econometric forecasts

Annals of Tourtsm Research, Vol. 19, pp. 450-466, 1992 0160-7383192 $5.00 + .oo Printed in the USA. All rights reserved. Copyright 0 199’2 Pergamon Press Ltd.

ECONOMETRIC FORECASTS Tourism Trends to 2000

Egon Smeral Austrian Inst. for Economic Research, Austria

Stephen F. Witt University of Wales, UK

Christine A. Witt University of Bradford, UK

Abstract: A complete system of demand equations is specified in order to generate forecasts of tourism imports and exports for various major geographical areas. The forecasts are presented for the period 1991-2000 under three alternative assumptions-there is no change in the external environment (baseline scenario), the completion of the single internal market of the European Community takes place, and the recent liberalization and general creation of market economies in Eastern Europe is allowed for. A comparison of the latter two scenarios with the baseline scenario permits the calculation of the effects of these changes on tourism demand. Keywords: tourism forecasts, system of demand equations, Eu- ropean Community internal market, Eastern Europe.

Rtsumt: Previsions econometriques: tendances du tourisme jusqu’a l’an 2000. On precise un systtme complet d’equations de demande afin de gCnCrer des previsions des importations et d’exportations de tourisme pour quelques regions gtographiques majeures. On fait des previsions pour les annees 1991-2000 sous trois suppositions alternatives: il n’y a aucun changement du milieu exttrieur (scenario de base); on realise un seul march6 interne pour la Communautt Europtenne; on prend en consideration les evCnements r&cents de la libtralisation et la creation gtntrale des economies du march6 en Europe de l’Est. Une comparaison entre les deux derniers scenarios et le scenario de base permet le calcul des effets de ces changements sur la demande du tourisme. Mots-cl&: previsions du tourisme, systtme d’equations de demande, march6 interne de la Communautt Europienne, Europe de l’Est.

INTRODUCTION

The planned completion of the single internal market for goods, services, people, and capital of the European Community (EC) by December 3 1, 1992, will result in a major change in the economic

Egon Smeral (Austrian Institute for Economic Research, A-1103 Postfach 91, Vi- enna, Austria) is a member of the Scientific Staff of the Institute and Lecturer in Tourism at the Vienna University of Economics. Stephen Witt is Lewis Professor of Tourism Studies, University of Wales, Swansea, UK. Christine Witt is Lecturer in Operations Management, University of Bradford.

450

SMERAL, WITT AND WITT 451

environment. The final removal of internal market barriers will result in the creation of a competitive market place similar to that of the United States; therefore, it will provide a major economic challenge for both EC and non-EC members. It is questionable whether all the goals of the program announced in the White Paper of 1985 (European Commission 1985) will be accomplished by the 1992 deadline, in particular the harmonization of indirect taxes, unification of the monetary system, and the control of mergers. But the EC’s economic system and environment will change dramatically, with the result that insiders will gain in welfare terms, and outsiders will lose. The removal of the internal barriers will create a new competitive environment for the tourism industry and will have marked effects on international travel patterns.

The unprecedented political changes that took place in Eastern Eu- rope in 1989 are also likely to have a major impact on the economic environment. The general creation of market economies in Eastern Europe, together with the unification of the German Federal Republic and the German Democratic Republic, are likely to have a marked effect on economic growth. But there is some uncertainty regarding the precise impact. For example, the extent of capital and technology transfer from the West to Eastern Europe in order to bring about economic restructuring will be a major determinant of the rates of growth of real gross domestic product (GDP).

This article assesses the impact on world tourism demand of the completion of the internal market of the EC at the end of 1992, together with the effects resulting from the recent political changes in Eastern Europe. The impacts are described by means of three scenarios: a baseline scenario that assumes the current state of affairs remains unchanged, an EC completion scenario, and a growth scenario (which reflects the new Eastern Europe dimension). The effects on tourism of the completion of the internal market are given by the deviation of the EC completion scenario from the baseline scenario. The impact of the recent political changes in Eastern Europe on tourism demand can be seen by comparing the growth scenario with the baseline scenario.

COMPLETION IMPACT OF THE SINGLE MARKET

In order that completion of the single internal market should take place, three types of barriers are to be eliminated: material barriers (controls and formalities with regard to international travel and foreign trade), technical barriers (e.g., different industry standards, national pro- tection in the case of public sector purchases, public subsidies contrib- uting to biased competition, and incomplete liberalization in the financial and transport services sectors), and tax barriers (different rates of value added tax and other indirect taxes).

The removal of these barriers together with the emergence of new competitive incentives will have four main effects: one, a marked re- duction in costs as a result of better exploitation of economies of scale in production; two, improved efficiency in enterprises, rationalization of industrial structures, and the setting of prices closer to the costs of production, all resulting from more competitive markets; three,

452 ECONOMETRIC FORECASTS

adjustments among industries on the basis of the changes in compara- tive advantage which come about in the new integrated market; and, four, a flow of innovations, new processes, and new products stimu- lated by the dynamics of the internal market.

