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ITALIAN OUTBOUND TOURISTS, TOURISTS' EXPENDITURE AND SATISFACTION

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The paper aims at investigating the expenditure behavior of Italian tourists travelling abroad for personal purposes. In particular, we focus on the relationship between expenditure and satisfaction of Italian outbound tourists over the period 2007-2017, by using data provided by Bank of Italy. We suggest using the quantile approach in estimating the effect of satisfaction on the different quantiles of tourism expenditure. This feature enriches the understanding of what determines heterogeneity in tourists spending behavior, which is a relevant information for policy makers and destination managers. To control for endogeneity between satisfaction and expenditure, we take advantage from the instrumental quantile estimator (IVQR), which allows us to obtain consistent estimates of model's parameters. Satisfaction with specific characteristics of the destination is found to be significant in affecting tourists' expenditure behavior, and this effect differs among quantiles and expenditure categories.
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ITALIAN OUTBOUND TOURISTS, TOURISTS’ EXPENDITURE AND SATISFACTION
Cristina Bernini & Federica Galli
Department of Statistical Sciences
Center for Advanced Studies in Tourism
Campus of Rimini -University of Bologna
P.tta Teatini 10, Rimini, ph. +390541434308
cristina.bernini@unibo.it federica.galli11@studio.unibo.it
Abstract: The paper aims at investigating the expenditure behavior of Italian tourists travelling
abroad for personal purposes. In particular, we focus on the relationship between expenditure and
satisfaction of Italian outbound tourists over the period 2007-2017, by using data provided by Bank
of Italy. We suggest using the quantile approach in estimating the effect of satisfaction on the
different quantiles of tourism expenditure. This feature enriches the understanding of what
determines heterogeneity in tourists spending behavior, which is a relevant information for policy
makers and destination managers. To control for endogeneity between satisfaction and expenditure,
we take advantage from the instrumental quantile estimator (IVQR), which allows us to obtain
consistent estimates of model’s parameters. Satisfaction with specific characteristics of the
destination is found to be significant in affecting tourists’ expenditure behavior, and this effect
differs among quantiles and expenditure categories.
Keywords: outbound tourists, tourism expenditure, satisfaction, expenditure category, instrumental
quantile regression
1. Introduction
The great recession of 2008-2009 and the following sovereign debt recession of 2011-2013, have
deeply affected the Italian tourists’ behavior and their decision making process. As underlined in
Bernini et al. (2019), the reduction in Italian households’ disposable income has negatively
influenced their expectation about future income; thus, this perception has pressed drops in their
expenditure and/or a change in consumption decisions.
In Italy, the crises have produced a reduction in the number of households participating in tourism,
and a decrease in the tourism expenditure of households who had a holiday. In particular, tourism
dynamics over the recessions are caused by two different issues: a cut in the percentage of tourists
and a lowering in the mean tourism expenditure. As suggested by Bernini et al. (2019): “the former
has an important effect on the consumption, because the crisis may have pushed the relatively less
well off out of the market. Those who did go on holiday could likely afford a longer holiday; this
evidence might indicate a change in travel patterns, with a reduction in the number of trips
accompanied by a longer stay.
Other than having modify the propensity to participate in the tourism market, the economic
recessions have modified the destination choice of Italian people (i.e, domestic versus international
travelling). Overall, Italian citizens appeared to decrease their domestic and international holidays
by about the same percentage
1
, but the reduction of domestic overnights is much higher than that
observed for the international holidays. With respect to 2007, the number of trips for personal
purposes in the national territory in 2013 diminished of 43%, while those directed to foreign
countries of one third. In the long run (2000-2017), the contraction in domestic trips is of -24% while
it remains substantially stable for the international ones (ISTAT, 2019).
Therefore, the economic trend and crises have changed the relationships between tourism industry
development and tourist destinations, and a new structure has occurring within the two markets of
the domestic and outbound tourism. In this framework, understanding the Italy growth in outbound
tourism and the characteristics of outbound tourism has important implications in terms of
economic and tourism marketing policies.
