98.2 outbound travel

8/13/2019 98.2 Outbound Travel

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Australian Outbound Holiday Travel Demand:

Long-haul Versus Short-haul

Krishna HamalAnalysis and Forecasting

Paper presented at the Australian Tourism and Hospitality Research Conference

Gold Coast, Queensland, Australia

11-14 February 1998

BTR Conference Paper 98.2

ISSN 1326-8309

ISBN 0 642 28504 7

Bureau of Tourism Research


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GPO Box 1545 Canberra ACT 2601AUSTRALIA

Telephone: (02) 6213 7136; Facsimile: (02) 6213 6983E-mail: [email protected]

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Preface

Outbound travel accounts for about 40 per cent of total international travel, which includesboth short-term overseas arrivals and resident departures. In recent times, the outboundtravel sector has expanded more rapidly than the domestic travel sector. The number ofshort-term resident departures has increased by an average of 4 per cent a year since 1991,

from 2.1 million in 1991 to 2.7 million in 1996.

Holiday travel dominates the outbound travel sector, accounting for 46 per cent of totalshort-term resident departures. The number of residents departing for holiday purposesincreased by 5 per cent a year, from 0.5 million in 1974 to 1.3 million in 1996. During thesame period, domestic holiday nights declined by 2.8 per cent suggesting possiblesubstitution between outbound and domestic holiday travel. Relatively cheaper prices ofoutbound travel might have encouraged Australians to substitute overseas holidaydestinations for domestic ones.

Previous studies by Hamal (1996 and 1997) observed that substitution occurs betweenoutbound and domestic holiday travel. However, the relationship was observed on anaggregate level, assuming that the magnitude of substitution between a domesticdestination and an overseas destination remains the same whether the overseas destinationis a long-haul or short-haul destination. In reality, this may not be true. A holiday travelleris more likely to substitute a short-haul rather than a long-haul overseas destination for adomestic destination. This is because prices of travel to short-haul overseas destinationsare expected to be more competitive with domestic travel prices than would travel prices tolong-haul overseas destinations. This paper examines substitution by outbound travellers tolong-haul and short-haul overseas holiday destinations. In this study, the USA and UK arechosen as long-haul destinations, whereas New Zealand, Indonesia, Singapore and Fiji are

selected as short-haul destinations.

Econometric models were used to estimate and analyse the demand parameters ofoutbound travel. The models were estimated using annual historical data from 1974 to1996. Data were obtained from the publications of the Australian Bureau of Statistics, theWorld Bank and the International Monetary Fund.

The empirical results suggest a substitution between domestic and outbound holiday traveland that the magnitude and significance of the elasticity of substitution vary by traveldistance to outbound destinations. Outbound travel is also observed to be influenced by

population, real household disposable income and own price.

Keywords

outbound travel, outbound travel model, Australian outbound tourism

Australian Outbound Holiday Travel Demand: Long-haul Versus Short-haul Page i


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1. Introduction

People travel for several reasons such as holiday, visiting friends and relatives (VFR),business, employment and sports, but holiday travel remains the dominant sector of theinternational travel market. According to travel literature, holiday travel to a destination is

influenced by two major attributes: the attractiveness of that destination and travellersability to travel to that destination in terms of situational constraints (Woodside andLysonski 1989; Um and Crompton 1990 and 1992; Crompton and Ankomah 1993).Situational constraints are those associated with factors such as income, travel prices, timeand health. Although these two attributes jointly influence the final choice of a destination(Um and Crompton 1990 and 1992; Hansen 1976; Woodside and Lysonski 1989), thelatter is empirically observed to be more important than the former (Um and Crompton1992).

Among several factors associated with situational constraints, travel prices have beenempirically observed to have a significant influence on travel demand (Hamal 1996 and1997). Holiday travellers are expected to compare the prices of taking holidays in differentdestinations and thereby to choose those destinations which maximise their holiday utility.In other words, the choice of a destination is determined not only by the price of a holidayin that destination but also by the prices of a holiday in substitute destinations. Therefore,the prices of substitute destinations are very important in analysing travel demand,especially for the development of marketing strategies.