These four effects will liberate resources for alternative productive use, which in turn will raise the total sustainable levels of consumption and investment in the EC economy. The Cecchini Report (Cecchini 1988) quantifies the potential economic gains of the single internal market, and postulates a minimum expected increase in the overall EC GDP of about 4.5 % and an expected decrease in the price level of approximately 6 %.

The general effects of the completion of the single European market have been considered so far, but not the expected impacts on tourism. The main impacts are several. One, travel will become cheaper as a result of various direct and indirect cost-saving effects. There will be lower cost inputs for the tourism industry (e.g., a cheaper labor force and capital available at lower interest rates). The major indirect cost- saving effects will arise through economies of scale and greater competition. Two, travel will become easier through the removal of controls at frontiers between EC member countries; standardized health, acci- dent, and liability insurances; EC passport; the general provision of medical care in emergency situations; and the use of the ECU as a currency medium. Three, access to travel information and reservations will improve because of the standardization of electronic information and reservation systems. Four, tourism supply will become more dif- ferentiated, so tourists will benefit from increased choice. Finally, the higher incomes received by EC citizens will increase tourism demand.

MODEL SPECIFICATION AND ESTIMATION PROCEDURE

In order to calculate long-term forecasts (to the year 2000) of tourism trends for the baseline scenario, the EC internal market completion scenario, and the Eastern Europe growth scenario, an econometric model of world tourism is developed. The model comprises a complete system of demand equations. As such, it provides a consistent model setting for the estimation of international tourism flows, in that all the tourism demand created in the generating countries considered in the study is allocated to the receiving countries and the “rest of the world” (i.e., the “adding up” condition is satisfied).

By far, the majority of previous econometric studies of the demand for international tourism utilize individual disaggregated demand equations (Little 1980; Loeb 1982; Martin and Witt 1987, 1988; Papa- dopoulos and Witt 1985; Stronge and Redman 1982; Uysal and Crompton 1984; Witt and Martin 1987), but such models would not permit simulations to explore the EC completion and Eastern Europe growth effects in a consistent international setting. Notable exceptions include the work of O’Hagan and Harrison (1984), Smeral (1988, 1989, 1990), van der Stelt and Velthuijsen (1989), van Soest and Kooreman (1987), and White (1985). In these studies, complete systems of demand equations are developed to explain tourist behavior.

The pioneering work of Stone (1954) in estimating a system of demand equations that was derived explicitly from consumer theory (the


linear-expenditure system) has been followed by various alternative specifications. O’Hagan and Harrison (1984) and White (1985) use the Almost Ideal Demand System developed by Deaton and Muellbauer (1980), whereas van der Stelt and Velthuijsen (1989) adopt the Rotter- dam model. Smeral (1988, 1989) and van Soest and Kooreman (1987) develop their own systems of demand equations.

The system of demand equations used in this article to forecast tourism trends to the year 2000 is a modified version of the linear- expenditure system, which is relatively easy to operationalize and, hence, is an ideal tool for practical forecasting purposes. In common with other complete systems of demand equations, the model incorporates the assumption of a two-stage budgeting process. In the first step, the volume of demand for domestic and foreign tourism goods and services by the consumers in the origin countries is determined, and, in the second step, the country of destination is determined by the prices of tourism goods and services in all possible destinations and the foreign travel budget restriction (Smeral 1988). The latter denotes the total amount of income that a consumer has allocated for spending on foreign travel.

International tourism demand is measured in terms of balance of payments figures, with inbound tourism being regarded as an export (travel credit items) and outbound tourism as an import (travel debit items). The main factors influencing tourism demand are income and relative prices (including the impact of exchange rates), as well as various special events. It is standard practice in demand analysis to include income and price as explanatory variables. However, in the case of tourism, there are two elements of price-those costs incurred by tourists while at the destination and those costs involved in reaching the destination. This study is limited to the first price element. Further- more, in addition to the own price effect, the impact on demand of prices of substitutes is particularly important in the case of tourism (which is discussed at some length in Martin and Witt 1988). Thus, the price variable is specified in relative form. On account of data availability and the restricted number of degrees of freedom available for use in estimation, the econometric model developed in this article is limited to income, relative tourist prices, and special events.

The approach adopted here should, therefore, be regarded as a first cut at the problem, and further work is required in order to make the models more realistic. In particular, the Martin and Witt (1988) study suggests that origin-destination transport costs should be included in the model in a similar form to the price indices specified in equations (1) and (2) 1 a er. t In fact, Martin and Witt (1988) also include the previous year’s tourism demand value and a separate exchange rate variable in the potential explanatory variable set. The lagged depen- dent variable reflects habit persistence and supply constraints. Ex- change rate is sometimes justified as a separate explanatory variable on the grounds that people are more aware of exchange rates than relative costs, and are driven to use the former as a proxy for the latter (even though it takes no account of relative inflationary movements). However, the empirical results obtained by Martin and Witt (1988) show that the previous year’s tourism demand value is not an important influence on tourism demand, and most previous research con-


cerned with modeling international tourism demand does not include exchange rate as an explanatory variable per se. With regard to transport cost, this variable is often omitted on the grounds of lack of data availability and potential multicollinearity problems (see, e.g., Uysal and Crompton 1984).

