The economic impacts of weather-related shocks in Nigeria A first step toward the quantification of fiscal risks 2025 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: +1-202-473-1000; Internet: www.worldbank.org Some rights reserved. This work is a product of the staff of The World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR). The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be construed or considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions. This work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Translations. If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. Adaptations. If you create an adaptation of this work, please add the following disclaimer along with the attribution: This is an adaptation of an original work by The World Bank. Views and opinions expressed in the adaptation are the sole responsibility of the author or authors of the adaptation and are not endorsed by The World Bank. Third-party content. The World Bank does not necessarily own each component of the content contained within the work. The World Bank therefore does not warrant that the use of any third-party-owned individual component or part contained in the work will not infringe on the rights of those third parties. The risk of claims resulting from such infringements rests solely with you. If you wish to reuse a component of the work, it is your responsibility to determine whether permission is needed for that reuse and to obtain permission from the copyright owner. Examples of components can include, but are not limited to, tables, figures, or images. All queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; e-mail: pubrights@worldbank.org About the cover: Birdseye view of Idanre, located in Ondo State, in the western part of Nigeria. During the wet season western Nigeria can receive up to 381 cm of rain. Photo: EyeEm Mobile GmbH | iStock.com. Design: ULTRAdesigns, Inc. The economic impacts of weather-related shocks in Nigeria A first step toward the quantification of fiscal risks ii | The economic impacts of weather-related shocks in Nigeria Table of Contents Executive Summary....................................................................................................................................................... vii Introduction. ........................................................................................................................................................................ 1 1 Overview of recent disaster and weather-related shocks in Nigeria.................................................3 1.1. Historical disaster trends highlight floods as one of the most significant disasters.....................................3 1.2. The devastating floods of 2012 led to unprecedented damages and losses.................................................. 6 1.3. The nationwide floods in 2022 affected a significant portion of the population. ........................................7 2 A first assessment of the economic impacts of weather-related shocks in Nigeria...................9 2.1. Potential damages associated with floods........................................................................................................... 10 2.1.1. National-level damages associated with floods..................................................................................... 10 2.1.2. State-level damages associated with floods........................................................................................... 11 2.2. Growth impact of weather-related events........................................................................................................... 13 2.2.1. Extreme precipitation anomalies have a negative effect on economic growth.............................. 13 2.2.2. Modeling the impact of floods on potential GDP growth................................................................... 16 2.3. Household-level impacts of weather-related shocks........................................................................................ 18 2.3.1. Welfare losses due to floods....................................................................................................................... 18 2.3.2. Floods can disproportionally impact conflict-affected areas.............................................................. 18 2.3.3. The impact of droughts on rural poverty................................................................................................. 19 3 Various risk drivers will shape the disaster and climate risk landscape in the future............ 21 3.1. Temperatures will continue increasing, augmenting water demands of ecosystems and hampering labor productivity............................................................................................................. 21 3.2. Extreme precipitation events are likely to become stronger and more frequent.......................... 21 3.3. Sea level rise will increase coastal flood risk in urban areas............................................................... 23 3.4. Demographic and urbanization trends will shape future disaster risk............................................. 24 4 Policy options to strengthen fiscal resilience against weather-related shocks......................... 27 References......................................................................................................................................................................... 31 iii | A first step toward the quantification of fiscal risks List of Annexes Annex A. Subnational distribution of flood impact and flood exposure.............................................................................. 33 Annex B. Historical flood exposure trends................................................................................................................................. 36 Annex C. Summary of the methodology to model the impact of floods on GDP growth................................................ 37 List of Figures Figure 1. Diagram of evolving disaster risk................................................................................................................................. 1 ....................................................3 Figure 2. Impacts of weather-related shocks and epidemics in Nigeria, 1980 – 2024. Figure 3. Population affected by floods (top) and count of floods by State (bottom), 1985 – 2024.............................4 Figure 4. Nigeria’s capacity to face weather-related events—selected World Risk Index components........................ 5 Figure 5. Breakdown of damages and losses by economic sector......................................................................................... 6 Figure 6. Breakdown of damages by economic sector.............................................................................................................7 ................... 9 Figure 7. A schematic view of the threats that weather-related shocks pose to Nigeria’s fiscal position. ............................................................................................................. 11 Figure 8. Loss exceedance curve for riverine floods. Figure 9. Damage that could be exceeded with an annual probability of 1% for countries in Sub-Saharan Africa.................................................................................................................................................. 11 Figure 10. Average annual damage from flood hazards in coastal cities............................................................................. 12 Figure 11. Evolution of annual precipitation anomalies in Nigeria, 1975 – 2022............................................................. 14 Figure 12. Effect of annual precipitation anomalies on per capita GDP growth............................................................... 14 Figure 13. Fitted curve for potential GDP loss.......................................................................................................................... 17 Figure 14. Potential GDP growth following a 1-in-100-year flood event scenario in 2025........................................... 17 ................................................. 19 Figure 15. The impact of droughts on rural poverty rates (left) and poverty gap (right). Figure 16. Historical annual average temperature (left) and projected changes by SSP scenario (right)..................... 22 Figure 17. Projected changes in the means of the distributions of total annual precipitation (left) and largest 1-day precipitation (right) under different SSP scenarios.............................................................. 22 Figure 18. Projected evolution of the annual probability of exceedance of maximum daily precipitation level .................................................................................... 23 at the end of the century under different SSP scenarios. Figure 19. Exposure to coastal flooding in Lagos in 2020 and 2080 under a high emissions scenario....................... 24 Figure 20. Evolution of urban and rural population................................................................................................................. 24 Figure 21. Urban population by settlement size....................................................................................................................... 25 Figure 22. Spatial distribution of damages and losses due to the 2012 floods (left) and damages ................................................................................................................................... 33 due to the 2022 floods (right). Figure 23. Per capita spatial distribution of damages and losses due to the 2012 floods (left) and damages due to the 2022 floods (right). ................................................................................................................................... 33 ................................................................. 34 Figure 24. Breakdown of the cost by State due to the 2012 and 2022 floods. iv | The economic impacts of weather-related shocks in Nigeria Figure 25. Building floor area exposed to floods in absolute value (left) and as percentage of State ...................................................................................................................................................... 35 building area (right). Figure 26. Building floor area by State (left) and Building floor area exposed to floods of the State as percentage of national total (right)...................................................................................................................... 35 Figure 27. Annual growth rates of built-up in safe areas vs flood-prone areas................................................................. 36 List of Tables Table 1. Summary of policy options to strengthen fiscal resilience against weather-related shocks....................... viii Table 2. Potential flood damages and losses estimated for Ibadan.................................................................................. 12 Table 3. Main econometric results........................................................................................................................................... 15 Table 4. Summary of policy options to strengthen fiscal resilience against weather-related shocks....................... 29 List of Boxes Box 1. An overview of DRM-related public expenditure using the BOOST database................................................. 8 Box 2. Weather-related shocks, fiscal risks, and contingent liabilities.......................................................................... 10 Box 3. Mexico: An integrated financial protection strategy against natural catastrophes....................................... 28 v | A first step toward the quantification of fiscal risks T his note has been prepared by a team composed of Joaquin Muñoz Díaz (DRM consultant, IAWU1), Rafael Van der Borght (DRM consultant, IAWU1) and Alex Girón (Economist consultant, EMFTX) under the guidance and supervision of Oscar A. Ishizawa (Lead DRM Specialist, IAWU1) with the contribution of Michel Matera (Practice Manager, IAWU1), Samer Matta (Senior Economist, EAWM2), Nyda Mukhtar (Economist, EAWM2), and Juan Jose Miranda (Senior Environmental Economist, SAEE3). Peer reviewers of the CREM PASA outputs under the Building Urban Flood Resilience in Nigeria (P180933) were Elif Ayhan (Lead Disaster Risk Management Specialist, Program Leader, SEADR), Nathan L. Engle (Senior Water Resources Management Specialist, SAEW2), and Thu Hang Vu (Senior Financial Sector Specialist, EFNRF). The Lekki-Ikoyi Link Bridge, the first cable-stayed bridge to be built in Nigeria. State Photo: mujibwaziri. vii | Lessons Learned Exercise for EP&R in Nigeria Executive Summary N igeria is increasingly affected by weather- The average annual damage to physical assets from related shocks, including floods and droughts, floods has been estimated at US$ 693 million (0.18% which have significant economic and fiscal of GDP). This annual average exhibits a significant consequences. This report provides a first assessment level of variability, making it pertinent to look into of these economic impacts, focusing on three key the extreme and infrequent events in order to gain a dimensions: (i) damage to physical assets, (ii) growth deeper understanding of the potential economic and impacts, and (iii) household-level impacts. It then fiscal impact of floods. Any given year, there is 1% discusses the fiscal risks that these economic impacts probability that damage from catastrophic floods will entail. In the absence of a clear strategy to manage exceed US$ 10 billion, (2.7% of GDP or 22.3% of public these impacts, governments at both the Federal and expenditure). This report also summarizes State- and State levels have often acted as an insurer of last resort. city-level assessments found in the literature, which This puts public finances under pressure through two are broadly consistent with national estimates. simultaneous channels: recovery and reconstruction due to damage to physical assets and support to affected Beyond direct damage to assets, floods also have populations (i.e., household-level impacts) raise public the potential to negatively affect economic growth. expenditures, while slower economic growth driven by Econometric analysis conducted for this report indirect impacts translates into lower-than-anticipated suggests that extreme precipitation anomalies produce revenue collection. By quantifying these economic negative effects on growth, with a major heavy rainfall impacts and clarifying their fiscal consequences, the event estimated to reduce Nigeria’s GDP per capita study aims to establish a foundation for policy dialogue growth by up to 3.2 p.p. Based on this empirical on managing disaster-related fiscal risks and enhancing evidence, a growth model was calibrated to further fiscal resilience. explore the growth impact of floods. Results suggest that a catastrophic flood event with a 1% annual Over the past decade, Nigeria has experienced major probability of occurring could reduce potential growth weather-related shocks, notably the devastating by 2.9 p.p., shifting downwards the GDP trajectory for floods of 2012 and 2022. The 2012 floods caused an a considerable period compared to a scenario without estimated US$ 9.5 billion in destroyed physical assets flooding. Importantly, under an alternative scenario (2% of GDP), while the 2022 floods resulted in damages where policies that prioritize disaster preparedness of US$ 6.7 billion (1.6% of GDP). The economic and fiscal resilience allow to speed up post-disaster consequences of these events have been severe, recovery and reconstruction periods, these growth with disruptions to key sectors such as agriculture, impacts are significantly reduced. infrastructure, and commerce. Droughts have further compounded economic vulnerabilities, particularly in The household-level impacts of weather-related shocks the northern regions, where they repeatedly constrain are also substantial, with disasters disproportionately agricultural productivity and contribute to rising poverty affecting the most vulnerable populations. Average and food insecurity. Although the lack of available data annual welfare losses due to floods are