In Australia, a substitution between domestic and outbound holiday travel is likely to occurbecause:

Australia is a developed country with a high level of per capita real householddisposable income. Therefore many Australians can afford to substitute overseasdestinations for domestic destinations.

Australia is a vast country where domestic travel to some destinations is more costlythan overseas travel to destinations surrounding Australia.

Australians appear to have a liking for travel in general, and overseas travel inparticular.

In recent decades, the prices of outbound holiday travel in real terms has declined by0.7 per cent a year since 1974 and by 1.7 per cent a year in the last ten years, largelydue to the development of aircraft technology and the liberalisation of international airroutes. The fuel efficiency and carrying capacity of airlines have improved with thedevelopment of aircraft technology, while the liberalisation of international air routes inseveral countries including Australia has resulted in competitive airfares oninternational routes. This means that the price of overseas travel has relatively declinedover the last ten years, and therefore more Australians can afford a holiday at overseasdestinations, especially those surrounding Australia such as New Zealand, Indonesia,Fiji and Singapore.

Australian Outbound Holiday Travel Demand: Long-haul Versus Short-haul Page 1


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A substitution effect between outbound and domestic holiday travel in Australia has beenempirically observed by Hamal (1996 and 1997). Figure 1 and Table 1 indicate thatdomestic holiday trips remained flat (zero growth) between 1979 and 1993 while thenumber of resident departures for holiday purposes during the same period increased by4.2 per cent a year to 1.2 million in 1993. In fact, the number of resident departures forholiday purposes increased by 5 per cent a year since 1974, from 0.5 million in 1974 to 1.3

million in 1996 (Table 2). Domestic holiday trips could not be compared to outbound tripsafter 1993 due to a break in series in domestic trips data in 1994-95.

Figure 1: Domestic and outbound holiday travel, 1979 - 1993

80

100

120

140

160

180

200

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

Trips(1979=100

)

Outbound trips

Domestic trips

* Excludes domestic trips data after 1993 due to a break in series in 1994-95.

Table 1: Domestic and outbound holiday trips (thousands)

Year Domestic trips Outbound trips

1979 18998 6711980 20060 7071981 20303 7361982 20001 791

1983 20450 7591984 21034 8611985 19371 9171986 19248 9021987 20959 9021988 20531 9411989 20169 11191990 20336 12261991 20206 11511992 18207 12071993 18817 1160

1994 19433* 1144



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1995 21506* 11401996 21939* 1263

Average annual growth rate (%): 1979 - 1993

0.0 4.2

* Break in data series

In Hamal (1996 and 1997), substitution between domestic and outbound travel in Australiawas observed on an aggregate level assuming that the magnitude of substitution between adomestic destination and a overseas destination remains the same whether the overseasdestination is a long-haul or short-haul. In reality, this may not be true. A holiday travelleris more likely to substitute a short-haul overseas destination for a domestic destination,

because

Table 2: Short-term resident departures by purpose of visit (thousands)

Year Business Holiday VFR Other Total

1974 117 457 140 56 7701975 117 557 176 62 9121976 125 601 181 66 9741977 133 584 188 66 9711978 153 638 204 68 10621979 168 671 246 91 11761980 180 707 235 82 12041981 189 736 226 65 12171982 197 791 236 62 12871983 196 759 237 62 1253

1984 226 861 265 67 14191985 238 917 288 69 15121986 256 902 309 73 15401987 289 902 333 99 16221988 330 941 343 84 16981989 386 1119 388 98 19901990 404 1226 439 102 21701991 396 1151 454 98 20991992 442 1207 491 136 22761993 476 1160 515 116 22671994 531 1144 561 119 2354

1995 612 1140 645 122 25191996 657 1263 684 128 2732

Average annual growth (%): 1974-1996

1974-1980 7.5 7.8 9.5 7.4 7.91981-1990 8.6 5.9 6.6 3.3 6.21991-1996 8.6 0.7 7.7 5.0 4.0