Econometric forecasting models are appropriate for the large changes in the causal variables that might be expected to take place over the period to the year 2000. In addition, the future directions of change of the causal variables can be accurately predicted, and reason- able estimates can be made regarding the magnitudes of the changes.

The model explains tourism flows to and from 18 major industrial countries (i.e., each country is considered as both a generator and a destination): Australia, Austria, Belgium, Canada, Denmark, Fin- land, France, Germany, Greece, Italy, Japan, The Netherlands, Nor- way, Spain, Sweden, Switzerland, United Kingdom, United States.

The demand system comprises 36 behavioral equations (one tourism import and one tourism export equation per country) and three definitional equations. The behavioral equations are specified in linear form and are estimated over the period 1975-1988 using annual data. Al- though the use of only 13 periods to estimate the model parameters may be criticized, this is regarded as a “second-best” solution. Ideally, a longer run of data would be preferable in terms of obtaining more reliable parameter estimates and forecasts, and indeed it would be possible to obtain data as far back as the 1950s. However, in the early 197Os, largely as a result of the first oil crisis, there were massive changes in the world economic environment (inflation on a scale not experienced in recent previous history, the breakdown of the Bretton Woods world money order, etc.). As a result, the elasticities associated with international tourism demand are likely to have changed. It was, therefore, decided to restrict the estimation period to 1975 onwards; less reliable coefficient estimates (i.e., coefficient estimates with higher variances) were thought preferable to biased coefficient estimates.

The model specification is as follows:

Importfunctions (generating countries)

Ml, = alj + azjYj[ + a3jRPGjl + tidjDVj:.t + Uj, (1)

Export functions (destination countries)

X;, = @Ii + PziTMt + P3iRPD;t + P,iDT/;, + Ui, (2)

Definitional equations 18

c M,, = TM, (3) j=l

18

c Xi, = TX, i=l

(4)

ROW = TM, - TX, (5)


j = 1,2, . . . , 18

i = 1,2, . . . , 18

t = 1,2, . . . , 14 (1 = 1975, . . . , 14 = 1988)

is tourism imports of generating country j in year t (US$ billion, 1980 prices) is GDP of generating country j in year t (US$ billion, 1980 prices) is the relative price index of generating country j in year t expressed as the ratio of price of tourism imports to the price of consumer goods and services, including domestic travel in US$(1980 = 100) is a dummy variable or trend variable for generating country i in year t is tourism exports of destination country i in year t (US$ billion, 1980 prices) is total tourism imports of the 18 generating countries in year t (US$ billion, 1980 prices) is the relative price index for destination country i in year t expressed as the ratio of country i prices to the other (compet- ing) destination country prices in US$ (1980 = 100) is a dummy variable or trend variable for destination country i in year t is total tourism exports of the 18 destination countries (US$ billion, 1980 prices) is net tourism imports from the rest of the world (US$ billion, 1980 prices) are random disturbance terms, and CYY,, . . . , CY+ and PI, . . . 7 f14 are unknown parameters.

The various price indices are weighted by current market shares. A dummy variable or trend variable is included in those tourism import or export functions where the preliminary empirical results indicated that this resulted in noticeable model improvement. The dummy variables represent events such as the energy crises of 1974 (which had an impact for some time afterward) and 1979 (Martin and Witt 1988) and the recession of the early-mid-1980s. These events caused considerable uncertainty and are, therefore, likely to have had a depressing influence on tourism demand. The trend variable may reflect a steady change in the popularity of a destination over the period as a result of changing tastes, and may take on either a positive or negative coefficient. A dummy or trend variable was not included in the initial regres- sions. But wherever examination of the residuals indicated problems, an appropriate dummy/trend variable was included if there was theo- retical justification. For example, the 1974 oil crisis is likely to have affected some origins/destinations more than others, and the effect may have lasted longer for some origins/destinations than others. Only


empirical investigation can show whether this oil crisis did have a statistically significant impact on tourism imports/exports, and how long the effect lasted.

The value of total tourism imports for all the 18 generating countries features as an explanatory variable in the tourism export functions as a result of the two-stage budgeting process. This variable repre- sents the foreign travel budget restriction. The data sources used in model estimation are the online databases of the Organisation for Eco- nomic Cooperation and Development (OECD) and the Internation- al Monetary Fund (IMF). The 36 behavioral equations are estimated individually, using ordinary least squares; then, the complete system of demand equations is solved iteratively, using the Gauss-Seidel method.

EMPIRICAL RESULTS FOR MODEL ESTIMATION

The empirical results corresponding to the estimation of model 1 for the 18 generating countries are given in Table 1. The income coefficient is always positive and statistically significant at the 5% level. The relative price index coefficient has the expected negative sign for all generating countries other than Spain, and is statistically significant at the 5 % level in most cases. It appears that price is not an important determinant of tourism imports for Spain, and the lack of statistical significance at the 5% level for the relative price coefficients for Japan and the United States casts some doubt over the importance of this variable for these generating countries. Dummy variables were intro- duced for 6 of the 18 generating countries: Belgium, Finland, Ger- many, Italy, Sweden, and Switzerland. For example, a dummy variable was included for Sweden that took the value one for 1975-1976 (representing the 1974 oil crisis) and 1983-1986 (representing the early-mid-1980s recession), and zero in all other years. For Italy, the dummy variable took the value one for 1981-1986 (representing the early-mid- 1980s recession), and zero in all other years. The remaining dummy variables featured in the tourism import functions tended to follow one of these two patterns. The R2 values generally indicate a high goodness-of-fit for the estimated equations; exceptions occur for France, Japan, and the United States. The values of the Durbin- Watson statistic are satisfactory for most countries but indicate that serial correlation may be present in some cases, especially the equation for Japan.