estimated at on post-disaster spending strongly limited the scope of approximately 0.4% of GDP, considering the broader the analysis, the fiscal consequences of these events social and economic disruptions beyond direct asset have been significant. Federal and State governments damages. Additionally, floods tend to have a more have been forced to allocate unplanned resources severe impact on conflict-affected areas, where for emergency response, relief, and recovery, often recovery is slower due to existing instability. In crowding out ongoing development programs. addition, droughts exacerbate rural poverty, with a viii | Lessons Learned Exercise for EP&R in Nigeria severe dry spell potentially increasing the rural poverty comprehensive reform agenda seeking to strengthen rate by up to 5 p.p. compared to a normal year. The fiscal resilience, enhance emergency preparedness and cost of mitigating this additional poverty induced by an response mechanisms, and foster long-term resilience extreme drought is estimated at 0.9% of GDP or 6.6% against floods and droughts. As this report focuses on of public expenditure. the economic and fiscal impacts of weather-related shocks, Table 1 summarizes the main policy options Under the combined effects of climate change, that the government could consider to strengthening demographic growth and rapid urbanization, the fiscal resilience against these shocks. Other dimensions impact of weather-related shocks could be further of emergency preparedness and response and long- exacerbated, threatening Nigeria’s development term resilience against drought and floods are covered prospects and macro-fiscal stability. To effectively under the two other assessments that complement this tackle these challenges, Nigeria must embark on a analysis. Table 1. Summary of policy options to strengthen fiscal resilience against weather-related shocks Policy options Timeline Strengthen the institutional and policy framework for fiscal risk management to incorporate weather-related fiscal risks within the broader fiscal risk management framework. Responsibility: Federal Ministry of Finance (FMoF), Debt Management Office, Federal Ministry of Budget and Economic Planning (FMBEP - Budget office) Incorporate weather-related fiscal risks as part of the overall fiscal risk management framework. Short term Establish or identify a unit/department with the mandate of managing contingent liabilities and explicitly Short term include those associated with disaster and climate risks. Delineate explicit and implicit contingent liabilities associated with weather-related risks at the Federal Medium term level and at the State level. Include a quantified assessment of weather-related risks in the Fiscal Risk Statement or the Medium-Term Medium term Expenditure Framework or any fiscal policy document. Develop a framework to articulate the financing of weather-related contingent liabilities between the Federal and State level. Responsibility: FMoF, FMBEP, Nigeria Governors Forum, National/State Emergency Management Agencies Assess and establish legal provisions to clarify how weather-related expenses are shared between the Short term different levels of government. Promote pre-arranged mechanisms to channel financial assistance for disaster relief from the Federal level to the States and local governments, including potential incentives to promote stronger preparedness Medium term actions at the State and local levels. Promote rules-based mechanisms to increase efficiency and transparency in post-disaster resources allocation and execution. Responsibility: FMoF, FMBEP, Ecological Fund office Conduct an in-depth review of the functioning of the Ecological Fund in the aftermath of weather-related Short term shocks to get a better understanding of its potential areas of improvement. Establish a clear legal framework for requesting, approving, disbursing, and executing public resources in Medium term the aftermath of a weather-related shock. Expand risk financing instruments and consolidate them within an integrated risk-layered approach to help smooth the fiscal impacts of weather-related shocks. Responsibility: FMoF, National Insurance Commission (NAICOM), Nigerian Agriculture Insurance Corp. (NAIC) Bring together existing and potential risk financing instruments under an integrated and strategic vision, Medium term considering the wider macroeconomic conditions. Conduct funding gaps analysis and assess diverse risk-financing options, including market-based Medium term instruments, to increase coverage against disaster risk. 1 | Lessons Learned Exercise for EP&R in Nigeria Introduction R ecent substantial disasters in Nigeria have Figure 1. Diagram of evolving disaster risk heightened concerns regarding the potential repercussions of extreme weather events on development prospects and macro fiscal stability. The floods in 2012 and the nationwide floods in 2022 underscored the country’s high vulnerability to weather- related events. For instance, the 2012 floods resulted in an estimated US$ 9.5 billion in destroyed physical and durable assets, equivalent to approximately 2% of the GDP, and led to an overall negative impact on real GDP growth of 1.4%. As the climate changes, Nigeria is expected to face more frequent extreme floods and droughts as well as new threats linked to rising temperatures and sea level rise in coastal areas. These challenges are exacerbated by the rapid demographic shifts and urban growth, Source: Authors based on IPCC (2012). intensifying the pressure on already insufficient urban infrastructure and essential services. Poorly planned and often informal urbanization further magnifies the discusses how these economic impacts put pressure exposure and vulnerability of the population to climate on public finances and constitute a considerable source and disaster risks within a context of limited adaptation of fiscal risk. Specifically, from a fiscal perspective, and response capacities (Figure 1). As risk drivers the growth effects of weather-related events can be evolve, disasters increasingly pose fiscal risks that could approached as traditional macroeconomic shocks that jeopardize the country’s development prospects, which slow down economic growth and result in lower-than- underscores the importance of effective DRM policies. anticipated fiscal revenues. On the other hand, potential Reducing disaster impacts hinges on strengthening damage to assets and well-being impacts constitutes governance, enhancing preparedness and response, contingent liabilities that could translate into additional and integrating disaster and climate resilience public expenditure when weather-related shocks measures into development and investment planning materialize. These effects must therefore become an to mitigate the growing risks faced by communities and essential dimension of fiscal policy making and be infrastructure. incorporated into the broader fiscal risk management framework to ensure an adequate budgetary response. The objective of this report is to provide an initial This assessment aims to establish a foundation for assessment of the economic impacts of weather-related engaging a policy dialogue with the Federal and shocks in Nigeria, focusing on three key dimensions: State governments on the management of fiscal risks (i) damage to physical assets, (ii) growth impacts, and associated with weather-related events. (iii) household-level impacts.1 In addition, this study This report is organized as follows: Section 1 presents an overview of disaster and weather-related shocks 1 Following Dell et al. (2014), in this report “weather-related events” refers to short-run temporal variation in climate variables, while in Nigeria, summarizing historical trends and focusing the word “climate” is reserved for the full distribution of outcomes over several decades. As such, “weather-related events” describe a particular realization from a given climate distribution. “Transition relate to the risks associated with transitioning to a lower-carbon risks”, which are sometimes viewed as “climate change risks” but economy are not covered in this report. 2 | Lessons Learned Exercise for EP&R in Nigeria on the large floods of 2012 and 2022, before briefly responsibilities of States in disaster risk management discussing key structural characteristics that hamper (DRM) or emergency response. Ideally, these aspects Nigeria’s capacity to face weather-related events. would be analyzed in a subsequent phase to enable a Section 2 is the core of the report and seeks to provide more comprehensive identification and quantification a comprehensive understanding of the threats that of the contingent liabilities of the Federal and State weather-related shocks pose to the country’s macro- Governments associated with weather-related shocks. fiscal position. It focuses on quantifying three key Another area of future analysis concerns the flow of dimensions of the impacts of weather-related shocks: (i) financial resources and budget transfers between damages to physical assets, through a review of existing Federal and State governments, which influences the literature that quantifies potential asset damages due fiscal capacity of States to respond to disasters. While to floods; (ii) growth impacts, through an econometric a review of available budget data was conducted using estimation of the effect of extreme precipitation BOOST and some local data sources, data limitations anomalies on economic growth, and a macroeconomic strongly constrained the depth of the analysis. Similarly, model calibrated to assess the potential impacts of this assessment could be further complemented with floods on GDP growth, accounting for indirect effects; a fiscal gap analysis of historical disasters, including and (iii) household-level impacts. Section 3 presents a a review of the financial protection instruments and discussion on the historical and future trends of key risk mechanisms available to the Government, which were drivers: climate change and urbanization, which may beyond the scope of this report. increase weather-related risks in the future. Based on these findings and drawing upon the best international This report is part of a broader policy package and practices in the management of fiscal risks associated complements two other key assessments. The first, with weather-related shocks, section 4 outlines policy Assessment of Flood and Drought Risk Management options aimed at strengthening financial preparedness in Nigeria Through the EPIC Response Framework, to be further refined through stakeholder consultations identifies gaps in Nigeria’s legal, institutional, and and future policy dialogue. technical capacities and proposes a comprehensive set of reforms and investments to strengthen flood This document is a first step to assessing the country’s risk management. The second, Lessons Learned Exercise capacity to quantify and manage the fiscal risks for Emergency Preparedness and Response in Nigeria, associated with weather-related shocks, with several facilitates discussions among key government and potential directions for further analysis. In a federal disaster relief agencies across Federal, State, and local system, fiscal responsibilities are shared between the levels, analyzing existing systems and procedures to Federal and State Governments. This report does not generate actionable recommendations for enhancing examine the legal framework of the specific fiscal disaster preparedness and response. 3 | Lessons Learned Exercise for EP&R in Nigeria 1 Overview of recent disaster and weather-related shocks in Nigeria T his section provides an overview of the trends change. Nevertheless, different datasets consistently and impacts of disaster and weather-related underscore floods as one of the primary disasters in shocks in Nigeria, highlighting the country’s Nigeria, warranting a particular focus in this study. It vulnerability to climate-related events. The section is crucial to acknowledge that historical statistics are also discusses the devastating floods of 2012 and 2022, likely incomplete and subject to reporting bias, as summarizing their economic, fiscal, and social impacts. consistent disaster tracking has only become more Additionally, it benchmarks Nigeria’s current capacity prevalent in recent decades. Consequently, exercising to address these shocks and the need for enhanced caution is essential when deriving conclusions from disaster risk management to strengthen resilience to this data. future weather-related shocks. In the past decade, a notable trend of severe flooding 1.1. Historical disaster trends highlight has emerged, leading to adverse consequences across floods as one of the most significant various sectors, including agriculture, infrastructure, disasters public health, and education. Floods in Nigeria are primarily characterized by the overflowing of Nigeria has long faced severe adverse natural riverbanks, the structural failure of critical dams, events and public health crises, challenges that significant inundation of residential areas due to the are intensifying due to climate change and rapid influx of rainwater runoff, and the displacement or urbanization. As indicated by historical disaster destruction of residential structures. Concurrently, occurrences, Nigeria has recurrently endured adverse there has been an upward trajectory in the number weather-related events, particularly floods (Figure 2). of individuals adversely affected by floods in the The country has also experienced recurrent droughts last decade (Figure 3, top). While recurrent yet in the Sudan-Sahel region in the north, significantly comparatively minor floods have implications for affecting agricultural productivity, food security, and impeding progress in poverty reduction, curtailing water availability. Notable drought periods include local economic activities, and hindering human 1972–1973, 1982–1983, and 1991–1995. The nation development, less frequent but more catastrophic is also exposed to various other hazards, including floods have the potential to affect a substantial portion extreme temperatures and storms, in addition to the of the population and exert significant repercussions on rising sea levels and coastal erosion attributed to climate the nation’s overall growth. Figure 3 (bottom) presents Figure 2. Impacts of weather-related shocks and epidemics in Nigeria, 1980 – 2024 Source: Authors based on CRED (2025). 4 | Lessons Learned Exercise for EP&R in Nigeria Figure 3. Population affected by floods (top) and count of floods by State (bottom), 1985 – 2024 Source: Authors based on CRED (2025). the spatial distribution of floods by State, highlighting heightened level of vulnerability to disasters. Figure the widespread nature of this issue across the country. 4 presents specific components of the World Risk A more detailed assessment of the spatial exposure of Index, offering insights into the driving factors of the floods is presented in Annex A. high vulnerability as well as Nigeria’s performance in comparison to peers. It is important to emphasize that Nigeria’s capacity to face weather-related events these values reflect national averages and considering remains low. Despite being less exposed to adverse Nigeria’s size and status as a Federal Republic, may natural events than other nations, Nigeria confronts hide regional heterogeneities.2 substantial challenges in terms of susceptibility, coping capacities, and adaptive capacities to address these 2 The risk index is computed as the geometric mean of the exposure index and the vulnerability index. The vulnerability index is itself events. As outlined in the World Risk Report (Bündnis computed as the geometric mean of the susceptibility index, Entwicklung Hilft, 2023), compared to its peers, lack of coping capacities index, and lack of adaptive capacities index which are presented in Figure 4. Nigeria’s exposure index Nigeria’s capacity to face weather-related events is (not presented) is low due to the absence of major earthquakes, low. The interaction of these factors contributes to a cyclones, and tsunamis. 