Forecasts of skier demand for Perisher Range …...iv CONTENTS FORECASTS OF SKIER DEMAND FOR...

Forecasts of skier demand for Perisher Range Resorts

Prepared for Earthtech

Centre for International Economics Canberra & Sydney

March 2005

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F O R E C A S T S O F S K I E R D E M A N D F O R P E R I S H E R R A N G E R E S O R T S

Contents

1 Introduction 1

2 The Australian ski market 2 The market for Australian skiers 2 Recent trends in skier numbers 3 The nature of visitors to Perisher 6 Climate Change 10

3 Projection framework 12

4 Projections 15 The scenarios 15 Key results: underlying trends 16 Uncertainty within the scenarios 18 Distribution of visitors throughout the year 20

5 Conclusions 24

References 25

Boxes, charts and tables 2.1 Destination shares for the Australian ski market 2 2.2 Annual winter visitation at Victorian Alpine resorts 3 2.3 Statistical evaluation of growth trends for Australian skier

numbers 4 2.4 Skier days at Perisher resorts (1989 to2004) 5 2.5 population proportions by age and income 7 2.6 Winter visitation against population growth 8 2.7 Forecast percentage population growth from 2002 8 2.8 Demographic origins of Perisher visitors 5year average (2000-

2004) 9 2.9 Snowy region visitation 1999–2002 10 2.10 Historic trend in average snow depths 11

iv

C O N T E N T S


4.1 Underlying trends for Scenarios A, B, C and D 16 4.2 Key results for skier days 17 4.3 Key results for numbers of skiers 17 4.4 Variation around key forecasts for scenario A 19 4.5 Variation around key forecasts for scenario B 19 4.6 Variation around key forecasts for scenario C 20 4.7 Variation around key forecasts for scenario D 20 4.8 Proportion of total visitor numbers by month Average 1992 to

2003 21 4.9 Ratios of summer to winter visitors and minimum to peak

visitors 21 4.10 Peak and minimum monthly numbers Visitor days 22 4.11 Peak and minimum monthly numbers Visitors 22

1


1 Introduction

The ski industry is highly variable, with large changes in visitor numbers from year to year. This variation is largely in response to changes in weather, particularly snowfall. At the same time, skiing is a very competitive industry, with resorts in Australia and overseas competing for what is a relatively small (compared with overall tourism) market of skiers.

The large variations in visitor numbers from year to year make it very difficult to discern overall trends in the market. At the same time, the degree of competition in the market means that the number of skiers going to any particular location will be depend very much on the development and marketing effort on the part of the resorts themselves.

In this report, we try to discern some underlying market parameters and trends in order to develop and implement a projection framework to estimate the magnitude of winter visitation (captured by skier days) to the Perisher Range Resorts.

Chapter 2 examines the key features of the market for Australian skiers, including the nature of competition, the evidence for any trends, and the nature of the participants themselves. Chapter 2 also considers the potential challenge posed by climate change.

Chapter 3 presents the modeling framework which is implemented using the data presented in chapter 2. Chapter 4 presents the result of four key scenarios for future demand. Chapter 5 concludes.

2


2 The Australian ski market

The market for Australian skiers As a destination that mostly serves Australians, visitor numbers to Perisher clearly depend on the aggregate Australian ski market. In the context discussed here, the Australian skiing market refers to the overall market for Australians that engage in snow activities, either in Australia, or overseas. Indeed, the overseas portion of this market is particularly important as it provides a major and growing source of competition to domestic resorts.

Table 2.1 summarises our estimates of the market shares of various destinations in the overall Australian ski market.

In 1998 an estimated 24 000 Australians traveled to Canada to ski. The number of Australian tourists traveling to the United States grew by approximately 4.5 per cent annually during the mid 1990s and the number of Australians travelling to New Zealand for the holidays during winter has risen by almost 6 per cent annually to 84 000 in 2003. Even if only 50 per cent of Australian winter tourists to New Zealand are skiing, this still represents a significant portion of Australian skiers.

