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Does international tourism spur international trade in SSA countries? A dynamic panel data analysis

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  • Odhiambo, Nicholas M
  • Saungweme, Talknice

Abstract

In this study, the relationship between tourism development and trade in 12 sub-Saharan African (SSA) countries is examined during the period 1995-2019. Three proxies of trade are used, namely the total trade, total exports, and total imports of goods and services to examine this linkage, thereby leading to three separate model specifications. A wide range of modern econometric techniques were also employed to examine the relationship between the various proxies of trade and tourist arrivals. These include i) cross-sectional dependence tests based on Breusch-Pagan (1980) LM, Pesaran (2004) scaled LM, Baltagi et al. (2012) bias-corrected scaled LM, and Pesaran (2004) CD; ii) a slope homogeneity test based on Pesaran and Yamagata (2008); iii) an ECM panel cointegration test based on Westerlund (2007); and iv) a heterogeneous panel causality model based on Dumitrescu and Hurlin (2012), among others. Using the dynamic ordinary least squares (DOLS) and the fully modified ordinary least squares (FMOLS), the study found that, overall, international tourism has a positive and significant impact on trade in SSA countries. This finding is also corroborated by the heterogeneous Granger causality test, which found a distinct unidirectional causal flow from international tourism arrivals to trade. The study, therefore, recommends that SSA countries should implement policies aimed at promoting international tourism in order to increase their international trade and boost their overall trade balance.

Suggested Citation

  • Odhiambo, Nicholas M & Saungweme, Talknice, 2021. "Does international tourism spur international trade in SSA countries? A dynamic panel data analysis," Working Papers 28345, University of South Africa, Department of Economics.
  • Handle: RePEc:uza:wpaper:28345
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    References listed on IDEAS

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    Keywords

    Tourism; trade openness; Granger-causality; panel analysis; SSA;
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