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Forecasting Domestic Tourism across Regional Destinations through MIDAS Regressions

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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.

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  • Nava, Consuelo R. & Osti, Linda & Zoia, Maria Grazia, 2022. "Forecasting Domestic Tourism across Regional Destinations through MIDAS Regressions," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202207, University of Turin.
    • Handle: RePEc:uto:dipeco:202207
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