As table 2.1 indicates, over 30 per cent of the market of Australian skier days is taken by overseas resorts, while Perisher has a 25 per cent market

2.1 Destination shares for the Australian ski market

Destination 1998 1999 2000 2001 2002 5 year average

% % % % % %Perisher 26 26 22 26 26 25 Thredbo 14 15 17 16 17 16 Victoria 26 26 32 26 28 28 Total domestic 67 66 71 67 71 69 New Zealand 7 8 7 9 8 8 North America 24 24 20 22 20 22 Europe 2 2 2 2 2 2 Total international 33 34 29 33 30 31 a Source: CIE estimates based on various sources

2 T H E A U S T R A L I A N S K I M A R K E T

3


share. This high proportion of Australians skiing overseas is supported by Perisher Blue’s 2004 Winter Survey which estimates that 31.5 per cent of Australian skiers travel abroad to ski.

Globally, ski markets are considered to be ‘mature markets’ in that they are not experiencing any significant growth. The fortunes of any particular resort depend very much on its ability to maintain market share and to increase the range of services it offers its customers.

The Australian ski market has been subject to increased competition in recent years — particularly from Canadian and New Zealand resorts — and this competition is expected to continue into the future.

Recent trends in skier numbers The number of skier days at any resort is highly variable from year to year, largely due to the dependence of skiing on random variables, in particular snow. Thus evaluating annual growth rates between particular points in time can be very misleading. It is important to take an overall view of skier numbers.).

Chart 2.2 shows a 20 year history for visitor numbers to Victorian Alpine resorts — illustrating very clearly that there is no systematic trend.

2.2 Annual winter visitation at Victorian Alpine resorts

600700800900

100011001200130014001500

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004Year

Visit

or da

ys (`

000s

)

Data source: The Alpine 2020 strategy, 2004

Statistical evaluation of the Victorian data reveals a strong positive correlation between snow depth and visitation. Even accounting for snow changes, there is no systematic trend in visitor numbers in Victoria (table 2.3). The Victorian Alpine Resort 2020 Strategy reports that the ‘flat trend’ in winter visitation ‘is not unique to Victoria but is part of a worldwide trend

4



in snow sports. In spite of the introduction of and growth of new sports like snow boarding, stable visitation suggests that the industry is mature’ (Department of Sustainability and Environment, 2004).

2.3 Statistical evaluation of growth trends for Australian skier numbers

Year (trend line)

coefficient test-statistic r-squared

Victorian visitor days* -0.04 -0.04 0.0001

Victorian visitor numbers** -0.22 -0.31 0.0044

Perisher visitor days*** 1.32 2.65 0.3337

Perisher cars**** 0.44 0.6 0.3664*1980 to 2003, **1985 to 2003, *** 1989 to 2004, **** 1992 to 2003, cars from Kosciusko road and portion of cars from Alpine Way going to Bullocks Flat Source: CIE estimates

Table 2.3 also summarises trends in visitor numbers and cars for Perisher. There is a significant trend — around 1.3 per cent a year — in visitor days, but no evident trend in the number of cars. The overall trend in skier days is also illustrated in chart 2.4.

The low growth trend for cars to Perisher (period 1992 to 2003) illustrates the uncertainty surrounding potential growth in the New South Wales market. Total cars can be assumed to be a reasonable proxy for skier numbers (issues of changing duration of stay or growth in coaches may affect the accuracy of this proxy). However the differences between the growth in skier days and the growth in car numbers, 0.76 per cent, offers some insight into the nature of growth in skiing demand for Perisher Range resorts. The duration of stay at the Perisher Range resorts range may be growing faster than the increase in visitor numbers.


5


2.4 Skier days at Perisher Range resorts (1989 to2004)

0100200300400500600700800900

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006Year

Skier

day

s (`0

00s

Data source: Ski Slope Master Plan 2002

Extended statistical evaluation is able to offer stronger support for the existence of growth in demand for skiing at Perisher Range resorts, however, the limitations of the data set prohibit substantive statistical findings. The 1.32 per cent annual increase in ski days at Perisher decreases to 1.2 per cent when the logged variables of snow depth and GDP growth rates and a dummy variable for 1995 are included in the regressions, however this figure remains significant (test-statistic of 2.52). It is important to incorporate these variables due to the low GDP growth rates at the start of the evaluation period (economic recession of the early 1990s) and the high variability of snow cover throughout the period of study. The dummy variable for 1995 is designed to capture any distortionary effects from the merger of the skiing resorts into the Perisher Range in 1995. Additional explanatory variables although desirable are not practical with the limited data set available. Incorporating the additional explanatory variables improves the accuracy of the predicted trend line and notably a statistically significant annual growth rate of approximately 1.2 per cent is still achieved.

