The impact of climate change on the tourism sector in the Caribbean

The main aim of this study is to estimate the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A typical tourism demand function, with tourist arrivals as the dependent variable, is used in the analysis. To establish the baseline, the period under analysis is 1989-2007 and the independent variables are destination country GDP per capita and consumer price index, source country GDP, oil prices to proxy transportation costs between source and destination countries. At this preliminary stage the climate variables are used separately to augment the tourism demand function to establish a relationship, if any, among the variables. Various econometric models (single OLS models for each country, pooled regression, GMM estimation and random effects panel models) were considered in an attempt to find the best way to model the data. The best fit for the data (1989-2007) is the random effects panel data model augmented by both climate variables, i.e. temperature and precipitation. Projections of all variables in the model for the 2008-2100 period were done using forecasting techniques. Projections for the climate variables were undertaken by INSMET. The cost of climate change to the tourism sector was estimated under three scenarios: A2, B2 and BAU (the mid-point of the A2 and B2 scenarios). The estimated costs to tourism for the Caribbean subregion under the three scenarios are all very high and ranges from US$43.9 billion under the B2 scenario to US$46.3 billion under the BAU scenario.

The impact of climate change on the macroeconomy in the Caribbean

In this study, an attempt is made to assess the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A methodological approach proposed by Dell et al. (2008) is used in preference to the traditional Integrated Assessment Models. The evolution of climate variables and of the macroeconomy of each of the nine countries over the period 1970 to 2006 is analyzed and preliminary evidence of a relationship between the macroeconomy and climate change is examined. The preliminary investigation uses correlation, Granger causality and simple regression methods. The preliminary evidence suggests that there is some relationship but that the direction of causation between the macroeconomy and the climate variables is indeterminate. The main analysis involves the use of a panel data (random effects) model which fits the historical data (1971-2007) very well. Projections of economic growth from 2008 to 2099 are done on the basis of four climate scenarios: the International Panel on Climate Change A2, B2, a hybrid A2B2 (the mid-point of A2 and B2), and a ‘baseline’ or ‘Business as Usual’ scenario, which assumes that the growth rate in the period 2008-2099 is the same as the average growth rate over the period 1971-2007. The best average growth rate is under the B2 scenario, followed by the hybrid A2B2 and A2 scenarios, in that order. Although negative growth rates eventually dominate, they are largely positive for a long time. The projections all display long-run secular decline in growth rates notwithstanding short-run upward trends, including some very sharp ones, moving eventually from declining positive rates to negative ones. The costs associated with the various scenarios are all quite high, rising to as high as a present value (2007 base year) of US$14 billion in 2099 (constant 1990 prices) for the B2 scenario and US$21 billion for the BAU scenario. These costs were calculated on the basis of very conservative estimates of the cost of environmental degradation. Mitigation and adaptation costs are likely to be quite high though a small fraction of projected total investment costs.

An assessment of the economic impact of climate change on the Agriculture Sector in Jamaica

The agricultural sector‟s contribution to GDP and to exports in Jamaica has been declining with the post-war development process that has led to the differentiation of the economy. In 2010, the sector contributed 5.8% of GDP, and 3% to the exports (of goods), but with 36% of employment, it continues to be a major employer. With a little less than half of the population living in rural communities, agricultural activities, and their linkages with other economic activities, continue to play an important role as a source of livelihoods, and by extension, the economic development of the country. Sugar cane cultivation has, with the exception of a couple of decades in the twentieth century when it was superseded by bananas, dominated the agricultural export sector for centuries as the source of the raw materials for the manufacture of sugar for export. In 2005, sugar cane itself accounted for 6.4% of the sector‟s contribution to GDP, and 52% of the contribution of agricultural exports to GDP. Production for the domestic market has long been the larger subsector, organized around the production of root crops, especially yams, vegetables and condiments. To analyse the potential impact of climate change on the agricultural sector, this study selected three important crops for detailed examination. In particular, the study selected sugar cane because of its overwhelming importance to the export subsector of agriculture, and yam and escallion for both their contribution to the domestic subsector as well as the preeminent role yams and escallion play in the economic activities of the communities in the hills of central Jamaica, and the plains of the southwest respectively. As with other studies in this project, the methodology adopted was to compare the estimated values of output on the SRES A2 and B2 Scenarios with the value of output on a “baseline” Business As Usual (BAU), and then estimate the net benefits of investment in the relevant to climate change for the selected crops. The A2 and B2 Scenarios were constructed by applying forecasts of changes in temperature and precipitation generated by INSMET from ECHAM inspired climate models. The BAU “baseline” was a linear projection of the historical trends of yields for each crop. Linear models of yields were estimated for each crop with particular attention to the influence of the two climate variables – temperature and precipitation. These models were then used to forecast yields up to 2050 (table1). These yields were then used to estimate the value of output of the selected crop, as well as the contribution to overall GDP, on each Scenario. The analysis suggested replanting sugar cane with heat resistant varieties, rehabilitating irrigation systems where they existed, and establishing technologically appropriate irrigation systems where they were not for the three selected crops.