5 | Lessons Learned Exercise for EP&R in Nigeria Figure 4. Nigeria’s capacity to face weather-related events—selected World Risk Index components Susceptibility: Structural characteristics that increase Nigeria the likelihood of suffering damage from disasters. It Indonesia indicates the extent of resilience and resources to Mexico mitigate the immediate consequences of disasters. South Africa It is computed based on indicators related to socioeconomic development (health, education, living standards, access to water and sanitation infrastructure, electricity, communication technology, and food security), societal and gender disparities, population facing violence, conflicts, and disasters (refugees, asylum seekers, and internally displaced persons), and the prevalence of diseases and epidemics. Lack of coping capacities refers to the absence of Nigeria abilities and measures of the society to counter Indonesia adverse impacts of natural events or climate change through direct actions and available resources in the form of formally or informally organized activities and measures, as well as to reduce damage in the South Africa Mexico immediate aftermath of an event and initiate recovery. Computed based on indicators related to the impact of recent adverse natural events and conflicts (population affected or killed in the last five years), control of corruption, rule of law, government effectiveness, political stability, health care capacities (personnel and structural capacities), and vulnerable groups (maternal and child mortality rates). Lack of adaptive capacities refers to lack of long- Nigeria term processes and strategies to achieve anticipatory changes in societal structures and systems to counteract, mitigate, or avoid future negative impacts. South Africa Computed based on indicators related to government expenditure and personnel size for research and Indonesia education, long-term health effects (children Mexico vaccination) and deprivation effects (risks due to unsafe water and sanitation sources, particulate matter air pollution, and child and maternal malnutrition), and investment capacities (capital formation and inflation). Source: Authors based on Bündnis Entwicklung Hilft (2023). 6 | Lessons Learned Exercise for EP&R in Nigeria Figure 5. Breakdown of damages and losses by economic sector Source: Authors based on the 2012 PDNA (Government of Nigeria, 2013). 1.2. The devastating floods of 2012 led of critical infrastructure and increased expenses to unprecedented damages and associated with providing essential social services losses3 and unanticipated emergency costs. These factors accounted for the remaining 17% of the overall costs Intense rainfall from July to October 2012 coupled or US$ 2.8 billion. However, it is likely that the actual with increased water levels from runoff caused the public costs exceeded these estimates in the years flooding of human settlements situated downstream following the floods, as governments tend to bear part of various dams. The combined value of damages of the damages and losses suffered by the population in terms of destroyed physical assets and economic through emergency aid, support to affected farmers losses in the most affected States was estimated at and housing reconstruction activities. US$ 16.9 billion, equivalent to 3.6% of the 2012 GDP. Figure 5 shows the distribution of damage and losses The macroeconomic and fiscal impacts of the 2012 across economic sectors, emphasizing the substantial floods can be summarized as follows: impact on physical asset destruction, which totals an estimated US$ 9.5 billion (equivalent to 2.0% of the › An overall negative impact on real GDP growth of 1.4% 2012 GDP), primarily affecting the housing sector. for 2012, accounting for the impact on production Conversely, losses were estimated at US$ 7.3 billion, losses in the economy (mainly the agriculture and oil equivalent to 1.6% of the 2012 GDP, with notable and gas sectors) and the extraordinary spending to impacts on the agriculture, commerce, and oil sectors. provide initial disaster relief. The impact of the floods was significantly skewed › A current account surplus reduced by 0.6% of towards the private sector, accounting for a nominal GDP compared to a no-flood scenario. Oil substantial 83% of the total damage and losses. In exports, comprising 70.4% of total exports and 75% contrast, the public sector—comprising Federal and of consolidated government revenues at that time, State Governments—suffered from the destruction constituted a major source of foreign exchange earn- ings. Flooding in oil-producing regions of the country 3 This section summarizes the results of the Post-Disaster Needs resulted in economic disruptions that generated a Assessment (PDNA) for the 2012 floods (Government of Nigeria, 2013). Assessments of damages and losses were limited to the loss in oil exports of approximately 0.6% of GDP. 12 most severely affected States. Under the PDNA framework, damage refers to the total or partial destruction of property › A fiscal deficit increase of 0.2% of GDP in 2012, and physical assets, including buildings and their contents, decomposed into a 0.07% of GDP decrease in infrastructure, inventories, etc. Losses correspond to variations in economic flows, including production shortfalls and unrealized tax revenue due to reduced economic activities sales. (particularly the oil and commerce sectors), and a 7 | Lessons Learned Exercise for EP&R in Nigeria Figure 6. Breakdown of damages by economic sector Source: Authors based on the 2022 GRADE (World Bank, 2022a). Note: Black lines represent the confidence interval. Estimates for buildings include building contents. Infrastructure includes energy, transport, WASH, flood management, communications, motors, social protection, and irrigation infrastructure. Agriculture includes crops, livestock, fisher- ies, and agricultural capital (local-scale irrigation, farm infrastructure, etc.). 0.1% of GDP increase in expenditure for emergency damage in the States of Jigawa, Rivers, Taraba, Cross recovery. This short-term impact is likely to have been River, and Delta. compounded by additional extraordinary expenses linked to the recovery and reconstruction activities A GRADE5 assessment was conducted to provide an that took place in subsequent years. initial evaluation of the damage by November 2022. This exercise estimated the total direct damage at › A muted impact on inflation, thanks to the Govern- US$ 6.7 billion, equivalent to approximately 1.6% ment’s efforts by releasing grains from strategic food of the 2021 GDP. This estimate has a large range of reserves and distributing high-yielding and flood-re- US$ 3.8 billion to US$ 9.1 billion, reflecting data sistant grain varieties to affected farmers. availability. The estimated damages are generally lower than those observed during the 2012 floods. 1.3. The nationwide floods in 2022 However, it’s important to note that some localized affected a large share of the areas experienced more significant impacts compared population across multiple States4 to the previous event.6 Figure 6 shows a sectoral From June to November 2022, heavy rainfall led to breakdown, highlighting that damage to residential serious flooding across all 36 States and the Federal buildings totaled approximately US$ 2.2 billion, while Capital Territory. The number of people affected has critical infrastructure (including roads, electricity, been estimated to be between 4.4 million and 4.9 WASH, irrigation, and river infrastructure) incurred million (around 2% of the country’s population), with around US$ 1.2 billion in damages. The agriculture the most severely affected States being Bayelsa (over sector experienced damages of US$ 1.8 billion. 50% of the State population), Anambra (12%), and Kogi (11%). Reports and modelling exercises suggest that in Beyond the immediate physical damage, the 2022 the order of half a million buildings were destroyed or floods placed significant fiscal pressures on affected damaged. Damage to agricultural crops was also severe, States, as they sought to allocate resources for as it is estimated that more than 1 million hectares of emergency response and recovery. An analysis of crops may have been flooded, with large agricultural 5 The Global Rapid post-disaster Damage Estimation (GRADE) approach: https://www.gfdrr.org/en/publication/global-rapid- post-disaster-damage-estimation-grade-approach 4 This section summarizes the results of the Global RApid post- 6 PDNA and GRADE methodologies differ significantly, making disaster Damage Estimation (GRADE) assessment for the 2022 it challenging to directly compare their results. The elevated floods (World Bank, 2022a). The GRADE assessment is a rapid economic damages observed during the 2012 floods can primarily approximation of the order of magnitude of damages following be attributed to variations in assumptions regarding losses, a catastrophe. Therefore, the results should be considered an including a greater impact on housing, higher agriculture-related approximation, in the absence of a more detailed, field-based post- factors, potentially deeper flooding, and more extensive inundation disaster needs assessment. Economic losses were not assessed. in agricultural and higher population and physical asset density. 8 | Lessons Learned Exercise for EP&R in Nigeria DRM-related public expenditures at both the Federal These insights underscore the challenges in financing and State levels was conducted and is presented in Box disaster preparedness and response and the need for 1, which highlights key findings on budget allocations, enhanced investment in DRM to strengthen Nigeria’s spending efficiency, and the role of key institutions. resilience to future weather-related shocks. Box 1. An overview of DRM-related public expenditure using the BOOST database An exercise to identify, quantify, and track public spending allocated to DRM-related activities was conducted to map the different governmental actions that contribute to strengthening the management of disaster and climate-related risks.7 Relevant administrative units, programs, and projects were analyzed based on the available budgetary information. The lack of consolidated data, coupled with varying levels of disaggregation and completeness, posed significant challenges in identifying major expenditures.8 State budget responses to extreme flooding: evidence from 2022 The 2022 floods likely imposed significant fiscal pressures on affected States, through unexpected additional expenditures for response and recovery—funded through ad-hoc budgetary arrangements at the State level as well as potential resources transferred from the Ecological Fund or relevant Ministries, Departments or Agencies. An analysis of State-level public expenditure shows that, on average, the 9 regions that registered more damages during the 2022 floods (ranked using per capita flood damage estimates from World Bank, 2022a) reported an 18.6% y/y increase in the executed budget (2021 – 2022), almost double the average reported by the remaining 9 regions with minor impacts from the floods (9.4% y/y). While it was not possible to identify the source of financing used to cover these extraordinary expenditures, anecdotal evidence suggests that transfers from the Ecological Fund played a primary role. However, considerable variability across States suggests that this difference cannot be exclusively attributed to the impacts of the floods. While indicative, these findings highlight the need for deeper analysis of State-level budget structures and local governments’ capacity to respond to climate-related events. Key insights from the Federal Government budget for 2017 – 2021 › Only 4.5% (2,258) of the programs and projects included in the Federal Government budget are DRM-related. These account for an annual average allocation of less than NGN 31 million (0.4% of total governmental expenses) which unveils the very limited mainstreaming of DRM considerations at the Federal level. 96% of these allocations are destined for capital expenditures. › A slight increase in DRM-related expenditures was observed in 2020 – 2021 vis-à-vis 2017 – 2019, driven by programs aimed at responding to emergencies and subsequent recovery. › The overall absorption rate of the identified programs remained below 20%.9 The execution of DRM-related activities was inconsistent and underperforming and contrasts with the absorption rate of non-relevant programs and projects (about 65%). › The most relevant agencies implementing DRM-related programs or activities are the Min. of Water Resources (31% of the total DRM-related expenditure executed), the Min. of Works and Housing (19%), and the Min. of Agriculture and Rural Development (11%). Key institutions like the Presidency and the Min. of Humanitarian Affairs, Disaster Management and Social Development, account together for less than 3% of the total sectoral expenditure. 7 DRM-related activities are activities that go beyond the traditional emergency response and include measures related to risk prevention and reduction, risk assessment or reconstruction and recovery, among others. Due to their crosscutting nature, these activities might be embedded in different programs and projects. A thorough review of all the budget lines was thus conducted to identify DRM-related expenditures as those activities that meet at least one of the following criteria: (i) programs and projects including relevant key words associated with meteorological phenomena, vulnerable basic infrastructure, or prevention and assistance actions; (ii) programs targeting power supply, drainage, solid waste management, water supply, and sanitation when directly linked to weather events as well as all the emergency response measures aiming to attend infrastructure mishaps; or (iii) activities led by the National Emergency Management Agency, and those programs funded by the Ecological Fund. 8 Disaggregated programmatic data for Federal government is available for 2017–2021, but it does not include data from foreign financial sources, among others. State-level information is only available for 2021–2022, but it is incomplete and inconsistent. 9 The absorption rate represents the proportion of executed expenditure relative to the initial allocation, serving as a key benchmark to assess the efficiency and effectiveness of budget implementation. A higher absorption rate indicates greater alignment with planned allocations, reflecting progress toward achieving the program’s objectives. 9 | Lessons Learned Exercise for EP&R in Nigeria 2 A first assessment of the economic impacts of weather-related shocks in Nigeria This section seeks to provide a comprehensive Collectively, these economic impacts put pressure on understanding of the threats that weather-related public finances and constitute a considerable source shocks pose to the country’s macro-fiscal position. of fiscal risk. From a fiscal perspective, the growth It focuses on quantifying three key dimensions of the effects of weather-related events can be approached impacts of weather-related shocks: as traditional macroeconomic shocks that slow down economic growth and thus result in lower-than- (i) Damage to physical assets: Subsection 2.1 anticipated fiscal revenues. On the other hand, potential reviews existing literature that quantifies national damage to assets and household-level impacts both and State-level potential asset damages due to constitute contingent liabilities that could translate floods. into additional public expenditure when weather- related shocks materialize (see Box 2 presents a formal (ii) Growth effects: Subsection 2.2 presents an definition of fiscal risks and contingent liabilities). econometric model estimated to empirically assess These effects must therefore become an essential the effect of extreme precipitation anomalies dimension of fiscal policy making and be incorporated on economic growth. This is complemented by a into the broader fiscal risk management framework to macroeconomic model which was calibrated to ensure an adequate budgetary response. Otherwise, assess the potential impacts of floods on GDP the restrained fiscal capacity to respond to weather- growth, accounting for indirect effects. related shock might extend the reconstruction period (iii) Household-level impacts: Subsection 2.3 briefly and/or left post-disaster needs unmet, which in turn presents three studies that assess the welfare could trigger negative spillovers and amplify the initial impact of floods, the impact of droughts on rural growth impacts of these shocks. Figure 7 provides poverty, and the differential impact of flooding in a schematic view of the conceptual framework conflict-affected versus non-conflict areas due to underpinning this chapter. the 2022 floods. Figure 7. A schematic view of the threats that weather-related shocks pose to Nigeria’s fiscal position Source: Authors. 