Forecasts for annual skier growth, in 1990, by Travers Morgan and Access Economics predicted annual growth of 2.0-4.6 per cent and 2.5-3 per cent respectively. In hindsight these growth rates were not achieved. A possible explanation is alluded to by Access Economics who qualify their estimate by noting that a real prices increase of as little as 1 per cent per annum could wipe out growth in skier demand.

The historical data seems to show that while there is no significant trend in skier numbers in Victoria, there does appear to be a trend at Perisher.

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A possible explanation is that Perisher was not a mature market in terms of the infrastructure that was in place over the study period. Three significant infrastructure developments have aided the growth of skiing demand at Perisher in recent years. First, in 1987 the construction of the skitube was completed. This revolutionised accessibility to the resort and enhancing the viability of day visitation. Second, in 1995, the merger of the Perisher-Smiggin Holes and Blue Cow-Guthega resorts and the ensuing development of an integrated ski circuit meant that skiing capacity was increased and the entire experience of skiing at Perisher was changed.

The improved access to Perisher, particularly for day visitors, can be seen as opening up the resort to a ‘new market’. An equivalent example is in mainland Europe where, ‘the growth of charter holidays in the summer led to a supply of cheap charter flights in winter and consequently opened up skiing to a completely new market’ (Riddington 1999).

Finally, significant investment in facilities (over $10 million), such as restaurants and a creche, in 1994–95 further improved the overall package offered by Perisher.

The proposed infrastructure developments (accommodation, facilities etc.) can be viewed as further necessary steps towards improving Perisher towards a providing the ‘full snow experience’ and becoming a mature market.

The nature of visitors to Perisher Range resorts The population demographics of the Australian ski market will clearly play a major role in setting bounds for future growth. The most significant demographic features of skiers at the Perisher Range resorts are their age, income levels and geographic origin.

Demographics of the skiing population

A major constraining factor to the growth of the skiing industry is the limited ‘population group’ that it appeals to. The skiing market is a unique tourism market — as an active tourist past time skiing generally appeals to ‘younger’ and more ‘physically able’ clientele. The latest demographic profiles of visitation to Perisher Range ski resorts (Perisher Blue 2004 Visitation Survey) estimates that 94.2 per cent of winter visitors are less than 50 years of age.


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Further, the high cost of skiing relative to other holiday activities, means that it targets people with relatively high incomes. Table 2.5 shows the small proportion of the population that the ski market relies on. Almost 50 per cent of skiers at Perisher come from an age and wealth category (15-54 years old and greater than $1500 weekly income) that contains only 2.5 per cent of the Australian population. Approximately 81.6 per cent of skiers at Perisher come from just 11.6 per cent of the population.

Chart 2.6 shows that while the skiing age population has grown steadily the random pattern of winter visitation to the Victorian resorts shows an essentially flat trend line. Hence, in per capita terms demand for skiing has fallen while overall the market is stable. Analysis of the Australian population growth, for people aged 15 to 59 over the period 1980 to 1995, shows an annualised growth rate of 1.59 per cent (calculated from ABS – Australian Demographic Statistics).

The small population group, too which skiing is marketed, and the slow growth of this population grouping offer an indication of why skiing growth is as low as it is and in the case of the Victorian market – falling in per capita terms. The fact that Victorian resorts have not maintained growth in line with historic population growth is possibly evidence that NSW and overseas skiing resorts are capturing market share from the Victorian resorts.

2.5 population proportions by age and income

Weekly income 15-19 20-24 25-34 35-44 45-54

Total Perisher

skiers % % % % % % %< $400 5.6 3.3 4.7 5.1 4.7 23.6 5.5 $400-$799 0.3 2.5 5.2 4.8 4.3 17.2 12.9 $800-$1499 0.0 0.4 2.8 3.1 2.8 9.1 33.7 $1500+ 0.0 0.0 0.6 1.0 0.9 2.5 47.9 not stated 1.0 0.7 1.1 1.0 0.9 4.7 NA

15-19 20-24 25-34 35-49 50+ Proportion of Perisher skiers 15.8 20.0 28.4 22.5 5.8 Source: Australia Bureau of Statistics: 2001 Census of Population and Housing; Perisher Blue 2004 winter survey results

8



2.6 Winter visitation against population growth

0

20

40

60

80

100

120

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Ski d

ays (

'0000

s)

Notes: 1982 –1995, population taken as the population between ages 0f 15-59, to best capture the movements in the potential skiing population.

