Chapter 1. Understanding the economic and fiscal impacts of disasters

Inverse relation of disaster impacts to income

The aggregate impact of disasters on economic growth is complex to measure and depends on a number of factors. Concerning aggregate growth, most studies find a negative relationship between the occurrence of disasters and economic growth in the medium to long run. For example, von Peter, von Dahlen and Saxena (2012), using data from Munich Re’s NatCat Service for 2,476 major natural catastrophes since 1960, found that the average disaster leads to a fall in growth of 1% of gross domestic product (GDP) upon impact and a cumulative loss to GDP of 2.6%. In another study, Felbermayr and Gröschl (2014) found that disasters can reduce per capita GDP by up to 6.8% on impact.

Disaster impacts are inversely related to income and an economy’s size. Organisation for Economic Co-operation and Development (OECD) economies with lower GDP per capita suffer relatively more fatalities, while those with higher GDP per capita experience larger absolute costs but lower costs as a percentage of GDP, reducing their relative economic impact (Figure 1.2). Among OECD economies, the United States, Japan and Italy have been most affected by large-scale disasters over the past 40 years, while Iceland, New Zealand and Australia are among those most affected relative to population size (OECD, 2014). Recent disasters in smaller OECD economies have had a large economic impact: damages and losses from the Chile earthquake in 2010 were around 18% of GDP, and from the Canterbury earthquakes in 2010 and 2011 were approximately 20% of New Zealand GDP.

The regional economic impact can be large and long-lasting (OECD, 2014). Hurricane Katrina, for example, caused an estimated USD 96 billion to USD 108 billion in economic losses, which were felt disproportionately by the impacted geographic area, its population and related economic activities. The impact on the national level, however, was only 0.1% of GDP (OECD, 2014). Hurricanes Harvey and Irma, which hit the United States in 2017, exceed that level of losses. The Great East Japan Earthquake destroyed or damaged 190 000 buildings, left the surrounding areas of the Fukushima nuclear plant (around 800 km²) uninhabitable and ruined 23 600 hectares of farmland (Ranghieri and Ishiwatari, 2014). The Pisco earthquake in 2007 resulted in USD 1.2 billion in economic losses, which equates to a slim 0.001% of Peru’s GDP, but it left the affected area devastated (EM-DAT, 2017).

Costly disasters – ranging from earthquakes to floods, wild fires and severe storms – have occurred in all of the case study economies in the last six years (Table 1.1), with damages worth several billions of US dollars. Generally speaking, storms accounted for nearly 30% of all disaster events over the past 40 years; but average damages from earthquakes were more than four times higher than those from storms, and average damages from droughts were around twice as high. Floods are the second-most frequent source of disasters, and the damages caused by floods are growing particularly rapidly in fast-urbanising areas (OECD, 2014).

Figure 1.2. Death toll and damages in OECD countries by income quartile, 1995–2010

Note: Data on the European heat wave of 2003 are not included due to the difficulty of determining the actual causes of death during this disaster.

Source: OECD, 2014.

Past economic damage figures provide important information on disaster trends and (indirectly) on the potential need for governments’ financial assistance. However, given the rapidly changing factors that are driving damage potential, estimates of future expected damages and their implications for government assistance are equally important; they help governments avoid underestimating and take worst-case scenarios into account. While there is a high degree of uncertainty concerning future trends in disaster exposure, several forces have been identified as drivers. Apart from socio-economic development (OECD, 2014), climate change is expected to affect the frequency and severity of extreme weather events (UNFCCC, 2012; World Bank Group, 2012; World Bank Group, 2014; Wolfrom and Yokoi-Arai, 2016). As a result, there is a need to refine deterministic analyses and interpretations of historical disaster events as well as available retrospective data, which tend to under-report low-frequency but high-impact events.

While this report is concerned with disasters caused by natural hazards, many of the approaches discussed could provide a basis for looking at contingent liabilities associated with man-made, technological or health hazards and their fiscal impact if these materialise.

Data on the estimates of past economic damage caused by (especially larger-scale) disasters can be found relatively easily, although the degree of comprehensiveness and accuracy varies (OECD, 2018). Significantly fewer sources and less systematic accounts can be found on disasters’ fiscal impact, i.e. the impact on government revenues and spending and related fiscal indicators, which is crucial information for governments’ identification of their contingent liabilities and adequate financial planning for disasters as part of public financial frameworks. The next section sheds light on this issue and provides evidence found through case studies.

The determinants of fiscal impacts of disasters

The fiscal impact of a disaster is a function of the changes in government expenditures and revenues caused by the disaster. Future potential expenditures that governments are expected to or legally obliged to make in response to disasters – that is, disaster-related contingent liabilities of government, can cause potential disaster-related fiscal risks (Box 1.2). Once a disaster event occurs, contingent liabilities turn into actual expenditures. Particularly in case of a major disaster, the expenditures resulting from such liabilities may cause deviations from the forecast fiscal outcomes. As a consequence, such expenditures could lead to an increase in public debt and, depending on their size, create a fiscal risk to government finances (Box 1.3), especially if a government has not made ex ante provisions to meet these possible costs (OECD, 2012; Mahul et al., 2014).

