## 1. Sea-Level Rise: Drivers and Projections

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---

### Introduction
- Sea-level rise (SLR) presents long-term risks in Aruba that can lead to sizable permanent costs with potentially large macroeconomic and fiscal consequences.
- Aruba cannot control global sea-level, but it can manage how it affects the country by adapting.
- IMF Staff estimates using the CIAM model find that planned coastline protection—in the form of dykes, revetment, floodgates, coastal dunes, etc.—can reduce losses by approximately 40 percent by avoiding permanent inundation of land and relocation of population.
- Estimates of protection costs in Aruba are around 0.4 percent of annual GDP with a moderate emission scenario and do not grow. This will likely require an increase in public spending as coastal protections are public infrastructure.
- Aruba’s economy and population are concentrated along an environmentally fragile coastline; strategic long-term planning and targeted investments can significantly reduce vulnerabilities and macroeconomic risks.

### Climate trends and projections
- Current climate characteristics:
  - Average annual mean temperature: 29.4 °C.
  - Average total annual precipitation: 426 mm.
- Historical changes:
  - The average mean annual temperature has increased by 1.6 °C with respect to pre-industrial levels.
  - Historical data show no changes in either the average total annual rainfall or its seasonality, despite considerable interannual variability.
  - High-resolution and high-frequency data do not reveal significant historical trends in drought and extreme precipitation events for Aruba, though nearby regions north of the 13th parallel show different trends that may shift southward.
- Model projections:
  - Median projections indicate temperature increases of additional 0.6 to 0.9 °C in 2050 and between 0.8 and 1.9 °C in 2085, relative to present levels, depending on the emission scenario.
  - Accounting for the present 1.6 °C warming above pre-industrial levels implies warming will exceed 2 °C and potentially approach 4 °C by the end of the century.
  - Precipitation is projected to decline by between 6 and 12 percent in 2050 and by between 9 and 29 percent by the end of the century.
  - Models indicate potential additional risks from longer dry periods and episodes with extreme heat, especially under high emissions scenarios, with large uncertainty.
- Sea-level projections and drivers:
  - With a moderate emission scenario, sea level is projected to increase by 0.71 m relative to its level in 2000.
  - Strong global emission cuts aligned with the Paris Agreement could limit SLR to 0.60 m by 2100.
  - Faster SLR from higher emissions and/or accelerated melting of Greenland and Antarctic Ice Sheets could lead to a rise of 1 m or more by the end of the century.
  - Due to inertia in land ice melting, sea-levels will continue to rise for thousands of years even if global mean temperature stabilizes during this century.
  - Local SLR can differ from global mean SLR due to factors including local vertical land movement; probabilistic local SLR projections (accounting for regional SLR, local vertical land movements, and uncertainty) are used for the Annex analysis.
  - Comparisons to more recent projections: Fox-Kemper et al. (2021) project 0.65 m (SSP2-4.5) and 0.86 m (SSP5-8.5) by 2100 for Aruba; the projections used here are broadly in line but differ by a few centimeters at percentiles.

### Sea-level rise impacts and adaptation
- Macro-critical exposure and concentration of assets:
  - Approximately 46 percent of all households live in coastal areas.
  - Coastal population density is well over 1,000 residents per km2.
  - Coastal areas host at least 10,000 tourists per km2.
  - The only airport, all major industrial facilities, the major hospital, and the only desalination plant are located on the coastline, marginally above sea-level.
- Risk amplification:
  - SLR introduces slow-moving risks and magnifies acute risks from floods and storm surges by impacting areas that house most economic activity and strategic assets.
  - Aruba lacks redundant capacity to quickly replace strategic assets, so SLR can cause acute macroeconomic risks by exacerbating extreme rainfall and storm surge impacts.
  - Potential fiscal and macroeconomic effects include lower fiscal revenues from production losses, higher expenditure to replace damaged public assets, and lower capital inflows from reduced tourism, creating risks for the balance of payments and long-term debt sustainability.
- Adaptation effectiveness and costs:
  - Planned coastline protection (dykes, revetment, floodgates, coastal dunes, etc.) can reduce losses by approximately 40 percent by avoiding permanent inundation of land and relocation of population.
  - Estimated protection costs in Aruba are around 0.4 percent of annual GDP under a moderate emission scenario and do not grow in the analysis—implying a likely need for increased public spending as these protections are public infrastructure.
- Policy emphasis:
  - Reducing global greenhouse gas emissions is crucial to limit the rate of SLR, but Aruba’s primary management tool for SLR this century is adaptation.
  - Strategic long-term planning and targeted investments are necessary to update historical adaptations and to mitigate future damages and macroeconomic risks.