The estimated results for the tourism export functions, as given in equation 2, are presented for the 18 destination countries in Table 2. The income coefficient has the expected positive sign and is signifi- cantly different from zero at the 5% level in each case. The relative price coefficients are “correctly” signed and statistically significant at the 5% level in most cases. However, price influences are not noticeable in the export functions for Greece, Japan, and Norway; for Spain, the 1 value is relatively low. Dummy variables are present for 14 out of the 18 tourism export equations: Australia, Austria, Denmark, Finland, France, Germany, Greece, Italy, Japan, The Netherlands, Spain, Switzerland, United Kingdom, and United States. For exam-


Table 1. Estimated Tourism Import Equations

Generating Country Constant

Explanatory Variables

Y RPG DV R2 D. W.

Australia

Austria

Belgium

Canada

Denmark

Finland

France

Germany

Greece

Italy

Japan

The Netherlands

Norway

Spain

Sweden

Switzerland

United Kingdom

United States

1.712 0.016 - 0.023 (8.30) (8.33) (- 8.69) 2.018 0.045 - 0.035

(1.24) (6.95) (- 2.42) 0.760 0.053 - 0.037

(1.35) (6.95) (-6.57) 6.982 0.013 - 0.068

(6.87) (3.93) (- 6.73) - 0.446 0.065 - 0.025

(-0.69) (9.02) (- 4.20) - 0.021 0.037 - 0.013

(-0.11) (19.73) (- 7.56) 7.398 0.015 -0.111

(5.16) (3.81) (- 3.98) 11.603 0.024 -0.143

(11.00) (10.92) (- 7.04) - 0.344 0.033 - 0.006

(-2.25) (6.10) (-2.40) -2.197 0.019 - 0.042

(-1.76) (11.89) (-4.50) - 4.522 0.012 - 0.039

(-0.59) (3.41) (-0.71) - 2.657 0.067 - 0.045

(-2.94) (8.59) (- 3.91) 0.836 0.053 - 0.023

(2.38) (16.75) (-5.91) - 3.031 0.019

(- 10.02) (14.09) -3.348 0.065 - 0.024

(-8.02) (13.68) (- 5.50) - 2.302 0.079 - 0.035

(-4.57) (30.87) (- 7.66) -5.734 0.043 -0.110

(-3.48) (21.60) (- 10.74) - 9.988 0.012 - 0.097

(- 1.40) (6.17) (-1.70)

- 0.323 (-3.70)

-0.145 (-5.11)

- 0.944

(-6.44)

- 0.872 (-6.12)

- 0.360 (-5.96)

- 0.240 (-5.21)

0.885 2.10

0.865 1.87

0.882 1.93

0.818 1.19

0.886 1.22

0.980 2.34

0.598 1.52

0.948 1.90

0.821 1.48

0.956 2.22

0.740 0.80

0.889 1.28

0.964 1.83

0.943 1.59

0.961 2.74

0.990 1.73

0.983 2.10

0.789 1.15

Note: The values in parentheses are t statistics.

ple, a dummy variable was included for Switzerland that took the value one for 1975-1977 (representing the 1974 oil crisis) and 1979 (representing the later oil crisis), and zero for all other years. For The Netherlands, the dummy variable took the value 1 for 1979-1983 (representing the later oil crisis and the early-mid-1980s recession), and zero in all other years. The dummy variables featured in the other tourism export functions also tended to follow one of these two patterns. The R2 values indicate a high level of goodness-of-fit for most of the equations; exceptions occur for Finland, Greece, and Italy. There are no extremely high or low values for the Durbin-Watson statistic.


Table 2. Estimated Tourism Export Equations

Destination Country Constant

Explanatory Variables

TM RPD DV R2 D. W.

Australia

Austria

Belgium

Canada

Denmark

Finland

France

Germany

Greece

Italy

Japan

The Netherlands

Norway

Spain

Sweden

Switzerland

United Kingdom

United States

- 0.242 0.024 (-0.55) (10.73)

7.598 0.028 (8.29) (8.70) 2.071 0.022

(4.82) (9.58) 1.868 0.025

(3.11) (6.52) 2.073 0.009

(8.57) (9.31) 1.453 0.003

(4.23) (2.32) 16.757 0.075 (6.16) (9.12) 5.155 0.044

(5.05) (11.86) 0.881 0.011

(4.16) (4.50) 16.843 0.075 (3.27) (3.10)

- 0.669 0.018 (-9.59) (21.41)

4.406 0.006 (11.33) (3.82)

