Tourism Demand and Expenditure

Tourism Demand and accustomPanel in coordinateation abridgment has appe ard in phaetonry look at research (Eilat and Einav, 2004 Garin-Munoz, 2007 and Naude and Saayman, 2005). The circuit card data exercises that were employ in the literature argon pooled logit regression, the generalise method of moments (GMM) procedure of Arellano and Bond (1991), generalised least squ ars (GLS) panel data regressions, and ordinary least squargon (OLS) panel data regressions (which comprise of fixed and random ca aim fabrics). Panel data analysis has some advantages over the time serial publication econometric models. It incorpo ordains much richer tuition from both(prenominal) time series and cross sectional data. This approach in addition reduces the occupation of multicollinearity and provides more(prenominal) than degrees of granting immunity in the model estimation. Therefore, it is suitable for forecasting the quest for phaetonry when the time series for all variants ar e swindleer, and cross-sectional information on these inconstant are also available. In spite of its advantages, the panel data approach has rarely been employ to touristry demand analysis. Four exceptions are put up in the post-2000 literature. Ledesma-Rodrguez and Navarro-Ibnez (2001) utilize the panel data method to model the demand for Tenerife touristry and established both static and participating panel models. In addition, Naud and Saayman (2005) and Roget and Gonzlez (2006) both employed the very(prenominal) panel data approach to examine demand for touristry in 43 Afri dope countries and the demand for rural touristry in Galicia, Spain, respectively.Dependent varyingSelecting a suit inconstant for symbiotic variable in touristry demand model is central. syndicate le et al (2006) in a body of work as Recent Developments in Econometric stamp and Forecasting with comparing tourism demand models ushers that Compared to tourism demand studies prior to 1990, the measures of tourism demand commence not changed much. Tourist arrivals were still the more or slight common measure in the last decade, followed by the tourer expenditure. In particular, tourist expenditure, in the form of either absolute reputes or budget shares, is requisite by the ad hocation of demand system models, such(prenominal) as the linear expenditure system (LES) and the AIDS. Compared with the tourism literature before 1990, recent studies pay more fear to disaggregated tourism markets by run affair (for example, Morley 1998 Turner et al 1998 Turner and Witt 2001a). Amongst various market segments, leisure tourism attracted the approximately research attention. 12 studies foc utilise on this particular tourism market (for example, Ashworth and Johnson 1990 Kulendran and Witt 2003b Song, Romilly, and Liu 2000 Song, Witt, and Li 2003). Different market segments are associated with dissimilar influencing factors and varying decision-making processes. There fore, studies at disaggregated levels give more precise insights into the features of the particular market segments. As a resultant, more specific and accurate information lavatory be provided to develop efficient selling strategies.Explanatory Variables assemble on the tourism economic theory the arrival of tourist is an encouraging factor for an different mortal that will be travelling to a sealed determination. Therefore whatever the number of tourists arrival in the current year in a certain end then, may be the tourist would fasten about back to this country next year if they have had a good experience from that particular cultivation. In the other hand, the information about the destination extends as people share their holiday experiences with relatives and friends therefore it can decrease the rate of uncertainty for potential visitors to that destination. According to Song, (song et al., 2003) the number of people choosing a certain destination in any year de pends on the number of people that chose it in the past years. There are many studies that apply the lagged myrmecophilous variable to explain the tourism demand. For example habibi(2009), Witt and Martin (1987), Fujii and Mak (1981), Garin-Munoz (2007), Garin-Munoz and Martin Montero (2007).Garin-Munoz (2007) discussed the justifications of including a lagged drug-addicted variable in tourism demand models. Two possible justifications are provided. Firstly, there is less uncertainty associated with holidaying in a country that you are already familiar with, compared with travelling to a previously unvisited foreign country, also tourism is generally risk averse and may feel more comfortable in choosing the same previous destination country. Secondly, knowledge about the destination extends as people talk about their holiday, indeed reducing the uncertainty for potential visitors to that destination.Own price The appropriate form of the price variable is by no means clear. In th e case of tourism there are two elements of price the damage of travel to the destination and the be of living for the tourist in the destination. Although the theoretical justification for including transport constitute as a demand determinant does not appear to be disputed, many authors exclude this variable from the set of explanatory variables on the grounds of potential multicollinearity problems and lack of data availability. (In fact, multicollinearity need