The Economics of Tourism and Sustainable Development THE FONDAZIONE ENI ENRICO MATTEI (FEEM) SERIES ON ECONOMICS AND THE ENVIRONMENT Series Editor: Carlo Carraro, University of Venice, Venice and Research Director, Fondazione Eni Enrico Mattei (FEEM), Milan, Italy Editorial Board Kenneth J Arrow, Department of Economics, Stanford University, Stanford, California, USA William J Baumol, CV Starr Center for Applied Economics, New York University, New York City, USA Partha Dasgupta, Cambridge University, Cambridge, UK Karl-Göran Mäler, The Beijer International Institute of Ecological Economics, The Royal Swedish Academy of Sciences, Stockholm, Sweden Ignazio Musu, University of Venice, Venice, Italy Henry Tulkens, Center for Operations Research and Econometrics (CORE), Université Catholique de Louvain, Louvain-la-Neuve, Belgium The Fondazione Eni Enrico Mattei (FEEM) was established in 1989 as a non-profit, nonpartisan research institution It carries out high-profile research in the fields of economic development, energy and the environment, thanks to an international network of researchers who contribute to disseminate knowledge through seminars, congresses and publications The main objective of the Fondazione is to foster interactions among academic, industrial and public policy spheres in an effort to find solutions to environmental problems Over the years it has thus become a major European institution for research on sustainable development and the privileged interlocutor of a number of leading national and international policy institutions The Fondazione Eni Enrico Mattei (FEEM) Series on Economics and the Environment publishes leading-edge research findings providing an authoritative and up-to-date source of information in all aspects of sustainable development FEEM research outputs are the results of a sound and acknowledged cooperation between its internal staff and a worldwide network of outstanding researchers and practitioners A Scientific Advisory Board of distinguished academics ensures the quality of the publications This series serves as an outlet for the main results of FEEM’s research programmes in the areas of economics, energy and the environment Titles in the series include: Game Practice and the Environment Edited by Carlo Carraro and Vito Fragnelli Analysing Strategic Environment Assessment Towards Better Decision-Making Edited by Pietro Caratti, Holger Dalkmann and Rodrigo Jiliberto Trade and Environment Theory and Policy in the Context of EU Enlargement and Economic Transition Edited by John W Maxwell and Rafael Reuveny Green Accounting in Europe A Comparative Study, Volume Edited by Anil Markandya and Marialuisa Tamborra The Economics of Tourism and Sustainable Development Edited by Alessandro Lanza, Anil Markandya and Francesco Pigliaru The Economics of Tourism and Sustainable Development Edited by Alessandro Lanza Director, Fondazione Eni Enrico Mattei (FEEM), Milan, Italy Anil Markandya Fondazione Eni Enrico Mattei (FEEM), Milan, Italy and Professor of Economics, University of Bath, UK Francesco Pigliaru Professor of Economics, University of Cagliari and CRENoS, Italy THE FONDAZIONE ENI ENRICO MATTEI (FEEM) SERIES ON ECONOMICS AND THE ENVIRONMENT Edward Elgar Cheltenham, UK • Northampton, MA, USA © Alessandro Lanza, Anil Markandya, Francesco Pigliaru, 2005 All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher Published by Edward Elgar Publishing Limited Glensanda House Montpellier Parade Cheltenham Glos GL50 1UA UK Edward Elgar Publishing, Inc 136 West Street Suite 202 Northampton Massachusetts 01060 USA A catalogue record for this book is available from the British Library ISBN 84542 401 Printed and bound in Great Britain by MPG Books Ltd, Bodmin, Cornwall Contents vii List of contributors Introduction Alessandro Lanza, Anil Markandya and Francesco Pigliaru 1 An investigation on the growth performance of small tourism countries Rinaldo Brau, Alessandro