10 | Lessons Learned Exercise for EP&R in Nigeria Box 2. Weather-related shocks, fiscal risks, and contingent liabilities Fiscal risks can be defined as significant deviations between budget results and initial budget forecasts or anticipated results (Cebotari et al., 2009). They arise from macroeconomic shocks (exchange rate variability, fluctuation in the oil price, etc.) or the realization of contingent liabilities (bailout of public companies, financial crises, climate shocks, etc.). The materialization of these contingent liabilities—which depends on a future and uncertain event (IMF, 2016)—can also lead to macroeconomic shocks when, due to rare but large-scale weather-related shocks, growth is revised downwards, and budget revenues reduced. Contingent liabilities associated with weather-related shocks can be “explicit” or “implicit”. They are explicit when they are legally grounded (e.g., legal or contractual obligations linked to the reconstruction of public infrastructure or the restoration of public services). However, floods and droughts often result in public spending that exceeds explicit contingent liabilities. This occurs when the Government, influenced by social vulnerabilities, political pressures, or the urgency to expedite post-disaster recovery to boost economic recovery, assumes responsibility for a portion of the losses experienced by the population through emergency aid, housing reconstruction, and other interventions (i.e., “implicit” contingent liabilities). However, these fiscal risks are intrinsically complex should be covered by the Government in the aftermath to quantify. Unless the government’s responsibilities of a disaster. Ideally, this analysis will be conducted in are clearly delimited and spelled out in binding fiscal a second phase to facilitate a proper identification and statements—which is not the case in Nigeria—there quantification of the contingent liabilities associated will be uncertainty surrounding the magnitude and with weather-related shocks in Nigeria. nature of liabilities that the State (both Federal and State-level) will have to bear in case of disasters. In fact, 2.1. Assessment of potential damages anecdotical evidence suggests that expenses related associated with floods to climate-related shocks go well beyond the costs 2.1.1. National-level damages associated with needed for restoring public assets and services. Social floods vulnerabilities, political pressure, or even the need to stimulate growth by speeding up recovery have meant While useful, the historical data presented in the that the government has repeatedly assumed a large part first section is insufficient to accurately assess the of the losses that affected private agents. Governments magnitude of potential losses associated with floods. at both the Federal and State levels have thus often acted As Nigeria grows its economy and expands its cities, as an insurer of last resort, with the overall fiscal impact the country accumulates more physical and productive of weather-related shocks depending on the amount assets. As new assets are built in risk-prone areas (see of implicit contingent liabilities that the government is Annex B), they inflate the exposure of the country, willing and/or able to finance. configuring a scenario of potential losses that is different from the historical pattern. Besides, given Developing a complete understanding of the economic restricted data availability, historical losses do not impacts that weather-related events pose to the capture the full spectrum of hazard conditions and country’s fiscal position is the first step to enhance may underestimate the impacts of large catastrophic the country’s capacity to manage the specific fiscal events. To get a more robust sense of the damage that risks associated with this type of shocks. The analysis floods could generate, historical analysis is usually proposed in this chapter shows that in Nigeria, weather- complemented with a probabilistic risk assessment. related shocks can affect economic growth and materialize considerable contingent liabilities. However, In the case of Nigeria, a probabilistic risk assessment the present analysis does not review the legal framework for floods was conducted under the GAR Atlas 2017 that could help delineate explicit contingent liabilities (UNDRR, 2017). It estimates the average annual damage nor discuss what implicit contingent liabilities could or associated with riverine flooding at US$ 693 million 11 | Lessons Learned Exercise for EP&R in Nigeria Figure 8. Loss exceedance curve for riverine floods Source: Authors based on UNDRR (2017). (0.18% of 2017 GDP).10 Probabilistic risk models were with their exceedance probability. When comparing originally developed by the international (re)insurance potential damages from extreme floods relative to industry and are based on scientific and engineering public expenditure within Sub-Saharan Africa, Nigeria studies of natural hazards and their impacts on specific is situated at a mid-level position, as illustrated in assets like buildings and infrastructure. Risk models Figure 9. This suggests there is considerable room for integrate high-resolution data on location and quality improvement in terms of both flood risk reduction and of properties to estimate potential damage of physical the strengthening of fiscal resilience against floods. capital for events with various likelihoods. Although the GAR 2017 is a global study not specifically calibrated Figure 9. Damage that could be exceeded for Nigeria, it constitutes a first quantification of the with an annual probability of 1% for countries potential direct damages due to riverine flooding. in Sub-Saharan Africa The annual damages exhibit a significant level of variability, making it pertinent to look into the extreme Mali and infrequent events in order to gain a deeper Nigeria understanding of the potential impact of floods. Any Mozambique given year, there is a 5% probability that damage resulting from riverine flooding will exceed US$ 4,180 million, equivalent to 1.1% of 2017 GDP or 9.3% of South Africa the same year’s public expenditure. There is also a 1% probability that damages will exceed US$ 10,064 million, equivalent to 2.7% of GDP or 22.3% of public expenditure.11 These results are presented in Figure 8, which relates the potential damage due to floods Source: Authors based on UNDRR (2017). 10 The average annual damage corresponds to the monetary value Note: Other countries are depicted in grey. To improve legibility, necessary to replace infrastructure and physical assets (public and Gabon (183%) and Somalia (160%) were removed from the figure. private) that are damaged or destroyed due to floods. 11 The return period associated with a level of damages corresponds to the inverse of the annual probability of exceeding said level. 2.1.2. State-level damages associated with For example, if the damage associated with a given flood has a floods return period 20 years, then the annual exceedance probability of that level is equal to 1/20 = 5%. This does not mean that this No other national-scale flood risk assessments were level of damages will be exceeded exactly once every 20 years, but rather that, in the very long term, the average period between identified in this review. However, several State- and these exceedances is 20 years. city-level assessments were found. These assessments 12 | Lessons Learned Exercise for EP&R in Nigeria Table 2. Potential flood damages and losses estimated for Ibadan Return period (years) 10 25 100 1000 Average Annual Losses Building damages 31.9 40.8 51.5 61.6 10.5 Total damages and losses 321.4 411.0 518.8 620.6 105.3 Source: World Bank (2014). Figure 10. Average annual damage from flood hazards in coastal cities Source: Authors based on World Bank (2022b). are broadly consistent with the nation-wide estimates › World Bank (2022b) provides an estimation of provided in the precedent subsection and are briefly the average annual damages due to rainwater and summarized below.12 coastal floods for eight coastal cities in Nigeria, including the largest coastal city of Lagos. Results › World Bank (2014) estimated the average annual are summarized in Figure 10. The estimated cost for damage and losses from floods in Ibadan at US$ Lagos was US$ 30.3 million, while the cost for the 105.3 million, and from a 1-in-100-year flood other assessed cities was estimated at less than US$ at US$ 518.8 million (Table 2). It is important to 5 million. emphasize that these figures are the outcome of a rapid risk assessment grounded in rainfall statistics InsuResilience (2021) estimated the average annual rather than a comprehensive hydrological modeling damage to buildings and infrastructure due to riverine approach. As a result, they should be viewed as an floods in Lagos at US$ 22.2 million, under current initial approximation of the damage and losses in climatic conditions. The study also shows that damage Ibadan. resulting from climate change and increased exposure and subsequent flooding could almost double in Lagos For reference, the drainage masterplan for Ibadan by 2050, summing up to US$ 40.9 million.13 designed to better manage flood risk estimates the cost of all the proposed drainage elements— 13 Besides these assessments, Croitoru et al. (2020) estimated the the channelization works, structures (culverts and net present value of the impacts of fluvial and pluvial floods in the bridges), and dams—at US$ 1,557.8 million (Dar, coastal zones of three States for the next 30 years. The economic cost of flooding (damage to buildings and infrastructure, forgone 2019). economic activity, and mortality) for Cross River were estimated at US$ 94 million (1.2% of the State’s GDP), for Delta at US$ 300 12 Due to variations in methodologies and resolutions among the million (2.1%), and Lagos at US$ 3,992 million (4.1%). However, as assessments, a formal comparison is not feasible. However, it is these figures represent the net present values of future damages prudent to note that the outcomes of the assessments are within and losses, they are not directly comparable with the other studies the same order of magnitude. presented. 13 | Lessons Learned Exercise for EP&R in Nigeria 2.2. Assessment of the growth impact annual frequency of the data, our model is constrained of weather-related events by limited observations. Recognizing the potential overlap of estimated effects with other exogenous Beyond direct damages to physical assets, weather shocks coinciding with precipitation anomalies—and related shock can lower growth prospects through considering data limitations—our findings should be indirect effects and disruptions to economic activity. interpreted with caution. To better understand the magnitude of the growth impacts associated with weather-related events, Monthly temperature and precipitation were obtained two complementary analyses were conducted. First from the Climate Research Unit gridded Time Series an empirical analysis of the effects of precipitation dataset, version 4.07 and aggregated on a national and anomalies on per capita GDP growth rates was annual basis. Annual GDP data were retrieved from the performed to assess whether and to what extent World Bank’s World Development Indicators database aggregated economic activity is sensitive to these and oil prices from the Energy Institute Statistical weather anomalies. A modelling assessment is then Review. Figure 11 shows the evolution of annual proposed to capture the impacts of large catastrophic precipitation anomalies measured in terms of Z-score floods on potential GDP growth and provide a more throughout the period. Interestingly, when splitting the comprehensive view of potential growth impacts. period of analysis into two equal subperiods, negative precipitation anomalies seem to have been reduced, 2.2.1. Extreme precipitation anomalies have a both in terms of frequency and intensity (three negative effect on economic growth anomalies below -1 during 1999–2022 vs six during Based on the analytical framework developed by the 1975–1998). Contrastingly, positive rainfall anomalies climate economics literature (see Dell et al., 2014), we are more evenly distributed across the entire period carry an econometric study to assess the causal effect and have even slightly increased during recent years of precipitation anomalies on Nigeria’s economic (five anomalies above 1 during 1999–2022 vs three growth during 1975–2022. The identification strategy during 1975–1998). These trends reflect regional of the empirical analysis is based on the hypothesis that climatic patterns and the progressive recovery of year-to-year variations in weather variables constitute overall precipitation levels in the Sahel and West Africa exogenous shocks. A first difference equation is used after the particularly marked droughts of the 1970s to reduce the potential omitted variable bias and and 1980s (Giannini et al., 2003). ensure stationarity. Our benchmark equation takes the following form: The results are presented in Table 3 and unveil a non- linear relationship between precipitation anomalies ∆! = + " !#$ + $ ! + % ! % + ! + !#$ + ! and GDP per capita growth rates (inverted U-shaped Where ∆Yt represents the growth rate of GDP per curve). Column 1 corresponds to the estimation of capita in year t, Ln Yt–1, is the natural log of the level the equation above and identifies this non-linear of GDP per capita in year t–1, Pt is a variable that represents precipitation anomaly on year t, which including lagged precipitation and temperature variables, as well is also included in its quadratic form to explore as other functional forms (cubic), alternative weather variables (population-weighted precipitation and temperature) and control non-linearities in the response of GDP to weather variables (Dated brent crude oil prices VS Nigerian Forcados Oil anomalies, T is the deviation of the annual temperature prices); and (ii) Following the climate economics literature, annual precipitation was standardized in the form of a Z-score to consider from its long-term average, Oilt–1 is the first difference the spatiotemporal heterogeneity of rainfall regimes and facilitate of oil prices in year t–1, and εt is the robust and the detection of precipitation anomalies. A value of 0 means that independently distributed error term.14 Given the annual rainfall is equal to its long-term average, while a positive (negative) value indicates an excess (deficit) of rainfall measured in terms of standard deviations. Additional event analysis as 14 Methodological notes: (i) To avoid bias associated with “bad proposed in Miller (2023) were conducted for the 2012 floods and controls” (or overcontrolling), the specification is purposefully suggest a pattern broadly consistent with the findings described parsimonious. Alternative specifications were also tested, here, although growth effects were hardly statistically significant. 