Data source: ABS 2002, Alpine 2020 strategy 2004.

Table 2.7 contains series A, B and C which represent three forecasted scenarios of population growth in Australia by age category, dependent on factors such as; mortality rates, fertility rates and net migration. What is evident from the range of forecasts is that older age groups are anticipated to grow at a faster rate than the prime skiing age (20-39). The population group (20–39) is anticipated to grow by 4.3 to 12.9 per cent by 2021, equating to annual growth rates of between 0.24 and 0.7 per cent, this fact must be considered when forecasting future skiing demand.

2.7 Forecast percentage population growth from 2002

Age group 2003 2006 2011 2021 2031

Per cent

Series A 10–19 0.5 2.0 2.8 4.0 11.520–39 0.7 2.8 5.7 12.9 14.340–59 2.5 7.7 13.2 20.4 27.4

Series B 10–19 0.4 1.7 2.0 -3.7 -3.820–39 0.5 2.0 3.8 8.5 7.040–59 2.4 7.4 12.2 17.0 21.1

Series C 10–19 0.3 1.3 1.1 -11.5 -19.120–39 0.2 0.8 1.3 4.3 -1.040–59 2.3 6.9 10.9 13.2 14.3Source: Australian Bureau of Statistics 2001 census of Population and Housing


9


Origin of skiers at Perisher Range resorts

Charts 2.8 and 2.9 show that the New South Wales skiing market is essentially reliant on patronage from New South Wales, the ACT and Queensland. Tourism from the Victoria and the rest of Australia is of little importance. Further the absence of international tourism to the region is notable. The 2002 Tourism New South Wales report for the Snowy Mountains estimated that of the international visitors visiting New South Wales, less than 1 per cent visited the Snowy Mountains (in 2002 there were approximately 21 000 international overnight visitors to the Snowy Mountains).

2.8 Demographic origins of Perisher Range resort visitors 5year average (2000-2004)

New South Wales74%

Overseas1%

Rest of australia2%

ACT6%

Queensland14%

Victoria3%

Data source: Perisher Blue 2004 Demographic Survey Results

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2.9 Snowy region visitation 1999–2002

Regional NSW24%

Queensland7%

Rest of australia2%

Sydney51%

ACT10%

Victoria6%

Data source: Tourism New South Wales, 2000, 2001, 2002

International visitation does not play a significant role in the Australian skiing market and there is no reason to suggest that this trend is likely to change. International competition is however a significant factor for Australia’s skiing demand but it is competition over Australian skiers rather than competition over the global skiing market.

Climate Change As an outdoor activity that depends on a particular kind of weather, skiing is potentially vulnerable to climate change. Recent research by the CSIRO (2003) found that there was no future scope for an improvement in average snow depths (which are expected to decrease), that average temperatures would be expected to increase and snowmaking be require more frequently (CSIRO, 2003).

The CSIRO analysis draws both on historical data and projections based on global climate models. Typical historical data on average snow depth is illustrated in chart 2.10, which shows snow depths for Spencers Creek over the period 1954 to 1998 (45 years). The chart shows an annual decrease in average snow depth of 0.45 per cent and an annual decrease in maximum snow depth of 0.19 per cent. This trend, however, is not statistically significant.


11


2.10 Historic trend in average snow depths

0

50

100

150

200

250

1954

1957

1960

1963

1966

1969

1972

1975

1978

1981

1984

1987

1990

1993

1996

cm

Data source: Snowy Mountains Hydro-electric Authority for Spencers Creek

The SLOPES submission to the current IPART review mentions (but does not provide references to) research in Victoria which apparently shows some relationship between cold air in Antarctica and Victorian Alps snow conditions. The submission claims that minimum temperatures have fallen in southern Victoria. We have been not been able to find evidence to corroborate this claim. Rather, it is contradicted by a recent report Climate Change in Victoria (undertaken by Whetton et al for the Victorian Department of Natural Resources and Environment, 2002) which finds increases in minimum temperatures in Victoria of 0.07 degrees per decade.

These different perceptions of climate change and its importance illustrate the difficulty in projecting what climate change may mean for visitation to the Perisher Range Resorts. While it is difficult enough to project the physical implications of climate change, it is even harder to predict human responses to such change.