Lanza and Francesco Pigliaru Forecasting international tourism demand and uncertainty for Barbados, Cyprus and Fiji Felix Chan, Suhejla Hoti, Michael McAleer and Riaz Shareef 30 Land, environmental externalities and tourism development Javier Rey-Maquieira Palmer, Javier Lozano Ibáđez and Carlos Mario Gómez Gómez 56 Tourism, increasing returns and welfare Jean-Jacques Nowak, Mondher Sahli and Pasquale Sgro 87 How to develop an accounting framework for ecologically sustainable tourism Cesare Costantino and Angelica Tudini The effect of climate change and extreme weather events on tourism Andrea Bigano, Alessandra Goria, Jacqueline Hamilton and Richard S.J Tol 104 173 Sustainable tourism and economic instruments: international experience and the case of Hvar, Croatia Tim Taylor, Maja Fredotovic, Daria Povh and Anil Markandya 197 Tourism and sustainable development: lessons from recent World Bank experience Anil Markandya, Tim Taylor and Suzette Pedroso 225 Using data envelopment analysis to evaluate environmentally conscious tourism management Valentina Bosetti, Mariaester Cassinelli and Alessandro Lanza 252 v vi Contents 10 A tale of two tourism paradises: Puerto Plata and Punta Cana – the determinants of room price in the Dominican Republic using a hedonic function approach Giovanni Ruta and Suzette Pedroso 269 11 A choice experiment study to plan tourism expansion in Luang Prabang, Laos Sanae Morimoto 288 Index 309 Contributors Andrea Bigano, Fondazione Eni Enrico Mattei, Italy Valentina Bosetti, University of Milan-Bicocca and Fondazione Eni Enrico Mattei, Italy Rinaldo Brau, University of Cagliari and CRENoS, Sardinia, Italy Mariaester Cassinelli, University of Milan-Bicocca and Fondazione Eni Enrico Mattei, Italy Felix Chan, School of Economics and Commerce, University of Western Australia Cesare Costantino, Istat – Environmental Accounting Unit, Italy Maja Fredotovic, Faculty of Economics, University of Split, Croatia Carlos Mario Gómez Gómez, University of Alcalá de Henares, Spain Alessandra Goria, Fondazione Eni Enrico Mattei, Italy Jacqueline Hamilton, Hamburg University, Germany Suhejla Hoti, School of Economics and Commerce, University of Western Australia Javier Lozano Ibáñez, University of the Balearic Islands, Spain Alessandro Lanza, Fondazione Eni Enrico Mattei, Italy Anil Markandya, Fondazione Eni Enrico Mattei, Italy and University of Bath, UK Michael McAleer, School of Economics and Commerce, University of Western Australia Sanae Morimoto, Department of Economics, Okayama Shoka University, Japan Jean-Jacques Nowak, University of Lille, France Javier Rey-Maquieira Palmer, University of the Balearic Islands, Spain Suzette Pedroso, World Bank, Washington, DC, USA vii viii Contributors Francesco Pigliaru, University of Cagliari and CRENoS, Sardinia, Italy Daria Povh, PAP-RAC, Split, Croatia Giovanni Ruta, World Bank, Washington, DC, USA Mondher Sahli, University of Wellington, New Zealand Pasquale Sgro, Johns Hopkins University, Bologna, Italy Riaz Shareef, School of Economics and Commerce, University of Western Australia Tim Taylor, Department of Economics and International Development, University of Bath, UK Richard S.J Tol, Hamburg University, Germany Angelica Tudini, Istat – Environmental Accounting Unit, Italy Introduction Alessandro Lanza, Anil Markandya and Francesco Pigliaru Tourism is big business and getting bigger In the 20 years from 1980 to 2000 global tourism receipts increased at an annual rate of nearly per cent, much faster than the rate of world economic growth of around per cent In 2000, income from tourism combined with passenger transport totaled more than $575 billion, making this sector the world number one export earner, ahead of automotive production, chemicals, petroleum and food (UNEP web site1) So it is no surprise that people are paying attention to tourism when they debate how the world can move to a more sustainable pattern of development Given