Demand for downhill skiing in subarctic climates

ABSTRACT

This paper investigates the determinants of ski lift revenues between 1998/1999 and 2014/2015 in 20 ski areas in Finland by differentiating among winter climate conditions. Results based on dynamic panel data estimations reveal that revenues depend positively on real GDP, snow depth, and an early Easter, and negatively on relative ski lift ticket prices. The magnitude of the link between ski lift revenues and snow depth is large, but ski areas in northern Finland are less sensitive to variations in natural snow depth than those in southern or central Finland. Winter seasons with low snowfall (i.e. between 30% and 75% below average) lead to a reduction of 23% in ski lift revenues in southern Finland, of 8% in central Finland, and of 5% in northern Finland. A high amount of natural snowfall early in the winter also has a positive impact on revenues for the overall season. Despite strong investments in snowmaking facilities, even ski areas at the highest northern latitudes are not insensitive to variations in natural snowfall.

KEYWORDS:

• Winter tourism
• Finnish ski resorts
• snow depth
• climate change
• demand for downhill skiing

Acknowledgements

The authors would like to thank Mr Harry Lindfors, Executive Director of SHKY, for providing data and helpful comments on an earlier version of this paper. We would also like to thank Mr Asko Hutila from the Finnish Meteorological Institute (FMI) for providing the snow depth data for this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCiD

Markku Vieru http://orcid.org/0000-0002-8833-5248

Notes

1. The data are provided by the Finnish Ski Area Association (SHKY), http://www.ski.fi/en/.

2. As of March 2016, SHKY’s web page (http://www.ski.fi/hiihtokeskukset) displayed 70 ski resorts.

3. However, as an example of snow uncertainty in Lapland, the traditional mid-November start of the International Ski Federation (FIS) Alpine Ski World Cup season in Levi was cancelled three times between 2004 and 2015 due to a lack of snow.

4. Since weather data for some weather stations contain partial gaps, FMI has provided interpolated snow depth data using the lat-lon hila model.

5. Elasticities that are statistically significant at the 10% level or better are used to calculate the effects.

6. Assumptions are 75% decline in snow depth in the south and 30% and in central and north Finland with elasticities of 0.32, 0.27, and 0.16, respectively. Total revenues are € 5.6 million in the south, € 32 million in the north and € 8.3 in central Finland.

7. Personal correspondence with SHKY.