2021
DOI: 10.1016/j.jhtm.2021.09.010
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COVID-19-related government interventions and travel and leisure stock

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Cited by 39 publications
(42 citation statements)
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References 45 publications
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“…The travel and leisure sector, which is assumed to become a susceptible sector, is analyzed with Covid-19 cases and the index returns relationship, which helps to understand the effect of Covid-19. Academic studies (Isaac & Keijzer, 2021;Morse et al, 2021;Wang et al, 2021a) provide the view that changes in government measures, leisure intentions, social life, and activity preferences owing to Covid-19 can impact the travel and leisure industry. Results show that the travel and leisure sectors have significant economic linkages and generate adverse reactions to Covid-19 cases in the long run.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…The travel and leisure sector, which is assumed to become a susceptible sector, is analyzed with Covid-19 cases and the index returns relationship, which helps to understand the effect of Covid-19. Academic studies (Isaac & Keijzer, 2021;Morse et al, 2021;Wang et al, 2021a) provide the view that changes in government measures, leisure intentions, social life, and activity preferences owing to Covid-19 can impact the travel and leisure industry. Results show that the travel and leisure sectors have significant economic linkages and generate adverse reactions to Covid-19 cases in the long run.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…Second, we look at the governments' responses to the corona crisis and examine their possible impacts on bank returns by employing fixed effect panel regression with interaction effects. Prior research focuses on the impact of COVID-19 policy regulations on other sectors such as energy commodities (Czech & Wielechowski, 2021), travel, tourism, leisure stock market (Wang, Zhang, Gao, & Yang, 2021; Yang, Mao, & Wen, 2021), and local food prices (Dietrich, Giuffrida, Martorano, & Schmerzeck, 2022) rather than banks.…”
Section: Introductionmentioning
confidence: 99%
“…The methodology applied was quantile regression (QR) analysis through a fitted linear model that allows price seasonality to be modelled and the non-linear effects of demand variation on the spot price to be evaluated [42][43][44]. Besides, the QR model is robust and provides more efficient estimations over the entire distribution spectrum to analyze the relations between different economic and social factors affected by the COVID-19 shock [45][46][47][48][49]. The study used data from 2018 and 2019 to compare the price returns with its response in 2020.…”
Section: Introductionmentioning
confidence: 99%