### CIAM model exercise and scenarios
- Model and inputs:
  - IMF staff uses the Coastal Impact and Adaptation Model (CIAM) to estimate costs of sea-level rise (SLR) and adaptation (Diaz, 2016).
  - CIAM divides global coastline into more than 12,000 segments; Aruba’s coastline (~70 Km) is treated as a single coastal segment.
  - Model inputs include projections of local sea-level rise from Kopp et al. (2014), data on capital, population, and wetland coverage by elevation, and storm surge events modeled at 1/10, 1/100, 1/1,000 and 1/10,000 year events.
  - Monetization includes Value of Statistical Life for loss of life and willingness to pay for biodiversity for wetland loss.
  - Protection options include hard barriers and soft solutions; CIAM does not consider nature-based protection without more granular data.
- Scenarios modeled:
  - No-adaptation (reactive relocation upon inundation).
  - Protection (investment in seawalls and barriers to avoid inundation).
  - Planned retreat (proactive, gradual relocation and allowing capital to depreciate).
  - Variants of retreat and protection to handle storm surge floods.

### Estimated costs and adaptation options (average annual, 2020–2099)
- No adaptation:
  - Central case annual average cost: 0.8 percent of GDP.
  - Full range across probabilistic SLR scenarios: between 0.4 to 1.4 percent of GDP annually.
  - Major cost components: permanent inundation and abrupt relocation costs; welfare losses metric.
  - Comparison: Centrale Bank van Aruba (2020, p. 39) estimates damages from major floods amount to between 1.5 and 2.1 percent of GDP per event; central SLR estimate implies damages equal to a major flood event every other year.
- Protection:
  - Coastal protection reduces average annual costs from 0.8 to 0.5 percent of GDP.
  - Estimated annual investment needed for coastal protection: approximately 0.4 percent of GDP annually throughout the century.
  - Economic value of wetland areas lost due to protection: equal to 0.1 percent of GDP annually.
  - Combined cost (protection investment plus wetland-loss externality): 0.5 percent of GDP annually.
  - Adaptation via protection reduces costs by approximately 40 percent compared to inaction.
  - Note: Coastal protection may exacerbate pluvial flooding by slowing drainage, possibly increasing investment needs beyond these estimates.
- Planned retreat:
  - CIAM estimates average annual cost: 0.2 percent of GDP between 2020 and 2099.
  - This is less than half the cost of protection and 80 percent less than the cost of inaction.
  - Long-term cost equals opportunity cost of land to which population and assets move, plus disutility from relocation and residual storm surge impacts.
  - Implementation relies on gradual relocation, rebuilding inland, and long-term coordination; in undeveloped coastal areas, preventing construction of long-lived capital may be least-cost.
- General model insight:
  - Coastal protection is usually least-cost in areas with large existing capital and high population density.
  - Planned retreat is usually least-cost in areas with low capital and population density.
  - Optimal mix varies by coastal segment and depends on projected incremental costs, opportunity costs of land, capital and population at risk, and SLR scenarios.

### Fiscal and distributional implications
- Government financing bounds (if government assumes full responsibility):
  - Upper bound for government financing needs ranges from 0.2 percent of GDP annually (planned retreat) to 0.8 percent of GDP annually (inaction).
  - If government is fully responsible for protection costs, public spending must increase by 0.4 percent of GDP annually, on average, between 2020 and 2099.
- In cases of inaction and planned retreat, there are no direct adaptation costs for the government under the scenario assumptions.
- If revenue and non-climate expenditure as a share of GDP remain constant, additional adaptation spending leads to deficits and increasing debt.
- Distributional effects:
  - Inaction or planned retreat shifts substantial costs to owners of coastal properties via accelerated capital depreciation, business disruption, disutility, and land depreciation.
  - Private adaptation may be inefficient due to coordination failures and negative externalities (e.g., increased erosion in neighboring areas).
  - Strong case for effective public coordination in managing coastal defenses.

