Sea level rise and its economic consequences

he Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) predicts global sea level to rise (SLR) by up to 60 cm by 2100 in response to ocean warming and glaciers melting. Moreover, it is expected that sea level rise might be of 1 meter or more in 2100 due to recent identified accelerated decline of polar ice sheet mass. This global rise of sea level will contribute to increased coastal inundation and erosion, ecosystem losses, saltwater intrusion on surface and groundwater across different regions. Regionally, sea level rise will depart from the global mean trend due to a range of meteorological, oceanographic and geological effects (Nicholls, 2002). Without proper mitigation and adaptation strategies, economic consequences of SLR could be immense depending on local and regional socio-economic and geographical conditions. Hence, the objective of this paper is to examine, analyze and understand the economic implications of sea level rise for different regions.The GEMINI-E3, a recursive dynamic general equilibrium model, is used in this paper to analyze the economic consequences of sea level rise for different regions. As most CGE models, GEMINI-E3 simulates all relevant markets, domestic and international, considered as perfectly competitive, which implies that the corresponding prices are flexible: markets for commodities (through relative prices), for labor (through wages), for domestic and international savings (through rates of interest and exchange rate). Time periods are linked in the model through endogenous real rates of interest determined through the balancing of saving and investments. Database required for the GEMINI-E3 model are taken from various sources mainly from Global Trade Analysis (GTAP) 6 database, UN population database, International Monetary Fund (IMF) government statistics, Organization for Economic Co-operation and Development (OECD) government revenue statistics, International Energy Agency (IEA) energy prices and taxes. Climate variable (global mean temperature) required to compute the sea level rise (SLR is calculated from semi-empirical relationship proposed by Rahmstorf, 2007) are provided from a statistical emulator of the PLASIM-GENIE model (the Hamburg Planet Simulator coupled to the grid-enabled integrated earth system model). In this paper, two scenarios will be simulated (i) with the restriction of temperature increase to 1 degree centigrade in 2050 relative to pre-industrial temperature level (ii) with the restriction of temperature increase to 1.2 degree centigrade in 2050 relative to pre-industrial temperature level. These climate scenarios are developed through the coupling between GEMINI-E3 and PLASIM-GENIE models. The result from this scenario will be compared with the baseline scenario where no such restriction in temperature increase is made. Incorporating sea level rise impacts in CGE model: Impact of sea level rise could be incorporated in CGE model through different assumptions (i) no protection from sea level rise such that some land area is lost, (ii) full protection from sea level rise such that no land area is lost (iii) optimal protection from sea level rise comes through the minimization of protection cost, land loss and wetland loss (Fankhauser, 1995). In GEMINI-E3, land is the factor inputs for production of agricultural products and regional investment equals to regional savings (savings from different economic agents) through real rates of interest. So, loss of land can be easily incorporated in the model by exogenously reducing land endowment of various economies in accordance to sea level rise impacts. Similarly, protection cost required to lessen the impacts of SLR could be incorporated through change in investments in construction sector by government. The revenue required by government to increase its investment will be collect through increase in tax on household consumption.Results are analyzed for different sectors and regions. There are 25 sectors (Coal, oil, natural gas, petroleum product, electricity, gaseous fuel, forestry, mineral products, chemical, rubber, plastic, metal and metal products, paper products publishing, land transport, sea transport, air transport, consuming goods, machinery and equipment goods, services, dwellings, construction, water, paddy rice, wheat, cereals, oilseeds and rest of agriculture sectors.) and 14 regions in the model. Sectoral and macroeconomic results are analyzed for various regions. It is expected that SLR will have negative effects on the economy, mostly affecting the agricultural sectors due to area of land loss. It is important to emphasis that sea level rise impacts considered here are only sub-set of the ways in which SLR impact economies. Other potential consequences include saltwater intrusion of surface and groundwater, and coastal wetlands (such as salt-marshes and mangroves) that could also have significant impacts.