the increasing importance of the sector, an enormous literature has emerged on the three pillars of sustainable development – environmental, cultural and economic – and on how tourism impacts on them and how these aspects of tourism can be enhanced In this active and somewhat crowded field, what is the purpose of introducing yet another book? In spite of all that has been produced, we would argue that we offer something special Unlike much of the literature that has primarily an environment and sociological perspective, our effort is firmly grounded in economics – its theory and applications Economics here is made to be the servant of policy in the field of tourism But economics has increasingly become a technical subject and its methods and results are not easy for the policy maker to comprehend In this book, we try to present some important economics results, and relate them to the policy debate If we are successful, our approach offers the prescriptions for moving tourism, and economic development generally, closer to a sustainable ideal, with a firm analytical anchor This is important if we are to be taken seriously by important decision makers in governments – in ministries of economy and finance, for example 302 The economics of tourism and sustainable development existing destinations, ten possible tours can be provided These are classified into three groups: (a) tours to enjoy natural environments (nϭ3), (b) tours to enjoy ethnic culture (nϭ1), and (c) tours to enjoy both (nϭ6) We also considered another alternative, that is, no participation, which implied staying in the town of Luang Prabang The choice probabilities of tours in each category are calculated and the tours with the highest probability are regarded as representative of each category Because there are relatively many tours of type (c), the highest two probabilities of tour (c) are chosen Then, the choice probability is re-estimated when these four representative tours and no participation are given The four out of the ten possible tours are shown in the upper portion of Table 11.8, which are labelled Nature, Ethnic, Mix and Mix 2.12 The next step is to consider the most preferred package tour when the new activities, trekking and a village visit, are included Based on the reestimation results, the four tours are extended to eight package tours (the lower portion of Table 11.8) To represent the costs of trekking and visiting an ethnic village, we used the results from Case and Case 2, which were US$3.5 and US$2.5 Figure 11.4 shows the choice probabilities for each package tour The choice probability that tourists will participate in any tour is 86.56 per cent The most preferred tours are Nature (13.20 per cent), which visits Pak Ou Caves and Sae Falls and partakes of trekking, and Nature (13.07 per cent), which visits Pak Ou Caves, Sae Falls and an ethnic village The second-most preferred tours are Mix 11, Mix 12, Mix 21 and Mix 22, all of which score about 12 per cent Table 11.8 Examples of tours Types Notation Destinations (a) (b) (c) Nature Ethnic Mix Mix Pak Ou Caves and Sae Falls Ban Phanom and Ban Sang Hai Pak Ou Caves and Ban Sang Hai Sae Falls and Ban Sang Hai (a)Ј Nature1 Nature2 Ethnic1 Ethnic2 Mix 11 Mix 12 Mix 21 Mix 22 Pak Ou Caves, Sae Falls and trekking Pak Ou Caves, Sae Falls and ethnic village Ban Phanom, Ban Sang Hai and trekking Ban Phanom, Ban Sang Hai and ethnic village Pak Ou Caves, Ban Sang Hai and trekking Pak Ou Caves, Ban Sang Hai and ethnic village Sae Falls, Ban Sang Hai and trekking Sae Falls, Ban Sang Hai and ethnic village (b)Ј (c)Ј 303 A choice experiment study in Laos Not join 6.69% Mix 22 11.93% Mix 21 12.05% Mix 12 11.84% Mix 11 11.95% Ethnic2 9.59% Ethnic1 9.69% Nature2 13.07% Nature1 0.00 13.20% 2.00 4.00 6.00 8.00 10.00 12.00 14.00 % Figure 11.4 Choice probabilities of package tours Finally, in order to show the potential of new tourism activities, the choice probabilities of