### Data needs, limitations, and methodological considerations
- CIAM limitations for Aruba:
  - Treats Aruba as a single coastal segment; uses average coastal slope and does not capture local coastal characteristics determining inundation, retreat, or protection optimality.
  - Does not capture interaction of SLR with ongoing coastal erosion processes in Aruba.
  - Does not consider increased risks from river floods or some nature-based solutions without hyper-resolution data.
- Required improvements:
  - Develop hyper-resolution maps of elevation, currents, tides, infrastructure, and population to enable more accurate assessments.
  - More granular coastal modeling and asset mapping to determine where protection versus retreat is optimal.
- Cost-benefit analysis (CBA) framework:
  - CBA is empirically and methodologically challenging but useful for identifying trade-offs and attractive policy options.
  - Best practices can be drawn from the Netherlands’ long-standing CBA tradition in flood risk management.

### Lessons and policy roadmap for efficient adaptation spending
- Key messages:
  - Long-term planning of adaptation can be highly effective at containing physical impacts and costs of SLR.
  - Adaptation should be integrated into sustainable development planning and macro-fiscal frameworks.
  - The optimal adaptation strategy will consist of protection in some areas and retreat in others.
  - Strong governance and coordination are required to implement complex, multidecadal adaptation transformations.
- Practical guidance:
  - Use CIAM insights as a baseline roadmap and supplement with hyper-resolution data and local engineering studies.
  - Leverage the strong ties between Aruba and the Kingdom of the Netherlands to access engineering solutions and cost-effective adaptation strategies.
  - Integrate adaptation planning into the National Climate Resilience Council (NCRC) efforts for a comprehensive National Action Plan.
  - Account for broader adaptation needs beyond SLR: increased energy for cooling, stormwater drainage improvements, and potential desalination capacity increases.

### Prioritization and resource allocation
- Government must carefully allocate resources across all possible uses, including adaptation to climate change, while considering the distributional effects of its programs.
- This requires:
  - concentrating government efforts and resources in key areas; and
  - collecting information on how effective spending is across alternative programs and how spending affects distinct groups in society (Bellon and Massetti, 2022a).

### When government intervention is warranted
- Individuals and firms often have strong incentives to adapt because many adaptation benefits tend to be local and private.
- Government intervention is warranted when adaptation has large externalities, for example:
  - coastal protection; and
  - strengthening public infrastructure.

### Role of cost-benefit analysis (CBA)
- Despite limitations, cost-benefit analysis (CBA) can help decision makers consistently collect, aggregate, and compare information on public adaptation projects.
- Adaptation investment and policy typically have trade-offs that are better assessed by comparing social costs and benefits using a systematic approach.
- Ethical choices about what to do, when, how, and at what cost should reflect societal preferences.
- CBA, complemented by analysis and correction of distributional impacts, can help decision makers maximize overall social welfare by avoiding wasting scarce resources.
- It is essential that CBA is applied to adaptation as well as to all other development programs in a consistent manner (Bellon and Massetti, 2022a).

