1 resultado para spatio-temporal data model
em Comissão Econômica para a América Latina e o Caribe (CEPAL)
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Resumo:
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.