these eight tours and no participation are compared to those of four package tours and no participation, which are described in Table 11.8 To show the result simply, eight package tours are re-integrated into four tours For example, Nature and Nature are grouped into Nature The comparison is shown in Figure 11.5 The choice probabilities of all tours increased, while the probability of no participation decreased by almost 50 per cent, from 13.44 per cent without new activities to 6.99 per cent with new activities Thus tourism potentials such as trekking and village tours can be expected to expand tourism in Luang Prabang CONCLUSIONS This chapter applies the CE approach to planning tourism expansion in Luang Prabang, Laos, while most studies have used TC and CV approaches The CE approach provides significant information about tourist preference, not only for existing destinations but also for non-existing activities This kind of study is of benefit to policy makers, as it helps them to decide how to extend tourism development, what kinds of activities are expected to be established, and to determine the costs of participating The results of the survey indicate that Pak Ou Caves and Sae Falls have the highest values of all existing destinations Regarding non-existing activities, the subjects are interested in trekking and visiting an ethnic village; 304 The economics of tourism and sustainable development % 30 25 20 15 10 Nature Ethnic Mix Mix Not join Without new activities With new activities Figure 11.5 Comparison of choice probabilities of package tours however, these not score higher than existing destinations The survey also finds that tourists are interested in visiting not only the World Heritage site, but also other destinations around Luang Prabang, which indicates the potential of tourism expansion The simple simulation investigates how the cost of participating in new activities, trekking and a village visit, changes the site choice The most preferred package tour is also examined by the simulation It shows that participation in any tours is increased by combining popular existing destinations with the new activities This study uses the conditional logit model, whose important property is independence from irrelevant attributes (IIA) This property implies that the introduction or removal of other alternatives does not affect the relative choice probabilities of the two main alternatives If the IIA hypothesis is violated, more complex statistical models are necessary such as the random parameter logit model and the nested logit model (Train, 2002) Some literature (Hanley, 2002; Schwabe et al., 2001) has tested the A choice experiment study in Laos 305 IIA assumption and found a violation This chapter can also test this assumption in order to determine whether the conditional logit model is appropriate The framework of this study can be extended to consider seasonality and potential tourist effects The value of natural resources like waterfalls would be flexible because of their seasonality in Laos Because of the large amount of precipitation during the rainy season, it is expected that the landscape will vary with the seasons, and so will tourism values Therefore further studies should consider the effect of seasonality on natural resources This study can also be extended to consider the preferences of potential tourists All respondents in this survey are tourists who have actually visited Laos and not people who have not been to Laos These people could be potential tourists once new tourism activities are provided and well-organized tours are available NOTES 10 Tourism development can, however, also negatively affect natural environments and socio-cultural conditions In cases where the natural environment is used as the tourism resource, that is, ecotourism, environmental conservation may be promoted However, large-scale or mass tourism development may generate various environmental