### Annex: simulated changes and sea-level rise projections
- Annex I includes maps of simulated changes for indicators of droughts and intense precipitations (Consecutive Dry Days; Intense Rainfall (RX1Day)) and for Total Annual Precipitation.
  - Source for maps: FADCP Climate Dataset (Massetti and Tagklis, 2024), using CMIP6 data (Copernicus Climate Change Service, Climate Data Store, 2021: CMIP6 climate projections).
  - Notes: Crosses indicate areas in which models disagree on both the magnitude and sign of precipitation changes. Dots indicate areas in which most models agree on the direction of change, but it cannot be excluded with high confidence that no change or change of a different sign is possible.
- Annex I. Table A1. Aruba: Sea-Level Rise Projections Relative to 2000 level (meters)
  - Global Mean
    - Paris (RCP2.6): 2030 = 0.14 [0.10 , 0.18]; 2050 = 0.25 [0.18 , 0.33]; 2070 = 0.35 [0.23 , 0.51]; 2100 = 0.50 [0.30 , 0.82]
    - Moderate (RCP4.5): 2030 = 0.14 [0.10 , 0.18]; 2050 = 0.26 [0.18 , 0.35]; 2070 = 0.39 [0.26 , 0.56]; 2100 = 0.60 [0.35 , 0.94]
    - Extreme (RCP8.5): 2030 = 0.14 [0.11 , 0.18]; 2050 = 0.29 [0.21 , 0.38]; 2070 = 0.47 [0.33 , 0.66]; 2100 = 0.77 [0.51 , 1.19]
  - Aruba (Local)
    - Baseline: 2030 = 0.02 [-0.03 , 0.07]; 2050 = 0.04 [-0.04 , 0.12]; 2070 = 0.05 [-0.06 , 0.17]; 2100 = 0.08 [-0.09 , 0.24]
    - Paris (RCP2.6): 2030 = 0.18 [0.10 , 0.26]; 2050 = 0.31 [0.19 , 0.45]; 2070 = 0.44 [0.24 , 0.67]; 2100 = 0.60 [0.31 , 1.01]
    - Moderate (RCP4.5): 2030 = 0.18 [0.10 , 0.25]; 2050 = 0.32 [0.19 , 0.46]; 2070 = 0.47 [0.27 , 0.71]; 2100 = 0.71 [0.35 , 1.15]
    - Extreme (RCP8.5): 2030 = 0.18 [0.11 , 0.26]; 2050 = 0.35 [0.21 , 0.50]; 2070 = 0.56 [0.34 , 0.83]; 2100 = 0.90 [0.53 , 1.40]
  - Notes: Global and Local Sea-Level Rise (SLR) probabilistic projections until 2100 under three emission scenarios (Paris - RCP 2.6; Moderate - RCP 4.5; Extreme - RCP 8.5). The range in brackets represents the 5th and 95th percentiles of the distribution of SLR for each emission scenario. Local SLR projections include information on local climate change induced SLR rates and a baseline projections of local vertical land movement (subsidence or uplifting) not caused by climate change.

*Source: sipea2025157*

### 1. Sea-Level Rise: Drivers and Projections .............................................................................

### 1. Sea-Level Rise: Drivers and Projections

### Introduction
- Sea-level rise (SLR) presents long-term risks in Aruba that can lead to sizable permanent costs with potentially large macroeconomic and fiscal consequences.
- Aruba cannot control global sea-level, but it can manage how it affects the country by adapting.
- IMF Staff estimates using the CIAM model find that planned coastline protection—in the form of dykes, revetment, floodgates, coastal dunes, etc.—can reduce losses by approximately 40 percent by avoiding permanent inundation of land and relocation of population.
- Estimates of protection costs in Aruba are around 0.4 percent of annual GDP with a moderate emission scenario and do not grow. This will likely require an increase in public spending as coastal protections are public infrastructure.
- Aruba’s economy and population are concentrated along an environmentally fragile coastline; strategic long-term planning and targeted investments can significantly reduce vulnerabilities and macroeconomic risks.

### Climate Trends and Projections
- Current climate characteristics:
  - Average annual mean temperature: 29.4 °C.
  - Average total annual precipitation: 426 mm.
- Historical changes:
  - The average mean annual temperature has increased by 1.6 °C with respect to pre-industrial levels.
  - Historical data show no changes in either the average total annual rainfall or its seasonality, despite considerable interannual variability.
  - High-resolution and high-frequency data do not reveal significant historical trends in drought and extreme precipitation events for Aruba, though nearby regions north of the 13th parallel show different trends that may shift southward.
- Model projections:
  - Median projections indicate temperature increases of additional 0.6 to 0.9 °C in 2050 and between 0.8 and 1.9 °C in 2085, relative to present levels, depending on the emission scenario.
  - Accounting for the present 1.6 °C warming above pre-industrial levels implies warming will exceed 2 °C and potentially approach 4 °C by the end of the century.
  - Precipitation is projected to decline by between 6 and 12 percent in 2050 and by between 9 and 29 percent by the end of the century.
  - Models indicate potential additional risks from longer dry periods and episodes with extreme heat, especially under high emissions scenarios, with large uncertainty.
- Sea-level projections and drivers:
  - With a moderate emission scenario, sea level is projected to increase by 0.71 m relative to its level in 2000.
  - Strong global emission cuts aligned with the Paris Agreement could limit SLR to 0.60 m by 2100.
  - Faster SLR from higher emissions and/or accelerated melting of Greenland and Antarctic Ice Sheets could lead to a rise of 1 m or more by the end of the century.
  - Due to inertia in land ice melting, sea-levels will continue to rise for thousands of years even if global mean temperature stabilizes during this century.
  - Local SLR can differ from global mean SLR due to factors including local vertical land movement; probabilistic local SLR projections (accounting for regional SLR, local vertical land movements, and uncertainty) are used for the Annex analysis.
  - Comparisons to more recent projections: Fox-Kemper et al. (2021) project 0.65 m (SSP2-4.5) and 0.86 m (SSP5-8.5) by 2100 for Aruba; the projections used here are broadly in line but differ by a few centimeters at percentiles.