14 | Lessons Learned Exercise for EP&R in Nigeria Figure 11. Evolution of annual precipitation anomalies in Nigeria, 1975 – 2022 Source: Authors. Precipitation anomalies n Deficit n Excess n Normal Figure 12. Effect of annual precipitation anomalies on per capita GDP growth Source: Authors. Hist. obs (1975–2022) ● Deficit ● Excess ● Normal relationship. Column 2 repeats the estimation without variables on the growth rate of the oil sector exclusively including control variables and confirms the presence is found to be insignificant. of a non-linear relationship, with high precipitation anomalies associated with negative and significant The growth effect of precipitation anomalies effects. To illustrate these effects, the impact of demonstrates statistical significance in the context precipitation anomalies estimated through the of extreme events, but not in the case of more specification of column 2 is presented in Figure 12. frequent or localized precipitation anomalies. When Finally, column 3 uses alternative population-weighted annual precipitation is two standard deviations above precipitation and temperature variables to test the its long-term average, its marginal impact becomes sensitivity of the results to different aggregation negative and statistically significant. Likewise, when methods and confirms that previous results hold. Using annual precipitation is two standard deviations below the growth rate of non-oil GDP as a dependent variable the mean, a statistically significant negative effect is reveals very close results, while the effects of weather observed. These negative effects become increasingly 15 | Lessons Learned Exercise for EP&R in Nigeria Table 3. Main econometric results Dependent variable: GDP/cap growth (1) (2) (3) Precipitation Zscore –0.14 –0.19 (0.88) (0.67) Sq. Precipitation Zsquare –1.53*** –1.63*** (0.38) (0.30) Pop W Precipitation Zscore 0.32 (0.98) Sq. Pop W Precipitation Zscore –1.12*** (0.30) Temp. Dev. 4.05 3.57 (3.12) (2.92) Lag Log GDPPC –3.24 –3.48 (4.58) (4.31) 1st Diff Oil prices 4.24*** 4.04*** (1.14) (1.35) Cosntant 25.94 1.86* 27.41 (33.78) (1.02) (31.89) Observations 44 48 44 Adjusted R 2 0.27 0.18 0.21 Residual Std. Error 4.53 (df = 38) 4.76 (df = 45) 4.71 (df = 38) F Statistic 4.11*** (df = 5; 38) 6.04*** (df = 2; 45) 3.28*** (df = 5; 38) Note: *p<0.1; **p<0.05; ***p<0.01 Source: Authors. important as the precipitation anomaly worsens, per capita growth rates above 3% in only 17 out of the reflecting the adverse economic effects associated 48 years considered. Effects associated with negative with the heavy rain and flooding, as well as the lack precipitation anomalies are in the same order of of precipitation leading to drought events. However, magnitude. It is important to keep in mind that these when precipitation anomalies are in the range of -2 aggregated effects might mask large losses and gains to 2 standard deviations from the mean (i.e., “normal” across territories and sectors as well as considerable weather conditions), they do not exhibit a statistically redistributive effects not captured here. In fact, the significant effect on growth. As expected for an oil- large size of the Nigerian economy might mitigate the producing country, an increase in oil prices has a impact of non-extreme precipitation anomalies and positive and statistically significant effect on growth. contribute to explain why only “tail” events produce significant growth effects. Quantitatively, it is estimated that the maximum annual rainfall anomaly recorded during the period More worryingly, results suggest that the decline (i.e., a Z-score of 1.75) is associated with a reduction in per capita GDP growth rates could be severely in per capita GDP growth of 3.2 p.p. This is a sizeable exacerbated when considering more important effect since the average GDP per capita growth rate precipitation anomalies: two standard deviations over the period 1975 – 2022 was 0.28% and—besides above the historical average of annual rainfall would high growth volatility—the country experienced GDP slow down per capita GDP growth by 5 p.p. Although 16 | Lessons Learned Exercise for EP&R in Nigeria precipitation anomalies of this magnitude have not rebound causing income levels to converge back to been observed during the historical period of analysis, their pre-disaster trend16 (Hsiang and Jina, 2014). climate change is expected to increase the frequency of rare extreme rainfall events (i.e., events in the tail of Following a flood, the magnitude of growth effects the distribution), which would increase the likelihood is mainly influenced by two factors: the extent of the of experiencing annual precipitation of this scale damage and the duration of the reconstruction. On (see subsection 3.2). More frequent tail events could the one hand, the greater the extent of damage, the therefore pose a substantial macroeconomic threat. more significant the reduction in the available stock To better understand the potential growth impact of of capital, potentially leading to substantial negative these tail events a modelling exercise is proposed in externalities. The magnitude of asset damage for the following subsection. different return periods is obtained from the previously presented results from UNDRR (2017). On the other 2.2.2. Modeling the impact of floods on hand, the duration of the reconstruction determines the potential GDP growth time required to replenish the capital stock and return to the pre-disaster growth trajectory. This duration can Beyond physical asset damage, floods can trigger be influenced by the institutional or fiscal capacity for macroeconomic dynamics that amplify initial fiscal reconstruction. In this analysis, the latter is assumed to risks. The direct impact of a flood is a decline in the be the constraining factor, and it is supposed that the available stock of capital for economic production, Government can allocate 2% of the public expenditure which can translate into a decrease in potential growth. annually to fund the reconstruction of the damaged To quantify this impact, an analysis based on the assets and must finance the full extent of the damage. analytical framework proposed by Hallegatte and Vogt- Reconstruction time is computed as the ratio between Schilb (2019) was carried out. The framework is based asset damage and public annual expenditure dedicated on an adapted Cobb-Douglas production function to post-disaster reconstruction.17 that seeks to better capture the nature of damage and productivity effects associated with floods.15 The model Using this framework, the potential asset damages translates capital damages to potential GDP losses and retrieved from the risk profile from UNDRR (2017) are does not take into consideration damages to human translated into a reduction of potential GDP growth and natural capital due to floods, nor the potential macroeconomic smoothing effects after the shock (see Annex C for a description of the model). However, it 16 This assumption is in line with the standard neoclassical growth theory, in which capital destruction generated by exogeneous assumes that growth will eventually “recover to trend”, shocks subsequently spur investment to replenish the capital which implies that growth would suffer for a finite stock and, over the medium term, puts product back to its steady state level. In practice, this “catch-up effect” will depend on a large period in the aftermath of a flood but should eventually range of factors including (i) the quality and criticality of the capital stock damaged or destroyed; (ii) the ability of the Government to put together and implement efficient counter-cyclical fiscal policies; and (iii) the absorption capacity of the economy. See Felbermayr and Gröschl (2014), Yang (2008), and Strobl (2011) for a more comprehensive discussion of these dynamics. 15 The adapted Cobb-Douglas function accounts for two major 17 A higher budget for recovery and reconstruction expenditure features: (i) the limited reallocation of capital between sectors increases the speed at which the stock of capital can be observed in the aftermath of a flood implies that production replenished and shortens the time required to put product back to losses resulting from the destruction of part of the capital stock steady state. The longer it takes to rebuild damaged infrastructure, are estimated using the average—and not marginal—productivity restore services, and return affected businesses to normal of capital; and (ii) besides the reduction of the stock of capital operation, the greater the overall output losses will be. Hence, available for economic activity, a flood can also make the shortening reconstruction times can have a positive impact in remaining unaffected capital less productive due to negative reducing output losses. Potential recovery and reconstruction externalities. This can be illustrated with the example of damages expenditure are therefore a critical variable to estimate potential to infrastructure: the destruction of a bridge renders certain GDP losses in the aftermath of a flood. The assumed value of 2% intact roads unusable, just as the destruction of a power plant can is chosen based on observations in other countries in the region render distribution lines unusable and reduce the productivity of and should be better calibrated following a funding gap analysis of unaffected businesses and assets. the post-disaster expenditure of the 2012 or 2022 floods. 17 | Lessons Learned Exercise for EP&R in Nigeria Figure 13. Fitted curve for potential GDP loss 3.0 p.p. 2.5 p.p. Potential GDP loss (p.p.) 2.0 p.p. 1.5 p.p. 1.0 p.p. 0.5 p.p. log. fit Model results 0 p.p. 0 20 40 60 80 100 Source: Authors. Return period Figure 14. Potential GDP growth following a 1-in-100-year flood event scenario in 2025 640 GDP (constant 2015 US$ billion) 620 600 580 560 GDP baseline projection GDP flood scenarion 540 2023 2024 2025 2026 2027 2028 Source: Authors. Year Note: Real annual GDP growth projection is set at 3% aligned with IMF estimates (IMF, 2023). (Figure 13). In general, the effect of floods on growth If an extreme flood causing direct asset damage is limited most of the time and has a 95% chance of equivalent to 2.7% of GDP occurs in 2025—a being less than 0.6 p.p. of GDP any given year.18 On the level of damage with a 1% annual probability of other hand, an extreme event with a 1% annual chance being exceeded—, potential GDP would be shifted of occurring has the potential to reduce potential GDP downwards for up to 9 years compared to a scenario growth by more than 2.9 p.p. This is aligned with the without flooding (Figure 14). This scenario would result results presented in subsection 2.2.1 on the effect of in an overall potential GDP loss of 2.9 p.p. relative to precipitation anomalies on per capita GDP growth, the non-flood scenario. This result is driven by the where results demonstrate a negative and statistically compounding effect observed after a large disaster, significant effect in the context of extreme events wherein the larger the level of damage, the larger the but not in the case of more frequent precipitation negative externalities and the longer the recovery anomalies. period given the limited fiscal capacity assumed. The model reflects this non-linear relationship between asset damage and economic losses and underscores 18 This considers the likelihood of experiencing a flood, which means that for many years the impact could be null as floods may not the potential underestimation of flood costs when occur. exclusively considering asset damage. In fact, for large 18 | Lessons Learned Exercise for EP&R in Nigeria catastrophic flood events, potential GDP losses can be 2.3. Assessment of household-level on a comparable scale to the asset damage itself. impacts of weather-related shocks These modelled losses can illustrate various fiscal policy 2.3.1. Welfare losses due to floods scenarios. An alternative scenario has been calibrated Like the growth effects analyzed above, asset losses assuming a broader set of disaster risk financing generated by floods also translate into well-being instruments and enhanced emergency preparedness losses. As a first approximation, these welfare losses and response capacities, which altogether allow the can be apprehended through the socioeconomic government to rapidly access funding in the aftermath resilience indicator developed by Hallegatte et of a flood and expedite the recovery process.19 Under al. (2017). According to this estimate, Nigeria’s this alternative scenario, the same extreme flood socioeconomic resilience has been estimated at 48%, would result in an overall potential GDP loss of 1.6 p.p. meaning that, on average, losses in well-being are compared to the no-flood scenario. This represents about twice as great as direct damages to assets when a 45% loss reduction compared to the extreme flood a disaster strikes. This index is calculated as the ratio scenario under a constrained fiscal capacity scenario. of asset losses to welfare losses and measures the This gain is driven by faster reconstruction and reflects ability of the economy to minimize the impact of asset the benefits of enhanced emergency preparedness losses on well-being. Based on the flood risk estimates and response capacities together with higher fiscal presented above from UNDRR (2017), this level of resilience to weather-related shocks. socioeconomic resilience suggests that the average annual welfare losses due to flooding are around 0.38% By implementing policies that prioritize disaster of GDP. Nigeria’s socioeconomic resilience remains low preparedness and fiscal resilience, it is thus possible to compared to that of sub-Saharan Africa countries.20 mitigate the longer-term economic costs of weather- related events and help affected communities to 2.3.2. Floods can disproportionally impact recover faster. These policy measures could include conflict-affected areas (i) strengthening the emergency preparedness and response systems in place by implementing some of Bih et al. (2024) studied the differential impact of the measures recommended in the Lessons Learned flooding in conflict-affected versus non-conflict areas Exercise for Emergency Preparedness and Response in due to the July 2022 floods. Understanding these Nigeria report; (ii) ensuring the fiscal capacity to fund dynamics is crucial for designing effective policies that post-disaster reconstruction activities through an enhance resilience and reduce the long-term burden adequate mix of disaster risk financing instruments on affected communities. The study used a difference- (e.g., contingency fund, contingent credit line, in-difference approach that leverages satellite-derived catastrophic insurance, etc.); and (iii) strengthening the nightlight radiance as a proxy for economic activity and capacity to manage the recovery and reconstruction combined it with flood footprints and conflict data. process, as even if financial resources are available, other institutional and supply side constraints could 20 The analysis considers the different abilities of poor and nonpoor hamper the reconstruction. people to cope with asset losses by modeling the effects of asset losses on consumption. Consumption losses are translated into well-being losses, considering the different impacts of a US$ 1 loss on poor and nonpoor individuals. Well-being loss at the country level depends on the distribution of impacts within the population, but it is expressed as the equivalent loss in national consumption. Thus, a finding that a disaster causes US$ 1 million in well-being losses means that the impact of a disaster on well-being is equivalent to a US$ 1 million decrease in country consumption, 19 In practical terms, this policy scenario is calibrated assuming that perfectly shared across the population. If socioeconomic resilience the Government can mobilize 4% of public expenditure annually is 50%, then well-being losses are twice as large as asset losses— to fund the recovery and reconstruction process, instead of 2%, that is, US$ 1 in asset losses from a disaster is equivalent to US$ 2 and efficiently allocate and execute those. in consumption losses, perfectly shared across the population. 