Purpose This paper attempts to evaluate how the Italian tourism industry has been affected by the COronavirus Disease 19 (COVID-19) outbreak in February and March 2020. Using monthly data, a mathematical model is proposed to calculate the effects of the COVID-19 outbreak. Methodology The paper calculates three metrics: the number of tourist arrivals, the tourist spending, and the income. Each metric deals with two types of data: normal behavior and outbreak behavior. Data on normal behavior regarding the whole of Italy are used to calculate what would have been the trend of a given metric if the COVID-19 outbreak had not occurred. Data on outbreak behavior regarding a small part of Italy contains information about the COVID-19 outbreak. These data are used as a sample to infer the whole population of Italy. In all the cases, data are modeled as a variable sinusoid, where maximum and minimum peaks are calculated through linear or polynomial regression. The proposed model is compared with a classical model, i.e., the SARIMA model. Findings Results reveal that the COVID-19 outbreak significantly impacted the total number of tourist arrivals and total income, reducing tourist arrivals by 18.27% in February and 91.75% in March. Originality This paper illustrates an alternative methodology to represent historical data related to tourism and their prediction trend for the future.
Analyzing the COVID-19 Impact on Italian Tourism Industry
A. Lo Duca;Andrea Marchetti
In corso di stampa
Abstract
Purpose This paper attempts to evaluate how the Italian tourism industry has been affected by the COronavirus Disease 19 (COVID-19) outbreak in February and March 2020. Using monthly data, a mathematical model is proposed to calculate the effects of the COVID-19 outbreak. Methodology The paper calculates three metrics: the number of tourist arrivals, the tourist spending, and the income. Each metric deals with two types of data: normal behavior and outbreak behavior. Data on normal behavior regarding the whole of Italy are used to calculate what would have been the trend of a given metric if the COVID-19 outbreak had not occurred. Data on outbreak behavior regarding a small part of Italy contains information about the COVID-19 outbreak. These data are used as a sample to infer the whole population of Italy. In all the cases, data are modeled as a variable sinusoid, where maximum and minimum peaks are calculated through linear or polynomial regression. The proposed model is compared with a classical model, i.e., the SARIMA model. Findings Results reveal that the COVID-19 outbreak significantly impacted the total number of tourist arrivals and total income, reducing tourist arrivals by 18.27% in February and 91.75% in March. Originality This paper illustrates an alternative methodology to represent historical data related to tourism and their prediction trend for the future.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.