The exposure of the US tourism subsector stocks to global volatility and uncertainty factors

ABSTRACT

In the face of uncertain circumstances and volatilities across tourism stocks, the current study attempts to investigate the connectedness of US tourism subsectors using time-varying vector autoregressions (TVP-VAR) technique for the period spanning 1 August 2008–31 August 2021. Moreover, we examined the influence of various financial and economic indicators to observe their impact on the connectedness of US tourism subsectors. Further, we employed Diebold and Yilmaz ([2012]. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66) connectedness approach to justify the robustness of our results. We find that hotels, transportation, and recreational are net transmitters of spillovers to the remaining US subsectors. We reported multiple time-varying attributes where the connectedness of US tourism subsectors was remarkably higher. In addition, the regression results reveal a positive and significant impact of financial and economic uncertainties on the connectedness. Finally, our findings were robust to the methodology employed, which substantially justified our estimator. We proposed numerous useful implications for policymakers, US government, tourism industry, investors, market players, and portfolio managers to benefit from the findings obtained.

KEYWORDS:

• Connectedness
• TVP-VAR
• US tourism subsectors
• financial and economic indicators
• uncertainty

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Please see: https://repositorio.cepal.org/bitstream/handle/11362/46502/3/S2000751_en.pdf

2 Please see: https://www.bbc.com/news/world-52103747

3 Please see: https://wttc.org/Research/Economic-Impact

4 Please see: https://www.bea.gov/data/special-topics/outdoor-recreation#:~:text=The%20new%20U.S.%20data%20show,for%20the%20nation%20in%202020.&text=The%20share%20was%200.8%20percent%20in%20the%20District%20of%20Columbia.

5 See https://money.usnews.com/investing/stock-market-news/slideshows/decades-biggest-events-on-wall-street?slide=2 retrived from September 29, 2021.

6 See https://www.reuters.com/article/us-usa-fed-2013-timeline-idUSKCN1P52A8 retrived from September 29, 2021.

7 As a robustness check, three models have been estimated. Model 1, regresses only the implied volatility (financial volatility) indexes on TCI. Model 2, regresses economic policy uncertainty (EPU) and infectious disease index (INFD) on TCI. In model three, though, we regress the implied volatility indexes, EPU, and INFD on TCI. The results across different models are almost the same and thus, we only discuss the results of model 3.

8 Please refer to Diebold and Yilmaz (2012).