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3 Projection framework

In order to develop projections of the number of skier days that could be expected at Perisher over the next 30 years, we have developed a flexible modeling framework that allows us to simulate various changes in the ski market. In developing this framework we have sought to capture:

competition both within the ski market, and between skiing and other tourist or recreational activities;

the underlying trends that have been observed in the past (discussed above); and

some of the underlying uncertainties in projecting ski numbers.

The framework we have developed consists of six main equations with facilities to incorporate uncertainty in the projections.

Key equations of the framework

The first equation is a basic identity relating the number of skiers at Perisher to past numbers:

St = Nt + δSt-1 (1)

where:

St is the number of skiers at Perisher at time t

Nt is the number of new skiers at Perisher in time t

δ is the retention rate of past skiers at Perisher.

The second equation is a market share relationship that defines the number of new skiers at Perisher as a function of Perisher’s market share of the overall number of Australian skiers. This is modeled as a binomial logit, a common scheme for modeling destination choice (in the ski context see for example, Riddington et al 2000).

tCOCP

CP

t Overallee

eNtt

t

*⎟⎟⎠

⎞⎜⎜⎝

⎛+

= ββ

β

(2)

3 P R O J E C T I O N F R A M E W O R K

13


where

β is a parameter reflecting overall competition in the market

CPt is an index of the characteristics of Perisher as a resort

COt is an index of the characteristics of other resorts

Overallt is the total number of Australian skiers in any one year, that can go to any resort, or overseas

The overall number of Australian skiers in one year is assumed to grow steadily according to

Overallt = (1+rt)*Overallt-1 (3)

where rt is the growth rate applicable at time t.

The next two equations define the evolution of the number of visits per skier at Perisher and the length of stay of each skier at Perisher. While these may remain constant, they could also increase over time, particularly as resort developments take place. Both of these are modeled as a logistic function, moving in an S shape towards a maximum attainable length of stay or number of visits. This is consistent with a learning style model of consumer behaviour (in the ski context, see for example Riddington 1999).

⎟⎠⎞

⎜⎝⎛+

= +− γα tIVte

MaxnvVisitsps1

(4)

⎟⎠⎞

⎜⎝⎛+

= +− λε tILte

MaxltLengthstay1

(5)

where:

Visitspst is the number of visits to Perisher per skier in year t

Lengthstayt is the length of stay (in days) at Perisher per skier in year t

Maxnv is the maximum number of visits to Perisher per skier

Maxlt is the maximum length of stay at Perisher per skier

IVt and ILt are indexes that represented variables determining the change in visits per skier and length of stay, at Perisher, respectively.

α, γ, ε and λ are parameters.

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3 P R O J E C T I O N F R A M E W O R K


The final equation relates the number of skier days to the number of skiers at Perisher.

SDAYSt = St * Visitspst * Lengthstayt (6)

where SDAYSt is the number of skier days at Perisher at time t.

The relationship between the peak and minimum numbers for visitation at Perisher is determined using the following equations.

PeakVt = Rpwt*St

MinVt = Rmpt*PeakVt

PeakVDt = Rpwt*SDAYSt

MinVDt = LSSt*MinVt

where:

PeakVt is the peak number of visitors at Perisher at t;

Rpwt is the ratio of peak to winter visitors at Perisher at t;

MinVt is the minimum number of visitors at Perisher at t;

Rmpt is the ratio of minimum to peak numbers at Perisher at t;

PeakVDt is the peak number of visitor days at Perisher at t;

MinVDt is the minimum number of visitor days at Perisher at t;

LSSt is the average length of stay at Perisher in summer.

Implementing the framework

The framework is implemented using the data outline above. The underlying model parameters are calibrated by imposing the various known data points, and then choosing the parameters to allow the model to reproduce past behaviour. This is a process of calibration rather than statistical estimation, as there is insufficient data to statistically estimate the model. While the model is calibrated, this does not mean that underlying parameters can be viewed as being certain.

Uncertainty is dealt with in the framework by undertaking Monte Carlo simulation of the model using assumed distributions of key model parameters. As will be discussed further below, we also incorporate uncertainty due to unknown snowfall in each year. This uncertainty is captured using the past distribution of snow fall around its mean value.

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4 Projections

We analyse potential future visitor numbers using four main scenarios, with a trend based estimate for each scenario, as well as stochastic variation around the trend for that scenario.

