Template-type: ReDIF-Paper 1.0
Author-Name: Nava, Consuelo R.      
Author-Email: consuelorubina.nava@unito.it  
Author-Name: Osti, Linda   
Author-Email: linda.osti@unibz.it     
Author-Name: Zoia, Maria Grazia
Author-Email: maria.zoia@unicatt.it
Author-Workplace-Name: University of Turin
Author-Workplace-Homepage: http://www.est.unito.it/
Title: Forecasting Domestic Tourism across Regional Destinations through MIDAS Regressions.
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.
Length: pages 37
Creation-Date: 2022-07
File-URL: https://www.est.unito.it/do/home.pl/Download?doc=/allegati/wp2022dip/wp_07_2022.pdf
File-Format: Application/PDF
Handle: RePEc:uto:dipeco:202207