An assessment of the economic impact of climate change on the health sector In Jamaica

Climate change is a naturally occurring phenomenon in which the earth‘s climate goes through cycles of warming and cooling; these changes usually take place incrementally over millennia. Over the past century, there has been an anomalous increase in global temperature, giving rise to accelerated climate change. It is widely accepted that greenhouse gas emissions from human activities such as industries have contributed significantly to the increase in global temperatures. The existence and survival of all living organisms is predicated on the ability of the environment in which they live not only to provide conditions for their basic needs but also conditions suitable for growth and reproduction. Unabated climate change threatens the existence of biophysical and ecological systems on a planetary scale. The present study aims to examine the economic impact of climate change on health in Jamaica over the period 2011-2050. To this end, three disease conditions with known climate sensitivity and importance to Jamaican public health were modelled. These were: dengue fever, leptospirosis and gastroenteritis in children under age 5. Historical prevalence data on these diseases were obtained from the Ministry of Health Jamaica, the Caribbean Epidemiology Centre, the Climate Studies Group Mona, University of the West Indies Mona campus, and the Meteorological Service of Jamaica. Data obtained spanned a twelve-year period of 1995-2007. Monthly data were obtained for dengue and gastroenteritis, while for leptospirosis, the annual number of cases for 1995-2005 was utilized. The two SRES emission scenarios chosen were A2 and B2 using the European Centre Hamburg Model (ECHAM) global climate model to predict climate variables for these scenarios. A business as usual (BAU) scenario was developed using historical disease data for the period 2000-2009 (dengue fever and gastroenteritis) and 1995-2005 (leptospirosis) as the reference decades for the respective diseases. The BAU scenario examined the occurrence of the diseases in the absence of climate change. It assumed that the disease trend would remain unchanged over the projected period and the number of cases of disease for each decade would be the same as the reference decade. The model used in the present study utilized predictive empirical statistical modelling to extrapolate the climate/disease relationship in time, to estimate the number of climate change-related cases under future climate change scenarios. The study used a Poisson regression model that considered seasonality and lag effects to determine the best-fit model in relation to the diseases under consideration. Zhang and others (2008), in their review of climate change and the transmission of vector-borne diseases, found that: ―Besides climatic variables, few of them have included other factors that can affect the transmission of vector-borne disease….‖ (Zhang 2008) Water, sanitation and health expenditure are key determinants of health. In the draft of the second communication to IPCC, Jamaica noted the vulnerability of public health to climate change, including sanitation and access to water (MSJ/UNDP, 2009). Sanitation, which in its broadest context includes the removal of waste (excreta, solid, or other hazardous waste), is a predictor of vector-borne diseases (e.g. dengue fever), diarrhoeal diseases (such as gastroenteritis) and zoonoses (such as leptospirosis). In conceptualizing the model, an attempt was made to include non-climate predictors of these climate-sensitive diseases. The importance of sanitation and water access to the control of dengue, gastroenteritis and leptospirosis were included in the Poisson regression model. The Poisson regression model obtained was then used to predict the number of disease cases into the future (2011-2050) for each emission scenario. After projecting the number of cases, the cost associated with each scenario was calculated using four cost components. 1. Treatment cost morbidity estimate. The treatment cost for the number of cases was calculated using reference values found in the literature for each condition. The figures were derived from studies of the cost of treatment and represent ambulatory and non-fatal hospitalized care for dengue fever and gastroenteritis. Due to the paucity of published literature on the health care cost associated with leptospirosis, only the cost of diagnosis and antibiotic therapy were included in the calculation. 2. Mortality estimates. Mortality estimates are recorded as case fatality rates. Where local data were available, these were utilized. Where these were unavailable, appropriate reference values from the literature were used. 3. Productivity loss. Productivity loss was calculated using a human capital approach, by multiplying the expected number of productive days lost by the caregiver and/or the infected person, by GDP per capita per day (US$ 14) at 2008 GDP using 2008 US$ exchange rates. 4. No-option cost. The no-option cost refers to adaptation strategies for the control of dengue fever which are ongoing and already a part of the core functions of the Vector Control Division of the Ministry of Health, Jamaica. An estimated US$ 2.1 million is utilized each year in conducting activities to prevent the post-hurricane spread of vector borne diseases and diarrhoea. The cost includes public education, fogging, laboratory support, larvicidal activities and surveillance. This no-option cost was converted to per capita estimates, using population estimates for Jamaica up to 2050 obtained from the Statistical Institute of Jamaica (STATIN, 2006) and the assumption of one expected major hurricane per decade. During the decade 2000-2009, Jamaica had an average inflation of 10.4% (CIA Fact book, last updated May 2011). This average decadal inflation rate was applied to the no-option cost, which was inflated by 10% for each successive decade to adjust for changes in inflation over time.