1974-1996 8.3 5.0 7.7 4.9 6.1



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the prices of short-haul overseas travel are expected to be directly more competitive withthe prices of domestic travel than would be the prices of long-haul overseas travel. This

paper examines the substitution behaviour of Australian travellers with respect to long-haul and short-haul overseas holiday destinations. Unlike Hamal (1996 and 1997), thisstudy uses outbound travel demand models to test the substitution between domestic

holiday travel and overseas holiday travel to short-haul and long-haul destinations. In thisstudy, the USA and UK are chosen as long-haul destinations, whereas New Zealand,Indonesia, Singapore and Fiji are selected as short-haul destinations.

2. Outbound travel

In Australia, outbound travel accounts for about 40 per cent of total international travelwhich includes both short-term overseas arrivals and resident departures. In 1996, 4.2million overseas visitors arrived in Australia compared to 2.7 million short-term Australianresident departures. In recent times, the outbound travel sector has expanded more rapidlythan the domestic travel sector. The number of short-term resident departures has increased

by an average of 6.1 per cent a year since 1974, from 0.8 million in 1974 to 2.7 million in1996 (Table 2 and Figure 2). The number of business and VFR departures grew morestrongly than the number of holiday and other departures.

Table 2: Short-term resident departures 1974-1996

0

200

400

600

800

1000

1200

1400

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

Thousands

Holiday

VFR

Business

Other

According to a periodical analysis of the growth rates of outbound travel, the rate ofincrease in the number of short-term resident departures for holiday purposes has

continuously declined over the period, from 7.8 per cent a year during 1974-1980 to 5.9



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As mentioned earlier, there are several factors associated with situational constraints thatmay have a significant influence on outbound holiday travel. However, the major variablesincluded in the econometric models of outbound travel in this study are population, realincome, the domestic and overseas prices of travel and accommodation, and exchangerates. The econometric models presented in equations (1) to (4) are single equation modelswhich are specified in a simple double log linear functional form. The double log linear

function is chosen because it is easy to estimate, provides superior fit, and the estimatedparameters can be directly interpreted as elasticities. In addition, the double logarithmiclinear function has been widely used in empirical studies of tourism demand (e.g, Loeb1982; Witt and Witt 1992; Skene 1993; Kulendran 1995; Hamal 1996, 1996/97 and 1997).

All of the four models were initially estimated to choose the best one.

(1) LHit = i 0 + i1LYt + i2LPt + i3LQit + i4LEXit

(2) LHit = i0 + i1LYt + i2LPt + i3LQit

(3) LH it = i0 + i1LYt + i2LRPit + i3LEXit

(4) LH it = i0 + i1LYt + i2 LREXit

where LHitis the log of per capita short-term resident departures for holiday purpose to theith destination; LYtis the log of per capita real household disposable income in thousands;LPtis the log of the price index of domestic holiday travel and accommodation deflated byCPI; LQit is the log of the price index of holiday travel and accommodation in the ith

destination country proxied by that countrys CPI; LEXit is the log of the annual averageexchange rate in the ith countrys currency per Australian dollar; LRP it is the log ofrelative prices of travel and accommodation (Pt/Qit) in the ith country; and LREXitis thelog of the exchange rate weighted by the prices of domestic and overseas travel andaccommodation.

Population, which is expected to influence outbound travel demand positively, is includedin the models by presenting dependent and independent variables on a per capita basis.This procedure is followed to avoid the consequences of a collinearity between populationand income.

The domestic and overseas prices of travel and accommodation represent respectively thecross-price and own-price of holiday travel and accommodation. The coefficient of cross-

price variable measures the substitution between domestic and outbound holiday travel,whereas the coefficient of own-price variable measure a change in the number of outboundholiday travellers due to a change in the prices of overseas travel and accommodation. Theestimated coefficients of own-price and cross-price variables are expected to haverespectively a negative and a positive sign.

