Comparar métodos

	Tourism Almost Ideal Demand System	Tourism Seasonality Index
Área	Tourism Hospitality	Tourism Hospitality
Família	Regression model	Regression model
Ano de origem	1980	2001
Autor original	Angus Deaton & John Muellbauer; Gang Li, Haiyan Song & Stephen F. Witt (tourism application)	Svend Lundtorp; Anastassios Tsitouras
Tipo	System-of-equations consumer demand model	Descriptive concentration index for seasonal demand
Fonte seminal	Deaton, A., & Muellbauer, J. (1980). An Almost Ideal Demand System. American Economic Review, 70(3), 312-326.	Lundtorp, S. (2001). Measuring Tourism Seasonality. In T. Baum & S. Lundtorp (Eds.), Seasonality in Tourism (pp. 23-50). Oxford: Pergamon/Elsevier. ISBN: 9780080436746
Outros nomes	Tourism AIDS Model, LAIDS Tourism Demand, Tourism Expenditure Allocation Model, System-of-Equations Tourism Demand	Tourism Seasonality Measurement, Seasonality Gini Coefficient, Seasonal Concentration Index, Tourism Seasonality Ratio
Relacionados	4	4
Resumo	The Almost Ideal Demand System (AIDS), introduced by Angus Deaton and John Muellbauer in 1980, is a system of demand equations grounded in consumer theory that models how a budget is allocated across competing goods through their expenditure shares. Applied to tourism, AIDS treats a tourist's total travel budget as allocated across competing destinations (or expenditure categories), with each destination's budget share depending on relative prices and real total expenditure. Because it estimates all share equations jointly and can impose the restrictions implied by economic theory — adding-up, homogeneity, and symmetry — the model yields a consistent set of income (expenditure) and own- and cross-price elasticities, including how destinations substitute for one another. Gang Li, Haiyan Song, and Stephen Witt's dynamic linear AIDS application demonstrated its value for both explaining and forecasting tourism demand.	Tourism seasonality measurement summarizes how unevenly tourism demand is distributed across the year. Destinations rarely receive visitors at a constant rate; arrivals, overnight stays, and revenue cluster in peak months and thin out in the off-season, straining capacity at the top and leaving resources idle at the bottom. Seasonality indices turn a monthly demand series into a single, comparable number measuring this temporal concentration. Simple ratios compare the peak month to the average or to the trough, while the Gini coefficient — long established in the study of inequality and adapted by Svend Lundtorp and others to tourism — captures concentration across all months at once via a Lorenz curve. Adjusted versions, such as Tsitouras's 'months equivalent' degree of seasonality, make the index easier to interpret and compare.