An assessment of the economic impact of climate change on the tourism sector in the Bahamas

The Bahamas is at great risk and vulnerability given its geographical features as a low-lying, sea encircled country. If projected sea level rise is reached by 2050, between 10-12% of territory will be lost, especially in coastal zones where the main tourism assets are located. Vulnerability could also be manifested if flight carbon emission taxes are established in the main source markets, representing an economic threat to the tourism sector for the islands. The impact of climate change on main tourism demand variables will cause some losses to the country‟s income and government revenues. This would be acting conjointly with some local threats to tourism assets and trends in future global tourism demand. The second and no less important threat is tropical cyclones, which may be associated with raising sea level. Estimations posited the amount of losses in excess of 2400 million US$ for the four decades under examination. It is to be pointed out that there is still a lack of comparatively accurate data collection and analysis on this subject, a point deserving more attention in order to deepen the understanding of, and to extract better lessons from these extreme events. In the same period, total estimated impacts of progressive climate change are between 17 and 19 billions of B$ with estimated discount rates applied. The Bahamas is a Small Island Developing State with low growth on GHG emissions (second in Latin America), as well as a relative short capacity to lower emissions in the future. The country has a relative delay in the application of renewable energy systems, a solution that, provided documented studies on-site, might turn out to be fundamental in the country‟s efforts to establish mitigation related policies. The Bahamas currently has institutions and organizations that deal with climate change-related issues and an important number of measures and courses of action have been set up by the government. Nevertheless, more coordination among them is needed and should include international institutions. This coordination is essential even for the first steps, i.e. to conduct studies with a bottom-up approach in order to draw more accurate programs on adaptation and mitigation. It is fundamental for tourism to keep track of potential losses in tourist attractions (and to act accordingly), related to correspondent losses in biodiversity, water resources and coastal erosion. Also, actions to fight climate change impacts might improve the islands security standards, quality of living and protect cultural and heritage assets. These elements may definitely shape the future of the country‟s competitiveness as a tourism destination. It is possible and necessary to decide about the options with good cost-benefit ratio and reasonable payback periods, notwithstanding that cost-benefit analysis requires more refined and accurate data to provide precise and locally adapted options.

An assessment of the economic impact of climate change on the tourism sector in Montserrat