Exchange rate is another important economic factor which is likely to have influence onoutbound travel, because the purchasing power of outbound visitors varies with a variation



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in exchange rate. Hence the exchange rate, whose coefficient is expected to have a positivesign, is included in the above models.

Model (1) is a relatively full model in the sense that it includes income, prices andexchange rate variables on an individual basis, whereas the other three models eitherexclude the exchange rate variable or specify these variables in different forms to increase

the degree of freedom in their estimation process. The exchange rate is excluded in model(2); the domestic and overseas prices of travel and accommodation are combined togetherto form a single relative price variable in model (3); and the exchange rate is weighted bythe relative prices of travel and accommodation to form a proxy for the real effectiveexchange rate variable.

The exclusion of the exchange rate in model (2) is based on historical data on exchangerate and outbound travel to major destinations. Although the outbound holiday travel to theUK and USA and their respective exchange rates have widely fluctuated in the short-run,they have remained respectively up-ward and down-ward trended over a long period oftime, from 1974 to 1996 (Figures 4 and 5). The number of short-term resident departures

to the UK and USA for holiday purposes has increased over the last 23 years despite thedepreciation of the Australian dollar against the UK pound and US dollar. One possiblereason for such an inverse relationship between outbound holiday travel and the exchangerate could be that the influence of the exchange rate is immediately passed over to the

prices of holiday travel and accommodation as observed in recent months in some Asiancountries which were hit hard by the recent financial crisis.

4. Data

Outbound travel models were estimated using annual historical data from 1974 to 1996.Data on short-run resident departures, population, real household disposable income, the

prices of travel and accommodation in Australia and overseas, consumer price indices andexchange rates were obtained from publications of the Australian Bureau of Statistics(ABS), the World Bank and the International Monetary Fund .

Since a long time series of data on the prices of travel and accommodation is not readilyavailable for overseas countries, the prices were proxied by the consumer price indices ofthose countries.



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Figure 4: Outbound holiday travel to the United Kingdom andthe UK exchange rate

60

70

80

90

100

110

120

130

140

150

160

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

Residentdepartures(thousan

ds)

0.40

0.45

0.50

0.55

0.60

0.65

0.70

Exchangerate(Pound/A$)

Outbound holiday travel

Exchange rate

Figure 5: Outbound holiday travel to USA and US exchangerate

0

50

100

150

200

250

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

Resident

departures(thousands)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

Exchangerate(US$/A$)

Outobund hoilday travel

US exchange rate



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5. Model estimation and results

One of the basic assumptions of a regression model is that all of its model variables arestationary implying that the means, variances and covariances of the individual modelvariables are independent of the time period. If one or more variables are nonstationary,then the basic assumption falls apart and the estimated model will have the 'spurious

regression problem' (Granger and Newbold 1974). This means that the error term will behighly correlated. Although the estimated ordinary least square regression coefficientsremain unbiased, they become inefficient (Gujarati 1988, p. 363). The standard errors areincorrect and the estimated t, F and R2values can be seriously overstated. As a result, anyhypothesis test based on these statistics would be meaningless. The 'spurious regression

problem' can be overcome by using cointegration and error correction mechanismsrecently developed by Engle and Granger (1987).

Stationary series are also known as integrated series. If a series becomes stationary aftertaking its first difference, the series is called integrated of order one. The order ofintegration in a data series can be tested using two types of unit root tests: the AugmentedDickey-Fuller (ADF) unit root test (Dickey and Fuller 1979) and the Phillips-Perron (PP)unit root test (Phillips and Perron 1988). Among these, the PP unit root test was used totest the stationarity of model variables in this study. This is because the test does not createa serious problem of losing degrees of freedom while adding more lag terms to correct anautocorrelation problem in the regression model.

The unit root test results indicate that the model variables are integrated of different orders.In such a situation, a cointegration and error correction mechanism can not be used toderive the long-run and short-run parameters of outbound travel demand. Rather, themodels (1) to (4) were estimated as simple double log linear regression models on the

assumption that the estimated demand parameters remain unbiased. According to theregression results, models (3) and (4) were less useful than models (1) and (2) in terms oftheir predictive power and the signs of their estimated regression coefficients. Therefore,these models were not adopted to analyse outbound travel demand. The estimatedregression statistics of the remaining models are presented by destination in tables B1 toB6 in Appendix B and discussed briefly below.