not be a problem instead, it may be a sign of cointegration, which would give notice the use of error correction models.) In certain studies where econometric forecasting models have been developed for international tourism demand, a specific destination tourists cost of living variable is incorporated in the models. Usually, however, the consumer price force in a country is taken to be a deputy for the cost of tourism in that country. In general, this procedure is adopted on the grounds of lack of more suitable d ata, e.g. an index defined over the basket of goods purchased by tourists, preferably than over the usual typical consumer basket (Kliman, 1981, p.490). (In fact, such indices are now published for certain countries and study(ip) t professs.) Whichever destination price variable is used, it needs to be adjusted by the rate of swop in order to transform it into stock certificate country currency.Exchange rates are also sometimes used separately to represent tourists living costs. Although they usually appear in addition to either a specific tourists cost of living variable or a consumer price index proxy, they may be the furbish up representation of tourists living costs. The usual justification for including an exchange rate variable in international tourism demand ladders is that consumers are more aware of exchange rates than destination costs of living for tourists, and and so are driven to use exchange rate as a proxy variable (Gray, 1966 Artus, 1970). However, the use of exchange rate al star can be misleading because even though the exchange rate in a destination may become more favourable, this could be counterbalanced by a relatively high inflation rate.Empirical results evaluating the precise form of the tourists cost of living element of the own price variable which should be overwhelmd in econometric forecasting models indicate that the exchange-rate-adjusted consumer price index (either alone or together with a separate exchange rate variable) is a reasonable proxy for the cost of tourism, but that exchange rate on its own is not an acceptable proxy (Martin and Witt, 1987). replacement prices Economic theory suggests that the prices of substitutes may be important determinants of demand. For example, an increase in holiday prices to substitute destination country may increase demand for holidays to another country.Mostly, those substitution possibilities allowed for in international tourism demand studies are restricted to tourists destinat ion living costs. A common form in which substitute prices go in the demand function is to specify the tourists cost of living variable in the form of the destination value relative to the origin value, thus merely permitting substitution between tourist visits to the foreign destination on a lower floor consideration and national tourism. The usual justification for this form of relative price index is that domestic tourism is the most important substitute for foreign tourism. Other studies incorporate substitute prices in a more sophisticated manner they allow for the reach of competing foreign destinations by specifying the tourists cost of living variable as destination value relativeto a weighted average value calculated for a set of alternative destinations, or by specifying a separate weighted average substitute destination cost variable.Just as tourists living costs in substitute destinations are likely to act upon the demand for tourism to a given destination, so trave l costs tosubstitute destinations may also be anticipate to have an impact. Furthermore, if the data are disaggregated by transport mode, then travel cost to the same destination by alternative transport mode(s) would influence tourism demand to a particular destination by a given transport mode. However, although some theoretical attention has been paid to the notion of substitute travel costs in the literature, they rarely feature in tourism demand functions.If a price variable is specified as own price elative to substitute prices, then the variable is listed generally under both own price and substitute prices in Table 1. The only exceptions are the very constraining cases where the restore substitute destination price considered is the cost ofAlthough travel costs had been considered in over 50% of the studies reviewed by both Crouch and Lim, in recent studies they did not attract as much attention as before, with only 24 studies including this variable. As precise measureme nts of travel costs were lacking, especially of the aggregate level, proxies such as airfares between the origin and the destination had to be used. However, only in a few cases did the use of proxies result in significant coefficient estimates. Another reason for insignificant exploits of travel costs may be related to all inclusive tours where charter flights are often used, andHence airfares bear little intercourse to published scheduled fares. The deterministic trend variable describes a steady change format, which is too restrictive to be realistic and may cause serious multicollinearity problems. With this borne in mind, recent studies have been less bully to acknowledge it in model specifications. This variable only appeared in 11 reviewed studies. To capture the effects of one-off events, pot variables have been commonly used. The two oil crises in the 1970s were shown to have the most significant