problems, such as soil erosion, water pollution and landscape degradation Tourism also often drives the citizens to change traditional lifestyles and culture as a result of expanded income distribution due to increases in the number of tourists and capital flow This chapter does not discuss these negative impacts but focuses on economic benefit; the former are beyond its aim Before the survey, the author interviewed some international tourists about site destinations which they had visited in Luang Prabang The exchange rate was US$ ϭ8500 Kip in August 2001 A tuk tuk is a three-wheeled taxi, also called a jambou, which can hold six to eight passengers A profile is a set of attributes that includes tour price, main sites and other forms of recreation described in our survey The design using all profiles is called a ‘complete factorial design’ As the number of attributes, levels, or both, increases, the design grows exponentially in size and complexity For profile design, see Chapter in Louviere et al (2000) Since the survey was undertaken at an airport, a bus station, and at piers, most of the tourists who were waiting for departure agreed to the interview However, tourists who had just arrived did not agree to the interview because they were in a hurry to start their travel Sampling bias, therefore, may exist, but it could not be tested because of too few arriving samples In the survey, subjects were only told the travel time to their destination by tuk tuk, except Pak Ou Caves (Table 11.3) No information was provided on other transport As another explanation for this result, a government officer commented that because the area around Kwangsi Falls is rather modernized it might be less attractive to tourists, who may prefer the natural environment of Luang Prabang The results in Model are used in this section judging from BIC, therefore the choice probability of visiting Ban Chang is not considered 306 11 12 The economics of tourism and sustainable development For cost of transport, the mean cost of transport in the pre-survey is used The choice probabilities of these tours were 11.49 per cent (Nature), 8.43 per cent (Ethnic), 10.40 per cent (Mix 1) and 10.49 per cent (Mix 2) REFERENCES Adamowicz, W., Swait, J., Boxall, P., Louviere, J and Williams, M (1997), ‘Perceptions versus Objective Measures of Environmental Quality in Combined Revealed and Stated 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Account Abegg, B 176 Abu Soma, Egypt, World Bank project 237, 238 accounting frameworks for sustainable tourism 104–24 adaptive behaviour 191–2 Addo Elephant National Park, World Bank project 247 AFEST (Accounting Framework for Ecologically Sustainable Tourism) 120–22 Africa, economic impact of tourism 228–9 Agnew, M 176, 177 agriculture, impact of tourism boom 87–100 aid and SITEs development 37 air pollution indicators, ESEPI framework 166 tourism share 124, 203 allocation of land, and tourism growth 74–8 Amelung, B 177 America, North, impact of climate change on tourism 176–7 Anderson, R.I 254 Armstrong, H.W 33, 34, 36 asymmetric models, tourist arrivals 44 autoregressive conditional heteroscedasticity (ARCH) model 41–4 balance of payments, impact of tourist numbers 38 Balearic Islands, tourist eco-tax 205–7 Banker, R.D 254 Barbados international tourist arrivals 39–41 tourism forecasting model 45–7, 50–52 bed number, as indicator of management expenses 258 Belize City, World Bank project 238 Bell, R.A 254 Bennett, J 61 Berndt, E.K 46 Bhutan, tourism tax 207 Bigano, A 178 biodiversity loss indicators, ESEPI framework 168 Bollerslev, T 31, 41 borrowing difficulties, SITEs 37 Bricker, D.L 254 Briguglio, L 34, 36 Brunstad, R.J 61 Burkina Faso, World Bank project 245–6 Bwindi Impenetrable National Park, World Bank project 247–8 Cahill, S 204–5 Cammarrota, M 125 Canada, impact of climate change on tourism 177 capital formation, tourism industries, TSA tables 158–61 Charnes, A 254 