United Kingdom

The UK models could not explain all the variation in outbound holiday travel to UK.

However, these models are a reasonably good fit with an adjusted R2value ranging from0.60 to 0.62. Among the two demand models, model (2) is chosen over model (1) becausethe exchange rate variable in model (1) has an unexpected sign. Model (2) suggests thatoutbound holiday travel to UK is positively influenced by income and the cross-price oftravel and accommodation and negatively by the own-price of travel and accommodation(Table A1 in Appendix). The estimated coefficients of all model variables are highlysignificant.

United States of America



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Both models of outbound holiday travel to USA show a very good fit with an adjusted R2value of 0.94 (Table A2 in Appendix). However, model (1) is chosen over model (2)

because the exchange rate variable has an expected sign for its estimated coefficient,though the coefficient is statistically insignificant. According to model (1), outboundholiday travel to USA is influenced positively by income, exchange rate and the cross-

price of travel and accommodation but negatively by the own-price of travel and

accommodation. However, the influence is observed to be statistically significant only inthe case of income and cross-price variables and not in the case of exchange rate and own-

price variables.

Fiji

The demand models of outbound holiday travel to Fiji are a reasonably good fit with anadjusted R2value ranging from 0.83 to 0.84 (Table A3 in Appendix). Since model (1) hasan expected sign for its exchange rate variable, the model is chosen over model (2). Inmodel (1), the estimated income and price elasticities are observed to be highly significant

and have the expected signs.

Indonesia

Both demand models of outbound travel to Indonesia have a high explanatory power withan adjusted R2 value of 0.99 (Table A4 in Appendix). However, model (1) is rejected infavour of model (2) because its exchange rate variable has an unexpected sign. With theexception of the own-price variable, all variables in model (2) have highly significantcoefficients with expected signs. In other words, outbound travel demand to Indonesia is

positively affected by income and the domestic price of travel and accommodation andnegatively by the price of travel and accommodation in Indonesia.

New Zealand

Like the UK models, the New Zealand outbound travel models do not have a highpredictive power, suggesting that there are some other factors influencing outbound traveldemand to New Zealand. The adjusted R2 value is observed to be 0.50 in model (1) and0.62 in model (2) (Table A5 in Appendix). Despite a relatively higher R2value, model (2)is rejected in favour of model (1), simply because the latter includes the exchange rate

variable with an expected sign. Short-term resident departures to New Zealand for holidaypurposes are observed to be positively influenced by income, exchange rate and the priceof travel and accommodation in Australia, whereas they are negatively influenced by the

price of travel and accommodation in New Zealand.

Singapore

Among the two demand models of outbound holiday travel to Singapore, model (1) ischosen over model (2), because model (1) has a relatively higher explanatory power and anexpected sign for the coefficient of its exchange rate variable (Table A6 in Appendix). As



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expected, the outbound travel to Singapore is positively influenced by income, exchangerate and the price of travel and accommodation in Australia, and negatively influenced bythe price of travel and accommodation in Singapore.

6. Demand elasticities of outbound travel

The estimated demand elasticities of outbound travel are summarised in Table 3. Onaverage, the number of resident departures is largely driven by the domestic prices oftravel and accommodation followed by the price of overseas travel and accommodationand real per capita income. The estimated income elasticities, which range from 0.63 to0.84, are positive and significant for all destinations except New Zealand and Singapore.The income elasticity of outbound travel to New Zealand is insignificant, whereas it isnegative and insignificant in the case of outbound travel to Singapore. That is, income isnot a driving



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Table 3: Estimated demand elasticities by destination

Destination

Income cross price own price Exchange

rate

Preferred

model

Long-haul

UK 0.840* 2.127* -1.828* -Model-2

(Adj-R2= 0.62)

