increase in climate finance and a greatly expanded transfer of this increase from developed nations and international development banks to developing nations, and for a reallocation of the increased funding from mitigation to adaptation.
Table 5 reinforces the inequity of global composite adaptation by shifting attention from an income dimension to a responsibility dimension. The most and least capable nations by CAI are compared according to their greenhouse gas emissions per capita. The most capable nations are also the main source of global greenhouse gas emissions, emitting nearly 3.5 times as much per capita as the least capable nations. Developing nations are not the source of climate change impacts that threaten them. Taken together, Tables 4 and 5 provide a strong confirmation of Stern’s (2006) double inequity.
Table 6 combines income and responsibility to provide a holistic confirmation of Stern’s double inequity of adaptation performance. The most and least capable nations by CAI are compared according to their generic inequity index GII, constructed as the geometric mean of their income and responsibility indices GDP per capita and GHG per capita. Laggards have mean CAI 57% of that of leaders, and a mean GII 14% of that of leaders. Those nations most capable of adapting to climate change are both wealthy and the source of most causal greenhouse gas emissions, and those nations least capable of adapting are neither wealthy nor the source of emissions. If laggards and leaders are defined more generously as the bottom and top 50 nations based on CAI, the magnitude of the double inequity is barely dented. The mean CAI of redefined laggards rises to 69% of that of redefined leaders, and their mean GII rises to 26% of that of redefined leaders.
The double inequity illustrated in Table 6 is confined to leaders and laggards, but the double inequity affects all nations, with a strong positive correlation between nations’ CAI and their GII of 0.684. To illustrate the entire distribution rather than just its upper and lower tails, GII indices for 131 nations are mapped in Figure 3.With few exceptions, the wealthy source nations are European nations and their Western Offshoots, and the poor recipient nations are in Africa, the Sub-Continent, and South Asia. A comparison of Figure 3, which maps GII, with Figure 2, which maps CAI, provides a vivid depiction of Stern’s double inequity. With a few notable exceptions, the two maps are nearly indistinguishable.
Tables 5 and 6, and Figures 2 and 3, have a geographical interpretation as well as an inequity interpretation. Composite adaptation leaders are relatively rich and largely responsible for climate change impacts, and are located at higher latitudes in the northern and southern hemispheres (e.g., Canada in the north and New Zealand in the south). Composite adaptation laggards are relatively poor and not responsible, and cluster at lower latitudes close to the equator (e.g., Togo and Papua New Guinea). This geographical interpretation was proposed by Nordhaus (1994), who compared GDP per capita with latitude and temperature for a sample of 77 nations. He found rich nations located in cool latitudes away from the equator and poor nations located in warm latitudes near the equator.
 Maddison (2006) introduced the term “Western Offshoots” to categorise the US, Canada, Australia, and New Zealand.
 GDP per capita data are 2019 GDP per capita PPP (current international $) from the World Bank (https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD).
 Greenhouse gas emissions per capita data are for 2016 sourced from Our World in Data (https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions).
 Three nations are deleted in constructing the generic inequity index GII. GDP per capita data are unavailable for Syria, and Bhutan and Gabon report negative greenhouse gas emissions. For explanations for Bhutan’s negative emissions see https://ourworldindata.org/co2/country/bhutan and for Gabon’s see https://ourworldindata.org/co2/country/gabon.
 Nordhaus was co-recipient of the 2018 Nobel Prize in Economic Sciences “for integrating climate change into long-run macroeconomic analysis”. In Nordhaus (1977), he originally proposed a global warming target of 2 C above pre-industrial levels now enshrined in the Paris Agreement.