contrary impacts on international tourism demand, followed by the Gulf W ar in the early 1990s, and the global economic recession in the mid 1980s. Other regional events and origin/destination-specific affairs have also been taken into account in specific studies.It should be noted that no effort has been made to examine the impact of tourism contribute in the tourism demand literature, which means that the problem of identification has been ignored. An implicit arrogance of this omission is that the tourism domain concerned is assumed to be sufficiently small and the offer cracking is infinite. To draw more robust conclusions with regard to demand elasticity analysis, however, this condition needs to be conservatively examined in future studies.Ferda Halicioglu, (2004) in a paper as An ARDL Model of International Tourist Flows to misfire tries to apply a co-integration technique on the international tourist arrivals to Tur separate. This study empirically examines aggregate tourism demand function for Tur tombstone using the time series data for the goal 1960-2002. The append tourist arrivals into Turkey are related to world income, relative prices and transportation cost. he employ bounds scrutiny co-integration procedure proposed by Pesaran et al. (2001) to compute the short and long-run elasticitys of income, price, and transportation cost variables. The empirical results indicate that income is the most significant variable in explaining the total tourist arrivals to Turkey and there exists a stable tourism demand function.Maria M. De Mello et al (2005) in a study A flexible general form of a Dynamic Almost Ideal Demand System (DAIDS) is derived to analyze the UK tourism demand for its geographically proximate neighbors France, Spain and Portugal, in the period 1969-1997. The results show that DAIDS is a data coherent and theoretically consistent model, providing prove of the robustness of this methodology to conduct tourism demand analysis in a temporal context. Moreover, the energetic model offers statistically s trong evidence on the inadequacy of the orthodox static AIDS and the other restricted models to reconcile consistently data and theory within their formulations. Estimates for tourism price and expenditure elasticitys are obtained, permitting a comparative analysis of the relative magnitudes and statistical relevance of long and short run sensibility of the UK tourism demand to changes in its determinants.Sara A. Proenca (2005) in Demand for Tourism in Portugal A Panel info Approach use a panel data techniques to estimate the demand function of tourism in Portugal by considering four main countries as the basic tourism suppliers, Spain, Germany, France and the U.K., responsible for almost 90% of the total tourism inflows in this country. In the demand function she introduces both the demand factors include per capita income, relative prices and the write out factors (public investment ratio, accommodation capacity) to explain tourism performance in Portugal. The result of the est imation the models shows that per capita income is the most important demand determinant and accommodation capacity the most important add on determinant explaining thus the tourism flow in Portugal and also, the accommodation capacity is the most important factor in attracting more tourism to this country.Vani K. Borooah (1999) in the supply of hotel modes in Queensland, Australia examines the supply decisions of hotel and motel owners with respect to guest fashions. This study employed an econometric analysis of supply responses in the hotel sector in the three Queensland regions of the Gold Coast, Whitsunday, and Cairns. The result shows that the supply of guest styles, in all three regions, was strongly responsive to increases in earnings (per occupied elbow mode) but was less influenced by increases in the elbow room military control rate or by changes in the interest rate. provided the relative strengths of earnings and occupancy rates in influencing supply responses may have much to do with the aggregation of individual hotels into a hit sector. Also, Increases in earnings might be a generalized phenomenon, affecting all hotels, and thus evoking a strong supply response from the hotel sector. In addition, increases in occupancy rates might be restricted to a subset of hotels, which are at the margin of being capacity- constrained, evoking a weaker response from the sector.Gonzalez and Moral (1995), in a study as the international tourism demand in Spain, try to find a precise indicator to measure the external demand of the tourist sector as one of the main problems in analyzing the potentialities is. They use tourists expenditure as the dependent variable, defined as the product of three factors the number of tourists, the length of their deposit and the daily average spending. Also About this put forward Cunha (2001) argues that the number of entrances is not a good approximation to express tourism demand since it ignores one of the most important aspects in this sector the demand of goods and services that tourists require during their permanence.Mello and Sinclair (2002), alternatively, use the share of tourism spending of the origin country to other destination countries to study tourism demand in the U.K. The authors argue that this variable captures the consumption behavior of the tourists and explains the