USA 0.628* 1.755** -0.993 0.173

Model-1

(Adj-R2= 0.94)

Short-haul

Fiji 0.794* 2.348* -2.2339* 0.108Model-1

(Adj-R2= 0.83)

Indonesia 0.821* 1.870* -0.196 -

Model-2

(Adj-R2= 0.99)

New

Zealand

0.006 1.157** -1.043* 0.147

Model-1

(Adj-R2= 0.50)

Singapore UES 1.350* -0.349 1.417*

Model-1

(Adj-R2= 0.64)

UNE denotes an unexpected sign.

factor for Australian outbound visitors to New Zealand and Singapore. The major drivingfactors are the price of travel and accommodation in Australia and those countries.

As expected, the estimated own-price elasticities which measure a change in the number ofresident departures to an overseas destination with respect to a change in price of traveland accommodation in that destination have a negative sign suggesting that outboundholiday travel demand is negatively affected by the overseas prices of travel andaccommodation. The absolute value of cross-price elasticity ranges from 0.20 to 2.23.

The estimated cross-price elasticities which measure a change in the number of residentdepartures to a overseas destination with respect to a change in the domestic prices oftravel and accommodation show that outbound holiday travel is positively andsignificantly influenced by the domestic prices of travel and accommodation. This suggest

a substitution between domestic and outbound holiday travel. In other words, outbound



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travellers do include the domestic prices of travel and accommodation in their final choicesof outbound destinations.

However, Table 3 and Figure 4 do not present clear cut evidence that the magnitude andsignificance of the coefficient associated with travellers substitution behaviour isinversely

Figure 4: Cross-price elasticity and its significance levelby destination

0.0

0.5

1.0

1.5

2.0

2.5

New

Zealand

Fiji Indonesia Singapore USA UK

Elas

ticity

0

0.04

0.08

0.12

0.16

Significa

ncelevel

Elasticity Significance level

related to travel distance to outbound destinations. Considering Sydney as a referencepoint to measure the distance between Australia and overseas destinations, the UK is muchfurther away than Indonesia, New Zealand and Singapore, yet it has a relatively largercross-price elasticity. Also, the level of significance of the cross price elasticity isrelatively higher in the UK model than in the New Zealand model. On the other hand, ifonly USA, Fiji and Indonesia are considered in the analysis of outbound travel demand,then there is evidence of an inverse relationship between travellers substitution behaviourand travel distance to outbound destinations.

One of the reasons for such mixed evidence could be that some models (UK, New Zealandand Singapore) have not fully explained the variation in outbound travel demand. Theadjusted R2 value is relatively low in these models ranging from 0.50 to 0.64 (Table 3).This means that the magnitude and significance level of cross price elasticity could bedifferent if some more variables were added in these models to increase their explanatory

power. In other words, the comparison of elastiicities between models with differentexplanatory power may not be a reasonable way to test the above hypothesis. Therefore,models with an adjusted R2 value of more than 0.80 are considered in this study tocompare the estimated cross price elasticities. The comparison is shown in Figure 5 whichclearly indicates that the further away an overseas holiday destination is, the less likely it isto be a substitute for a domestic holiday destination. In other words, Australian outbound

travellers are very sensitive to domestic prices of travel and accommodation while



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selecting a short-haul overseas holiday destination such as Fiji and Indonesia, but not somuch while choosing long-haul destinations such as USA.

7. Conclusions

The available information suggests a substitution between outbound and domestic holidaytravel in Australia. During 1979 to 1993, the domestic holiday trips remained flat while thenumber of resident departures for holiday purposes increased by 4.2 per cent a year. Thesubstitution behaviour of domestic holiday makers has been statistically tested in previousstudies but on an aggregate level, without due attention to whether an outbound destinationis

Figure 5: Cross price elasticity and its significance levelby destination

0.0

0.5

1.0

1.5

2.0

2.5

Fiji Indonesia USA

Elasticity

0

0.04

0.08

0.12

0.16

Significancelevel

Elasticity Significance level

a long-haul or short-haul destination. In this study, the substitution behaviour of outboundholiday travellers has been analysed with an emphasis on long-haul versus short-hauldestinations. The substitution behaviour of outbound holiday travellers is likely to change

by travel distance between domestic and outbound destinations.