19 | Lessons Learned Exercise for EP&R in Nigeria Figure 15. The impact of droughts on rural poverty rates (left) and poverty gap (right) Source: Adapted from Gascoigne et al. (2024). The results indicate that, immediately following the poverty threshold, added up for all poor households), flood, conflict-affected areas experienced a 1.2% relative to an average year. larger decline in nightlight radiance compared to non-conflict areas. This statistically significant finding Results suggest that if the poorest rainfall conditions suggests that the compounded presence of conflict experienced in the past 13 years were to occur today, exacerbates the economic disruption caused by rural poverty would be 5 p.p. higher compared to the floods. Additional analysis confirms that the larger the year with average rainfall. Furthermore, poverty is 12 p.p. casualties of the conflict, the smaller the nightlight higher under the worst weather conditions compared radiance. Time-series evidence shows that, although to the best conditions observed in the last 13 years.21 both groups initially follow a similar trajectory, the recovery of economic activity—as inferred from The difference in the total poverty gap between the nightlight radiance—is notably slower in conflict- worst and best weather conditions amounts to 2011 US$ affected regions. This prolonged recovery implies that 2.4 billion (PPP). This represents the cost of a perfectly structural vulnerabilities related to conflict not only targeted social protection scheme designed to mitigate amplify the immediate impact of flooding but also the increase in poverty caused by weather conditions, delay the return to pre-disaster economic conditions. equivalent to approximately 0.9% of 2023 GDP or 6.6% of public expenditure. This figure is significant considering 2.3.3. The impact of droughts on rural poverty that in 2021, Nigeria spent only 0.7% of its GDP on social safety nets (World Bank, 2023). Given that perfect Gascoigne et al. (2024) assessed the increase in rural targeting is unlikely, the actual cost could be much higher. poverty rates and the associated costs of mitigating this Identifying alternative mechanisms to reduce the impact amplified poverty gap across 13 scenarios in Nigeria, of rainfall on household income and consumption—such each reflecting the weather patterns observed over as investing in soil conservation, water management the past 13 years. The results show how each scenario practices, or strengthening households’ ability to generate would influence poverty today if those weather income in unaffected sectors during adverse years—could conditions were to occur under present circumstances. help mitigate this cost. Each point in Figure 15 represents the estimated change in the rural poverty rate (the proportion of 21 This is a significant impact, which may be an underestimate, as households whose simulated consumption falls below the model does not incorporate the impact of drought on broader market dynamics, particularly those affecting urban areas, where the US$ 1.90 poverty line) and the poverty gap (the the impact could be substantial. The share of the rural population total shortfall between household consumption and the covered by livelihood zones included in the analysis is 55%. Lagos, Nigeria: Rainy season Photo: it:peeterv 21 | Lessons Learned Exercise for EP&R in Nigeria 3 The critical role of risk drivers in shaping future disaster and climate risks T he impact of weather-related events is is expected to persist across all climate scenarios, expected to intensify in the future due to with a magnitude contingent upon global emissions evolving risk drivers. This section discusses trajectories. The increase may range from +1.2°C key trends shaping disaster risk in Nigeria, focusing (under SSP1-2.6) to +4.7°C (under SSP5-8.5) by 2100, on climate change—particularly shifts in temperature relative to the average temperature observed between and precipitation—and the dynamics of demographic 1995 and 2014 (Figure 16, right). growth and urbanization. Specifically, rising temperatures are expected to increase water demand Moreover, the maximum annual temperature is and elevate the risk of droughts, while more frequent projected to follow a similar trajectory, with the and intense extreme precipitation events will heighten occurrence of temperature anomalies becoming more flood hazards. This section also highlights the effects frequent and severe. This elevation in temperatures of sea level rise on coastal flood risk. Additionally, it is expected to augment evapotranspiration and, discusses the implications of rapid urban growth, which consequently, the water demands of plants and is increasing exposure to floods. Understanding these ecosystems. This phenomenon has the potential to evolving trends is essential for strengthening Nigeria’s amplify the severity of drought episodes, even in the resilience and informing effective DRM strategies. absence of significant changes in precipitation patterns. In urban areas, the impact of high temperatures is 3.1. Temperatures will continue expected to be further aggravated by urban heat island increasing, augmenting water effects and could pose serious threats to both labor demands of ecosystems and productivity and human health. hampering labor productivity 3.2. Extreme precipitation events are Temperatures in Nigeria are expected to exhibit likely to become stronger and more a sustained rise due to climate change across all frequent scenarios, resulting in an annual average temperature that could exceed 30°C under the high warming Climate projections indicate significant changes scenarios.22 Between 1971 and 2023, Nigeria in rainfall patterns in Nigeria. High global warming experienced an annual average temperature rise of scenarios predict a considerable increase in precipitation 0.02°C per year, resulting in an overall increase of during extreme rainfall events (largest 1-day and 5-day approximately 1.0°C (Figure 16, left).23 This trend cumulative precipitation), with a smaller increase in total annual precipitation, particularly in the low- 22 The climate projections are extracted from the results of the climate warming scenarios (Figure 17). An illustrative Coupled Model Intercomparison Project — phase 6 (CMIP6). They are available on the World Bank’s Climate Change Knowledge example is the SSP5-8.5 scenario which forecasts an Portal. Representative Concentration Pathways (RCPs) describe average increase of 13.5% in total precipitation by the different levels of greenhouse gases and other radiative forcings end of the century, from 1,018 mm to 1,156 mm. At that could occur in the future, ranging from 1.9 to 8.5 W/m2. On the other hand, the Shared Socioeconomic Pathways (SSPs) the same time, the maximum daily precipitation would are five projected scenarios of global socioeconomic changes increase by 49%, from 36 mm to 54 mm. These trends through 2100. They provide narratives describing alternative and plausible socioeconomic developments, including variables such of changes in precipitation are generally consistent as population, growth economic, education, urbanization, and rate among the different climate scenarios.24 of technological development. 23 This increase was estimated by regressing annual temperature of each year against an annual time trend , using the equation: 24 Climate change can be understood as a statistically significant , where is the intercept and the error. The coefficient is highly deviation from the natural variability of a given variable. In significant and is multiplied by the number of years in the sample the case of Nigeria, the median estimate of the SSP1-1.9 and to obtain the average trend in temperature change. SSP1-2.6 scenarios suggests a statistically significant increase 22 | Lessons Learned Exercise for EP&R in Nigeria Figure 16. Historical annual average temperature (left) and projected changes by SSP scenario (right) Source: Authors with data from the Climate Change Knowledge Portal. Figure 17. Projected changes in the means of the distributions of total annual precipitation (left) and largest 1-day precipitation (right) under different SSP scenarios Source: Authors with data from the Climate Change Knowledge Portal. If adaptation measures are not implemented, climate 100 years is equivalent to 99 mm (i.e., this is the change will exacerbate the risk of flooding and the precipitation level that has a 1% probability of being economic impacts of extreme precipitation, as climate exceeded each year). Yet, by 2085 under the SSP5- scenarios converge towards an increase in extreme 8.5 scenario, the level of maximum daily precipitation precipitation which is strongly correlated with currently exceeded once every 100 years is expected flooding. For example, the daily maximum precipitation to be exceeded on average every 12 years. This implies that currently occurs on average at least once every that the annual probability of having daily rainfall greater than 99 mm will increase from 1 to 8% by the end of the century (Figure 18). The empirical assessment in precipitation only in certain regions. Changes for other SSP scenarios are significant across the country. The results presented of the effect of rainfall on growth highlights how an correspond to the spatial average for the country. Yet, these abnormally high level of rainfall is associated with trends could be heterogeneous across different regions. 23 | Lessons Learned Exercise for EP&R in Nigeria Figure 18. Projected evolution of the annual probability of exceedance of maximum daily precipitation level at the end of the century under different SSP scenarios Extreme precipitation (99mm) Strong precipitation (89mm) Frequent precipitation (66mm) 5% 10% 15% 20% 25% 30% 35% 40% Annual exceedance probability x Today ● SSP1–1.9 ● SSP1–2.6 ● SSP2–4.5 ● SSP3–7.0 ● SSP5–8.5 Source: Authors with data from the Climate Change Knowledge Portal. Note: Frequent precipitation corresponds to a rainfall level (in mm) which has an annual probability of 10% of being exceeded, under current climatic conditions. Strong precipitation has an annual probability of exceedance of 2%, and extreme precipitation has a probability of 1%. a reduction in the country’s per capita GDP growth sufficient flood protection measures are established. (see subsection 2.2.1). Without measures to adapt to Projections indicate that rising sea levels could inundate these new trends, more frequent and/or more intense extensive areas of low-lying land, necessitating extreme precipitation could therefore have a direct and mass migrations and placing considerable strain on increasingly significant negative impact on Nigeria’s infrastructure and resources. As of 2025 in Nigeria, growth trajectory. 1.1 million people were exposed to a 1-in-100 coastal flood. By 2080, this number could rise to between 1.7 3.3. Sea level rise will increase coastal flood risk in urban areas and 2.2 million people, depending on the climate SSP scenario considered. This only accounts for sea level With an extensive coastline of over 850 km, coastal rise and not the demographic and urbanization process flooding is a critical risk in Nigeria. The combination of the country will experience. seasonal heavy rainfall, rising sea levels, storm surges, and coastal erosion significantly increases the likelihood A compelling example of coastal risk is Lagos, the of coastal flooding, which overwhelm drainage systems largest coastal city in Nigeria. An assessment of and inundate low-lying areas leading to severe flooding, property damage, and loss of life. These risks are extreme coastal flood exposure was conducted for the intensified by climate change, population growth and city, evaluating the potential impacts of sea level rise high population density, rapid urbanization, informal by 2080 on an increased exposure to coastal flooding settlements, poor urban planning, and industrial (Figure 19). As of 2025, 1.1% of Lagos’ population is activities. The Lagos, Rivers, Bayelsa, and Delta States exposed to coastal flooding.25 However, by 2080, this are particularly at risk due to their large populations exposure could increase to 2.8% due to sea level rise and critical infrastructure located in flood-prone zones. under an intermediate emissions scenario (SSP2-4.5), Notably, 90% of the population exposed to coastal and to 3.6% under a high emissions scenario (SSP5- flooding resides in these States. 8.5). It is important to note that these projections do not account for the anticipated growth in population. The increase in sea levels significantly heightens the risk of coastal flooding, presenting a severe and 25 Defined as areas that have an annual probability of 1% of being potentially lasting threat to low-lying regions unless flooded. 24 | Lessons Learned Exercise for EP&R in Nigeria Figure 19. Exposure to coastal flooding in Lagos in 2020 and 2080 under a high emissions scenario Source: Authors with data from Fathom 3. Coastal erosion and environmental degradation The population concentrates in four city clusters: further exacerbate coastal risks, driven by both natural Kano, the Lagos–Ibadan corridor and surrounding area, processes and human activities such as sand mining, around Port Harcourt, and from Abuja to Jos. Lagos, deforestation, and unregulated coastal development. the largest megacity, has about 17 million people. Coastal populations and ecosystems face significant There are 15 metropolitan areas with over 1 million risks due to the degradation of mangrove ecosystems, people, 25 large cities (500,000 to 1 million people), which increases the exposure to storm surges and tidal 19 medium-sized cities (300,000 to 500,000 people), flooding. Additionally, saline intrusion into agricultural along with hundreds of smaller towns (Figure 21). lands reduces crop yields, threatening food supply Urban populations are growing at all levels across the in affected regions. The Niger Delta—home to a country: from the large metropolitan cities to State significant portion of Nigeria’s oil reserves—is heavily capitals and smaller secondary and tertiary cities impacted by oil spills and industrial pollution, leading to contamination of water sources and adverse effects Figure 20. Evolution of urban and rural population on marine life. 3.4. Demographic and urbanization trends will shape future disaster and climate risks Urban settlements in Nigeria are currently home to an estimated 130 million people, about half of the total population. The pace of urbanization has been rapid, with urbanization rates surging from 30% in 1990 to 56% in 2025, surpassing the Sub-Saharan Africa average of 44%. Over the past decade, the urban population has experienced a notable average annual growth rate of 4.2%. It is expected that this trend will persist, with median projections indicating about 264 Source: Authors based on UN DESA (2018, 2022). million urban dwellers by 2050. In contrast, the rural Notes: Median projections are shown by the dashed lines. Shaded population has nearly reached its peak (Figure 20). areas show the 80% and 95% prediction intervals. 25 | Lessons Learned Exercise for EP&R in Nigeria Figure 21. Urban population by settlement size of the urban population has been accompanied by both the intensification of development in already existing built-up areas, and by the appearance of new suburban development and the progressive absorption of adjacent, formerly peri-urban, settlements. This urban expansion, driven by urban population growth, is expected to continue and likely accelerate in coming decades (World Bank, 2016). The urbanization trends occurring in Nigeria will shape future disaster and climate risk. On the one hand, the rural population is not expected to decrease in the coming decades, as urbanization is mainly driven by population growth. This suggests that ceteris paribus, the rural exposure base to disasters will not Source: Authors based on UN DESA (2018, 2022). change significantly—although hazard conditions and vulnerability will evolve due to climate change and (World Bank, 2016). By 2035, Nigeria is projected to structural transformation. On the other hand, urban account for 24% of the population living in cities with risk will evolve significantly as cities expand and over 1 million inhabitants across Sub-Saharan Africa. densify. As urban exposure will undoubtedly increase, risk reduction policies will be critical to reduce A noticeable trend in Nigeria’s urbanization is the vulnerabilities and alleviate the impacts of climate accelerated spatial expansion of cities. The growth change. 26 | Lessons Learned Exercise for EP&R in Nigeria Lagos, Nigeria: Rainy season. Photo: it:peeterv. 