The scenarios

Scenario A: continued growth

This scenario is essentially based around a continuation of the positive overall trends observed in Perisher over the past decade. This scenario assumes continued development of the resort (that is, it assumes the proposed expansion takes place) so that Perisher is able to hold its own against competitor destinations. It also assumes that the overall market for skiers continues to grow at apparent historical rates. In addition, it assumes an increasing trend in length of stay — consistent with ongoing development of the resort. This scenario also assumes that climate remains unchanged.

Scenario B: competition with alternatives

This scenario is similar to scenario A in terms of assumptions about Perisher maintaining its competitiveness against other destinations, but assumes that all resorts face increasing competitive pressure from alternative holiday destinations. That is, the growth of the overall ski population is assumed to slow dramatically. This scenario also assumes that climate remains unchanged.

Scenario C: no new investment

These scenario is based around the assumption that resort development does not take place at Perisher and that investment in infrastructure is not maintained. At the same time, other competing resorts are assumed to increase their investment and marketing in an attempt to capture more

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4 P R O J E C T I O N S


market share. As a consequence, Perisher rapidly loses competitiveness. This scenario also assumes that climate remains unchanged.

Scenario D: climate change — one possibility

This is the most difficult scenario to implement as it is concerned with the implications of climate change. Within this scenario, we assume that resort development continues to take place and that Perisher holds its own against competitors. That is, it implicitly assumes that all resorts can hold their own as far as snow making is concerned. However, the overall market for skiers is assumed to decline, as is the growth rate of length of stay.

Key results: underlying trends Chart 4.1 illustrates the underlying trends for skier days under each of the core scenarios, and tables 4.2 and 4.3 summarises key results for selected years.

4.1 Underlying trends for Scenarios A, B, C and D

0

200

400

600

800

1000

1200

1400

1989

1992

1995

1998

2001

2004

2007

2010

2013

2016

2019

2022

2025

2028

2031

2034

Thou

sand

s

A

B

D

C

Data source: CIE estimates


17


4.2 Key results for skier days

Scenario Measure 2010 2015 2025 2035Scenario A Skier days (‘000) 788 869 1073 1274 Average growth(%) a 1.7 2.0 2.1 1.7 Scenario B Skier days (‘000) 769 820 937 1028 Average growth(%) a 1.3 1.3 1.3 0.9 Scenario C Skier days (‘000) 720 707 662 604 Average growth(%) a 0.2 -0.4 -0.7 -0.9 Scenario D Skier days (‘000) 738 751 775 800 Average growth(%) a 0.6 0.4 0.3 0.3a Refers to period up to that year. For example, the growth rate in the 2010 column refers to the growth from 2004 to 2010, while the rate in the 2015 column refers to growth from 2010 to 2015, and so on. Source: CIE estimates

4.3 Key results for numbers of skiers

Scenario Measure 2010 2015 2025 2035Scenario A Skier number (‘000) 174 178 185 193 Average growth(%) a 0.5 0.5 0.4 0.4 Scenario B Skier number (‘000) 170 168 162 155 Average growth(%) a 0.1 -0.2 -0.3 -0.4 Scenario C Skier number (‘000) 165 157 136 114 Average growth(%) a -0.4 -1.0 -1.4 -1.7 Scenario D Skier number (‘000) 169 166 159 151 Average growth(%) a 0.0 -0.3 -0.4 -0.5a Refers to period up to that year. For example, the growth rate in the 2010 column refers to the growth from 2004 to 2010, while the rate in the 2015 column refers to growth from 2010 to 2015, and so on. Source: CIE estimates

There is a wide range of potential outcomes from these various scenarios. Scenario A shows strong growth with an initial increase in the growth of skier numbers over time (reflecting the learning elements of the model, where skier numbers build up as word gets around about the development of new facilities) followed by a slight slowing (as competitors respond).

Scenario B has growth rates around about the same as those seen historically, with a slight decline in the later years. The decline in skier numbers is more dramatic in this scenario, reflecting competition from other tourist possibilities. Skier days grow more slowly because of the growth in length of stay built into the scenario.

Scenario C is quite pessimistic, with declines in skier days and skier numbers. These declines accelerate overtime as word gets out about the lack of resources at Perisher as well as about the relative attractiveness of other destinations.

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Scenario D still shows growth in skier days, but a slow decline in the number of skiers. But as will be argued further below, the responses of consumers to the prospect of climate change is very uncertain. Under the scenario as implemented, the decline in the overall skier market is offset by the continued attention to developing the resort and success in slowly increasing visitor days.

