Forecasting Domestic Tourism across Regional Destinations through MIDAS Regressions

Consuelo Nava (), Linda Osti () and Maria Zoia

Department of Economics and Statistics Cognetti de Martiis. Working Papers from University of Turin

Abstract: Over the years, benefits of domestic tourism have been shadowed by the exponential growth of international tourism, despite the former representing a crucial resource, especially at times of geopolitical instability and pandemics. Therefore, forecasting domestic tourism across different regions and sub-regions becomes fundamental to determine its viability as a substitution of international tourism during the COVID-19 pandemic and to evaluate the effectiveness of governmental incentive policies introduced for its promotion. To this aim, and given the availability of data sampled at different frequencies, mixed data-sampling (MIDAS) models have been employed to estimate and predict domestic tourism expenditures, arrivals, and overnight stays. To this aim, we consider the specific case of Italy for illustrative purposes.

Pages: pages 37
Date: 2022-07
New Economics Papers: this item is included in nep-for, nep-tur and nep-ure
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