The number of resident departures is observed to be largely driven by the domestic pricesof travel and accommodation followed by the prices of overseas travel and accommodationand real per capita income. Income was not observed as a significant factor in the case ofoutbound travel to New Zealand and Singapore. The estimated own-price elasticities werefound to have expected signs suggesting that the outbound holiday travel demand isnegatively influenced by the price of travel and accommodation in overseas destinations.

The estimated cross-price elasticities which measure the substitution between domesticand outbound holiday travel demand show that outbound holiday travel is positively and

significantly influenced by the domestic price of travel and accommodation. In other



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words, outbound travellers do substitute overseas destinations for domestic ones. However,there is no clear cut evidence suggesting that the magnitude and significance of acoefficient associated with travellers substitution behaviour is inversely related to traveldistance to outbound destinations. This could have resulted from defects in the estimatedmodels of outbound holiday travel to the UK, New Zealand and Singapore. These modelshave not fully explained the variation in outbound travel demand. If the results from these

models are excluded from the analysis of outbound travel demand, then there exists clearcut evidence on the inverse relationship between the magnitude and significance ofsubstitution and travel distance to outbound destinations. In summary, Australian outboundtravellers are very sensitive to the domestic price of travel and accommodation whileselecting a short-haul overseas holiday destination, but less sensitive while choosing long-haul destinations.



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References

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Dickey, D., and W.A. Fuller (1979). Distribution of the Estimates for Autoregressive Time Series with a

Unit Root.Journal of the American Statistical Association74: 427-431.Engle, R.F., and C.W.J. Granger (1987). Cointegration and Error Correction: Representation, Estimation and

Findings.Econometrica 55: 251-276.

Granger, C.W.J., and P. Newbold (1974). Spurious Regressions in Econometrics. Journal of Econometrics

2: 111-120.

Gujarati, Damodar N. (1988),Basic Econometrics,Second ed., McGraw-Hill, Singapore.

Hamal, K. (1996), Substitutability Between Domestic and Outbound Travel in Australia, a working paperpresented at the Australian Tourism and Hospitality Research Conference, Coffs Harbour, Australia, 6-9

February.

Hamal, Krishna (1996/97),Modeling Domestic Holiday Tourism Demand in Australia: Problems and

Solutions,Asia Pacific Journal of Tourism Research,1(2), 35-46.

Hamal, K. (1997), Substitutability Between Domestic and Outbound Travel in Australia,Pacific Tourism

Review,1(1), 23-33.

Hansen, F. (1976). Psychological Theories of Consumer Choice.Journal of Consumer Research 3: 117-142.

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335-346.

Skene, J. (1993). Time Series Properties, Demand and Forecasts: Short-Term Visitors to Australia from New

Zealand.Working paper no. 86. Canberra: Bureau of Industry Economics.Skene, J. (1996). Estimating Tourisms Economic Contribution,Research Paper No. 2, Bureau of Tourism

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Um, S., and J.L. Crompton (1990). Attitude Determinants in Tourism Destination Choice. Annals of Tourism

Research17: 432-448.

Um, S., and J.L. Crompton (1992). The Roles of Preceived Inhibitors and Facilitators in Pleasure Travel

Destination Decisions.Journal of Travel Research30: 18-25.

Witt, S.F., and C.A. Witt (1992). Modeling and Forecasting Demand in Tourism.London: Academic PressLimited.

Woodside, A.G., and S. Lysonski (1989). A General Model to Traveller Destination Choice. Journal of

Travel Research 27: 8-14.