choice experiment and tourism expansion planning 288–9 Luang Prabang 291–305 Christie, I 228–9, 231 Clark, C 73 climate impact on tourism 175–6 Italy 181–2 309 310 Index climate change impact on tourism 173–4, 176–90 indicators, ESEPI framework 167 coastal zone pollution indicators, ESEPI framework 168–9 conditional volatility, tourist arrivals, SITEs 30–32, 39–53 congestion costs of tourism 201–3 Coral Reef Rehabilitation project, Indonesia 245 Corden, W.M 101 Costa Rica Biodiversity Resources Development Project 244, 248 eco-markets project 245 costs of tourism 87, 227 Crespi, J 177 Croatia eco-tax 210–19 tourism 208–10 Croes, R 200, 220 Crompton, D 228–9, 231 Crouch, G.I 200 cultural heritage, impact of tourism 204, 236 Cyprus international tourist arrivals 39–41 tourism forecasting model 45–6, 48, 50–52 data envelopment analysis (DEA) 254–67 Davies, T 204–5 de Freitas, C.R 175, 176 De Haan, M 111 DEA (data envelopment analysis) 254–67 Deiva Marina, efficiency of tourism management 260–63 demand for tourism and environmental quality 199–201 forecasting of 30–32, 45–53, 174–5 destination image, role of climate 175–6 development aid, SITEs 37 Ding, C.G 37 discounting, and environmental degradation 69–72 Dittman, D.A 254 Dixon, J 204, 234 domestic supply and internal tourism consumption, TSA tables 144–55 domestic tourism consumption, TSA tables 130–33 Dominica, tourist eco-tax 207–8 Dominican Republic room price determinants 275–87 tourism impact, World Bank project 239 tourism industry 269–75 Dommen, E 34 Drake, L 61 Driving Force–Pressure–State–Impact– Response (DPSIR) model 112–13 Dutch disease 101 Easterly, W Easterly–Kraay (E–K) Small States Dataset 9, 26 ecologically sustainable tourism, accounting framework 104–24 economic impact of tourism 87–99, 204–5, 227–32 economic theory studies, climate change and tourism 177–8 eco-taxes 5–6, 198–201, 205–8, 210–20 impact on tourist economy 199–201 visitor survey, Hvar 214–19 EGARCH model 44 employment hotels 231 impact of tourist numbers 38 tourism industries, TSA tables 156–7 Engle, R.F 31, 41 Englin, J 177 environment challenges to tourism, Dominican Republic 272–4 environmental accounts 113–17 environmental impact of tourism 69–79, 118–20, 201–5, 234 Dominican Republic 273 Hvar, Croatia 210 indicators, ESEPI framework 166–72 environmental quality impact of eco-tax 199–200 and tourism demand 200–201 environmental sustainability, see sustainable development; sustainable tourism 311 Index environmental variables and room price 278 ESEPI (European System of Environmental Pressure Indices) 117–20, 166–72 Europe climate impact on tourism 179–90 tourism climate index 177 European Strategy for Environmental Accounting 114 European System of Environmental Pressure Indices (ESEPI) 117–20, 166–72 Eurostat environmental projects 118 exponential generalized ARCH model (EGARCH) 44 external satellite accounts 106 externalities and land allocation effect on tourism growth 77–8 and tourism expansion costs 66–9 Fiji international tourist arrivals 39–41 tourism forecasting model 45–6, 49–52 fiscal policy, impact of tourist numbers 38 Fleischer, A 61 Fondazione Eni Enrico Mattei 179 forecasting tourism demand 4, 30–32, 45–53 Freeman, M 276 functional satellite accounts 106 Gallarza, M.G 175 GARCH model 31–2, 43–4 GDP growth rates, SITEs 35–6 gender and tourism development 233–4 generalized ARCH model (GARCH) 31–2, 43–4 Global Environmental Facility (GEF) projects 241–4, 245–8, 249 global models, climate change and tourism 178–9 Glosten, L 43 Gössling, S.M 175 green golden rule level 70–72 growth, small tourism countries (STC) 8–23 comparative performance 10–13 determinants 13–17 heterogeneity 17–20 mechanisms 20–22 Hamburg Tourism Model 178 Hamilton, J.M 178 Hart, S 252 Hazari, B.R 87 Heal, G 70 health, impact of tourism development 237 hedonic price method, room price determinants 276 heterogeneity, STC growth 17–20 Hiemstra, S.J 200 Honduras, World Bank