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Tourism and growth in Lebanon: new evidence from bootstrap simulation and rolling causality approaches

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Abstract

A multivariate model incorporating tourist arrivals, real output, and the real exchange rate is estimated to study the causal relationship between tourism and economic growth in Lebanon. This study covers the monthly data from January 1995 to December 2011. The Granger causality between the variables of interest is determined using the TYDL bootstrap causality approach. Then, we apply the Granger causality with rolling regression technique to evaluate the stability of the tourism-led growth hypothesis in Lebanon. We find that the tourism-led growth hypothesis is supported empirically in the case of the Lebanese economy. Meanwhile, we also find some evidences of uni-directional Granger causality running from the real exchange rate to tourism and economic growth in Lebanon. Therefore, tourism can be used a policy instrument to stimulate long-term economic growth in Lebanon.

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Notes

  1. The real effective exchange rate data for Lebanon is incomplete.

  2. We are aware of the fact that industrial production index (IPI) is an alternative measure for economic activity, and it is also been used by some existing studies on tourism-growth nexus (e.g. Lean and Tang 2010; Tang and Tan 2013). However, the coverage of coincident indicator is much broader than the IPI that consists only of manufacturing, mining, and electricity and gas industries.

  3. It is essential to clarify the meaning of unstable parameter and unstable causal relationship as they are not the same. Unstable parameters imply the change in magnitude of estimate parameters over the analysis period. In other words, it is also known as structural change. Therefore, the impact of unstable parameters can be removed by capturing the structural change via dummy variable. On the other hand, the unstable causality does not relate to the change in magnitude (e.g. positive or negative); rather, it refers to the consistency of the causality inferences over a period of time. Thus, Tang (2010, (2013b) recommended to use time-varying analysis such as incorporating rolling procedure into the Granger causality test to detect the stability of causal relationship between the variables of interest.

  4. Apart from the aforementioned violations, the application of leveraged bootstrap simulation approach would also help to improve the robustness of the causality results in small sample owing to the choice of high-order VAR system (i.e. 15 lags) that consumes high degree of freedom (Hacker and Hatemi-J 2006; Tang and Abosedra 2014). To conserve space, the leveraged bootstrap testing procedure to re-calculate critical values for Granger causality is not presented here. However, interested reader may refer to Gunduz and Hatemi-J (2005).

  5. In terms of Granger causality, Tang and Abosedra (2014) found strong evidence of uni-directional causality in the long-run. On the contrary, our findings suggest that there is a bidirectional causality between tourism and economic growth in Lebanon. Excluding the exchange rate by Tang and Abosedra (2014) could be one of the possible explanations for the discrepancy of causality results.

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Acknowledgments

We would like to thank the three anonymous reviewers and Robert M. Kunst (coordinating editor of the Empirical Economics) for their constructive comments and suggestion given on the earlier draft of this research paper. We are also very grateful to Abdulnasser Hatemi-J for providing the GAUSS routines to conduct the leveraged bootstrap causality test and the multivariate ARCH test. Any flaws and omissions that remain in this research paper are of our own responsibility.

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  1. Centre for Policy Research and International Studies, Universiti Sains Malaysia, 11800, USM, Penang, Malaysia

    Chor Foon Tang

  2. College of Business Administration, American University in the Emirates, Dubai, UAE

    Salah Abosedra

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  1. Chor Foon Tang
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Correspondence to Chor Foon Tang.

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Tang, C.F., Abosedra, S. Tourism and growth in Lebanon: new evidence from bootstrap simulation and rolling causality approaches. Empir Econ 50, 679–696 (2016). https://doi.org/10.1007/s00181-015-0944-9

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