A framework to investigate the economic growth impact of sea level rise

First, sea level rise will lead to the definitive loss of land. Land is a natural resource and matters for economic production. In our framework, land is part of natural capital 'E'; a loss of land is thus a loss of capital, with negative consequences on output. According to existing modelling studies, this loss will affect particularly agricultural production¹ (see Bosello et al 2007). Where land is scarce (or, equivalently, where all useable land is used for agriculture), the associated economic cost can be assessed by the land market value (or the value of farms, as in Mendelsohn et al (1994)).

As stated in Yohe (1991), the land market price cannot always be used directly to assess the economic cost of sea level rise. Indeed, land prices are often very high on the coastline, because of amenities (e.g., sea views) and of the proximity to port infrastructure. But if and where the coastline shifts and this land is lost, these amenities are transferred to land farther from the current coastline. So, sea level rise leads to a loss (from land loss) and a gain (from additional amenities in farther-inland locations). Only the net loss should be taken into account. Over the long-term, therefore, the economic loss from definitive land loss should not be calculated with the coastline land values, but using the farther-inland land values. These values being much lower than coastal ones, the economic cost of sea level rise is much more limited than could be derived from local land prices.

In addition to market economic impacts, sea level rise threatens some ecosystems and natural habitats. These potential losses can also be recorded as a decrease in natural capital E. These ecosystems provide important services like breeding zones for fish. If these services are included in economic output, these losses translate into an economic loss. If a narrow definition of GDP is used, then welfare losses exceed GDP losses.

When these services disappear, their value is lost or they have to be replaced by artificially provided services (e.g., protection from storm surge by a mangrove can be replaced by a dike; in that case, we substitute additional physical capital K for lost natural capital E). In the narrow definition of economic growth, in which ecosystem services are not included, replacing ecosystem-based services by artificially provided services would increase GDP, and enhance economic growth. But the impact on welfare would be negative, because increased investment means reduced consumption.

Sea level rise can lead to the definitive loss of infrastructure and productive capital, i.e. to a loss of physical capital K. In some coastal areas, indeed, it is more rational to withdraw inland than to try to protect the area.

As discussed in Yohe et al (1996) and West et al (2001), we could imagine that this withdrawal will take place naturally, with the value of assets and investments regularly decreasing as the risk in the zone increases. At the time the zone should be evacuated, the assets would be at the end of their lifespan and would therefore have a zero value. In this case, the cost of withdrawal would be null. However, this is difficult to imagine for several reasons.

First, West et al (2001) discuss the role of anticipation and foresight, as only unrealistically perfect foresight would allow for this low-cost solution. Second, an urbanized zone is composed of many types of assets (housing, roads, etc) that have very different life spans, and it is difficult to imagine that all of these assets can arrive at full depreciation at the same time. Third, it is not possible to stop all maintenance and to use housings and roads that deteriorate over time and whose comfort and safety are compromised. We can clearly see that we cannot avoid abandoning assets that are still useable (with, therefore, a non-zero cost), even with a coordinated withdrawal organized by local authorities ('strategic withdrawal').

Sea level rise might also affect social capital (Turner et al 1996). Indeed, a fraction of the population only would be affected by sea level rise and would require additional protection expenditures and support, at least in most countries. This could create political and social tensions since policies would have large redistributive effects: if large investments are made, the rest of the population can see them as inappropriate; if necessary investments are not made, the population at risk may feel unprotected by its government (Luisetti et al 2011). The resulting social and political tensions may be a strong obstacle to the smooth functioning of the institutions that is necessary to sustain balanced economic growth (e.g., Alesina et al 1996, Rodrik 1999).

The impact of sea level rise on economies and societies will not only go through the definitive inundation of some locations. In places that are not definitely inundated, the risk from coastal floods will increase (see, e.g., Hanson et al 2011). And this effect is reinforced by existing trends, with cities—and especially coastal cities—growing rapidly in response to trends in economic structure and life styles. Confronted with growing population, land scarcity and infrastructure gap, more marginal and high-risk land is urbanized every year.