In particular, the analysis of outbound tourism is relevant for two main reasons. First, even if the
literature has focused largely on inbound tourism and its contribution to the economy, the outbound
tourism is fundamental in determining the level of a country’s welfare. As underlined by Dai, Jjang,
Yang & Ma (2017), outbound tourism should be stimulated because of its positive impact on either
tourists satisfaction or the development of tourism sector and country’s wealth. In particular, they
affirm: “Outbound tourism is part of the promotion of a comprehensive national tourism
development strategy that includes the enhancement of international exchanges and other aspects
of the country's soft power.” Opportune marketing policies supporting the outbound tourism reflect
the citizens’ open-mindedness and country’s economic strength. Moreover, outbound tourism
encourages to spread abroad the culture and the values of a country, and to boost collaboration and
integration among nations.
Second, outbound tourism is a good measure of the citizens’ well-being, because it is likely to decline
during crisis, negative feelings or bad moods. Customers increase their tourism expenditure only if
they feel confident about the economic condition of their country. Demir & Gozgor (2018) show that
tourism growth relies on the nation’s economic condition and that economic policiesuncertainty
1
Over 2007-2013, Italian people having a domestic and an international trip per 100 inhabitants reduce of
30.3% and 31.9%, respectively.
affects the tourism industry. Dragouni, Filis, Gavriilidis & Santamaria (2017) provide evidence that
there are spillover effects of shocks to feelings and moods on outbound tourism demand. Besides,
economic recession determines the decision of tourists to reduce their tourism expenditure
differently for the domestic and international destinations. Eugenio Martin & Campos Soria (2014)
show that the global economic crisis of 2009 produced a drop in international tourism, allowing new
opportunities for domestic tourism. However, such adjustment in tourism destination is not
homogeneous for all country, being affected by the climate and GDP of the areas of origin. As
concerns the decision to spend on trips abroad, Bernini et al (2019) demonstrate that the effect of the
economic crisis appeared to be more severe than for the domestic holidays. The crisis changed
household consumption patterns and travelling abroad becomes a luxury good. As in Eugenio
Martin & Campos Soria (2014), Bernini et al (2019) provide strong statistical evidence of
heterogeneous effects among tourists with respect to the area of origin.
In this study, we analyze the expenditure behavior of Italian tourists travelling abroad for personal
purposes. In particular, we focus on the relationship between expenditure and satisfaction of Italian
outbound tourists, representing the first novelty of this analysis. A very few studies has investigated
the effect of satisfaction on tourism expenditure (Yeung, Ramasamy, Chen & Paliwoda, 2013;
Disegna & Osti, 2016; Jurdana & Frleta (2017), showing that satisfaction is a determinant of tourist
expenditure and that tourist’s expenditure depends on the different domains that defines the overall
satisfaction. At our knowledge, no studies have yet analyzed the role of satisfaction on tourists
travelling abroad, even if outbound tourists’ satisfaction is a very important issue for policy makers.
As Dai, Jiang, Yang & Ma (2017) emphasize, international tourists’ satisfaction helps destination
countries to improve their offer in accordance to outbound tourists preferences; moreover,
outbound tourism policies support the whole development of the tourism industry of a country.
In line with Disegna & Osti (2016), we improve the analysis by investigating not only the relationship
between total expenditure and overall satisfaction, but also focusing on how the expenditure of
Italian tourists for restaurants, accommodation and shopping depends on satisfaction for meals,
hotels and shopping, respectively.
The third novelty of the analysis regards the statistical approach used in investigating the
expenditure function; we suggest using the quantile approach in estimating the effect of perceived
satisfaction on the different quantile of expenditure. Studies making use of a quantile estimator are
quite recent and include Chen & Chang (2012), Hung, Shang, & Wang (2011, 2012), Saayman &
Saayman (2012), Lew & Ng (2011), and Thrane & Farstad (2011). To note, Chan & Chang (2012) used
both an OLS and a quantile approach to investigate the effect of travel agents on their customers
total travel expenditures adding also the level of satisfaction as a determinant of total expenditure.
