A global assessment of adaptation investment from the perspectives of equity and efficiency


Equity and efficiency should be considered when allocating resources for climate change adaptation. More than a decade after the Least Developed Countries Fund approved adaptation funds for 18 countries in 2003, it is possible to take the stock of investment data and to test empirically whether equity and efficiency have been factored into adaptation investment decision-making. To evaluate equity, one must determine if resources were distributed to areas of greatest need. Vulnerability assessments provide information on the global distribution of the need for adaptation. To evaluate efficiency, one must compare cost and benefit of an investment. Although it is difficult to assess ex-ante the cost and benefit of investment strategies, it is possible to measure efficient use of expenditures with readiness assessment, as a metric of capacity to deploy adaptation resources. We used vulnerability and readiness measures of the Notre Dame Global Adaptation Initiative (ND-GAIN) Country Index as proxies of equity and efficiency. This article quantitatively interrogates—through the lens of public fund allocation—the roles of vulnerability and readiness in shaping adaptation investment decisions. Our findings suggest that countries facing increasing impacts from climate change have received more adaptation investments from international sources than countries with less vulnerability. Further, international investments also preferentially flow to countries that are more ready to deploy adaptation resources. Since the most vulnerable countries are likely to be less ready for investment, our findings support the efforts to improve the investment potential of the most vulnerable countries by investing first to enhance their readiness, in order to unlock adaptation solutions.

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The ND-GAIN’s Country Index was built based on the groundbreaking work done at the Global Adaptation Institute in Washington DC. Special thanks are given to Bruno Sánchez-Andrade Nuño, who contributed his technical talents during the earlier years of the Index. Authors also want to give thanks to Notre Dame graduate students and supporting staffs who have been held accountable for the project in many fronts: Martin Murillo, Milan Budhathoki, Jishan Liao, Benjamin Mayala, and Alexandra Gumm. This work was done with tremendous supports from many foremost intellectual leaders in the field of climate change and adaptation. Authors are grateful to the following: Dennis Bours from the Global Environmental Facility, Cyril Caminade from the Liverpool University, Nitesh Chawla from the Department of Computer Science at Notre Dame, William Cheung from the University of British-Columbia, Michael Clark from the University of Michigan, Joyce Coffee from Climate Resilience Consulting, James Ford from McGill University, Francis Gassert from World Resource Institute, Patrick Gonzalez from the US National Park Service, Martina Grecequet from University of Minnesota, Alan Hamlet from the College of Engineering at Notre Dame, Alexandra Lesnikowski from McGill University, David Lodge from the Cornell University, Edwin Michael from the Department of Biological Science at Notre Dame, Patrick Murphy from Palo Alto Research Center, Mark Musumba from the Earth Institute, Felix Portmann from Goethe-Universität, Tien Shiao from H&M, Claudia Tebaldi from National Center of Atmospheric Research, and Abigail Wozniak from the Department of Economics at Notre Dame.

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Correspondence to Chen Chen.


Appendix 1. Literature review for vulnerability and readiness assessments

Table 4 Methodologies for quantifying the components of vulnerability
Table 5 Methodologies for quantifying the components of readiness

Appendix 2. Summarizing ND-GAIN country index metrics

Table 6 Rationale of the vulnerability indicators in ND-GAIN Country Index
Table 7 Rationale of readiness indicators in ND-GAIN Country Index

Appendix 3. Correlation of the proposed control variables

Table 8 Correlation matrix of the proposed control variables for the CFU model
Table 9 Correlation matrix of the proposed control variables for the AII model

Appendix 4. ND-GAIN’s Vulnerability-Readiness Matrix

Figure 2 visualizes vulnerability and readiness scores in the Vulnerability-Readiness Matrix (VRM) that illustrates a country’s position in a two-dimensional plane. The median vulnerability and readiness scores from 1995 to 2014 delineate four quadrants on the VRM. To explore the spread of countries across the parameter space of the index, we plot all countries on the VRM from the most recent data publication for the year 2014. The VRM shows that countries with higher readiness tend to have lower vulnerability and vice versa.

Fig. 2

Vulnerability-Readiness Matrix, based on 2014 data. Each dot represents one country. The median vulnerability and readiness scores from 1995 to 2014 delineate four quadrants on the matrix. Countries occupy one of the four quadrants of the matrix according to their vulnerability and readiness scores. The countries are grouped according to the geographic locations: (1) Sub-Saharan Africa; (2) South Asia; and (3) rest of the World (data source: Notre Dame Global Adaptation Initiative)

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Chen, C., Hellmann, J., Berrang-Ford, L. et al. A global assessment of adaptation investment from the perspectives of equity and efficiency. Mitig Adapt Strateg Glob Change 23, 101–122 (2018). https://doi.org/10.1007/s11027-016-9731-y

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  • Adaptation Investment
  • Assessment
  • Climate change
  • Readiness
  • vulnerability