### Sea-Level Rise Impacts and Adaptation
- Macro-critical exposure and concentration of assets:
  - Approximately 46 percent of all households live in coastal areas.
  - Coastal population density is well over 1,000 residents per km2.
  - Coastal areas host at least 10,000 tourists per km2.
  - The only airport, all major industrial facilities, the major hospital, and the only desalination plant are located on the coastline, marginally above sea-level.
- Risk amplification:
  - SLR introduces slow-moving risks and magnifies acute risks from floods and storm surges by impacting areas that house most economic activity and strategic assets.
  - Aruba lacks redundant capacity to quickly replace strategic assets, so SLR can cause acute macroeconomic risks by exacerbating extreme rainfall and storm surge impacts.
  - Potential fiscal and macroeconomic effects include lower fiscal revenues from production losses, higher expenditure to replace damaged public assets, and lower capital inflows from reduced tourism, creating risks for the balance of payments and long-term debt sustainability.
- Adaptation effectiveness and costs:
  - Planned coastline protection (dykes, revetment, floodgates, coastal dunes, etc.) can reduce losses by approximately 40 percent by avoiding permanent inundation of land and relocation of population.
  - Estimated protection costs in Aruba are around 0.4 percent of annual GDP under a moderate emission scenario and do not grow in the analysis—implying a likely need for increased public spending as these protections are public infrastructure.
- Policy emphasis:
  - Reducing global greenhouse gas emissions is crucial to limit the rate of SLR, but Aruba’s primary management tool for SLR this century is adaptation.
  - Strategic long-term planning and targeted investments are necessary to update historical adaptations and to mitigate future damages and macroeconomic risks.

*Prepared by Emanuele Massetti (FAD).*

### 10. This calls for a long-term adaptation plan for SLR that is both effective in reducing risks and

### sipea2025157 - 10. This calls for a long-term adaptation plan for SLR that is both effective in reducing risks and

### CIAM model exercise and scenarios
- IMF staff uses the Coastal Impact and Adaptation Model (CIAM) to estimate costs of sea-level rise (SLR) and adaptation (Diaz, 2016).
- CIAM divides global coastline into more than 12,000 segments; Aruba’s coastline (~70 Km) is treated as a single coastal segment.
- Model inputs and features:
  - Projections of local sea-level rise from Kopp et al. (2014).
  - Data on capital, population, and wetland coverage by elevation.
  - Storm surge events modeled (1/10, 1/100, 1/1,000 and 1/10,000 year events).
  - Monetization of loss of life using the Value of Statistical Life and wetland loss using willingness to pay for biodiversity.
  - Protection options include hard barriers and soft solutions; CIAM does not consider nature-based protection without more granular data.
- Scenarios modeled:
  - No-adaptation (reactive relocation upon inundation).
  - Protection (investment in seawalls and barriers to avoid inundation).
  - Planned retreat (proactive, gradual relocation and allowing capital to depreciate).
  - Variants of retreat and protection to handle storm surge floods.