The size of the government’s expenditure in the event of a disaster depends of course on the severity of the disaster itself, but also on the government’s rate of compliance with meeting its liabilities – that is its ability and willingness to meet its ex ante commitments to shoulder specific disaster-related costs, or to go beyond them.

Disaster impacts on government spending: Explicit contingent liabilities

Explicit disaster-related contingent liabilities are payment obligations based on government contracts, laws or clear policy commitments that could fall due in the event of disaster. Expenditures triggered by the destruction of public assets and infrastructure, along with spending due to pre-arranged commitments, fall under this category. The exact level of explicit contingent liabilities depends on the legal and contractual payment obligations that could be triggered by a disaster. The role of governments as providers and owners of public infrastructure, as set out in various government policies, also influences the level of explicit contingent liabilities. Moreover, where the government has a role in providing insurance for public or private assets, such as in New Zealand (Earthquake Commission, EQC), France (CATNAT scheme) and Japan (Japan Earthquake Reinsurance, JER) (Box 1.4), this role creates an explicit contingent liability for a portion of the claims payments due under the insurance coverage provided (OECD, 2015)2.

Governments may find alternative ways to meet their pre-disaster commitments in nominal terms, such as through inflationary money creation, thereby not meeting them in real terms.

Disaster impacts on government spending: Implicit contingent liabilities

Implicit disaster-related contingent liabilities are expenditures the government makes in response to a disaster without any previous formal commitment to make them. The expectation for such payments might arise from political or moral pressure, or could reflect the government’s attempt to speed up recovery in order to stimulate growth. The size of a government’s implicit contingent liability may be influenced by a government’s past spending on disaster recovery and compensation beyond its legal obligation, or by the relative political power of key affected population groups.

Unlike explicit contingent liabilities, implicit contingent liabilities tend to be challenging to identify and quantify3. Although recovery and compensation expenditure in response to previous disasters should serve as a point of reference for estimating expected post-disaster government assistance, it can be difficult for governments to accurately predict the contingent liabilities arising from moral expectations and political pressure (Brixi and Schick, 2002; OECD, 2015). When statutory levels of compensation or cost-sharing arrangements between levels of government are exceeded in response to a disaster, explicit commitments can generate additional implicit commitments. In other words, due to the implicit assumption that the government will serve as insurer or guarantor of last resort, implicit contingent liabilities may arise even from explicit contingent liabilities. Still, high levels of insurance coverage for exposed assets may help limit the size of a government’s implicit contingent liabilities: if economic costs to households and businesses are covered by insurance, the political pressure on governments to provide economic relief may be smaller, hence reducing the government’s implicit contingent liability.

Disaster impacts on government revenues

Disasters can also have impacts on government revenues, especially through their negative impact on economic activity. This is usually the consequence of a decline in various tax as well as non-tax revenues, but it could also be caused by disruptions to tax collection efforts. In principle, disasters could also lead to revenue gains, either through increased revenues following a strong post-disaster economic rebound fuelled by reconstruction activities, or through increased receipts in international aid. Changes to the value of assets and liabilities of governments are often directly linked to changes in expenditure and revenue flows. For example, a reduction in the value of public infrastructure assets due to a disaster might be responsible for a corresponding increase in expenditure on the affected assets. While the latter clearly constitutes a fiscal impact caused by a disaster, a change in government asset values by itself might be overlooked in accounting for the fiscal impacts of disasters, not least because many governments do not publish comprehensive balance sheets that include non-financial assets. To properly assess fiscal impacts, the effect of disasters on an economy’s balance sheet should be comprehensively taken into account.

Indirect fiscal impacts of disasters

In addition to government expenditures and risks to revenues arising from disasters, there are a number of potential indirect disaster-related fiscal impacts, which are more difficult to observe, but no less important to consider. These include the possible deterioration in the terms at which the government can refinance public debt or raise additional debt in the short term. For example, Standard & Poor's Rating Services (2015a, 2015b) estimate that a 1-in-250-year cyclone could downgrade ratings by four or more notches in many economies. A four-notch credit rating downgrade is likely to lead to an increase in borrowing costs of 20–40 basis points or more (Hanusch et al., 2016). Disasters might also weaken public finances through the impact on domestic equity markets, where public financial asset portfolios (e.g. sovereign wealth funds) could lose value, and through a reduction in the net worth of government-owned insurance companies or banks exposed to the disaster.

When assessing fiscal risks posed by disasters, it is important to keep in mind that disasters can also raise additional revenues. Additional revenues, albeit earmarked, may be obtained through inflow of financial assistance (e.g. financial support from other governments or organisations for recovery interventions), which may reduce the government’s reconstruction liabilities. Insurance payments may also reduce the government’s liability, as they cover at least part of the spending demands arising from disaster recovery needs.