Uncertainty within the scenarios There are two sources of potential variation within these scenarios. First, variation because of the inherent variability in the amount of snow from year to year. The historical numbers in chart 4.1 give a sense of this variability around the underlying trend. Second, the various parameters in the underlying forecasting model are uncertain, and will not necessarily take the central values implicit in the results presented above.

To address both these sources of uncertainty, we undertake stochastic analysis within each of the scenarios outlined above. In this stochastic analysis we:

allow the key market parameters to vary by up to twenty percent around their central values;

use the distribution of past snow fall around the trend to address the uncertainty around the amount of snow in each year.

assume that under the climate change scenario, the variability of snow will increase.

Scenario A

Chart 4.4 shows the probability distribution for selected years for forecasts of skier days under scenario A. Not surprisingly, the distributions get wider over time, reflecting increased uncertainty in the future. While there is some overlap between the distributions, there is clearly a tendency to increased numbers of skier days.


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4.4 Variation around key forecasts for scenario A

400 600 800 1000 1200 1400 1600 1800 2000 2200

20102015

2025

2035


Scenario B

Chart 4.5 shows the distributions of skier days for scenario B. Here there is a much greater tendency to overlap than under scenario A, reflecting the slower growth under this scenario.

4.5 Variation around key forecasts for scenario B

400 600 800 1000 1200 1400 1600 1800 2000 2200

20102015

2025

2035


Scenario C

Chart 4.6 shows the probability distributions for scenario C. There is a large degree of overlap here, particularly between 2010 and 2015. However, the distributions are not as wide as previously, showing slightly more certainty.

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4.6 Variation around key forecasts for scenario C

400 600 800 1000 1200 1400 1600 1800 2000 2200

2015

2035

2025 2010


Scenario D

Chart 4.7 shows the probability distribution for scenario D. In this case there is almost complete overlap of the very wide probability distributions. This reflects the inherent uncertainty about the future effects of climate change.

4.7 Variation around key forecasts for scenario D

400 600 800 1000 1200 1400 1600 1800 2000 2200

2015

2025

2035

2010


Distribution of visitors throughout the year

Basic trends

Perisher is currently essentially a winter resort. In this way it contrasts with Thredbo which has relatively more summer visitation. Chart 4.8 illustrates the distribution of visitor numbers over the year using car number statistics. Cars along Kosciuszko road essentially go to Perisher, while those


21


along the Alpine Way go to Thredbo, as well as to the ski tube at Bullocks Flat.

4.8 Proportion of total visitor numbers by month Average 1992 to 2003

0

0.05

0.1

0.15

0.2

0.25

0.3

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Prop

ortio

n

Kosciusko Rd

Alpine Way

Data source: National Parks and Wildlife Services

The relative importance of winter visitation for Perisher has been increasing over time. Chart 4.9 shows the trend in the ratio of summer to winter visitors. This ratio is declining at around 4 per cent a year. Chart 4.9 also shows the ratio of the minimum to the peak number of visitors. This ratio is also declining, at around 2.6 per cent per year.

4.9 Ratios of summer to winter visitors and minimum to peak visitors

0

0.1

0.2

0.3

0.4

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Summer/Winter

Minimum/Peak

Data source: National Parks and Wildlife Services

Currently, around 35 per cent of winter visitation occurs in the peak month, while the ratio of minimum to peak visitors is around 5 per cent.

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Distribution of visitors for the scenarios

Charts 4.10 and 4.11 summarise projections for peak and minimum monthly numbers (for both visitor days and visitor numbers) under each scenario.

4.10 Peak and minimum monthly numbers Visitor days

Scenario Measure 2010 2015 2025 2035Scenario A Peak (‘000) 276 287 343 382 Minimum (‘000) 3 6 9 12 Scenario B Peak (‘000) 269 271 300 308 Minimum (‘000) 3 5 8 9 Scenario C Peak (‘000) 252 262 258 242 Minimum (‘000) 3 3 3 2 Scenario D Peak (‘000) 258 293 325 360 Minimum (‘000) 3 6 12 19Source: CIE estimates

4.11 Peak and minimum monthly numbers Visitors

Scenario Measure 2010 2015 2025 2035Scenario A Peak (‘000) 61 59 59 58 Minimum (‘000) 3 4 5 6 Scenario B Peak (‘000) 59 55 52 47 Minimum (‘000) 3 4 4 5 Scenario C Peak (‘000) 58 58 53 46 Minimum (‘000) 3 3 3 2 Scenario D Peak (‘000) 59 65 67 68 Minimum (‘000) 3 4 6 7Source: CIE estimates

The relationship between peak and minimum numbers varies by scenario and is in fact driven by a number of different determinants in each case. These are summarised below.

