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- Applied Tourism Economic Impact Analysis - Introduction to Demand
Forecasting

theory the authors suggest that expert opinion can make very valuable contributions to the forecasting exercise The process that the Australian Tourist Commission goes through to set tourism targets which are essentially forecasts is cited as an example of a valuable integrated approach Smith S L J 1995 Forecasting Tourism Demand and Market Trends In Tourism Analysis A Handbook Essex Longman Group Limited Second Edition 116 149 This chapter introduces the concepts of tourism demand and forecasting Almost all forecasting involves predicting the tourism demand at some point in the future In the neoclassical conception of demand demand is seen as a function of price However many other variable or demand shifters may have an influence on price From the tourism perspective these include age education tastes previous experience with the product advertising product innovation government policy or new technology As a luxury good the demand for tourism tends to be quite elastic while the income elasticity of different tourism products can differ considerably as some recreation goods may actually show declining consumption with increasing income The chapter reviews the forecasting methods of simple regression gravity models probabilistic travel model and the Delphi technique Archer B H 1994 Demand Forecasting and Estimation Travel Tourism and Hospitality Research A Handbook for Managers and Researchers J R Brent Ritchie and Charles R Goeldner ed New York John Wiley and Sons Ltd Second Edition 105 114 Demand forecasting in tourism research is reviewed from the perspective of which method is most appropriate given the research question the time period specified and the information needs of managers Factors which will govern the choice of method include the purpose the time period being forecasted the degree of accuracy required the availability of information the forecasting environment and the cost of producing the forecast Inaccuracies in forecasting result may result from five different factors inappropriate model incorrect use error calculation in relationships in model significant variables omitted and data used may have been inadequate or inappropriate A review of quantitative qualitative and technological forecasting techniques and the factors which influence tourism demand are also included Witt S F and C A Martin 1989 Demand Forecasting in Tourism and Recreation Progress in Tourism Recreation and Hospitality Management Volume 1 C P Cooper ed New York Belhaven Press 4 32 This book chapter provides a detailed description of the many tourism demand forecasting methodologies available to researchers including univariate time series multivariate regression econometric Box Jenkins multivariate method and qualitative forecasting techniques They also provide a survey of literature on accuracy analysis in tourism demand forecasting Calantone R J C A di Benedetto and D Bojanic 1987 A Comprehensive Review of the Tourism Forecasting Literature Journal of Travel Research 26 2 28 39 This paper reviews the state of tourism demand forecasting describes the different methods used and critiques each method in turn They provide a useful table with ranks the different forecasting methods based on their most appropriate time horizon cost of implementation and complexity of the

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Introduction%20to%20Forecasting.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Demand Forecasting
Accuracy

well as statistical time series model Lim C and M McAleer 2001 Forecasting Tourist Arrivals Annals of Tourism Research 28 4 965 977 This study evaluates various exponential smoothing models for accuracy in predicting quarterly tourist arrivals to Australia The Holt Winters Additive and Multiplicative Seasonal models outperform the Single Double and the Holt Winters Non Seasonal Exponential Smoothing models in forecasting The results of this paper show that one should be concerned about seasonality in forecasting and that in this case the existence of unit roots does not seem to be an important issue Tideswell C T Mules and B Faulkner 2001 An Integrative Approach to Tourism Forecasting A Glance in the Rearview Mirror Journal of Travel Research 40 November 2001 162 171 This study evaluated the results of tourism forecasting exercise in South Australia for the period of 1996 1998 An integrated times series and Delphi process was used to forecast tourism demand from both the international and domestic market Three methods of generating time series forecasts were used Holt s exponential smoothing a naive method using average annual rate of change from the past 11 years and a linear trend using regression analysis A group of 26 tourism industry practitioners responded to a Delphi survey and provided comments in a follow up group meeting process The final forecasting method used was based on the results of the Delphi process Grouped forecasting trends e g all international visitors were quite accurate but forecasts for segments of the market e g Japanese visitors were not as accurate This was particularly true for small market segments Over all the naive approach to demand forecasting was most accurate confirming the results of earlier studies Witt S F and C A Witt 1992 Modeling and Forecasting Demand in Tourism San Diego Academic

