From Climate Variability to Weather Risk: the Impact of Snow Conditions on Tourism Demand in Austrian Ski Areas

Mag. Christoph Töglhofer From Climate Variability to Weather Risk: The Impact of Snow Conditions on Tourism Demand in Austrian Ski Areas Doctoral Thesis to be awarded the degree of Doctor of Social and Economic Sciences (Dr. rer.soc.oec.) at the University of Graz, Austria Ao. Univ.-Prof. Dr. Roland Mestel Institute of Banking and Finance Univ.-Prof. Dr. Stefan Schleicher Department of Economics Wegener Center for Climate and Global Change Graz, January 2011 . Author’s Declaration Unless otherwise indicated in the text or references, or acknowledged above, this thesis is entirely the product of my own scholarly work. Any inaccuracies of fact or faults in reasoning are my own and accordingly I take full responsibility. This thesis has not been submitted either in whole or part, for a degree at this or any other university or institution. This is to certify that the printed version is equivalent to the submitted electronic one. Date: Signature: Acknowledgements I have had the fortune to work on my Ph.D. thesis under the supervision of my advisers Roland Mestel and Stefan Schleicher. Special thanks also to Franz Prettenthaler, who supported me and my work wherever possible. The sharing of their knowledge during the course of research for this thesis has been invaluable. Over the years I have been lucky to work with many tremendous people at the Wegener Center for Climate and Global Change (WEGC) and the Centre for Eco- nomic and Innovation Research (POLICIES) at Joanneum Research. I am indebted for valuable contributions and fruitful discussions to Judith Köberl, Petra Amrusch, Nadja Vetters, Markus Zahrnhofer, Nikola Rogler, Stefan Schiman, Franz Eigner, Birgit Bednar-Friedl, Andreas Gobiet and many others. My thanks goes in particular to Michael Pock for providing this LATEX template as well as to Florian Ladstädter, Lisa Kapper, Barbara Pirscher and Matthias Themessl for sharing their experience with LATEX and R respectively. Thanks to all office colleagues for contributing to the excellent and unique working atmosphere and to the WEGC and EconClim team under the lead of Gottfried Kirchengast and Karl Steininger, who provided me an excellent surrounding and infrastructure for my work. I am grateful to Wolfgang Schöner and Roland Potzmann (ZAMG), Jürgen Weiß (Statistik Austria), Alex Stomper (MIT, IHS) and Franz Hartl (Österreichische Hotel- und Tourismusbank) for providing data and support as well as Maria Unterberger for proofreading. I benefit from extensive and very helpful comments received during several scientific conferences and summer schools as well as a research visit at the Univer- sity of Lausanne (UNIL) under the supervision of Hansjoerg Albrecher. Furthermore, I acknowledge financial support from the Jubiläumsfonds of the ÖNB (Central Bank of the Republic of Austria) for the research project EWCR1 (Economics of Weather and Climate Risks 1) as well as from a research grant from the URBI faculty of the University of Graz. Most of all, I would like to thank my family and friends, who have been of great support while writing this thesis and throughout my entire life. v Abstract In this thesis a methodological framework for assessing non-catastrophic weather risk is presented and applied on the winter tourism industry in Austria. Using meteorological data from a snow cover model developed by the ZAMG as well as data on overnight stays in municipalities from Statistics Austria for the winter seasons 1972/73 to 2006/07, impacts of snow conditions on tourism demand are estimated for 185 Aus- trian ski areas. Modelling focuses on a three-step approach. First, the distribution of several weather indices (days with snow depth >1 cm and >30 cm respectively, mean snow depth etc.) is modelled with several non-parametric and parametric approaches. Second, the dependency of overnight stays on snow conditions is estimated with an Autoregressive Distributed Lag (ADL) model. Then, in order to provide indicators of weather risk, information from these modelling steps is combined. The resulting risk is expressed as Value at Risk(weather), in short VaR(weather), which corresponds to the maximum loss from adverse weather conditions which is not exceeded with a given probability level over a given period of time. Results strongly emphasize the importance of considering both the probability of an event and its potential impact for estimating weather risks. Trend analyses provide evidence that the probability of seasons with adverse natural snow conditions substan- tially increases. They reveal a decline in snow conditions for most areas, e. g. with a −0.45 % per year change in days with snow depth >1 cm for the median area. At the same time, impact analyses show a predominantly positive, but