### Estimated costs and adaptation options (average annual, 2020–2099)
- No adaptation:
  - Central case annual average cost: 0.8 percent of GDP.
  - Full range across probabilistic SLR scenarios: between 0.4 to 1.4 percent of GDP annually.
  - Major cost components: permanent inundation and abrupt relocation costs; welfare losses metric.
  - Comparison: Centrale Bank van Aruba (2020, p. 39) estimates damages from major floods amount to between 1.5 and 2.1 percent of GDP per event; central SLR estimate implies damages equal to a major flood event every other year.
- Protection:
  - Coastal protection reduces average annual costs from 0.8 to 0.5 percent of GDP.
  - Estimated annual investment needed for coastal protection: approximately 0.4 percent of GDP annually throughout the century.
  - Economic value of wetland areas lost due to protection: equal to 0.1 percent of GDP annually.
  - Combined cost (protection investment plus wetland-loss externality): 0.5 percent of GDP annually.
  - Adaptation via protection reduces costs by approximately 40 percent compared to inaction.
  - Note: Coastal protection may exacerbate pluvial flooding by slowing drainage, possibly increasing investment needs beyond these estimates.
- Planned retreat:
  - CIAM estimates average annual cost: 0.2 percent of GDP between 2020 and 2099.
  - This is less than half the cost of protection and 80 percent less than the cost of inaction.
  - Long-term cost equals opportunity cost of land to which population and assets move, plus disutility from relocation and residual storm surge impacts.
  - Implementation relies on gradual relocation, rebuilding inland, and long-term coordination; in undeveloped coastal areas, preventing construction of long-lived capital may be least-cost.
- General model insight:
  - Coastal protection is usually least-cost in areas with large existing capital and high population density.
  - Planned retreat is usually least-cost in areas with low capital and population density.
  - Optimal mix varies by coastal segment and depends on projected incremental costs, opportunity costs of land, capital and population at risk, and SLR scenarios.

### Fiscal and distributional implications
- Government financing bounds (if government assumes full responsibility):
  - Upper bound for government financing needs ranges from 0.2 percent of GDP annually (planned retreat) to 0.8 percent of GDP annually (inaction).
  - If government is fully responsible for protection costs, public spending must increase by 0.4 percent of GDP annually, on average, between 2020 and 2099.
- In cases of inaction and planned retreat, there are no direct adaptation costs for the government under the scenario assumptions.
- If revenue and non-climate expenditure as a share of GDP remain constant, additional adaptation spending leads to deficits and increasing debt.
- Distributional effects:
  - Inaction or planned retreat shifts substantial costs to owners of coastal properties via accelerated capital depreciation, business disruption, disutility, and land depreciation.
  - Private adaptation may be inefficient due to coordination failures and negative externalities (e.g., increased erosion in neighboring areas).
  - Strong case for effective public coordination in managing coastal defenses.

### Data needs, limitations, and methodological considerations
- CIAM limitations for Aruba:
  - Treats Aruba as a single coastal segment; uses average coastal slope and does not capture local coastal characteristics determining inundation, retreat, or protection optimality.
  - Does not capture interaction of SLR with ongoing coastal erosion processes in Aruba.
  - Does not consider increased risks from river floods or some nature-based solutions without hyper-resolution data.
- Required improvements:
  - Develop hyper-resolution maps of elevation, currents, tides, infrastructure, and population to enable more accurate assessments.
  - More granular coastal modeling and asset mapping to determine where protection versus retreat is optimal.
- Cost-benefit analysis (CBA) framework:
  - CBA is empirically and methodologically challenging but useful for identifying trade-offs and attractive policy options.
  - Best practices can be drawn from the Netherlands’ long-standing CBA tradition in flood risk management.

### Lessons and policy roadmap for efficient adaptation spending
- Key messages:
  - Long-term planning of adaptation can be highly effective at containing physical impacts and costs of SLR.
  - Adaptation should be integrated into sustainable development planning and macro-fiscal frameworks.
  - The optimal adaptation strategy will consist of protection in some areas and retreat in others.
  - Strong governance and coordination are required to implement complex, multidecadal adaptation transformations.
- Practical guidance:
  - Use CIAM insights as a baseline roadmap and supplement with hyper-resolution data and local engineering studies.
  - Leverage the strong ties between Aruba and the Kingdom of the Netherlands to access engineering solutions and cost-effective adaptation strategies.
  - Integrate adaptation planning into the National Climate Resilience Council (NCRC) efforts for a comprehensive National Action Plan.
  - Account for broader adaptation needs beyond SLR: increased energy for cooling, stormwater drainage improvements, and potential desalination capacity increases.

*Source: IMF staff calculations using the CIAM model (Diaz, 2016); analysis in sipea2025157.*

### 20. With many competing needs, the government of Aruba must carefully allocate resources

### 20. With many competing needs, the government of Aruba must carefully allocate resources

### Prioritization and resource allocation
- Government must carefully allocate resources across all possible uses, including adaptation to climate change, while considering the distributional effects of its programs.
- This requires:
  - concentrating government efforts and resources in key areas; and
  - collecting information on how effective spending is across alternative programs and how spending affects distinct groups in society (Bellon and Massetti, 2022a).