projects 239, 246 hotels return on investment 229 services, effect on room price 278 Hu, Y 175 Hughes, G 204 Huybers, T 61 Hvar, Croatia, tourism 209–10 eco-tax 210–19 hybrid flow accounts 115–17 IBRD/IDA funding, impact on tourism 235–6 inbound tourism consumption, TSA tables 128–9 index approach, tourism and climate change 176–7 Indonesia, World Bank project 245 infrastructure, effect on room price 278–9 Integrated Environmental and Economic Accounts 2003 (SEEA2003) 105, 113–14, 115–17 internal tourism consumption, TSA tables 136–7 international tourist arrivals, SITEs 39–52 island economies 34 Ismail, J.A 200 Istat, environmental accounting project 118 Italy climate 181–2 312 Index tourism data 182–3 tourism impacts on environment 253–4 tourism management efficiency 260–65 TSA implementation 122–4 WISE case study 181–9 Jeantheau, T 44 Johnson, R 202 Kaim, E 175 Kee, P 111 Kraay, A 8, Krinsky, I 298 Krupp, C 176 Kuznets, S 33 labour demand, effect of tourism boom 95 Lancaster, K.J 174 land use and tourism development 56–79 and tourism price 59–62 Lanza, A 20, 57, 74 Laos, tourism 289–305 leakage, tourism investment 231–2 Lebanon, World Bank project 240 Liguria, efficiency of tourism management 260–63 Lim, C 174 Lindbergh, K 202 Ling, S 43 Liou, F.M 37 Lise, W 178 location, effect on room price 278 Lohmann, M 175, 176 Loomis, J.B 177 López, R.A 61 Luang Prabang, tourism development 288–305 Lucas, R 20 Macedonia, World Bank project 239 Madagascar, World Bank project 240 manufactures, relative price of tourism 73–4 manufacturing sector, impact of tourism boom 87–100 marine environment indicators, ESEPI framework 168–9 Markowski, M 177 Matzarakis, A 176 McAleer, M 43, 44 McBoyle, G 176 McFadden, D 295 Mendelsohn, R 177 Mgahinga Gorilla National Park Conservation, Uganda 248 minimum efficient scale, small economies 33 models climate change and tourism 178–9 international tourist arrivals 41–4 Moeltner, K 177 Morey, R.C 254 Morley, C.L 174 multiplier effects of tourism 38 National Account Matrix (NAM) 115, 117 Neary, J.P 101 Nelson, D.B 43, 44 Netherlands, climate impact on tourism 190 Ng, A 87 North America, impact of climate change on tourism 176–7 Nyman, J.A 254 outbound tourism consumption, TSA tables 134–5 ozone layer depletion indicators, ESEPI framework 169 package tour choices, Luang Prabang 301–3 Palutikof, J.P 177 Panagariya, A 101 Partnership for National Ecosystem Management Project (PAGEN) 245–6 Peru, World Bank project 247 Pigliaru, F 20, 57, 74 Pike, S 175 pollution effects of congestion 202 effects of tourism 203 Index Pooled Travel Cost Model (PTCM) 177–8 population, SITEs 33 poverty impact of tourism 232–3 SITEs 37 Poverty Reduction Strategies and tourism 232–3 price of tourism effect of land allocation 59–62 elasticity, impact of eco-tax 199–200 relative to manufactures 73–4 production accounts, tourism industries, TSA tables 138–43 productive uses, land 57–9 PRSPs (Poverty Reduction Strategies) and tourism 232–3 Pruckner, G.J 61 PTCM (Pooled Travel Cost Model) 177–8 Puerto Plata, tourism industry 274–87 Punta Cana, tourism industry 274–87 Ramaswamy, R 73 Read, R 33, 34, 36 recreation activity, impact of climate change 177 relative prices effect of tourism boom 94 tourism to manufactures 73–8 resident welfare, effect of tourism boom 96–9 resource depletion indicators, ESEPI framework 169–70 Richardson, R.B 177 Ritchie, J.R.B 175 Robb, A.L 298 Robinson, E.A.G 33 room price determinants, Dominican Republic 275–87 Rosen, S 276 Rowthorn, R.E 73 satellite accounts 106–11 Scott, D 176 Sectoral Infrastructure Projects (SIPs) 118 Seddighi, H.R 174 SEEA2003 (Integrated Environmental 313 and Economic Accounts 2003) 105, 113–14, 115–17 Shareef, R 33, 35, 37 Shaw, R.N 200 Shephard, N 44 Shoemaker, S 175 SIPs (Sectoral Infrastructure Projects) 118 Small Island Tourism Economics (SITEs) 30–53 characteristics 32–5 impact of tourism 35–9 tourist arrivals 39–53 small tourism countries (STCs) 8–23 comparative growth performance 10–13 growth determinants 13–17 growth heterogeneity 17–20 growth mechanisms 20–22 Social Accounting Matrix 125 social impacts of tourism 232–4 socially optimal tourism development 65–6 sojourn fee, Hvar 212 South Africa, World Bank project 247 Spain, tourist eco-tax 205–7 Statistics Sweden, environmental accounting project 118 Steurer, A 114 summer tourism, impact of temperature 183, 185 sustainable development and tourism 226–34 World Bank projects 234–50 sustainable tourism 197–8 accounting framework 111–24 symmetric GARCH model 43–4 temperature correlation with tourism 176, 183, 185 Theocharous, A.L 174 Tisdell, C.A 79 Tol, R.S.J 177, 178 tourism and climate 175–6 and climate change 173–4, 176–90 congestion effects 201–3 consumption, TSA tables 128–37, 144–55, 162 costs 87, 227 314 Index demand, see demand for tourism development planning, Laos 288–305 effect on economy 87–100 environmental impact, see environmental impact of tourism establishments, TSA tables 164–5 firms, adaptive behaviour 191–2 gross fixed capital formation, TSA tables 158–61 index approach, climate change 176–7 management evaluation 252–67 price, see price of tourism and SITEs 35–53 and small countries growth 8–23 and sustainable development 226–34 World Bank projects 234–50 Tourism Satellite Account (TSA) 107–11 Italy 122–4 Recommended Methodological Framework (TSARMF) 104, 107–11 tables 128–65 Tourist Areas Restoration Fund, Balearic Islands 206–7 tourist eco-taxes, see eco-taxes tourists adaptive behaviour 191 source countries, SITEs 39 see also visitors toxics dispersion indicators, ESEPI framework 170 trade, SITEs 36–7 transport and tourism development 236 tourist preferences, Laos 298 trekking route cost, Luang Prabang 300–301 TSA, see Tourism Satellite Account TSARMF (Tourism Satellite Account – Recommended Methodological Framework) 104, 107–11 Tsur, Y 61 Tunisia, World Bank project 240 Uganda, World Bank project 247–8 uncertainty in tourism arrivals, SITEs 35–8 urban environment problems indicators, ESEPI framework 170–71 urbanization, impact on tourism, Dominican Republic 274 USA, impact of climate change on recreation activity 177 value added, environmental accounts 114 Van Wijnbergen, S 101 Vanegas, M 200, 220 village tour cost, Luang Prabang 301 Viner, D 176, 177 visitors numbers forecasting satisfaction and tourism pricing 59–60 see also tourists volatility, international tourist arrivals, SITEs 30–32, 39–53 vulnerability of SITEs 36 Wanhill, S 202 waste amount as indicator of environmental costs 258–9 generated by tourism 204 indicators, ESEPI framework 171 water pollution impact of tourism 203 indicators, ESEPI framework 171–2 water treatment plants, effect on room price 279 water use, impact of tourism 203–4 Weather Impacts on National, Social and Economic Systems (WISE) project 179–90 weather variable in WISE project 180–81 welfare effects of tourism 3, 94, 96–9 willingness to pay (WTP) congestion charges 201–2 eco-charge, Hvar 214–19 winter tourism, impact of temperature 176, 183, 185 WISE project (Weather Impacts on National, Social and Economic Systems) 179–90 Witt, C.A 174 Index Witt, S.F 174 women, impact of tourism 233–4 World Bank 315 poverty reduction strategies and tourism 232–3 tourism and sustainable development projects 226–50 ... Markandya and Marialuisa Tamborra The Economics of Tourism and Sustainable Development Edited by Alessandro Lanza, Anil Markandya and Francesco Pigliaru The Economics of Tourism and Sustainable Development. .. deviation of the growth rates of the various groups of countries The standard deviation of STCs is higher than that of OECD countries, and is slightly lower than that of all the other groups and of the. .. value Are they converging to the high per capita GDP of the Bahamas? Are most of the STCs 20 The economics of tourism and sustainable development converging to that level? If, on the other hand, convergence