This report provides an analysis and evaluation of the likely effects of climate change on the tourism sector in Montserrat. Clayton (2009) identifies three reasons why the Caribbean should be concerned about the potential effects of climate change on tourism: (a) the relatively high dependence on tourism as a source of foreign exchange and employment; (b) the intrinsic vulnerability of small islands and their infrastructure (e.g. hotels and resorts) to sea level rise and extreme climatic events (e.g. hurricanes and floods); and, (c) the high dependence of the regional tourist industry on carbon-based fuels (both to bring tourist to the region as well as to provide support services in the region). The effects of climate change are already being felt on the island. Between 1970 and 2009, there was a rise in the number of relatively hot days experienced on the island. Added to this, there was also a decline in mean precipitation over the period. Besides temperature, there is also the threat of wind speeds. Since the early 20th century, the number of hurricanes passing through the Caribbean has risen from about 5-6 per year to more than 25 in some years of the twenty-first century. In Montserrat, the estimated damage from four windstorms (including hurricanes) affecting the island was US$260 million or almost five times 2009 gross domestic product (GDP). Climate change is also likely to significantly affect coral reefs. Hoegh-Guldberg (2007) estimates that should current concentrations of carbon dioxide in the Earth’s atmosphere rise from 380ppm to 560ppm, decreases in coral calcification and growth by 40% are likely. The report attempted to quantify the likely effects of the changes in the climatic factors mentioned above. As it relates to temperature and other climatic variables, a tourism climatic index that captures the elements of climate that impact on a destination’s experience was constructed. The index was calculated using historical observations as well as those under two likely climate scenarios: A2 and B2. The results suggest that under both scenarios, the island’s key tourism climatic features will likely decline and therefore negatively impact on the destination experience of visitors. Including this tourism climatic index in a tourism demand model suggests that this would translate into losses of around 145% of GDP. As it relates to coral reefs, the value of the damage due to the loss of coral reefs was estimated at 7.6 times GDP, while the damage due to land loss for the tourism industry was 45% of GDP. The total cost of climate change for the tourism industry was therefore projected to be 9.6 times 2009 GDP over a 40-year horizon. Given the potential for significant damage to the industry, a large number of potential adaptation measures were considered. Out of these, a short-list of 9 potential options was selected using 10 evaluation criteria. These included: (a) Increasing recommended design wind speeds for new tourism-related structures; (b) Construction of water storage tanks; (c) Irrigation network that allows for the recycling of waste water; (d) Enhanced reef monitoring systems to provide early warning alerts of bleaching events; (e) Deployment of artificial reefs and fish-aggregating devices; (f) Developing national evacuation and rescue plans; (g) Introduction of alternative attractions; (h) Providing re-training for displaced tourism workers, and; (i) Revised policies related to financing national tourism offices to accommodate the new climatic realities Using cost-benefit analysis, three options were put forward as being financially viable and ready for immediate implementation: (a) Increase recommended design speeds for new tourism-related structures; (b) Enhance reef monitoring systems to provide early warning alerts of bleaching events, and; (c) Deploy artificial reefs or fish-aggregating devices. While these options had positive benefit cost ratios, other options were also recommended based on their non-tangible benefits: an irrigation network that allows for the recycling of waste water, development of national evacuation and rescue plans, providing retraining for displaced tourism workers and the revision of policies related to financing national tourism offices to accommodate the new climatic realities.

An assessment of the economic impact of climate change on the tourism sector in Saint Lucia

This report provides an analysis and evaluation of the likely effects of climate change on the tourism sector in Saint Lucia. Clayton (2009) identifies three reasons why the Caribbean should be concerned about the potential effects of climate change on tourism: (a) the relatively high dependence on tourism as a source of foreign exchange and employment; (b) the intrinsic vulnerability of small islands and their infrastructure (e.g. hotels and resorts) to sea level rise and extreme climatic events (e.g. hurricanes and floods); and, (c) the high dependence of the regional tourist industry on carbon-based fuels (both to bring tourist to the region as well as to provide support services in the region). The effects of climate change are already being felt on the island. Between 1970 and 2009 there was a rise in the number of relatively hot days experienced on the island. Added to this, there was also a decline in mean precipitation over the period. In addition to temperature, there is also the threat of increased wind speeds. Since the early twentieth century, the number of hurricanes passing through the Caribbean has risen from about 5-6 per year to more than 25 in some years of the twenty-first century. In Saint Lucia, the estimated damage from 12 windstorms (including hurricanes) affecting the island was US$1 billion or about 106% of 2009 GDP. Climate change is also likely to significantly affect coral reefs. Hoegh-Guldberg (2007) estimates that should current concentrations of carbon dioxide in the Earth’s atmosphere rise from 380ppm to 560ppm, decreases in coral calcification and growth by 40% are likely. This report attempted to quantify the likely effects of the changes in the climatic factors mentioned above on the economy of Saint Lucia. As it relates to temperature and other climatic variables, a tourism climatic index that captures the elements of climate that impact on a destination’s experience was constructed. The index was calculated using historical observations, as well as those under two, likely, Special Report on Emissions Scenarios (SRES) climate scenarios: A2 and B2.