0.158 0.008 (1.77) (7.07) 0.958 0.152

(0.29) (12.29) 2.873 0.017

(6.96) (9.68) 4.398 0.022

(6.64) (7.33) 6.336 0.070

(4.71) (9.45) 6.382 0.183

(3.39) (11.87)

- 0.006 (-2.15)

- 0.036 (-3.71)

- 0.019 (-5.78)

- 0.009 (-2.32)

- 0.013 (-5.87)

-0.010

(-2.72) -0.146

(-5.86) - 0.033

(- 3.81)

-0.136 (-2.11)

- 0.030 (-9.67)

- 0.042 (-1.18)

- 0.032 (-9.82)

-0.027 (-3.89)

- 0.044 (-3.13)

- 0.079 (- 5.87)

- 0.267 (-4.36)

- 0.535 (-5.72)

-0.134 (-3.65)

-0.071 (-2.19)

- 1.061 (- 4.96)

- 0.451 (-4.38)

- 0.360 (-4.71)

- 1.867 (-3.89)

-0.112 (-4.29)

- 0.237 (-5.60)

- 1.267 (-3.26)

- 0.363 (-3.95)

- 1.124 (- 5.03)

-2.318 (- 4.87)

0.961 1.30

0.911 1.53

0.957 1.87

0.822 1.59

0.947 1.52

0.524 1.33

0.960 2.40

0.959 2.31

0.796 2.18

0.690 1.73

0.977 2.69

0.964 1.83

0.806 1.17

0.939 1.70

0.978 1.91

0.927 1.45

0.915 2.26

0.963 2.26

Note: The values in parentheses are t statistics.

FORECASTS TO THE YEAR 2000

Baseline Scenario

The average annual growth rate of European gross domestic product (GDP) is expected to accelerate to almost 3% a year throughout the 199Os, whereas that of Canada and the United States is expected to decline (Table 3). Economic growth in Europe during the current decade is expected to be faster than that in North America (in contrast


Table 3. Average Growth Rate per Year of Real GDP (Percentage Increases)

Countries 1981-1990 1991-2000

9 EC countries 2.3 2.9 14 European countries 2.3 2.8 Australia 3.1 3.4 Japan 4.2 4.0 Canada 3.2 2.4 United States 3.0 2.5 4 Non-European countries 3.3 3.0 All Countries 2.9 2.9

Sources: On-line databases of the OECD, IMF, Economic Commission for Europe and Austrian Institute for Economic Research, plus authors’ estimates.

to the 198Os), but slower than in Australia and Japan. It is generally expected that continental Europe and the Pacific Basin will be the dynamic heart of the world economy during the 1990s.

The baseline scenario assumes constant relative prices throughout the period to the year 2000. Examples of relative prices for tourism imports and exports over the period 1975-1988 are given in Tables 4 and 5, respectively. The data are presented for 5 of the 18 countries: Austria, Canada, France, United Kingdom, and United States. Al- though they display considerable movement, there do not seem to be any clear trend patterns in the time series. In such circumstances, and in the absence of any prior knowledge regarding likely future movements in relative prices (as is the case with the baseline scenario), standard practice is to assume that relative prices remain constant.

As far as the dummy/trend variables are concerned, it is assumed that all future values are zero, except in the cases of Austria and

Table 4. Relative Prices: Tourism Imports

Year Austria Canada France United United

Kingdom States

1975 101.3 68.0 86.2 112.0 78.6 1976 97.0 59.9 87.3 118.9 72.7 1977 95.3 67.2 93.0 118.4 76.6 1978 98.2 80.3 94.2 118.9 86.4 1979 101.5 92.7 100.5 118.1 95.3 1980 100.0 100.0 100.0 100.0 100.0 1981 103.4 85.7 105.0 93.5 85.2 1982 103.7 77.0 110.8 96.2 77.7 1983 101.4 68.1 107.6 96.9 70.5 1984 98.8 63.6 108.9 100.7 62.7 1985 98.3 65.6 107.2 99.8 61.5 1986 97.6 80.9 104.1 111.8 76.2 1987 95.3 86.9 103.2 114.2 86.4 1988 94.9 85.0 108.9 106.7 91.0


Table 5. Relative Prices: Tourism Exports

Year Austria Canada France United

Kingdom United States

1975 96.9 127.4 100.9 82.0 110.1 1976 99.3 139.1 97.6 76.5 114.6 1977 104.7 128.2 95.7 79.2 112.3 1978 106.2 112.1 98.0 81.1 104.1 1979 102.7 102.2 98.7 87.1 99.4 1980 100.0 100.0 100.0 100.0 100.0 1981 92.0 116.3 93.4 102.6 117.0 1982 92.7 128.1 88.5 99.1 127.0 1983 95.2 142.0 87.4 94.1 137.2 1984 94.2 147.2 85.7 90.5 149.4 1985 93.1 143.7 87.3 91.7 153.2 1986 102.2 117.2 92.5 86.3 124.3 1987 106.4 108.9 93.6 85.1 109.5 1988 104.0 114.4 90.9 91.1 106.8

Switzerland. For these two Alpine countries, it is assumed that there is a change in tastes in their favor. They are well established holiday destinations and have the advantage of a relatively healthy environment, particularly in comparison with Mediterranean countries. It is expected that the state of the environment will play an increasing role in determining holiday choice in the future. The impact of the good environmental conditions is assumed to be stronger for Austria than Switzerland. Some environmental deterioration has taken place in the Swiss Alps, and Austria has more open space, unspoiled countryside, and so on. It is also assumed that the EC does not gain any new members before 2000. (The latter is a working hypothesis that reflects the present state of knowledge, but, e.g., political developments may result in the EC entering into a loose confederation with the European Free Trade Association [EFTA] countries and those in the former Eastern Bloc .)