If adequate measures are not implemented, this increase in risk could translate into larger economic losses for coastal floods, including large losses in productive capital and infrastructure. Model-based case studies show, e.g., on Copenhagen (Hallegatte et al 2011), that the increase in risk could be very large where protections become insufficient. In our growth framework, this increase in risk would translate into additional losses of physical capital K. But disasters have other consequences.

In terms of human capital, disasters have a direct impact through injuries and loss of lives. But it has also been shown that disasters can have long-lasting consequences on child development (Santos 2007, Alderman et al 2006), with large consequences on labour productivity, health costs, growth and welfare. Moreover, disasters lead to significant migrations. After Katrina, for example, migrations outside the affected area, including permanent migrations (Landry et al 2007), have been observed. If disasters lead to out-migration, there will be consequences on economic growth; these consequences would be amplified if—as suggested by the Katrina case, see Zissimopoulos and Karoly (2007)—high-skilled, high-productivity workers are more able to migrate than the average population.

There are also consequences on social capital. First, risk perceptions influence the willingness to invest, and the trust in an economically successful future. Second, some disasters have led to political instability and conflicts in the past, especially when governmental support of affected population was ineffective (see Homer-Dixon (1999), and a discussion in Gleditsch and Urdal (2002)). These conflicts have negative consequences on long-term economic growth.

Finally, disasters can reduce natural capital, for instance when hurricane storm surges destroy mangroves, i.e. decrease natural capital E. These impacts reduce ecosystem services, with consequences on economic production Y and welfare.

If growth is understood more broadly and in welfare terms, then other impacts of natural disaster need to be included. Lindell and Prater (2003) and Tierney (2006) provide a summary of these impacts, including social impacts, health impacts and psychological impacts.

Sea level rise is a progressive and dynamic process, and a continuous adaptation process will take place to cope and react to it. This adaptation process will aim at (i) avoiding definitive loss of land and capital when their value is high; (ii) reducing coastal flood risks to acceptable levels in human settlements; (iii) retreating from areas that are not protected.

Several model-based analyses of adaptation in coastal areas have been proposed (Yohe 1991, Fankhauser 1994, Yohe et al 1996, West et al 2001, Yohe and Tol 2002, Yohe et al 2011). The 'cost' of sea level rise depends on assumptions on how adaptation can be carried out. With perfect adaptation (rational actors, no externalities, perfect foresight), the residual cost (after adaptation) remains small (e.g., Nicholls and Tol 2006).

The cost of adaptation is the sum of all investments (and maintenance costs) necessary to protect human settlements located in at-risk areas. OECD (2008) estimates that the annualized costs for optimal levels of protection are typically relatively modest, frequently less than 0.1% of national GDP. However, adaptation costs may be high relative to the GDP of coastal areas, as it is not guaranteed that protection costs will be absorbed fully at the national level. It is useful to note that the assumptions on protection costs are particularly simple in these analyses that are based on broad estimates of hard protection building costs (e.g., Hoozemans et al 1993, Heberger et al 2009). In reality, protection costs for cities (e.g., New Orleans) can be much higher, because of the cost of land to build the protection, or because of the need for mobile protections to maintain port operations.

Darwin and Tol (2001) analyse the indirect impact of these investments in a static framework. In a growth framework, these expenditures can increase GDP by increasing demand, but they are clearly part of the defensive expenditures that should not be accounted in welfare-improving economic output.

In the simplest growth theory, i.e. a Solow–Swan economic growth framework with constant saving ratio, exogenous technical change and decreasing return on capital, a permanent loss in any of the four capitals does not reduce the long-term economic growth rate. Instead, the economy converges towards a pathway with the same growth rate, but with reduced GDP and consumption levels. In such a framework, indeed, the long-term economic growth rate is linked to technical progress only, which is assumed exogenous.