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Forecasting%20Accuracy.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Times-Series Forecasting
Models

evaluated for inbound tourism to Denmark for one two three and four year predictions The time varying parameter TVP and long run static cointegration regression model perform most consistently The naive or no change time series model is not far behind in terms of accuracy especially for predictions in years one and two Kulendran N and S F Witt 2001 Cointegration Versus Least Squares Regression Annals of Tourism Research 28 2 291 311 Least squares regression models that explain international tourism demand have been shown to generate less accurate forecasts than the naive no change model This study investigates if the reason for such mediocre forecasting performance is the failure to adopt recent developments in econometric methods in the areas of cointegration error correction models and diagnostic checking The empirical results demonstrate that the forecasts produced using these methodological developments are more accurate than those generated by least squares regression but that these newer econometric models still fail to outperform the no change model as well as statistical time series model Tideswell C T Mules and B Faulkner 2001 An Integrative Approach to Tourism Forecasting A Glance in the Rearview Mirror Journal of Travel Research 40 November 2001 162 171 This study evaluated the results of tourism forecasting exercise in South Australia for the period of 1996 1998 An integrated times series and Delphi process was used to forecast tourism demand from both the international and domestic market Three methods of generating time series forecasts were used Holt s exponential smoothing a naive method using average annual rate of change from the past 11 years and a linear trend using regression analysis A group of 26 tourism industry practitioners responded to a Delphi survey and provided comments in a follow up group meeting process The final forecasting method used was

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Time-Series.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Exponential Smoothing
Forecasting Models

most appropriate methods in this case study A useful comparative table is included listing the advantages and disadvantages of each method for predicting seasonal visitor patterns depending on the quality and characteristics of the data available for analysis Lake States Examples Other Examples Lim C and M McAleer 2001 Forecasting Tourist Arrivals Annals of Tourism Research 28 4 965 977 This study evaluates various exponential smoothing models for accuracy in predicting quarterly tourist arrivals to Australia The Holt Winters Additive and Multiplicative Seasonal models outperform the Single Double and the Holt Winters Non Seasonal Exponential Smoothing models in forecasting The results of this paper show that one should be concerned about seasonality in forecasting and that in this case the existence of unit roots does not seem to be an important issue Tideswell C T Mules and B Faulkner 2001 An Integrative Approach to Tourism Forecasting A Glance in the Rearview Mirror Journal of Travel Research 40 November 2001 162 171 This study evaluated the results of tourism forecasting exercise in South Australia for the period of 1996 1998 An integrated times series and Delphi process was used to forecast tourism demand from both the international and domestic market Three methods of generating time series forecasts were used Holt s exponential smoothing a naive method using average annual rate of change from the past 11 years and a linear trend using regression analysis A group of 26 tourism industry practitioners responded to a Delphi survey and provided comments in a follow up group meeting process The final forecasting method used was based on the results of the Delphi process Grouped forecasting trends e g all international visitors were quite accurate but forecasts for segments of the market e g Japanese visitors were not as accurate This was particularly true for

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Exponential%20Smoothing.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Econometric Forecasting
Models

most cases they have poorer accuracy than more simple techniques This paper claims to present the most comprehensive comparison to date of the performance of econometric forecasting models with a tourism context The six econometric models evaluated are all special cases of a general autoregressive distributed lag specification Two time series models are also evaluated for baseline comparison Each of the models are evaluated for inbound tourism to Denmark for one two three and four year predictions The time varying parameter TVP and long run static cointegration regression model perform most consistently The naive or no change time series model is not far behind in terms of accuracy especially for predictions in years one and two Greenidge K 2001 Forecasting Tourism Demand An STM Approach Annals of Tourism Research 28 1 98 112 This study utilized a Structural Time Series Model to explain and forecast tourist arrivals to Barbados from its major generating markets A structural times series model combines econometric regression and time series analysis This study was able to capture most of the information that is normally left in the residuals of common tourism demand regression models Furthermore it was able to do so using components which have direct interpretations and which can give the planner further insights into tourism behavior Kulendran N and S F Witt 2001 Cointegration Versus Least Squares Regression Annals of Tourism Research 28 2 291 311 Least squares regression models that explain international tourism demand have been shown to generate less accurate forecasts than the naive no change model This study investigates if the reason for such mediocre forecasting performance is the failure to adopt recent developments in econometric methods in the areas of cointegration error correction models and diagnostic checking The empirical results demonstrate that the forecasts produced using these methodological developments