spending component of this economic activity. It is possible to observe an increase in the tourism inflow accompanied by a reduction in spending explained by higher domestic inflation and shorter length of stay. For this reason the expenditure approach is preferable to the inflows approach to study the demand for tourism behavior from the heading of view of the hosting country. Rodriguez and Ibanez (2001) use the number of visitors lodged in the destination country as the dependent variable to study the demand for tourism in a panel data approach. The choice of this variable to express tourism demand (in com parison with the number of tourist entrances) has the advantage to consider the length of the stay and to exclude tourists that are hosted to family or friends houses. According to the literature review, the most appropriate variable to be used as the dependent variable in the demand for tourism equation is tourism receipts from the point of view of the receiving country or tourism spending from the point of view of the supplying country (Tse, 1999 Lathiras and Siriopoulos, 1998). However, check to Crouch and Shaw (1992), almost 70% of the studies that estimated tourism demand functions have used the number of visitors (entrances) as the dependent variable (Quiand Zhand, 1995 Morris, Wilson and Bakalis, 1995 Kulendran, 1996 Akis, 1998). The main reason for this choice has been the unavailability of data on tourism spending.Naude ,W.A. A. Saayman (2004) in a paper about determination of tourism arrivals in Africa use cross-section and panel data for the period 1996 to 2000 to deli neate the determinants of tourism arrivals in 43 African countries, taking into account the country of origin of tourists. The results suggest that political stability, tourism infrastructure, marketing and information and the level of development in the destination are key determinants of travel to Africa. Typical developed country determinants of tourism demand, such as the level of income in the origin country, the cost of travel and the relative prices, are not that significant in explaining the demand for Africa as a tourism destination. They are recommended that attention should be given to improving the overall stability of the continent and the availability and quantity of tourism infrastructure.ONeil Malcolm (2003) in study about Tourism Maturity and Demand in Jamaica estimates a demand function for Jamaicas tourist product. An error correction model (ECM), structural time model (STM) and an autoregressive base average (ARIMA) model were employed. The ECM was more robust t han the ARIMA and STM models in predicting tourism demand. The ECM and ARIMA models captured the major turning points in the series well and provided reasonably good forecasts. In contrast to the findings of Henry and Longmore (2002), the results indicate that source country income is significant. The explanatory power of the ECM improved with the inclusion of the tourism density ratio, implying that researchers should include inter-action factors in tourism demand models. The empirical analysis indicates that Jamaica has a mature tourism product. The empirical analysis indicates that tourism demand is predominantly explained by income in source country. The absolute price, relative price and exchange rate have very marginal, and in most cases no significant impact on tourism demand. The finding also suggests that Jamaica is a maturing destination for the USA and UK markets. Of the three models estimated the ECM was the most appropriate in explaining tourism demand. It was found tha t the inclusion of the tourist density ratio in the regression improved the explanatory power of the model. The unit price of the service was found to be insignificant.Smith, S. L. J. (1995) describes the challenges with describing and defining tourism. Particularly, it focuses on defining tourism as a demand-side concept from the perspective of the person taking the trip or supply-side from the perspective of the commercial enterprise supplying the tourism product or service. On the demand-side tourism can be classified by length of stay, typeface of expenditure, type of traveler, type of trip, transport mode or accommodation type. On the supply-side, the tourism industry can be classified first by whether the commercial enterprise and secondly by the type of tourism product such as passenger air transport, camping, recreation and entertainment.Empirical Study in Tourism TaxBase on Gooroochurn and Sinclair (2005) study that tourism revenuees are welfare-enhancing since the destination country can transfer the tax to foreign tourists. They found that tax on tourism was more efficient and frank than levying tax on other sectors in country. However, gosling peetersceron and dubois (2005) argue that destinations adopting eco-taxes on tourism may possibly concentrate from welfare loss. Similarly, Jensen and Wanhill, (2002) suspect that worldwide increases in both numbers and rates of tourism taxes in recent years are not welfare-enhancing, since governments seem to consider tourism taxes as easy money, giving them permission to deviate from economic rationality. The past literature includes a number of studies on the impact of tourism taxes on destinations welfare, often with controversial findings (Bird, 1992Clark and Ng, 1993Dimanche, 2003Forsyth and Dwyer, 2002Gago, Labandeira, Picos, and