EC Completion Scenario

It is assumed that the impact of the completion of the internal market will continue until 2000. The formation of the single European market will result in an increase in the growth rate of GDP for EC member countries (particularly those in Southern Europe) and also European non-EC countries, but with the EC countries showing the largest gains. The completion of the EC internal market is not expected to affect GDP growth rates for non-European countries. The values selected in this study should be regarded as the minimum increases likely to occur. The additional annual GDP growth for the years 1993-2000 is assumed to be as follows. Non-European countries: Australia, Canada, Ja- pan, United States: 0.0%. Non-EC European countries: Austria, Finland, Norway: 0.2%; and Sweden, Switzerland: 0.3%. EC countries: Bel- gium, Denmark, Germany, The Netherlands, United Kindom: 0.5%; France: 0.6%; and Greece, Italy, Spain: 0.7%.


The EC completion scenario also allows for a change in the relative prices of tourism imports and exports, with EC members tending to gain in price competitiveness in general (particularly Southern Euro- pean countries) at the expense of non-EC European countries. This occurs on account of increased competition, economies of scale, capital available at lower interest rates, and so on. It is assumed that the relative prices of non-European countries remain unchanged. The completion of the EC internal market is assumed to result in several annual changes in the relative prices of tourism exports during the period 1993-2000. Non-European countries: Australia, Canada, Japan, United States: 0.0 % . Non-EC European countries: Austria, Finland, Nor- way: + 0.6 % ; and Sweden, Switzerland: + 0.5 % . EC countries: France: +0.2%; Belgium, Denmark, Germany, Netherlands: 0.0%; Greece, Italy, Spain: -0.1%; and United Kingdom: -0.4%.

The relative prices of tourism imports for the various countries will change in exactly the opposite fashion. Thus, the annual changes in the relative prices of tourism imports will be - 0.6 % for Austria, 0.0 % for Germany, +0.4% for United Kingdom, and so on. The trend/ dummy variable assumptions for the forecast period are the same as for the baseline scenario.

Eastern Europe Growth Scenario

The assumption underlying the growth scenario is that the GDPs of all countries considered in the study grow at a rate of 0.5 70 per year higher than for the baseline scenario. The liberalization of Eastern Europe is expected to stimulate the world economy. (As far as the Eastern European economies themselves are concerned, however, the first part of the 1990s is expected to be a period of shrinking real incomes, followed by recovery in the second half of the 1990s.) The Eastern Europe growth scenario assumes constant relative prices in the same manner as does the baseline scenario, and also makes the same dummy variable/trend assumptions.

Forecasts

The forecasts of tourism imports and exports for the baseline, EC completion and growth scenarios for the European Community, West- ern Europe, North America, non-European countries, and all countries are presented in Tables 6-10, respectively. The EC completion scenario starts to have an impact after 1992, and the growth scenario starts to affect tourism imports and exports from 1991 onward. The creation of the single European market has an impact on tourism imports and exports in Western Europe, but is assumed to have no impact on tourism imports for non-European countries.

Table 11 examines the cumulative impact of the completion of the internal market of the EC, as well as the economic growth resulting from the liberalization of Eastern Europe by comparing the continuous growth paths of the EC completion and growth scenarios with those of the baseline scenario. Table 11 shows, for example, that the creation of the single European market will result in an increase in the average


Table 6. Tourism Import and Export Scenarios: European Community (US$ Billion)

Year

1980 1985 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Imports Exports

EC EC Baseline Completion Growth Baseline Completion Growth

41.98 41.36 44.79 57.07 61.33 67.34 64.43 64.43 64.98 70.03 70.03 70.52 67.43 67.43 68.57 72.76 72.76 73.77 70.51 71.12 72.26 75.57 75.93 77.13 73.67 74.93 76.08 78.45 79.19 80.60 76.93 78.86 80.03 81.42 82.56 84.18 80.27 82.93 84.10 84.48 86.03 87.88 83.70 87.13 88.30 87.62 89.62 91.71 87.23 91.47 92.64 90.85 93.31 95.67 90.86 95.96 97.12 94.18 97.12 99.76 94.59 100.59 101.74 97.60 101.06 103.98

annual growth rate of GDP of 0.6 % in the European Community over the period 1993-2000 ( corresponding to Cecchini’s 1988 prediction of a cumulative increase in GDP of 4.5 %), a 0.8 7% increase in the growth rate of tourism imports, and a 0.5% increase in the growth rate of tourism exports.