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Econometric%20Models.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Delphi Forecasting
Method

of 1980 Time series analysis the causal methods of multivariate regression and gravity and trip generation models and the qualitative techniques of surveys expert group processes and Delphi modeling are all discussed The author concludes that integrated techniques which combine quantitative methods with expert judgment may be the most accurate Archer B H 1976 Demand Forecasting in Tourism Bangor University of Wales Press This book explores the sate of the art of tourism forecasting in 1976 In particular the techniques of multi variable regression models gravity and trip generation models linear system analysis and expert based Delphi models are explained The components and theory of tourism demand are detailed and the theoretical basis of each model is outlined Lake States Examples Other Examples Tideswell C T Mules and B Faulkner 2001 An Integrative Approach to Tourism Forecasting A Glance in the Rearview Mirror Journal of Travel Research 40 November 2001 162 171 This study evaluated the results of tourism forecasting exercise in South Australia for the period of 1996 1998 An integrated times series and Delphi process was used to forecast tourism demand from both the international and domestic market Three methods of generating time series forecasts were used Holt

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Delphi%20Method.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Judgement Aided
Forecasting Models

of econometric models have become an end in itself Instead techniques that rely on both quantitative analysis and expert involvement are touted as more useful as they integrate forecasting into the strategic planning exercise This allows decision makers to understand the forecasting process and may lead to decision making which more reflective of the tourism forecasts Likewise while citing chaos theory the authors suggest that expert opinion can make very valuable contributions to the forecasting exercise The process that the Australian Tourist Commission goes through to set tourism targets which are essentially forecasts is cited as an example of a valuable integrated approach Uysal M and J L Crompton 1985 An Overview of Approaches Used to Forecast Tourism Demand Journal of Travel Research 23 Spring 7 15 This paper presents a brief review of the tourism forecasting literature as of 1985 Three qualitative techniques are examined simple survey techniques Delphi models and judegement aided models Three quantitative techniques are also reviewed Time series gravity and trip generation models and multivariate regression models Archer B H 1980 Forecasting Demand Quantitative and Intuitive Techniques International Journal of Tourism Management 1 1 5 12 This paper reviews the art of demand forecasting in

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Judgment%20Aided.htm (2014-11-22)

Open archived version from archive - Applied Tourism Economic Impact Analysis - Recreational Demand
Forecasting

demand and supply of marina slips in the area and estimated the economic impact of a marina in Sheboygan Using secondary data the authors concluded that boating was a growing activity and the supply of slips was inadequate Total spending with a 200 slip marina in place would amount to about 3 million with an estimated 64 jobs generated The authors warn that the costs of the marina must be carefully looked at and planned for Drewiske D 1984 Economic Impact Potential for the Racine Harbor Development Project Madison WI Recreation Resources Center University of Wisconsin Extension This study analyzed the planned improvements for the Racine Harbor A demand analysis was conducted and found that the planned marina rehabilitation will begin to fill demand The marina was expected to have a positive economic impact on employment income and the public sector Total economic impact was estimated at close to 20 million The number of full time equivalent jobs was estimated to be about 400 Other Examples Loomis J B 1995 Four Models for Determining Environmental Quality Effects on Recreational Demand and Regional Economies Ecological Economics 12 1995 55 65 This paper addresses the paucity of research which links recreational demand modeling with regional economic analysis modeling The choice to participate in a recreational activity at a particular site are based on four related recreation choices 1 decision to participate in a given recreation activity 2 decision about which of the available sites to visit 3 decision about the frequency of trips to take to a given site and 4 decision about length of stay at the recreation site Each of these four recreational choice decisions is related to and influenced by environmental quality and site facilities When modeling the economic impact of the improvement or degradation of environmental quality or site facilities it is important to consider all four factors or risk underestimating the economic impact of the change Brown T L and N A Connelly 1994 Predicting Demand for Big Game and Small Game Hunting License The New York Experience Wildlife Society Bulletin 22 172 178 The paper presents of the results of a study using ordinary least squares regression to model big game and small game license sales A relatively limited and inexpensive database that included license sales license cost demographic variables and available resources data for New York for 1962 1991 was used in the modeling process The independent variables used in the analysis included 1 license cost and ability to pay e g income 2 size of the general population to which hunters belong 3 degree of urbanization 4 access to the resource and 5 supply of games species and perceived probability of harvest success Time series regression analysis of license sales offers a seldom used opportunity for state wildlife agencies to improve their understanding of the demand for small and big game hunting at the state level Tay R S and P S McCarthy 1994 Benefits of Improved Water Quality A Discrete Choice Analysis of

Original URL path: http://urpl.wisc.edu/people/marcouiller/projects/clearinghouse/Recreational%20Demand.htm (2014-11-22)

Open archived version from archive