27 | Lessons Learned Exercise for EP&R in Nigeria 4 Policy options to strengthen fiscal resilience to weather-related shocks T his report examines the challenges that weather- within the FMoF (such as the CL&RAM Unit). This unit related disasters pose to Nigeria’s macro-fiscal would be responsible for delimitating and quantifying position. It provides a first assessment of the these impacts and ensuring their disclosure in binding economic impacts of droughts and floods, focusing on fiscal statements—such as the Fiscal Risk Statement three key dimensions: (i) damage to physical assets, (ii) annexed to the national budget or the Medium-Term growth impacts, and (iii) household-level impacts. The Expenditure Framework. Strengthening the capacity of study then describes how these impacts put pressure the FMoF to quantify, monitor, and manage weather- on the public finances and constitute a considerable related contingent liabilities is the first step to enhance source of fiscal risk. Based on these findings and Nigeria’s ability to anticipate and mitigate the fiscal drawing upon the best international practices in the risks associated with weather-related shocks. management of fiscal risks associated with weather- related shocks, a set of policy options are outlined Develop a framework to articulate the financing of below to be further refined through stakeholder weather-related contingent liabilities between the consultations, additional analysis as proposed above, Federal and State level. In a federal system, fiscal and policy engagement with competent authorities. responsibilities are shared between the Federal and These policy options are summarized in Table 4. These State Governments. However, in Nigeria, the specific measures aim to strengthen fiscal resilience, enhance arrangements to share the financing of weather-related disaster preparedness and response mechanisms, and contingent liabilities are not clearly delineated in legally foster long-term resilience to climate and disaster risks. binding documents, which creates two major issues. First, it might generate a situation of moral hazard in Strengthen the institutional framework for fiscal which States have no interest in protecting themselves risk management to incorporate weather-related against risk since they expect the Federal government fiscal risks within the broader fiscal risk management to assume a large part of the losses, even though framework. While Nigeria’s 2024–2026 Medium- there is no formal commitment to do so. Second, this Term Expenditure Framework recognizes disasters as uncertainty favors ad-hoc arrangements and arbitrary potential risks to the country’s medium-term outlook, decisions in the potential transfer of resources between it does not clarify the Government’s responsibility regarding contingent liabilities associated with different levels of government, which in turn hampers weather-related events, nor does it provide a a quick and efficient public financial management of quantitative assessment of these risks. Quantifying post-disaster expenditures. To address this, Nigeria disaster-related contingent liabilities is essential could start by establishing legal provisions and financial for adequately improving the budgetary capacity arrangements to clarify how disaster-related expenses to respond to weather-related events. However, are shared between levels of government. These from an institutional point of view, it seems that no arrangements should rule how the Federal government specific Ministry, Department, or Agency is explicitly provides financial assistance to the States for disaster tasked with the management of weather-related fiscal relief. Inspired by the experience of other federal risks. A Contingent Liability & Risk Asset Management countries highly exposed to disaster risk (e.g., Mexico, (CL&RAM) Unit under the Debt Management Office see Box 3), Nigeria could (i) determine eligibility for was established in 2018 but it does not seem to deal federal support through objective trigger mechanisms with weather-related contingent liabilities. Following for accessing federal funds (e.g., declaration of a state best international practices, Nigeria could begin by of emergency) and (ii) outline predefined rules for explicitly assigning this competency to a “risk unit” resource allocation between Federal and State levels. 28 | Lessons Learned Exercise for EP&R in Nigeria Box 3. Mexico: An integrated financial protection strategy against disasters and climate risks To protect the federal budget, the Mexican federal government had established a strong institutional framework around the now-defunct Natural Disaster Fund (FONDEN). This fund developed a layered financial risk management strategy that aimed to achieve a threefold goal: retain risk in an efficient way, optimize risk transfer, and incentivize states to enhance their disaster preparedness measures. › Efficient risk retention: An annual budget provision of at least 0.4% of programmable spending each year was allocated to the FONDEN. These resources could be capitalized beyond the annual budget cycle and, more importantly, the FONDEN operational manual provided clear rules to ensure the efficient and transparent execution of post-disaster funds. Two elements in FONDEN’s operational manual are worth highlighting: (i) rule-based allocation of funds (i.e., funds are allocated based on an independent assessment of damage), which significantly reduced discretionary power in the use of FONDEN resources; and (ii) pre-agreed procurement contracts with registered official providers enabled a predictable and swift response for some of the emergency measures and goods that were recurrently needed in the aftermath of a disaster. › Leveraging transfer risk: FONDEN developed a comprehensive program aimed at transferring disaster risk through (i) indemnity-based reinsurance (to cover public buildings and infrastructure) and (ii) catastrophe bonds. Mexico was in fact the first sovereign to issue a parametric catastrophe bond in 2006 to cover earthquakes in three specific zones. Under the bond’s terms, investors receive principal and interest payments unless an event triggers the transfer of principal amounts to the government. This trigger is based on the physical characteristics of the natural hazards considered (i.e., wind speed for cyclones, magnitude for earthquake) as measured by an independent third party. Subsequent bonds have included more natural hazards and different regions of the country. In 2018, Mexico partnered with Chile, Peru, and Colombia to issue a parametric catastrophe bond, obtaining more than a billion dollars in coverage. › Incentivize disaster preparedness at the state level: A cost-sharing mechanism was designed whereby FONDEN covered 100% of the reconstruction costs for federal assets and 50% for local assets during the first disaster event. However, if local governments did not purchase insurance after receiving financial support through FONDEN, their share of reconstruction costs increased in subsequent events. Likewise, states were required to conduct and submit risk assessments to become eligible for risk mitigation financing through the FOPREDEN Program for Natural Disaster Prevention. These measures collectively encouraged Mexican states to adopt proactive disaster risk management practices while offering fiscal support in case of severe shocks, thereby enhancing their resilience against disasters. Promote rules-based mechanisms to increase financial support mechanisms from the Federal efficiency and transparency in post-disaster resources government could be designed to incentivize stronger allocation and execution. Until now, the Ecological preparedness actions at the State level. For instance, Fund has served as the primary financial resource for State Emergency Management Agencies could oversee flood response efforts, yet its efficiency, transparency, channeling disaster relief fund requests to the Fund and alignment with the Emergency Preparedness through a pre-established damage assessment format and Response system could be further improved. to foster greater coordination and efficiency in disaster Establishing a clear legal framework for requesting, response financing. approving, disbursing, and executing Fund resources in the aftermath of a weather-related shock would Expand risk financing instruments and consolidate enhance efficiency and transparency. Clearly defining them within an integrated risk-layered approach to the criteria for financial support through the Fund— help smooth the fiscal impacts of weather-related including guidelines for funding allocated relative to shocks. This approach involves strategically combining damage estimates and the timeline for disbursement— risk retention and risk transfer instruments in a cost- would allow for a more effective disaster response and efficient manner, tailored to the frequency and severity recovery process, while helping clarify the dynamics of weather-related events it aims to address. The of Federal-State support in disaster risk financing strategy allocates risk retention instruments to manage mentioned in the previous paragraph. Additionally, frequent, low-intensity events, while risk transfer 29 | Lessons Learned Exercise for EP&R in Nigeria Table 4. Summary of policy options to strengthen fiscal resilience against weather-related shocks Policy options Timeline Strengthen the institutional and policy framework for fiscal risk management to incorporate weather-related fiscal risks within the broader fiscal risk management framework. Responsibility: Federal Ministry of Finance (FMoF), Debt Management Office, Federal Ministry of Budget and Economic Planning (FMBEP - Budget office) Incorporate weather-related fiscal risks as part of the overall fiscal risk management framework. Short term Establish or identify a unit/department with the mandate of managing contingent liabilities and explicitly Short term include those associated with disaster and climate risks. Delineate explicit and implicit contingent liabilities associated with weather-related risks at the Federal level Medium and at the State level. term Include a quantified assessment of weather-related risks in the Fiscal Risk Statement or the Medium-Term Medium Expenditure Framework or any fiscal policy document. term Develop a framework to articulate the financing of weather-related contingent liabilities between the Federal and State level. Responsibility: FMoF, FMBEP, Nigeria Governors Forum, National/State Emergency Management Agencies Assess and establish legal provisions to clarify how weather-related expenses are shared between the Short term different levels of government. Promote pre-arranged mechanisms to channel financial assistance for disaster relief from the Federal level to Medium the States and local governments, including potential incentives to promote stronger preparedness actions at term the State and local levels. Promote rules-based mechanisms to increase efficiency and transparency in post-disaster resources allocation and execution. Responsibility: FMoF, FMBEP, Ecological Fund office Conduct an in-depth review of the functioning of the Ecological Fund in the aftermath of weather-related Short term shocks to get a better understanding of its potential areas of improvement. Establish a clear legal framework for requesting, approving, disbursing, and executing public resources in the Medium aftermath of a weather-related shock. term Expand risk financing instruments and consolidate them within an integrated risk-layered approach to help smooth the fiscal impacts of weather-related shocks. Responsibility: FMoF, National Insurance Commission (NAICOM), Nigerian Agriculture Insurance Corp. (NAIC) Bring together existing and potential risk financing instruments under an integrated and strategic vision, Medium considering the wider macroeconomic conditions. term Conduct funding gaps analysis and assess diverse risk-financing options, including market-based instruments, Medium to increase coverage against disaster risk. term 30 | Lessons Learned Exercise for EP&R in Nigeria instruments are employed to deal with less frequent, Bonds or Cat-Swaps. Bringing existing and potential catastrophic events.26 Risk retention instruments instruments together under a strategic vision helps typically correspond to budget contingent lines and decide on the right combination of instruments and budgetary reallocation, emergency funds (e.g., the highlights potential funding gaps for future shocks. Ecological Fund in Nigeria), and contingent credit The combination of instruments under such a strategy lines such as the Catastrophe Deferred Drawdown must be tailored to the risk aversion of the government Option (Cat DDO) offered by the World Bank. Risk and the broader macroeconomic context. Importantly, transfer instruments refer to traditional insurance these instruments must be carefully designed and or other market-based instruments such as Cat- combined to avoid inefficiencies. For instance, the government has introduced multiple policy documents 26 A cost-efficient mix of instruments seeks to first use the cheaper funding sources, reserving the most expensive instruments for proposing additional funds alongside the Ecological exceptional circumstances. Risk transfer instruments have a direct Fund, such as the Climate Change Fund and the Flood cost to public finances (e.g., risk premiums for insurance) but they can spread the financial burden of shocks across years and budget Fund, mentioned under the Climate Change Act and exercises. On the other hand, risk retention instruments do not the 2021 National Flood Emergency Preparedness imply an upfront payment, though they come with opportunity costs as they entail forgoing alternative public investments. While and Response Plan, respectively. Without a clear insurance offers adequate protection against extreme events, it coordination framework, these efforts might produce becomes prohibitively expensive when applied to frequent, low- intensity events. Therefore, retaining the lowest layer of risk fragmentation, duplication, or inefficiency in the fiscal through risk retention instruments is a more suitable approach. response to disasters. References 31 | Lessons Learned Exercise for EP&R in Nigeria References Bih, K. B., Desjonqueres, C. G. H., Jafino, B. A., Blanc, Resilience of the Poor in the Face of Natural Disasters. E., & Masson, S. 2024. Impacts of Disasters in Conflict Climate Change and Development. World Bank. Settings: Evidence from Mozambique and Nigeria (No. Hallegatte, S., & Vogt-Schilb, A. 2019. Are losses from 10995). The World Bank. natural disasters more than just asset losses? The Bündnis Entwicklung Hilft. Ruhr University Bochum role of capital aggregation, sector interactions, and – Institute for International Law of Peace and Armed investment behaviors. In: Okuyama Y., Rose A. (eds) Conflict (IFHV). 2023: WorldRiskReport 2023. Focus: Advances in Spatial and Economic Modeling of Disaster Diversity. Berlin. Impacts. Cebotari, A., Davis, J., Lusinyan, L., Mati, A., Mauro, Hsiang, S., & Jina, A. 2014. The causal effect of P., Petrie, M., & Velloso, R. 2009. Fiscal risks: Sources, environmental catastrophe on long-run economic disclosure, and management. International Monetary growth: Evidence from 6,700 cyclones (No. w20352). Fund. National Bureau of Economic Research. Centre for Research on the Epidemiology of Disasters Intergovernmental Panel on Climate Change (IPCC). (CRED). 2025. EM-DAT: The international disaster 2012. Managing the Risks of Extreme Events and database. Université Catholique de Louvain. Disasters to Advance Climate Change Adaptation: Croitoru, L., Miranda, J. J., Khattabi, A., & Lee, J. J. 2020. Special Report of the Intergovernmental Panel The Cost of Coastal Zone Degradation in Nigeria: Cross on Climate Change, Cambridge University Press, River, Delta and Lagos States. World Bank. Cambridge UK, and New York, NY, USA. Dar. 2019. Integrated Flood Risk Management and International Monetary Fund (IMF). 2012. Fiscal Drainage Masterplan for Ibadan City. Report Volume Transparency, Accountability, and Risk. Washington 1/3: Main Report. D.C. Dell, M., Jones, B., & Olken, B. 2014. What Do We International Monetary Fund (IMF). 2016. Analyzing Learn from the Weather? The New Climate–Economy and Managing Fiscal Risks: Best Practices. Washington Literature. Journal of Economic Literature, 52(3), 740 – D.C. 798. International Monetary Fund (IMF). 2023. 2022 Article Felbermayr, G., & Gröschl, J. 2014. Naturally negative: IV Consultation—Press Release; Staff Report; Staff The growth effects of natural disasters. Journal of Statement; and Statement by the Executive Director development economics, 111, 92-106. for Nigeria. February 2023. IMF Country Report No. 23/93. Gascoigne, J., Baquie, S., Vinha, K., Skoufias, E., Calcutt, E., Kshirsagar, V., Meenan, C., & Hill, R. 2024. InsuResilience. 