The EC completion scenario incorporates the impact of both changing relative prices and income growth; hence, Table 11 does not permit direct calculation of price or income elasticities from this scenario. By contrast, the Eastern Europe growth scenario just allows for higher

Table 7. Tourism Import and Export Scenarios: Western Europe (US$ Billion)

Year

1980 1985 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Imports Exports


50.89 53.00 56.42 70.45 77.34 83.97 81.06 81.06 81.77 87.38 87.38 87.95 84.80 84.80 86.25 90.83 90.83 92.01 88.64 89.39 90.88 94.38 94.74 96.20 92.58 94.13 95.65 98.01 98.76 100.51 96.62 99.02 100.57 101.75 102.89 104.96

100.78 104.06 105.65 105.58 107.16 109.55 105.05 109.27 110.89 109.51 111.54 114.28 109.43 114.63 116.30 113.55 116.06 119.17 113.93 120.17 121.88 117.70 120.72 124.21 118.56 125.88 127.64 121.95 125.51 129.40


Table 8. Tourism Import and Export Scenarios: North America (US$ Billion)

Year

Imports Exports


1980 15.92 1985 27.36 1990 30.24 1991 31.42 1992 32.64 1993 33.90 1994 35.18 1995 36.50 1996 37.86 1997 39.24 1998 40.66 1999 42.12 2000 43.61

31.42 31.66 32.64 33.13 33.90 34.65 35.18 36.22 36.50 37.84 37.86 39.50 39.24 41.21 40.66 42.98 42.12 44.80 43.61 46.67

14.69

12.32 24.40 25.61 26.84 28.10 29.40 30.74 32.12 33.53 34.99 36.48 38.02

25.61 25.83 26.84 27.29 28.26 28.81 29.73 30.37 31.24 31.98 32.80 33.65 34.41 35.37 36.07 37.16 37.79 39.00 39.55 40.90

income growth rates than the baseline scenario, with relative prices remaining unchanged, so that the income elasticities of demand for tourism imports can be calculated directly for the various geographical areas under consideration. For the European Community, a 0.5% increase in GDP results in a 0.8% increase in tourism imports, yield- ing a value of 1.5 for the income elasticity of demand. Table 11 shows that the elasticities for the various areas range between 1.4 and 1.5, indicating that tourism demand is highly responsive to income changes. This supports previous findings where international tourism

Table 9. Tourism Import and Export Scenarios: Non-European Countries (US$ Billion)

Year

Imports Exports


1980 22.13 1985 38.34 1990 45.35 1991 47.44 1992 49.59 1993 51.81 1994 54.10 1995 56.46 1996 58.89 1997 61.40 1998 63.99 1999 66.66 2000 69.41

47.44 47.79 49.59 50.32 51.81 52.94 54.10 55.65 56.46 58.46 58.89 61.37 61.40 64.38 63.99 67.51 66.66 70.75 69.41 74.10

16.31 14.82 28.15 29.61 31.09 32.62 34.18 35.79 37.45 39.15 40.91 42.71 44.57

29.61 29.88 31.09 31.64 32.81 33.46 34.57 35.34 36.40 37.29 38.28 39.30 40.21 41.37 42.21 43.52 44.28 45.74 46.41 48.03


Table 10. Tourism Import and Export Scenarios: All Countries (US$ Billion)

Year

Imports Exports


1980 73.02 1985 94.77 1990 122.70 1991 128.50 1992 134.39 1993 140.45 1994 146.68 1995 153.08 1996 159.67 1997 166.45 1998 173.42 1999 180.59 2000 187.97

128.50 129.56 134.39 136.57 141.20 143.81 148.23 151.30 155.48 159.03 162.96 167.02 170.67 175.28 178.62 183.81 186.83 192.63 195.30 201.75

69.31 85.27

112.13 116.99 121.93 126.99 132.19 137.54 143.03 148.66 154.46 160.41 166.52

116.99 117.83 121.93 123.65 127.54 129.66 133.33 135.86 139.29 142.25 145.43 148.85 151.76 155.66 158.28 162.69 165.00 169.94 171.92 177.43

generally appears to be regarded as a luxury (Martin and Witt 1988; Witt 1980).

CONCLUSIONS

A complete system of demand equations has been developed to generate long-term forecasts of tourism demand for various major geographical areas. The forecasts of tourism imports and exports have been calculated for the period 1991-2000 under three different scenarios: baseline scenario that assumes the current state of affairs remains unchanged, EC completion scenario that allows for the likely impacts

Table 11. GDP, Tourism Import, and Tourism Export Scenarios Relative to Baseline up to Year 2000

Area

GDP Imports Exports

Growth EC

EC Compl. EC Compl. Growth (% % Income Compl. Growth

(% Increases)” Increases)” Increases” Elasticity (% Increases)

European Community

Western Europe North America Non-European

Countries All Countries

0.6 0.5 0.8 0.8 1.5 0.5 0.7 0.5 0.5 0.8 0.8 1.5 0.4 0.6 0.0 0.5 0.0 0.7 1.4 0.5 0.8

0.0 0.5 0.0 0.7 1.4 0.5 0.8 0.2 0.5 0.6 0.7 1.5 0.4 0.7

“Absolute deviation of average growth rate per year in percentage points.


of the completion of the single internal market of the EC at the end of 1992, and growth scenario that reflects the increased world growth likely to result from the liberalization of Eastern Europe.