However, as well underlined by Mortazavi (2018), the models relating satisfaction to expenditure
generate inconsistent estimates because of an endogeneity problem; overall satisfaction is correlated
with the error term (also the level of satisfaction depends on the total expense), largely affecting
parameter estimates. Therefore, our contribution consists in estimating the relationship between
tourism expenditure and satisfaction, controlling for endogeneity to obtain consistent estimates. We
suggest using an instrumental quantile estimator (IVQR) that can manage endogeneity thanks to IV
estimators at the different quantiles of the expenditure. Then, this approach allows us to obtain
consistent estimations of the effect that the satisfaction has on total expenditure across the different
quantiles of the expenditure of Italian tourists that go on holiday abroad.
Finally, we use a large and comprehensive database provided by the Bank of Italy, exploiting micro-
information on the degree of satisfaction and expenditure expressed by Italian tourists who travel
abroad for personal purposes over the period 20072017 never used before.
2. Literary Review
A wide tourism literature has examined determinants of visitor expenditure (see Brida & Scuderi
(2013) for an extensive review); while there are very few studies that considers satisfaction as a
determinant.
According to Wang et al. (2006), the consumption behavior of tourists depends on a large set of
determinants that can be classified in four categories: economic constraints, socio-demographic, trip-
related, and psychographic characteristics.
The evidence on economic constraints mainly confirms a positive and significant effect of income on
tourist spending (Alegre et al, 2009; Fleischer & Rivlin, 2009; Eugenio-Martin & Campos-Soria, 2011;
Bernini & Cracolici, 2015, 2017). Other variables such as the ownership of economic assets, indicators
of financial difficulties and health care expenditures may result in a significant relationship with
spending, contributing to the definition of constraints for leisure choice (among others: Alegre et al.,
2010; Hong et al., 2005; Hung et al., 2012).
Literature has highlighted the relevance of household and householder characteristics. The size and
composition of household (Yang & Lin, 2004; Nicolau & Más, 2005a 2005b; Alegre & Pou, 2004), the
home ownership (Hong, Kim & Lee, 1999), and the geographic location of households (Xu et al.,
2017; Lin et al., 2015) affect the level of tourism consumption. Gender, age and life cycle are used as
proxies of individual preferences also in tourism (Uysal et al., 1996; Eugenio-Martin & Campos-
Soria, 2011; Bernini & Cracolici, 2015). Besides, higher level of education has a positive effect on the
decision to participate in tourism and to consume (Van Soest & Kooreman, 1987; Alegre & Pou, 2004;
Nicolau & Más, 2005a, 2005b) as it reflects economic constraints and easier access to information.
People with a stable job are more inclined to travel than unemployed people (Alegre et al, 2010;
Eugenio-Martin & Campos-Soria, 2011).
Different trip-related variables resulted in a frequently significant relation with spending, such as
accommodation, travel destination, means of transportation, typology of intermediary for
reservation, travel distance, and time of the holiday (among others: Jang et al., 2002; Jang, Ismail, &
Ham, 2002). Length of stay and party size (Brida et al., 2012; Jang et al., 2002) as well as variables
related to travel cost, information source, and previous travel experiences may also have a role in
influencing the participation in the tourism market (Marcussen, 2011b).
As for psychographic characteristics of householders, there is evidence that self-concepts, lifestyle,
attitudes, opinions and perceptions of the trip experience effect tourism spending (Lehto et al, 2002;
Demby, 1974). However, official surveys rarely observe psychological characteristics of the
consumer directly, and this can be one of the reasons for such limited use. Conversely, the topic of
tourists’ satisfaction has been largely discussed to improve tourism product and service, to design
management and marketing strategies (Kozak & Rimmington, 2000; Munier & Camelis, 2013) and
to measure a destination competitiveness and performance (Enright & Newton, 2004; Alegre &
Garau, 2010; Munier & Camelis, 2013). However, a very few studies have analyzed satisfaction as a
determinant of expenditure even if that is very interesting for tourism policies. As well underlined
by Homburg et al (2005) when customer experience elevated states of satisfaction, they perceive a
high outcome of an exchange and therefore are willing to pay more ... because this still results in an
equitable ration of outcome to input (Homburg et al, 2005, p 85).