In the case of sea level rise, however, the process is slow and continuous over centuries, and this progressive reduction in capitals would translate into reduced long-term economic growth, even in a Solow–Swan framework.

In models with endogenous growth, productivity becomes endogenous. If sea level rise makes it necessary to invest more in coastal defences, the additional investment can crowd out other investments, and in particular investments in research & development. This crowding-out effect could then lead to reduced productivity growth and to reduced growth rates.

On the other hand, an increase in investment may also bring economic benefits in the form of higher activity and higher growth, if the economic situation is of insufficient demand, underproduction and unemployment (e.g., during an economic crisis). This stimulus effect can bring benefits, but one has to note that—in absence of sea level rise—the same stimulus could be obtained by investing in other useful infrastructure (housing, drinking water infrastructure, etc) instead of defensive investments.

Econometrics analyses at national scale have reached different conclusions on the impact of disasters on growth. Some suggest that natural disasters have a positive influence on long-term economic growth (e.g., Skidmore and Toya (2002)). Others, like Noy and Nualsri (2007), Noy (2009), Hochrainer (2009) and Raddatz (2007), suggest that the impact on growth is negative. As suggested by Cavallo and Noy (2011) and Loayza et al (2009), large disasters may have a negative impact on growth while smaller ones sometimes enhance growth through increased demand.

At local scale, Strobl (2011) investigates the impact of hurricane landfall on county-level growth in the US. He finds that economic growth is reduced on average by 0.79% point in counties affected by a hurricane landfall, and increased by only 0.22% point the following year.

But in the case of increasing disaster losses due to sea level rise, one can be concerned more about poverty traps than with small changes in growth rate. Disasters, indeed, destroy assets and wipe out savings, and can push households into 'poverty traps', i.e. situations where productivity is reduced, making it impossible for households to rebuild their savings and assets (Carter et al 2007, Dercon 2004, 2005, Lopez and Servén 2009, Van den Berg 2010).

These poverty traps at the micro level could lead to macro-level poverty traps, in which entire regions could be affected (Hallegatte et al 2007, Hallegatte and Dumas 2008). In our framework, this poverty traps can be interpreted as situations in which economic output becomes so low that populations cannot invest any more in the four capitals necessary to grow output.

Some have made the case that economic growth will reduce disaster losses in the future, by increasing resilience. However, the relationship between wealth and disaster vulnerability may not be monotonic. Growth and development can be risk reducing or risk increasing, depending on their structure and patterns. Hallegatte (2011) shows that—even assuming that economic agents behave in a perfectly rational way—natural disaster losses can grow faster than wealth in response to economic growth.

A few papers have investigated this question for sea level rise, but models remain too simple to investigate all mechanisms. Deke et al (2001) use a recursive calculable general equilibrium (CGE) model, in which the dynamics is equivalent to a Solow–Swan growth model, to investigate the impact of the costs of coastal protection on economic growth and activity. They do not take into account land losses and additional flood risks, but the costs of coastal protection are subtracted from total investment in physical capital. Investment is thus distributed between unproductive coastal protection (defensive expenditures) and productive net investment. In their framework, protection costs reduce the capital stock, and hence economic output and future consumption. Their results suggest a very small impact of sea level rise on growth (with reduction in capital of less than 0.05% in all regions but India where capital is reduced by 1.3%), but they only consider a 13 cm sea level rise in 2100, which is extremely optimistic.

Using the same methodology, but accounting for all impacts of climate change (including sea level rise), Kemfert (2002) finds large GDP losses (up to 1.6% in 2050). This large loss arises from the reduction in investment and its impact on accumulation, not from direct climate change.

As also suggested by Fankhauser and Tol (2005) and Hallegatte et al (2007), these preliminary results support the idea that dynamic effects can dominate direct effects, and that current analyses focusing on direct losses from sea level rise need to be complemented with macro-economic analyses. In particular, it would be interesting to test whether conclusions on long-term impacts are dependent on which growth theory is used.