2021. CLIMADA Climate Risk Analysis. The Welfare Cost of Drought in Sub-Saharan Africa. Urban flood resilience against riverine floods in Uganda Available at SSRN 4839472. and Nigeria. June 2021. InsuResilience Solutions Fund. Giannini, A., Saravanan, R., & Chang, P. 2003. Oceanic Miller, D. L. 2023. An Introductory Guide to Event Forcing of Sahel Rainfall on Interannual to Interdecadal Study Models. Journal of Economic Perspectives 37 (2): Time Scales. Science, vol. 302, pp. 1027-1030, 2003. 203–30.DOI: 10.1257/jep.37.2.203 Government of Nigeria. 2013. Nigeria: Post-Disaster Strobl, E. 2011. The economic growth impact of Needs Assessment. 2012 Floods. June 2013. hurricanes: Evidence from US coastal counties. Review of Economics and Statistics, 93(2), 575-589. Hallegatte, S., Vogt-Schilb, A., Bangalore, M., & Rozenberg, J. 2017. Unbreakable: Building the 32 | Lessons Learned Exercise for EP&R in Nigeria United Nations, Department of Economic and Social World Bank. 2016. From Oil to Cities: Nigeria’s Affairs (UN DESA), Population Division. 2018. World Next Transformation. Directions in Development. Urbanization Prospects: The 2018 Revision. Washington, DC: World Bank. doi:10.1596/978-1- United Nations, Department of Economic and Social 4648-0792-3. World Bank. 2022a. GRADE Note on Affairs (UN DESA), Population Division. 2022. World the June-November 2022 Nigeria Floods. November Population Prospects 2022. 2022. United Nations Office for Disaster Risk Reduction World Bank. 2022b. Living on the water’s edge. Flood (UNDRR). 2017. The Global Assessment Report risk and resilience of coastal cities in Sub-Saharan on Disaster Risk Reduction. Atlas. Unveiling Global Africa. Disaster Risk. World Bank. 2023. Nigeria Development Update: World Bank. 2014. Project Appraisal Document on a Seizing the Opportunity (English). June 2023. Proposed Credit in the Amount of SDR 129.1 Million Washington, D.C. World Bank Group. (US$ 200 Million Equivalent) to the Federal Republic Yang, D. 2008. Coping with disaster: The impact of of Nigeria for the Ibadan Flood Management Project. hurricanes on international financial flows, 1970-2002. The BE Journal of Economic Analysis & Policy, 8(1). Annex A 33 | Lessons Learned Exercise for EP&R in Nigeria Subnational distribution of flood impact and flood exposure T he 2012 floods were marked by significant and losses suffered due to the 2012 floods (left) and damages and losses concentrated in 12 States, damages due to the 2022 floods (right) by State based with a major portion shouldered by just three on the PDNA and GRADE reports. Per capita estimates States: Bayelsa, Rivers, and Anambra. In contrast, are presented in Figure 23. While it is important damage from the 2022 floods was widespread to note that the methodologies employed and the across the country. Figure 22 illustrates the damages outcomes are not directly comparable, the side-by- Figure 22. Spatial distribution of damages and losses due to the 2012 floods (left) and damages due to the 2022 floods (right) Source: Authors based on the 2012 PDNA (Government of Nigeria, 2013) and 2022 GRADE (World Bank, 2022a). Figure 23. Per capita spatial distribution of damages and losses due to the 2012 floods (left) and damages due to the 2022 floods (right) Source: Authors based on the 2012 PDNA (Government of Nigeria, 2013) and 2022 GRADE (World Bank, 2022a). 34 | Lessons Learned Exercise for EP&R in Nigeria Figure 24. Breakdown of the cost by State due to the 2012 and 2022 floods 2012 2022 Taraba Rivers Cross River Yobe Delta Imo Bayelsa Adamawa Jigawa Kebbi Borno Kogi Benue Niger Lagos Anambra Akwa Ibom Sokoto Ebonyi Zamfara Kwara Kano Katsina Bauchi Edo Ondo Nasarawa 3,000 2,000 1,000 0 500 100 200 300 400 500 Damages (blue) and Losses (orange) Damages (Million US$) (Million US$) Source: Authors based on the 2012 PDNA (Government of Nigeria, 2013) and 2022 GRADE (World Bank, 2022a). Note: States not depicted in the illustration experienced relatively fewer damages and losses. Note that there is a difference in scale between the two mentioned years. side visualization underscores the complex dynamics Figure 25 illustrates the building area exposed to of flood events from a spatial standpoint and the floods, both in absolute terms and as percentage of potential for extensive flooding across the country. An the State building area. When combined with historical alternative representation of this data is presented in data, these results emphasize that the southern and Figure 24. northeastern States are the areas deserving increased attention. Figure 25 (left) shows that southern States The 2012 and 2022 events provide two distinct have a greater amount of building floor area exposed snapshots of the spatial distribution of damage, but to floods in absolute terms compared to the northern they are not fully representative of the potential regions. This outcome is somewhat expected, given spatial distribution of future floods. A proper risk that a significant portion of the overall building floor assessment requires among others a high-resolution area is also situated in these States, as shown in hydrological model to simulate surface runoff based Figure 26 (left). A notable exception is Bayelsa, a State on precipitation, and vulnerability curves to associate a with a low number of buildings and small population level of flooding with a monetary estimate of damages, yet largely exposed to floods, as confirmed by the which were not available for Nigeria. To deepen the substantial damage it sustained in 2012 and 2022. understanding of the spatial distribution of floods, we rely instead on a spatial overlay of flood hazard maps water depth exceeding 30 cm during a 1-in-100-year flood event with high-resolution building footprint exposure data (which represents a flood that has a 1% chance of occurring in to identify the building area by State that is located in any given year). The following data was used for the overlay: (i) a flood-prone area.27 Fathom hazard maps for fluvial and pluvial floods with a return period of 100 years; (ii) Google’s Open Buildings, which provides high-resolution building footprints for the country; (iii) GADM 27 A building is classified as exposed to floods, or located in a flood- for information of the country’s administrative divisions; and (iv) prone area, when the area it occupies is projected to experience a Africapolis, which provides a delineation of city extents. 35 | Lessons Learned Exercise for EP&R in Nigeria To address the variability in exposure across different Bayelsa (62%), Delta (23%), Jigawa (17%), and Rivers regions, the building floor area exposed to floods is (15%). Each of these States experienced significant normalized by the overall building floor area in the State damage in either 2012 or 2022. The building floor area and presented in Figure 25 (right). At the national level, exposed to floods of each State was also normalized 6.4% of built-up is located in flood-prone areas, but by the national total building floor area in flood-prone this is distributed heterogeneously across States. The zones and presented in Figure 26 (right) which shows a States with the highest relative exposure to floods are similar spatial distribution as the one above described. Figure 25. Building floor area exposed to floods in absolute value (left) and as percentage of State building area (right) Source: Authors based on the Fathom and Google’s Open Buildings datasets. Figure 26. Building floor area by State (left) and Building floor area exposed to floods of the State as percentage of national total (right) Source: Authors based on the Fathom and Google’s Open Buildings datasets. Annex B 36 | Lessons Learned Exercise for EP&R in Nigeria Historical flood exposure trends From a temporal perspective, on a national scale, the and enforceable flood zoning planning, particularly in growth of built-up in flood-prone areas follows a trend urban settings, to mitigate the potential future impact similar to that in safe areas (Figure 27). The historical of urban growth.28 growth patterns of built-up in flood-prone areas and safe areas were assessed by overlaying the GHSL2023 28 A region is classified as flood-prone if the projected water depth built-up surface settlement and Fathom datasets. A during a 1-in-100-year flood event exceeds 30 cm; otherwise, further urban-rural disaggregation shows that at the it is classified as safe. The following data was used to compute urban level, the expansion of built-up areas has had a the estimates presented: (i) Fathom hazard maps for fluvial and pluvial floods with a 100-year return period; (ii) the GHSL built- similar trajectory in both flood-prone and safe regions. up surface dataset, providing built-up area estimates at a 100m However, at the rural level, growth in safe areas has resolution between 1975 and 2020; and (iii) GHS-SMOD which classifies built-up in urban and rural. It is important to note that marginally outpaced growth in flood-prone regions. the model has its limitations, with one significant constraint being This observation highlights the need for comprehensive the absence of data regarding flood defense infrastructure. Figure 27. Annual growth rates of built-up in safe areas vs flood-prone areas Urban Rural 5% 4% Built-up growth (%) 3% 2% 1% 0% 1980 1990 2000 2010 2020 1980 1990 2000 2010 2020 Built-up growth in safe areas Built-up growth in flood-prone areas Source: Authors based on the GHSL and Fathom datasets. " % () " #$" % () () = ! ⋅ #$" ! −+ , ! ⋅ ! = ! ⋅ +1 − , ! ! Annex C 37 | Lessons Learned Exercise for EP&R in Nigeria " ! ≝ ! ⋅ #$" ! Δ() =to Summary of the methodology model () − ! the impact of floods on GDP = growth ! ⋅ +1 − % () , − ! ! The framework developed by Hallegatte and Vogt- = − ⋅ of damaged % () capital. If K0 denotes the initial capital Schilb (2019) is the departure point to calibrate a stock (in the absence Where = ! /! denotes the average of disaster damage), the initial produ model to quantify the growth impact of the potential labor (assumed unaffected by disasters), and Ka(t) is capital stock damage due to a flood. A Cobb-Douglas the amount of affected capital that cannot produce due production function with two factors capital and labor to a disaster, then production Y at time t is given by: * () &'() (t) = is adjusted to include a variable that tracks the amount ⋅ ⋅ 4! − * ()5 % () ! % () " () = ! ⋅ #$" − + ! % () " , ! ⋅ #$" ! = ! ⋅ +1 −() , % () " #$" () ()= " ⋅ #$" − + , ! " ⋅ #$" = ⋅ +1 − % , ! - % ! ! ! ! ! #$" −+ , ! ⋅ ! = ! ⋅ +1 − , ! ! ! ! ! = − 9 ⋅ % () ⋅ $+, ! Where in the absence of a disaster, production in time t and an amount Ka(t) of capital is affected and t = 0 is denoted ! ≝ ! " ⋅ #$" ! . If a flood strikes in cannot produce, the change in output Δ() is: Δ() = () − ! Δ() = () − ! % () ) = () − ! %− = ! ⋅ +1 () , − ! % () = ! ⋅ +1 − ,− ! ! = ! ⋅ +1 − , − ! = − ⋅ % () ! ! = − ⋅ % () = − ⋅ % () Where = ! /! denotes the average produ Where = ! /! denotes the average Where productivity of the average These indirect produ effects can be significant and = ! /! denotes /! denotes the average produ capital before the disaster. Under the three-factor Cobb- differentiated depending on the event and country Douglas function, output is reduced proportionally * () to context. Specifically, certain types of infrastructure &'() (t) =() ⋅ ⋅ 3! − * ()4 (transportation systems, communication networks, the average (not marginal) productivity of* capital. This− ()4 &'() (t) = ⋅ () ! ⋅ 3 ! * energy grids, etc.) are necessary for non-infrastructure ⋅ ⋅ 4! − * ()5 aligns with the hypothesis that large floods ! are likely to ! capital (machinery- and equipment) to be used evenly affect the different categories of capital, so that () % effectively. For -instance, % () $+, bridge can make a destroyed the economic value of - the destroyed ()capital = ! " is⋅ #$" better ! −+ , !" ⋅ #$" ! ==− 8 ⋅ ! ⋅ +1 − % () ⋅ , some ! of the =− unaffected roads 8 ⋅!% () useless ⋅ $+, ! for some people, through captured =− 9 average the ⋅ $+, of capital, productivity ⋅ % () the same way ! a destroyed power station can make rather than marginal ! (which would be the case had the distribution lines useless and reduce the productivity destroyed capital been the least productive capital in of (directly) unaffected business and assets. To model the economy). Similarly, this implies that instant and these negative externalities, the affected capital Ka(t) costless reallocation of the unaffected capital to where is decomposed as the sum of damaged capital Ka(t) it is most productive is impossible. Δ() = () − ! (directly affected by the disaster), and inoperative % () capital !"#$ () (which is left unproductive as it Catastrophes have a direct impact on economic = ! ⋅ +1 − , − relies ! on ! the damaged capital), so the growth through the reduction of capital stock. Yet, = − ⋅ %! () = " () + #$%& () . It is further assumed () reduced capital stock has an indirect effect with the that the inoperative capital is proportional to the Where = ! /! denotes the average produ occurrence of ripple effects that reduce the fraction of capital damaged by the disaster (! ()/" ) productivity of capital that was not directly affected. and corresponds to: * () &'() (t) = ⋅ ⋅ 3! − * ()4 ! - = − 8 ⋅ % () ⋅ $+, ! 38 | LessonsΔ() Learned () −for =Exercise EP&R in Nigeria ! % () = ! ⋅ +1 − , − ! ! = − ⋅ % () Where ! − " () is the amount of capital that Damaged capital ! () is assumed to reduce to zero Where = ! / remains undamaged by denotes ! the the average produ disaster and β is a constant. exponentially, so that about 95% of the reconstruction has been achieved after a reconstruction time N of Finally, it is assumed that the damaged capital is years: ! () = ! (0) ⋅ "#$/& . Further assuming a * () repaired over &'() time, enabling (t) = the ⋅ ⋅ 3!−analysis * ()4 of economic discounting rate ρ, the Net Present Value (NPV) of the ! activity dynamics due to the decrease in capital. output losses is given by: - = − 8 ⋅ % () ⋅ $+, ! The model is calibrated as follows: Damaged capital For a flood of a given magnitude, reconstruction time is directly retrieved based on the results from UNDRR is calibrated as the ratio between asset damage and (2017) for different return periods.29 The average pro- annual expenditure dedicated to post-disaster recon- ductivity of capital μ is retrieved from the World Penn struction. Tables v10.01 and equals in 2019. Total capital stock ! is computed based on the average productivity There is significant uncertainty associated with the of capital and GDP, which is retrieved from the World estimated metrics, as they are obtained through a Bank’s World Development Indicators. Calibrating the simplified framework with important limitations. parameter β is challenging as it is highly event depen- The model focuses on a simple production function dent. A conservative approach is thus taken and a value and does not account for many dimensions of the of β = 0.2 is chosen. This implies that if 5% of the total economy. A more comprehensive model such as a capital is directly damaged by a disaster, then 1% of the structural or general equilibrium model would better remaining capital (! − " ) cannot produce. The dis- represent potential GDP growth reduction to asset counting rate is set to a standard value of 6%. Finally, damages. Indeed, the production function is generally limited fiscal resilience is assumed so that the Govern- one component of these models. Yet, this simple ment can only mobilize 2% of the general government framework provides a first order of magnitude estimate total expenditure (retrieved from IMF’s WEO) annually of the potential economic losses due to floods. It is to finance the reconstruction of the damaged assets. important to highlight that the model only seeks to quantify output losses because of asset damage, and 29 Floods can affect private and public assets, with the magnitude and distribution of the private-public split of damages being the impacts to human capital, labor productivity, and event-dependent and highly uncertain. Given that disaster-related natural capital are not included in this assessment contingent liabilities have not yet been quantified, it is assumed that the government is fully responsible of financing the costs although they could have significant effects on growth associated with asset damages. and are relevant for future research. Flooded Maiduguri, capital of Borno State. Photo: Sadiqnanic