declining depend- ence of overnight stays on snow conditions. Especially for lower lying areas a positive relationship is found, while higher lying areas typically show no dependency on their own snow conditions. Instead, some of them negatively depend on average Austrian snow conditions. Importantly, temporal analyses (moving estimates, comparison of extreme seasons etc.) reveal that impacts have decreased in recent years. A possible explanation for this decrease is the major increase in snowmaking and a subsequent decline in dependency on natural snow conditions. Of course, other factors such as an increased supply of tourist activities less sensitive to weather conditions might also be the reason for this observed trend. Overall, estimates of the 95%-VaR(weather), which correspond to a 1 in 20 year event, range from a 1.7 % to 50.5 % loss in overnight stays in ski areas, with a 7.2 % loss for the median ski area. This corresponds to a loss in sales of up to 19 million Euro, with a 500 000 Euro loss for the median ski area. Aggregating individual ski areas losses yields a total 95%-VaR of 157 million Euro for the accommodation industry. vii viii Abstract Potential biases in these estimates are discussed, most notably a likely underestimation due to uncertainties in the meteorological data and a likely overestimation as estimates are based on the average adaptation level in the study period. In a final step, linking weather risk estimates to financial ratios for hotels like the profit ratio, the return on investment or the debt ratio, clearly reveals that lower lying and smaller areas are more vulnerable, as they typically do not only face higher weather risk, but also tend to be less profitable and exhibit higher debt ratios. Zusammenfassung Die vorliegende Dissertation präsentiert einen methodischen Ansatz zur Schätzung nicht-katastrophaler Wetterrisiken sowie dessen Anwendung am Beispiel des öster- reichischen Wintertourismussektors. Dabei werden für 185 Schigebiete und die Win- tersaisonen 1972/73 bis 2006/07 die Auswirkungen der Schneebedingungen auf die Nächtigungsnachfrage geschätzt. Die Modellierung erfolgt anhand von 3 Schritten: (1) wird die Verteilung mehrerer Wetterindices (Tage mit Schneehöhe >1 cm bzw. >30 cm, mittlere Schneehöhe etc.) mit unterschiedlichen nicht-parametrischen sowie parametrischen Ansätzen modelliert, (2) wird die Abhängigkeit der Nächtigungen von den Schneebedingungen mithilfe von ADL (’autoregressive distributed lag’)-Modellen geschätzt, und (3) wird das resultierende Risiko mithilfe des Value at Risk(Wetter) bzw. VaR(Wetter) dargestellt, welcher den maximalen wetterbedingten Verlust wieder- gibt, der mit einer bestimmter Wahrscheinlichkeit in einer bestimmten Periode nicht überschritten wird. Die Resultate unterstreichen die Wichtigkeit, im Zuge der Analyse von Wetter- risiken sowohl die Wahrscheinlichkeit des Auftretens eines Ereignisses als auch dessen mögliche Schadenshöhe zu betrachten. Trendanalysen weisen auf eine erhöhte Wahr- scheinlichkeit von Wintern mit ungünstigen Schneebedingungen hin. Gleichzeitig zeigen Impact-Analysen eine vorwiegend positive, aber abnehmende Abhängigkeit der Nächtigungen von den Schneebedingungen. Besonders in tiefergelegenen Schigebieten lässt sich eine positive Abhängigkeit von den eigenen Schneeverhältnissen beobachten. Höher gelegene Gebiete weisen hingegen eher eine negative Abhängigkeit von den durchschnittlichen, österreichweiten Bedingungen auf. Untersuchungen der zeitlichen Entwicklung der Effekte (’moving estimates’, Vergleich von Extremsaisonen) deuten auf eine Abnahme der negativen Auswirkungen von schneearmen Wintern hin, welche möglicherweise durch die starke Zunahme der Nutzung von künstlicher Beschneiung bedingt ist. Insgesamt zeigen die Schätzungen des 95%-VaR(Wetter), welche einem 20-jährigen Ereignis entsprechen, je nach Schigebiet einen wetterbedingten Nächtigungsrückgang um 1.7 % bis 50.5 % (Median: 7.2 %). Dies bedeutet umgerechnet einen Umsatzver- lust um bis zu 19 Millionen Euro (Median: 500 000 Euro). Eine Aufaggregation der Verluste ergibt für die Beherbergungsunternehmen einen 95%-VaR(Wetter) von 157 Millionen Euro. Diese Schätzung beinhaltet insbesondere Unsicherheiten bezüglich der Qualität der meteorologischen Daten (mögliche Überschätzung) und der Annahme eines durchschnittlichen Adaptionsniveaus (mögliche Unterschätzung). Des Weiteren ix x Zusammenfassung macht eine Analyse des Zusammenhangs zwischen dem geschätzten Wetterrisiko und mehreren betrieblicher Kennzahlen der Hotellerie (Umsatzrendite, Return on Invest- ment, Fremdkapitalquote) deutlich, dass tiefer gelegene und typischerweise kleinere Schigebiete deutlich gefährdeter sind, weil sie neben einem höheren Wetterrisiko meist auch eine geringere Rentabilität und höhere Verschuldung aufweisen.

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