New insights into an old issue – examining the influence of tourism on economic growth: evidence from selected small island developing states

Abstract

This paper uses relatively new heterogeneous panel autoregressive distributed lag cointegration methods to re-examine the long-run equilibrium and Granger causality relationship between tourism and economic growth for the small island developing states (SIDSs). In addition, the study incorporates energy consumption and foreign direct investment (FDI) as alternative growth determinants, during the period 1995–2014. After allowing for the heterogeneous country effect, a positive and statistically significant long-run equilibrium relationship between tourism, energy consumption, FDI, and gross domestic product, with a moderate convergence rate towards the long-run path is confirmed. The panel Granger causality test as proposed by Dumitrescu and Hurlin [(2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460.] shows bidirectional causality running from tourism to economic growth, from tourism to energy consumption and from energy consumption to economic growth, and unidirectional causality between FDI and tourism, between economic growth and FDI, and between FDI and energy consumption. Our empirical findings provide support for tourism-induced growth, tourism-induced energy consumption, tourism-induced investment, and the energy consumption-economic growth relationship in the case of SIDSs. Our empirical results resonate with the existing findings with major policy implications for the SIDSs.

Keywords:

• tourism earnings
• economic growth
• cointegration
• granger causality
• dynamic panel model
• small island developing states

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Seyi Saint Akadiri http://orcid.org/0000-0001-8901-7965

Notes

1 For brevity of space, we could not discuss in detail the remaining panel unit root test conducted.

2 For brevity of space, we could not discuss the panel causality techniques in detail. For more information on the approach, interested readers should see Dumitrescu, and Hurlin (2012).