A comparison of the EC completion scenario and the baseline scenario permitted the computation of the cumulative impact of the completion of the internal market of the EC on tourism imports and exports in each area considered. The average annual growth rate of tourism imports would increase by 0.8% in the EC and Western Eu- rope and by 0.6% overall as a result of the EC completion (it is assumed that there is no increase for non-European countries), and the average annual growth rate of tourism exports would increase by between 0.4 % and 0.5 %. A comparison of the growth scenario and the baseline scenario enabled the cumulative impact of the recent political changes in Eastern Europe on tourism imports and exports to be calculated. The average annual growth rate of tourism imports would increase between 0.7% and 0.8% and that of tourism exports between 0.6% and 0.8%.

Careful examination of the development possibilities of the various destinations, as indicated by the projected tourism export growth rates, will provide an indication of the potential investment opportunities available to tourism firms. The income elasticity figures estimated in the study (I .4-i .5) suggest that foreign tourism is regarded as a luxury, in line with previous findings.

Considerable scope exists for expanding the research reported in this article. The tourism import and export functions could be modified to incorporate additional explanatory variables, in particular the cost of travel between origin and destination countries. More countries could be included in the model if appropriate data were available. For example, the analysis could be extended to include countries in Eastern Europe, as well as the missing Western European destinations. Finally, the forecasts would be improved if a more detailed examination of the interrelationship between tourism and the state of the environment were carried out, and the resulting implications for future patterns of tourist flows incorporated in the model. 0 0

AcknowledEment - Some of the initial work for this article was carried out with financial support from the Institute for Tourism at the University of St. Gallen, Switzerland.

REFERENCES

Cecchini, P. 1988 The European Challenge 1992: The Benefits of a Single Market. Aldershot,

UK: Wildwood House. Deaton, A., and J. Muellbauer

1980 An Almost Ideal Demand System. American Economic Review 70:312-326. European Commission

1985 Completing the Internal Market: White Paper from the Commission to the European Council. Brussels: European Commission.

Little, J. S. 1980 International Travel in the U.S. Balance of Payments. New England Eco-

nomic Review (May/June):42-55. Loeb, P.

1982 International Travel to the United States: An Econometric Evaluation. Annals of Tourism Research 9:7-20.


Martin, C. A., and S. F. Witt 1987 Tourism Demand Forecasting Models: Choice of Appropriate Variable to

Represent Tourists’ Cost of Living. Tourism Management 8:233-246. 1988 Substitute Prices in Models of Tourism Demand. Annals of Tourism Research

15:255-268. O’Hagan, J. W., and M. J. Harrison

1984 Market Shares of US Tourist Expenditure in Europe: An Econometric Analy- sis. Applied Economics 16:919-931.

Papadopoulos, S. I., and S. F. Witt 1985 A Marketing Analysis of Foreign Tourism in Greece. Proceedings of Second

World Marketing Congress, August 1985, S. Shaw, L. Sparks and E. Kaynak, eds., pp. 682-693, University of Stirling.

Smeral, E. 1988 Tourism Demand, Economic Theory and Econometrics: An Integrated Ap-

proach. Journal of Travel Research 26:38-43. 1989 Economic Models of Tourism. In Tourism Marketing and Management

Handbook, S. F. Witt and L. Moutinho, eds., pp. 113-118. Hemel Hempstead: Prentice Hall.

1990 Tourismus 2000. Vienna: Signum. Stone, J. R. N.

1954 Linear Expenditure Systems and Demand Analysis: An Application to the Pattern of British Demand. Economic lournal64:511-527.

Stronge, W. B., and M. Redman 1982 U.S. Tourism in Mexico: An Emnirical Analvsis. Annals of Tourism Research

I

9:21-35. Uysal, M., and J. L. Crompton

1984 Determinants of Demand for International Tourist Flows to Turkey: Tourism Management 5:288-297.

van der Stelt, D., and J. W. Velthuijsen 1989 Supply and Demand on the Tourism Market: A Feasibility Study for a Simula-

tion Model of the Netherlands. Amsterdam: Stichting voor Economisch Onder- zoek der Universiteit van Amsterdam.

van Soest, A., and P. Kooreman 1987 A Micro-Econometric Analysis of Vacation Behaviour. Journal of Applied

Econometrics 2:215-226. White, K. J.

1985 An International Travel Demand Model: US Travel to Western Europe. Annals of Tourism Research 12: 529-545.

Witt, S. F. 1980 An Abstract Mode-Abstract (Destination) Node Model of Foreign Holiday

Demand. Applied Economics 12:163-180. Witt, S. F., and C. A. Martin

1987 Econometric Models for Forecasting International Tourism Demand. Journal of Travel Research 25:23-30.

Submitted 8 October 1990 Revised copy submitted 8 April 1991 Accented 22 Anril 1991 Finaicopy submitted 10 June 1991 Refereed anonymously Coordinating Editor: Milton B. Redman

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