Micro-analyses of Tourist Expenditure by Ying Wang

Tourist expenditure is an important measure of international tourism demand. This study is a review of expenditure analyses in a tourism context presenting a range of theoretical factors that could potentially affect tourism demand and expenditure. 

In addition, a review of 16 tourism expenditure studies that used micro data was conducted, to elicit the sample size, model specification, as well as the dependent and independent variables. The study concluded that greater emphasis should be given to micro-economic modelling of tourism demand and the investigation of the effect of psychological and supply-related factors on tourist expenditure. 

Keywords: review, tourist expenditure,micro-economic analyses 

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 1.    A Review of Micro Analyses of Tourist Expenditure 

 2. Abstract Tourist expenditure is an important measure of international tourism demand. 

This study is a review of expenditure analyses in a tourism context presenting a range of factors that could affect tourism demand and expenditure. 

A review of 27 tourism expenditure studies that used micro data was conducted, to elicit the sample size, model specification, as well as the dependent and independent variables. The study concluded that greater emphasis should be given to micro-economic modelling of tourism demand and to the investigation of the effect of psychological and destination-related factors on tourist expenditure.  

 3. Introduction 

Most existing studies used the numbers of tourist arrivals as the measurement of international tourism demand (Lim, 1999; Song & Witt, 2000). However, the tourism product is not just one commodity, but a bundle of goods and services purchased by tourists. The purchasing behaviour of tourists is also likely to vary because tourists differ in terms of their demographics, length of stay, types of accommodation used, purpose of visit, and many other aspects. These variations lead to differences in expenditure among tourists. Consequently, the use of tourist arrivals, which does not reflect tourist consumption patterns and expenditures, can not precisely measure tourism economic impact on the destination.   As economic impacts are expenditure driven, theoretically, it would be useful if tourism expenditures were used more frequently in tourism demand studies. As Cai (1999, p. 16) remarked, "market demand, when expressed in dollar amount, should be a preferred measurement of its substantiality". Wang, Rompf, Severt, and Peerapatdit (2006, p. 333) also pointed out that tourism expenditure is "typically scrutinised by policy makers, planning officials, marketers and researchers for monitoring and assessing the impact of tourism on the local economy".   There have been several reviews of tourism demand studies (Crouch, 1994; Lim, 1997, 2006; Li, Song, & Witt, 2005; Song & Li, 2008); these studies focus on demand analyses in general rather than at the micro level. This paper reviews studies on micro-economic modelling of tourist expenditure. The purpose of the study is to provide a reference for researchers in relation to the sample size, model specification and variables used. A typology of international tourism demand studies is presented 

 4 where micro-economic analysis of tourist expenditure is an important component.  This is followed by a review of studies that focus on modelling tourist expenditure at the micro level. A conclusion is drawn and a number of directions for future research are indicated. Types of International Tourism Demand Study Numerous empirical studies on international tourism demand have been undertaken to explain the possible factors that influence tourist flows worldwide. This study classifies existing demand studies into categories .The demand for tourism can be examined at a macro- or micro-economic level. Tourism demand studies at the macro-economic level are usually concerned with the analysis of aggregated demand. Based on the types of data used, such studies can be classified as time series, cross-sectional and pooled analyses. Time series data refer to data collected over time. Such data enables the modelling of trends, seasonalities and cycles (Hanke, Wichern, & Reitsch, 2001). In many cases, aggregated time series data on inbound and outbound tourists are used to analyse the demand for travel by one or more origin countries for a tourism destination. However, a relatively small sample size is a major problem in time series analysis due to the unavailability of data over a long period (Crouch, 1994; Lim 1997).   

