Forecast of tourism demand with the use of fuzzy and cointegration econometric techniques

Abstract

Econometric models for the forecast of tourism demand are developed in this paper. In order to assess the long-run trends concerning principal tourism generating countries, the Johansen's maximum likelihood techniques are applied. For a better assessment of the short-run trends, the estimated error correction terms are introduced to the first difference models to estimate the short-run relationships (Error Correction Models, ECMs). Based on the results given by the ECMs, fuzzy regression models are suggested and then compared in order to provide the forecasting ability of both techniques (Fuzzy and ECMs). Finally, for the evaluation of forecasting performance, the Theil's Inequality Coefficient is applied.