The 2011 Great East Japan Earthquake

The March 2011 Great East Japan Earthquake, followed by the tsunami and nuclear power accident, imposed an exceptional cost on Japan’s central government. The triple disaster caused an estimated USD 300 billion in total economic costs, of which USD 210 billion was estimated to be damages. Quarterly GDP declined by 2.1% in the second quarter of 2011. The total central government funding for the event represented 4% of Japan’s 2010 GDP and 20.7% of the initial general account budget. Funding was initially allocated to disaster relief, recovery and reconstruction through the general contingency budgets for fiscal years 2010 and 2011. Subsequent funding was allocated through three supplementary budgets in the 2011 fiscal year: one relied largely on the issuing of bonds, one was financed primarily via cuts in previously authorised expenditure, and one was funded by budget surplus from the previous fiscal year. In the 2012 fiscal year, additional financing was appropriated, most of which was obtained through the issuing of reconstruction bonds (Sato and Boudreau, 2012; Mahul, Benson and Boudreau, 2013). In addition to experiencing expenditure impacts, the government also immediately enacted tax relief measures for affected populations and industries, and built tax incentives into its reconstruction policy, which were sometimes complemented by subsidies (Sato and Boudreau, 2012; Mahul, Benson, and Boudreau, 2013; Law Library of Congress, 2013).

The 2010–11 Canterbury earthquake sequence in New Zealand

The most costly disaster experienced by New Zealand has been the Canterbury earthquake sequence in 2010/11. The cumulative impact of the earthquakes is an example of the significant fiscal impact major disasters can have. As happened with the Great East Japan Earthquake, the government’s budget was impacted simultaneously on the expenditure side (to pay for damaged assets and other liabilities) and on the revenue side (due to foregone tax receipts and foregone revenues from the government’s own operating services). In the year to June 2011, the net fiscal outlays related to the earthquake were USD 6.3 billion. The government shouldered an estimated one-third of the total estimated costs through natural disaster insurance provided by the EQC (Box 1.4) and central government resources (IMF, 2016).

The 2016 Financial Statements of the Crown present consolidated information regarding the fiscal impact of this earthquake sequence in New Zealand. The total cost at the end of fiscal year 2016 was USD 10.3 billion, and the earthquake-related obligations still faced are estimated at USD 1.5 billion. The cost of repairing or replacing physical assets owned by the central government amounted to USD 706 million, or 6.8% of total central government costs6. The central government provided significant contributions for the reconstruction of public assets owned by subnational governments (local/district councils and regional councils7); it paid USD 1.19 billion to restore essential subnational government infrastructure (such as water supply and wastewater and storm water services) damaged during the earthquakes. The government-owned Earthquake Commission, which provides insurance coverage against earthquake and other perils for residential property, has paid out (net of reinsurance receipts) about USD 5.3 billion in compensation for privately owned residential property. Finally, the central government exceptionally provided USD 806 million to settle residential property claims for policies held with a private insurance company, AMI8. See Table 1.3for a summary of public expenses related to the earthquakes.

The 2016 Fort McMurray wildfire in Canada

The Fort McMurray wildfire was one of the most costly disasters in Canada’s recent history. It spread across an area of 590 000 hectares in northeast Alberta between May and July 2016, destroyed 2 400 homes and buildings, affected 88 000 people and resulted in damages amounting to USD 4.6 billion (EM-DAT, 2017). Estimates suggest that an additional USD 2.2 billion in indirect damages should be included in cost estimates, with businesses in the Fort McMurray area experiencing an estimated net revenue loss of CAD 54.7 million (USD 45.1 million) (Alam and Islam, 2017).

The Fort McMurray wildfire had a negative effect on Alberta’s overall GDP; the lost oil sands production alone resulted in an estimated 0.33% drop in provincial GDP in 2016, translating to a 0.06% drop in nationwide GDP. Overall, the net effect on the provincial economy in the second quarter was estimated as a 1% reduction in GDP growth. Support from the government of Alberta (such as the provision of CAD 1 250 (USD 960) per adult and CAD 500 (USD 380) per dependent to evacuated households) and reconstruction activities, however, helped offset the impact on Alberta’s economy (Antunes and Bernard, 2017; Conference Board of Canada, 2016). The impact of the wildfire on Alberta GDP is shown in Figure 1.3.

Figure 1.3. Impact of Fort McMurray wildfires on Alberta GDP

Source: Antunes and Bernard, 2017

To support the government of Alberta in bearing the costs of this disaster, the federal government of Canada provided CAD 468.7 million (USD 385.7 million) in financial support via the Disaster Financial Assistance Arrangements (DFAA), which largely covered the costs of the initial response to the fire, including first responders and evacuee relief. In addition, the Alberta government provided around CAD 160 million in emergency funding to affected households in the Fort McMurray area. Much of the remaining cost of the wildfire has been borne by insurers, as most residential and business insurance policies cover fire damage (Antunes and Bernard, 2017).