Observations collected at a single point in time across a number of units are called cross-sectional data that are often used to compare tourism demand across countries at one point in time instead of over time periods. The analysis of cross-sectional data 

 

5. May take the form of single equation or system of equations. Despite being closer to consumer behaviour theories, the latter is less common in a tourism context (Li, Wong, Song, & Witt, 2006b). A recent development in tourism literature is the introduction of various specifications of the Almost Ideal Demand System (AIDS) (i.e. Li, Song, & Witt, 2006a; Mangion, Durbarry, & Sinclair, 2005). Time series data on a cross-section of economic units are called pooled data (Hill, Griffith, & Judge, 2001). Pooled data contain cross-sectional information reflecting the differences in tourism demand between countries and time series information reflecting the changes within a country over time. The use of pooled data also increases the number of observations and hence the degree of freedom, which helps to address concerns related to unreliable estimates generated due to the use of small sample sizes. Few empirical studies in the tourism literature have utilised pooled data to analyse international tourism demand (Crouch, 1994; Lim, 1997 & 2006).  Comprehensive reviews of tourism demand analyses by Crouch (1994), Lim (1997 & 2006); Li et al. (2005), Song and Li (2008) have shown much advancement in research at the macro level with the application of new models such as AIDS and Time Varying Parameter (TVP). This study is not meant to replicate previous research effort; rather it differentiates itself by focusing on micro-economic studies.  Crouch (1994) argued that, "the majority of studies have been macro-economic in nature, …. Micro-economic studies of individual or household tourism behaviour are rare" (p. 41). As indicated by the name, micro-economic studies use micro data, which are collected on individual economic decision-making units (Hill et al., 2001). In micro-economic studies of tourism, individuals, households or firms are often the 

 6. Unit of analysis. 

Most studies at the micro-economic level can be classified into three groups. Studies in the first group are concerned with optimal choice in tourism demand. In these studies, the choices of tourists are put in a discrete choice framework and the influences of different aspects of tourist decision-making processes on the choice are taken into consideration. The second group of studies examines the important factors that affect individual tourist expenditures on a given trip and this group is of particular interest to this paper. The third group comprises a small number of studies aimed at modelling tourism prices, for instance using hedonic pricing method. A Review of Micro-economic Analyses of Tourist Expenditure Understanding tourist expenditure is critically important because "tourism is an expenditure-driven economic activity" and "the consumption of tourism is at the centre of the economic measurement of tourism and the foundation of the economic impacts of tourism" (Mihalic, 2002, p. 88).  

 Analysis of tourism demand has been predominantly at the macro-economic level that uses aggregated data such as total arrivals and expenditure in a tourist destination by a market (Crouch, 1994; Lim, 2006; Rosselló-Nadal, Riera-Font, & Capó-Parrilla, 2006). This relates to a high degree of variance in cross-sectional data, which makes modelling an individual's demand for a product more complex and less accurate than modelling the demand for a group of people. Aggregation tends to average out individual idiosyncrasies and consequently, as the level of aggregation increases, both the reliability and accuracy of the model improve. This said, studies using highly aggregated data are less valuable to tourism planning and policy making than those based on data of a lower level of aggregation (Smith, 1995). Deaton and Muellbauer 7 (1980) commented that existing studies often "treated aggregated data as if they had related to a single consumer. There is…no general reason to suppose that this is valid. Even so, it often appears as though models that ignore aggregation phenomena fit as well as those that explicitly allow for them" (p. 80). Lim's (2006) survey of tourism demand analyses showed that out of the 124 studies reviewed, only 8 used survey data at a micro level. This finding supports the view that there is a need for more micro-econometric studies in this area.   Although macro and micro economic studies serve different purposes, micro-econometric models have three advantages over macro-econometric models (Alegre and Pou, 2004). Firstly, the models do not deviate too far from theoretical economic consumer models. Secondly, they allow for the control of participation bias, which is introduced when the analysis is based on aggregated data. Thirdly, they acknowledge the diversity and heterogeneity of consumer behaviours that are ignored in studies using highly aggregated data.  

 This review of micro-economic tourism demand studies has identified 27 that used expenditure as the measurement of an individual's demand for tourism. The following sections present these studies in terms of sample size, modelling method, as well as the dependent and independent variables used. Sample sizes and modelling methods Apart from the earliest study undertaken in 1977 (Mak, Moncur, & Yonamine, 1977) researchers have only shown a renewed interest in the subject since the 1990s. This interest has grown rapidly since the turn of the century with 21 out of the 27 studies being conducted in or after 2000 .Subsequently, these data can be accessed by researchers, which has resulted in a growing focus on the micro-data analysis of the tourism expenditure sub-classifications. Examples of this include the works of academics such as Wang & Davidson (2010), and Brida & Scuderi (2013). Wang & Davidson (2010), in their survey of 27 studies, consider expenditure as the measure of individuals' tourism demand. ...

