Resumen de Imputation of large gaps in tourism management time series

José María Caridad y Ocerín , Juan Antonio Marmolejo Martín , Petr Fiala , Lorena Caridad López del Rio

• The tourist industry relies every day in the capability to foresee the near future: in fixing prices offered to potential customers, adapting the number of employees to demand, making available a certain number of rooms, and so on. The statistics used are both internal and from the Statistical Institutes and specialized companies. But it is usual to find gaps in the time series data, sometimes quite large.

  And, to analyze temporal data, it is convenient to avoid missing data, and outliers. We propose a strategy for dealing with large gaps in series related to this sector, based on obtaining back and forward forecast to minimize the forecasting errors. In a case study, using the average daily rate (ADR) for the Spanish hotels in a long period, the methodology proved to produce smaller RMSE, and get reliable forecasts.