Rodriguez, 2009 Levine, 2003Litvin, Crotts, Blackwell, and Styles, 2006Mak, 1988Mayor and Tol, 2007Palmer and Riera 2003Piga, 2003).According to Corey Gerant Mathew s, (2004), some(prenominal) sources suggest that reductions or the elimination of tourism marketing have a proscribe effect on travel to and revenues of the target country, On the other hand, several evidence suggest that tourism tax could support other plans in the destination country such as education, transportation, life guarding, zoos, and other programs and services that would also draw additional tourists to the area.Mak and Nishimura (1979) drew a conclusion in which they estimated the influence of a hotel room tax on hellos tourist industry using single equation estimation approaches. They utilized cross section data on individual visitor parties, had placid by hello Visitors Bureau (HBV) in 1974. Like cross section demand studies, that study was detracted from by the difficulty and imprecision in measurement of the prices.A similar conclusion was reached by Bonham, Carl and Byron Gangnes (1996) in Intervention epitome with Co-integrated Time Series The Case of the Ha waii Hotel Room Tax. In this article, they analyzed an intervention of a room tax levied by the state of Hawaii in 1987. In that study room tax was found not to have a noticeable statistically significant contribution to room revenues. They analyzed the ex-post effect of the room tax on revenues using a time series econometrics textile.Hailin Qu, Peng Xu, Amy Tan (2004) in a paper as A simultaneous equations model of the hotel room supply and demand in Hong Kong use a system of include demand and supply equations to identify the important factors that influence the hotel room supply and demand, and their overall impact on the Hong Kong hotel industry. In the model of tourism supply they used average hotel room rate as dependent variable. They employed 19 years of time series data in simultaneous equations econometric framework. The result of estimation of model show that the overall goodness-of-fit of both demand and supply models is very high, suggesting high predictive power. Mo re ever, Empirical results indicate that hotel room price and tourist arrivals are significant factors driving the demand for hotel rooms. In addition, 1990-91 recession and the 1997-98 Asian financial crisis had a significant negative impact on the demand for hotel rooms in Hong Kong. At the same time, hotel room quantity demanded, room occupancy rate, last periods room price, labor cost, last periods average price of Grade A surreptitious offices, and the Asian financial crisis had a significant impact on room price in the short run.H. Tsai et al,(2006) in Examining the hotel room supply and demand in Las Vegas A simultaneous equations model try to identify the important factors that influence the hotel room supply and demand, in Las Vegas employing econometric variables in a simultaneous framework during 1992-1999. In the model of tourism supply they used average hotel room rate as dependent variable. The results show that room rate for the current calendar month, the 3-month Tr easury bill rate and gaming revenue per room for the 12-month prior are the three determinants of the room supply function, while consumer price index for the current month is the only determinant of the room demand function. This study also employs the 2SLS technique, but tests different econometric variables in the Las Vegas context.At the beginning they modeled the empirical treatment of hotel room revenues employing a variant of the multi-input transfer function methodology developed by Box and Jenkins (Box, Jenkins and Reinsel,1994).They method extends the rudimentary transfer function model to include long term co-integration relationships between room revenues and major explanatory variables.Once an appropriate pre-intervention model has been identified, it is applied to the post-intervention sample. they model appears to provide strong evidence against any significant permanent effect of the room tax on either the level or growth rate of after-tax hotel room revenues and thi s is not a move conclusion. As Bonham et al. (1992) indicated, a rise of 5% in room rates is less than 1.5% of the total cost of a typical Hawaiian vacation. Therefore, noticeable adjustments to room demand are improbable. The tax is invisible to the tourist when planning a Vacation as the tax is added to room bills on checkout. Hawaii was not was not imposing or rising room tax during the period of time. The Undesirable adverse effect of Hawaiis tax on competitiveness would decrease to the extent that taxes were increasing in competing markets.John O. Spengler and Muzaffer Uysal(1989) in a study as considerations in the hotel taxation process try to analysis the tax on hotel room. This paper is think to put the notion of hotel taxation into perspective providing a framework of elements which tax experts and hospitality speci9lists deem important. include tax elements consist of economic considerations, tax incidence, tax progressivity and equity, and tax exportability. These elem ents are also examined as part of.a process under conditions of inelastic and elastic demand. Finally, a brief discussion of taxation insurance implications was provided. Given the importance .of the hotel tax to members of the tourism industry and policy makers, a