### When government intervention is warranted
- Individuals and firms often have strong incentives to adapt because many adaptation benefits tend to be local and private.
- Government intervention is warranted when adaptation has large externalities, for example:
  - coastal protection; and
  - strengthening public infrastructure.

### Role of cost-benefit analysis (CBA)
- Despite limitations, cost-benefit analysis (CBA) can help decision makers consistently collect, aggregate, and compare information on public adaptation projects.
- Adaptation investment and policy typically have trade-offs that are better assessed by comparing social costs and benefits using a systematic approach.
- Ethical choices about what to do, when, how, and at what cost should reflect societal preferences.
- CBA, complemented by analysis and correction of distributional impacts, can help decision makers maximize overall social welfare by avoiding wasting scarce resources.
- It is essential that CBA is applied to adaptation as well as to all other development programs in a consistent manner (Bellon and Massetti, 2022a).

### Annex: simulated changes and sea-level rise projections
- Annex I includes maps of simulated changes for indicators of droughts and intense precipitations (Consecutive Dry Days; Intense Rainfall (RX1Day)) and for Total Annual Precipitation.
  - Source for maps: FADCP Climate Dataset (Massetti and Tagklis, 2024), using CMIP6 data (Copernicus Climate Change Service, Climate Data Store, 2021: CMIP6 climate projections).
  - Notes: Crosses indicate areas in which models disagree on both the magnitude and sign of precipitation changes. Dots indicate areas in which most models agree on the direction of change, but it cannot be excluded with high confidence that no change or change of a different sign is possible.

- Annex I. Table A1. Aruba: Sea-Level Rise Projections Relative to 2000 level (meters)
  - Global Mean
    - Paris (RCP2.6): 2030 = 0.14 [0.10 , 0.18]; 2050 = 0.25 [0.18 , 0.33]; 2070 = 0.35 [0.23 , 0.51]; 2100 = 0.50 [0.30 , 0.82]
    - Moderate (RCP4.5): 2030 = 0.14 [0.10 , 0.18]; 2050 = 0.26 [0.18 , 0.35]; 2070 = 0.39 [0.26 , 0.56]; 2100 = 0.60 [0.35 , 0.94]
    - Extreme (RCP8.5): 2030 = 0.14 [0.11 , 0.18]; 2050 = 0.29 [0.21 , 0.38]; 2070 = 0.47 [0.33 , 0.66]; 2100 = 0.77 [0.51 , 1.19]
  - Aruba (Local)
    - Baseline: 2030 = 0.02 [-0.03 , 0.07]; 2050 = 0.04 [-0.04 , 0.12]; 2070 = 0.05 [-0.06 , 0.17]; 2100 = 0.08 [-0.09 , 0.24]
    - Paris (RCP2.6): 2030 = 0.18 [0.10 , 0.26]; 2050 = 0.31 [0.19 , 0.45]; 2070 = 0.44 [0.24 , 0.67]; 2100 = 0.60 [0.31 , 1.01]
    - Moderate (RCP4.5): 2030 = 0.18 [0.10 , 0.25]; 2050 = 0.32 [0.19 , 0.46]; 2070 = 0.47 [0.27 , 0.71]; 2100 = 0.71 [0.35 , 1.15]
    - Extreme (RCP8.5): 2030 = 0.18 [0.11 , 0.26]; 2050 = 0.35 [0.21 , 0.50]; 2070 = 0.56 [0.34 , 0.83]; 2100 = 0.90 [0.53 , 1.40]
  - Source: Sea-level rise projections from Kopp et al. (2014) derived from the CIAM model database (Diaz, 2016).
  - Notes: Global and Local Sea-Level Rise (SLR) probabilistic projections until 2100 under three emission scenarios (Paris - RCP 2.6; Moderate - RCP 4.5; Extreme - RCP 8.5). The range in brackets represents the 5th and 95th percentiles of the distribution of SLR for each emission scenario. Local SLR projections include information on local climate change induced SLR rates and a baseline projections of local vertical land movement (subsidence or uplifting) not caused by climate change.

*Source: sipea2025157 - 20. With many competing needs, the government of Aruba must carefully allocate resources*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025157.pdf_