The weather and macroeconomic determinants of whale-watching tourism: a Markov regime-switching analysis

Abstract

Taking in sail is essential for a whale-watching excursion, which makes the demand for whale-watching tourism sensitive to the weather. The purpose of this paper is to examine the implications of two potential demand-side determinants, that is, weather and macroeconomic conditions, on the business cycle of Taiwan’s whale-watching tourism industry. By exploiting a Markov regime-switching model, this study finds that temperature and relative price changes are crucial determinants of the demand for whale-watching tourism, no matter whether in the peaks or in the troughs. Nevertheless, the influences of sunshine hours, rainfall and real GDP per capita on the demand for whale-watching tourism depend heavily on the phases of business cycle. The empirical results provide some inspiration for sustainable management of Taiwan’s whale-watching tourism.

Keywords:

• Whale-watching
• weather
• Markov regime-switching model
• business cycle

JEL Classification:

• E32
• L83
• Z32

Notes

1 According to Hoyt (2001), the economic benefits worldwide have been more than USD $1 billion each year since 1998. Kuo, Chen, and McAleer (2012) also show that the number of whale-watchers has increased from a little more than 4 million in 1991 to 13 million in 2008. The tourism expenditure is more than USD $2.1 billion in 2008.

2 For instance, Cornejo-Ortega et al. (2013) examine the effects of mass international travellers on the ecosystem and the sustainability of whale-watching tourism, in the case of Islas Marietas. Cornejo-Ortega et al. (2014) find that most developed country tourists realize that their travel activities generate more carbon emissions and hasten climate change, which will deteriorate the marine ecosystem and impede the sustainable development of whale-watching tourism.

3 Jwu and Jeng (2005) show that, without development, the economic loss of whale-watching industry at Guishan area is higher than the other two sea areas. Therefore, they suggest government set priorities on investing Guishan area.

4 Fraser’s dolphin, orcas, false killer whales and pantropical spotted dolphin are also observable usually.

5 Data source: Annual Statistical Report on Tourism, published by Tourism Bureau, Ministry of Transportation and Communications, Taiwan.

6 The direct economic benefit here only includes the ticket price. Food, film, souvenirs and other are not included.

7 They show that rainfall has a positive impact on sightseeing and sport holiday and has a negative impact on skiing.

8 Tourism Bureau in Taiwan released the database “Visitors to the Principal Scenic Spots in Taiwan” since 2004.

9 Since the database “Visitors to the Principle Scenic Spots in Taiwan” does not explicitly separate tourists into domestic and inbound visitors.

10 The reference dates of the phases of Taiwan’s macroeconomic business cycle are determined by National Development Council, Taiwan. See: http://www.ndc.gov.tw/en/cp.aspx?n=20E7E5EED4327F75. Hence, the business cycle of Guishan whale-watching tourism and Taiwan’s macroeconomic business cycle are uncorrelated to each other.

11 Coefficient −0.03 in the peaks and 0.02 in the troughs, which are slight impacts.

12 The issue discussed in Lim (1999) focuses on inbound tourists. Garín-Muñoz (2009) also shows that international travellers have higher price elasticities to tourism demand than domestic travellers.