Abstract
This paper analyses the effects of the shadow economy on the total tourism spending of citizens for 84 countries from 1995 to 2017. The empirical framework is that of panel quantile regression with fixed effects. We also analyse the simultaneous effects of the shadow economy on domestic and outbound tourism spending using seemingly unrelated regressions. We first show that increases in the shadow economy appear to reduce total tourism spending: the increases are less dominant in countries with higher levels of travel activities. Moreover, the shadow economy negatively affects domestic and outbound tourism spending in the global sample, while different effects exist in subsamples. Lastly, we show that for the two sub-periods (1995–2007 and 2008–2017), the effects of the shadow economy on total tourism spending are mostly consistent in both periods except for statistically insignificant effects in the case of low- and lower-middle-income countries. The effects of the shadow economy on domestic and outbound tourism are also consistent in the two periods. However, the shadow economy exerted a significant positive impact on outbound tourism for upper-middle-income countries after the 2008 global financial crisis.
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Data can be provided upon reasonable requests.
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Notes
Results were calculated by the author(s) from the tourism spending data of every economy from the World Travel and Tourism Council (real values). Tourism consumption in 2020 dropped severely due to the COVID-pandemic and may not fully reflect the size of tourism markets for the period 1995–2019; thus, we do not present this here.
More detail about the structural quantile functions (or the instrumental variable quantile regression) can be found on page 17 and in Table 10, Appendix.
It is worth noting that these databases contain some of the most reliable data on the shadow economy.
We are thankful to an anonymous reviewer for their helpful comment.
The price level in the destination country is more important for decision-making by tourists undertaking outbound travel. However, this study focuses on the aggregate data for outbound tourism spending rather than bilateral tourism spending. Therefore, we use domestic price levels in the function of outbound tourism spending with the implication that an increase in domestic price levels would raise the relative price of domestic tourism services in comparison with outbound travel. The increase in relative price would then motivate tourists to choose outbound travel in exchange for domestic travel. We appreciate a helpful comment from an anonymous reviewer on this point.
Tourists’ travel decisions are linked strongly to their income (in an aggregate manner, GDP); and the literature of the shadow economy indicates that informal economic activities are a pervasive sector in the process of economic development (Medina and Schneider 2019).
This study performed the panel Granger non-causality test by Dumitrescu and Hurlin (2012) to examine statistical causality between the shadow economy and tourism spending. The results can be provided upon request. The results imply that there may be statistical evidence of mutual causality between the shadow economy and tourism spending.
We ran 20 bootstrap replications.
It is important to note that the data for tax complexity were only available for 2016, 2018, and 2020, while data on the percentages of the population who borrowed from a formal financial institution were also missing for several countries. Therefore, we only included these analyses for robustness checks. We appreciate the thoughtful comment from an anonymous reviewer.
Total tourism spending is the sum of domestic and outbound tourism spending.
Since international travel also uses the services of domestic tourism businesses.
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Acknowledgements
We thank the editor and two anonymous reviewers who kindly reviewed this paper and provided valuable suggestions and comments. We also greatly appreciate the insightful comments on previous versions of this paper provided by Professor Gabriel S. Lee (University of Regensburg, Germany).
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The study is funded by the University of Economics Ho Chi Minh City (UEH), Vietnam.
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CPN contributed to conceptualization, methodology, data curation, validation, formal analysis, writing—original draft preparation, and writing—reviewing and editing; BQN contributed to data curation, robustness analysis, and writing—reviewing and editing.
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See Tables 7, 8, 9, 10 and 11.
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Nguyen, C.P., Nguyen, B.Q. Does the shadow economy matter for tourism consumption? New global evidence. Empir Econ 65, 729–773 (2023). https://doi.org/10.1007/s00181-022-02354-x
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DOI: https://doi.org/10.1007/s00181-022-02354-x