synthesis of the key variables which influence the taxation process is paramount. This paper has explored these variables individually and in combination.It is hoped that this effort has furthered a better understanding of the hotel taxation process. This understanding, however, should be backed by reliable and relevant research.In specific, research should be conducted which addresses the First, the demand supply elasticitys for visitor destinations should be studied. Findings from this line of study will determine in general whether it is the visitor or the hotelier who bears the greater consequence of the tax. This will. Provide answers to the question of tax incidence. Second, research should address questions relati ng to the income characteristics of visitors, the proportion of business travelers to tourists, and the economic consequences of the tax for tour operators, meeting planners and corporations. These questions concern the concept of tax equity and progressivity. Third, research is suggested regarding the exportability of a hotel tax. Studies addressing the percentage of hoteliers and employees who are local residents, and the percentage of hotel guests who are residents of the local community would be relevant. Last, questions concerning the use of pecuniary resource derived from the tax must be answered. Research should address whether finances used in the past for progression and upgrading visitor attractions have increased visitor demand. In addition, the most appropriate and efficient use of funds should be addressed. With sufficient information supplied by research, and adherence to general guidelines in policy formation, legislators will be better able to make just and rationa l decisions concerning the hotel tax.E.Aguilo et al. (2005) in a study as The short-term price effect of a tourist tax through a dynamic demand model for the Balearic Islands. The objective of this paper is to identify the markets sensitivity to price changes in travel-related services or groups of services, assuming that one of the main factors that influences travel decisions is the information on the destination that consumers receive. In order to include this effect, the study applies a combination of a diffusion model and a traditional economic utility theory model to tourists visiting the Balearic Islands (Spain) from the United Kingdom, Germany, France and the Netherlands. The result shows that The effect of the tourist tax on tourism supplies has not been assessed.Richard M. hushing (1992) in Taxing Tourism in Developing Countries show that in principle there is a strong economic case in many, countries for taxing tourism more than at present, but that the constitution of the industry and administrative difficulties severely limit what can be done in practice. This analysis and a review of the fiscal instruments available to most developing countries suggest three main conclusions first, more attention should be paid to introducing adequate chargingPolicies where possible second, special taxes on hotel accommodation are generally the key to tourist taxation and third, there is little reason to provide special incentives for investment in the tourist industry. According to Bonham, Carl and Byron Gangnes (1996) in Intervention Analysis with Co integrated Time Series The Case of the Hawaii Hotel Room Tax. Room taxes are touted by proponents as a way to shift the local. tax burden to non-residents, while the travel industry claims the levies significantly harm their competitiveness. In this study, they analyze the effect on hotel revenues of the Hawaii room tax using timeseries intervention analysis. They specify a time series models of revenue behavior that captures the long-term co-integrating relationships among revenues and important income and relative price variables, as well as other short-run dynamic influences. They also, estimate the effect on Hawaii hotel room revenues of the 5% Hawaii hotel room tax introduced. in January 1987. The result show that no evidence of statistically significant tax impacts.Fujii, Edwin, Mohammed Khaled and pack Mak (1985) in a paper as The Exportability of Hotel Occupancy and Other Tourist Taxes attempt to examine the incidence and exportability of an ad valorem hotel room occupancy tax for Hawaii vis-a-vis alternative tourist taxes. The study employs a system approach and times series data (1961-1980. Results indicate that a hotel room tax is readily, though not fully, shifted/exported. It is more readily exported than similar taxes levied on excise/sales tax, since taxes levied on non-lodging expenditures also degenerate heavily on residents. Results also suggest that taxes imposed on tou rist spending have a moderately large negative output effect on the visitor industry.Hiemstra, Stephen J. and Joseph A. Ismail (1992) In their study as Analysis of Room Taxes Levied on the Lodging Industry try to summarize a study of the impacts of room taxes on the lodging industry by (1) reporting the findings of Phase 1I of an overall study assessing the negative impacts on number of rooms rented of room taxes levied on the lodging industry, and (2) applying the price elasticity of market demand found instp 1 to the average amounts of room taxes paid, as measured in Phase I of the overall study. The elasticity measurement comes from a statistical model based on data from a national pro