... Examples of this include the works of academics such as Wang & Davidson (2010), and Brida & Scuderi (2013). Wang & Davidson (2010), in their survey of 27 studies, consider expenditure as the measure of individuals' tourism demand. A great variety of modelling methods are highlighted, but multiple regression analysis remains the most common method employed. ...

... The studies using microeconomic data generally seek to model consumer behaviour and the data requirement can be enormous. Wang & Davidson (2010) identify three types of dependent variables used to measure demand. These are the total amount spent on the trip or total amount per day or amount per day per person (Wang & Davidson, 2010). ...

Analysing the drivers of itemised tourism expenditure from the UK using survey data

... Although "...tourists' spending at destinations around the world is the bread and butter of the tourist economy" (Thrane, 2016, p. 31), some of the related factors have not been sufficiently examined. Regarding their research, Wang and Davidson (2010) have highlighted that the differences in people's consumer behaviour can explain micro-level analyses better, as macrolevel research aggregates travel and expenditure data. Their analysis of existing studies found that income, socio-demographic and trip-related characteristics are the most frequently examined factors of tourist expenditure. 1 Brida and Scuderi (2013) have reported so-called psychographic variables 2 in addition to economic, socio-demographic and trip-related factors in their analysis of published studies.. In their review of micro-analyses of tourist expenditure, Wang and Davidson (2010) concluded that "... theoretically, psychological and destination-related factors may also affect the level of expenditure. Despite this, there has been a limited effort to investigate the role of these variables, presenting a potential area of interest for future research" (p.. For example, extraversion or neuroticism can be considered from stable psychological characteristics. Hence, a still valid requirement to take into account psychological variables in econometric models reflected by researchers for several years (Wang and Davidson, 2010;Brida and Scuderi, 2013;Mehran and Olya, 2019 and others), remains a challenge also for future research. This challenge can be addressed by paying attention to other characteristics which are the subject of psychological science research and which could be expected to be related to the expenditure behaviour of tourists. ...

Psychological Factors of Tourist Expenditure: Neglected or Negligible?

... The structural dimension of tourism demand bases its theoretical underpinnings on the microeconomic theory of tourism demand and, consequently, this demand has been analyzed extensively by microeconomic modelling exercises (Brida & Scuderi, 2013;Wang & Davidson, 2010). At aggregate level, the cross-sectional heterogeneity of tourism demand can be incorporated into multiple equation specifications through the consideration of a system of equations or through the Almost Ideal Demand System (De Mello et al., 2001;Durbarry & Sinclair, 2003;Papatheodorou, 1999). ...

Gravity models for tourism demand modeling: Empirical review and outlook

... Compared to the determinants in the other three groups, less salient factors such as motivation, satisfaction, and taste are rarely included in the tourism analysis as psychological traits (Aguiló et al., 2017;Brida et al., 2014;Di Vaio et al., 2018;Domènech et al., 2020) because these variables pose problems of endogeneity with the residuals of dependent variables in econometric analyses, presenting challenges in statistical analysis (Bernini and Galli, 2019). Although satisfaction with different aspects of the destination has a lasting relationship with the amount of money spent (Brida et al., 2014;Disegna and Osti, 2016;Gargano and Grasso, 2016;Jurdana and Frleta, 2015), Wang and Davidson (2010) reported that satisfaction does not contribute much to tourist spending. Analyses of other psychological traits have also produced very striking results; Di Vaio et al. (2018), for instance, noted that cruise passengers traveling on a super-sized vessel tend to spend significantly less while onshore compared to other passengers (Doménech et al., 2020). ...

Modeling censored tourism expenditures in Turkey with non-normal and heteroscedastic errors: An application of the inverse hyperbolic sine double-hurdle model

... Most studies on tourist expenditure are focused on microeconomic models since they are considered to be closer to theoretical economic consumer models under a global optic [Alegre and Pou 2004, Wang and Davidson 2010, Lin et al. 2015, Konstantakis et al. 2017]. Compared to studies at the macro level, micro-economic models have the advantage of closely mimicking theoretical economic consumer models and can include the diversity and heterogeneity of consumer behaviour that is often cancelled out when aggregate information is used [Kumar et al. 2018]. ..