Scenario A

Under this scenario we expect the relative importance of the peak month to decline as the developments at the resort lead to attempts to fill out the entire ski season. At the same time, we expect the ratio of the minimum to the peak numbers to increase (that is, for summer visitation to become more important) as attempts are made to use the resort throughout the year. As a consequence, the difference between peak and minimum numbers narrows over time, for both visitors and visitor days.


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Scenario B

While this scenario projects slower overall winter growth, we have assumed that the relationships between minimum and peaks are the same as for scenario A. While greater competition with other tourism destinations means lower overall growth, we are effectively assuming that the entire distribution of visitors shifts down (relative to scenario A) by the same amount.

Scenario C

Under this decline scenario, we expect that the overall importance of the winter peaks will increase, as without new resort development there will be less interest in summer visitation. This is offset to a degree by the overall declines in winter visitation, so the relationship between the minimum and the maximum remains roughly constant.

Scenario D

Under this climate change scenario there are two potential developments, each moving in different directions. On the one hand, climate change is likely to lead to a shorter season so the relative importance of the peak month will increase. At the same time, climate change elsewhere in Australia may make the mountains appear to be more attractive in summer, and so the ratio of the minimum to the peak is likely to increase. Potentially, the number of days stay in summer will also increase. Overall under this scenario, the relationship between the minimum and the peak narrows.

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5 Conclusions

The projections presented in this report show that it is possible to derive a wide range of estimates of future visitor numbers to Perisher. The magnitude of these estimates depends very much on what is likely to happen in terms of resort and infrastructure development.

Indeed, the number of visitors should not be viewed a particular number that will occur regardless of what is done at the resort. Rather, the number of visitors in the future will very much depend on infrastructure and resort developments that are set in train now. The differences between numbers with and without the developments are quite large.

The other feature of projecting visitor numbers is uncertainty. Both weather (even not accounting for any systematic climate change) and underlying parameters of the ski market are uncertain, which means there will inevitably be wide confidence intervals attached to any particular projections. This uncertainty is a fundamental feature of the ski market and needs to be taken into account when considering infrastructure developments.

With these qualifications in mind, we consider that either scenario B or scenario C are the most likely to occur. Scenario B is conditional on new developments taking place at the resort. These developments are essential if Perisher is to maintain its competitiveness as a destination. Given that there is a lot at stake, we expect that these developments will take place, although, of course, this is not guaranteed. If new developments do not take place, then we consider scenario C to be a likely outcome.

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References

ABS 2001, Census of Population and Housing (2015.0), Australian Bureau of Statistics, Canberra.

ABS 2002, Estimated Age Distribution of the Population: States and Territories" (3201.0), Australian Bureau of Statistics, Canberra, annual.

Australian Demographic Statistics" (3101.0), Australian Bureau of Statistics, Canberra, quarterly.

Department of Sustainability and Environment, 2004, “Alpine 2020 strategy”

Hennessy, K., Whetton, P., Smith, I., Bathols, J., Hutchinson, M., Sharples, J., 2003, “The impact of climate change on snow conditions in Australia”.

Perisher Blue Pty Limited (2002), “Ski Slopes Master Plan”

Riddington, G.L., (1999) “Forecasting Ski Demand: Comparing Learning Curve and Varying Parameter Coefficient Approaches”, Journal of Forecasting vol. 18, pp. 205-214.

Riddington, G.L., Sinclair, C. and Milne, N. 2000 “Modelling choice and switching behaviour between Scottish ski centres” Applied Economics, 32, 1011-1018.

Trewin, D., 2003, “Population Projections: Australia 2002 to 2101”, Australian Bureau of Statistics.

New South Wales Tourism Profile, December 2002, Tourism New South Wales, Sydney



Perisher Blue 2004, Perisher Blue 2004 Winter Survey Results and 2004 Winter Traffic Study

Whetton, P.,Suppiah, R., McInnes, K., Hennessy, K., and Jones, R. 2002 Climate Change in Victoria: High resolution regional assessment of climate change impacts, Victorian Department of Natural Resources and Environment, May.

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