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Appendix

Table A1: Regression statistics of holiday models: United Kingdom

Variable

Estimated

coefficient T-ratio

Significance level Other statistics

MODEL (1)LY_AU 1.199 2.702 0.02 N= 23

LP_AU 2.685 2.367 0.03 Adj-R2= 0.60LQ_UK -2.462 -2.272 0.04 DW = 1.73

LEX_UK -0.558 -1.580 0.13

INTERCEPT -2.399 -1.732 0.10

MODEL (2)

LY_AU 0.840 2.145 0.05 N= 23

LP_AU 2.127 1.904 0.07 Adj-R2= 0.62LQ_UK -1.828 -1.741 0.10 DW = 1.85

INTERCEPT -1.471 -1.151 0.26

Table A2: Regression statistics of holiday models: United States

Variable

Estimated

coefficient T-ratio


MODEL (1)LY_AU 0.628 1.949 0.07 N= 23LP_AU 1.755 1.465 0.16 Adj-R2= 0.94

LQ_US -0.993 -0.632 0.54 DW = 2.16LEX_ US 0.173 0.440 0.67

INTERCEPT -3.020 -1.616 0.12

MODEL (2)LY_AU 0.638 2.014 0.06 N= 23LP_AU 1.516 1.352 0.19 Adj-R2= 0.94

LQ_ US -0.762 -0.498 0.62 DW = 2.21INTERCEPT -3.049 -1.623 0.12

Table A3: Regression statistics of holiday models: Fiji

Variable

Estimated

coefficient T-ratio


MODEL (1)LY_AU 0.794 5.575 0.01 N= 23

LP_AU 2.348 3.530 0.01 Adj-R2= 0.83LQ_FJ -2.233 -3.044 0.01 DW = 2.16

LEX_ FJ 0.108 0.345 0.73INTERCEPT 0.546 0.603 0.55

MODEL (2)

LY_AU 0.776 6.859 0.01 N= 23

LP_AU 2.166 6.340 0.01 Adj-R2= 0.84

LQ_ FJ -2.029 -5.399 0.01 DW = 2.20

INTERCEPT 0.332 0.5000 0.62



23/23

Table A4: Regression statistics of holiday models, Indonesia

Variable

Estimated

coefficient T-ratio


MODEL (1)LY_AU 0.723 3.666 0.01 N= 23

LP_AU 1.758 3.815 0.01 Adj-R2= 0.99

LQ_ID -0.001 -0.004 0.99 DW = 2.03

LEX_ ID -0.177 -0.882 0.39INTERCEPT -6.830 -4.590 0.01

MODEL (2)

LY_AU 0.821 5.297 0.01 N= 23

LP_AU 1.870 4.313 0.01 Adj-R2= 0.99

LQ_ ID -0.196 -0.595 0.56 DW = 2.11INTERCEPT -7.927 -10.260 0.00

Table A5: Regression statistics of holiday models, New Zealand

Variable

Estimated

coefficient T-ratio


MODEL (1)LY_AU 0.006 0.035 0.97 N= 23

LP_AU 1.157 1.636 0.12 Adj-R2= 0.50

LQ_NZ -1.043 -1.874 0.08 DW = 1.76

LEX_ NZ 0.147 0.468 0.65INTERCEPT 1.362 1.689 0.11

MODEL (2)

LY_AU 0.096 0.876 0.39 N= 23

LP_AU 0.933 1.817 0.09 Adj-R2= 0.62

LQ_ NZ -0.846 -2.178 0.04 DW = 2.14

INTERCEPT 1.316 1.824 0.08

Table A6: Regression statistics of holiday models, Singapore

Variable

Estimated

coefficient T-ratio


MODEL (1)LY_AU -0.285 -0.837 0.41 N= 23

LP_AU 1.350 2.148 0.05 Adj-R2= 0.64LQ_SN -0.349 -0.270 0.79 DW = 1.66

LEX_ SN 1.417 2.358 0.03

INTERCEPT -3.433 -0.753 0.46

MODEL (2)

LY_AU 0.130 0.338 0.74 N= 23

LP_AU 0.459 0.721 0.48 Adj-R2= 0.61LQ_ SN -0.671 -0.391 0.70 DW = 2.04

INTERCEPT 1.704 0.329 0.75

98.2 outbound travel

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