Recently, a few contributions have examined the effect of perceived satisfaction on tourist
expenditure. Kim, Prideaux, & Chon (2010) and Chen & Chang (2012) find a positive correlation
between visitor satisfaction and level of expenditure. Disegna & Osti (2016) evidence that
satisfaction with different aspects of the visit influences spending. In particular, they studied how
tourist’s expenditure depends from the different categories that defines the overall satisfaction
finding that the relationship between the aspects with which the tourists are satisfied and the
corresponding expense of the product categories is particularly relevant (for example satisfaction
with the landscape affects positively the choice of tourists of spending on accommodation and
transportation). Yeung, Ramasamy, Chen & Paliwoda (2013) show that customer satisfaction plays
a crucial role in determining consumption expenditure and this relationship is stronger in countries
with higher economic freedom. Besides, Jurdana & Frleta (2017) found that satisfaction is a
determinant of tourist expenditure, but in this case not all the dimensions of satisfaction were
significant predictors of expenditure. Only satisfaction that relates with the diversity of facilities
(sports facilities, entertainment opportunities diversity of cultural events, facilities for children,
excursion offer, shopping opportunities) contributes significantly to increase tourist’s daily
expenditure. As for the meeting and convention industry, Zhang, Qu & Ma (2010) investigate the
role of perceived satisfaction (i.e, referred to the categories of environment, facilities, accessibility
and hotel, food and attraction) on the total expenditure. They found that the hotel, food and
attraction factors are the most important predictors to attendee’s overall expenditure. Besides, this
study suggests that tourist’s satisfaction has a positive effect on overall expenditure.
However, neither of these studies discusses the issue of possible endogeneity involved when
tourism expenditure is regressed on tourist satisfaction (while satisfaction may influence spending,
the latter may also affect the former). This may be a relevant problem from a statistical perspective
because the coefficient estimates are biased and inconsistent in the presence of endogeneity
(Verbeek, 2012). Consequently, biased and inconsistent estimates cannot be used for policy and
decision making. The only contribution discussing this issue is the study by Mortazavi (2018), who
explained that the models relating satisfaction and expenditure generate inconsistent estimators
because there is a problem of endogeneity. That is, the overall satisfaction is endogenous and it is
correlated with the error term (also the level of satisfaction depends on the total expense).
Controlling for endogeneity, the author finds that the estimated elasticity of expenditures with
respect to overall satisfaction by means of IV is 27 percentage points smaller than the estimate by
OLS. This implies a severe overestimation if endogeneity is not taken into account.
3. Data
The analysis is performed on the data collected by the Bank of Italy through the survey ‘International
Tourism in Italy’ (Banca d’Italia, 2018). Since 1996, tens of thousands of randomly selected inbound
and outbound travellers are interviewed each year at frontier posts and are asked questions on
personal characteristics, the features of their trip and their satisfaction. The survey data include
gender, age, profession, country of origin, the accommodation facilities used, the reason for the
holiday, the number of travellers, overnight stays, expenditures and opinions of the place (at the
municipality level) where the longest period of the holiday was spent (Alivernini, Breda & Iannario
2014).
Our analysis focused on Italian tourists travelling abroad, whose main purpose is ‘tourism, holiday
and leisure’, over the period from 2007 to 2017. Tourists are interviewed at the frontier when they
come back to Italy. Besides usual individual and trip specific information, the travellers are also
asked about their total expenditure and expenditure categories such as transport, accommodation,
restaurant, shopping and other expenditures. Tourists are invited to evaluate the overall degree of
satisfaction with their stay and with different aspects of the trip, on a 10-point Likert-type scale
ranging from 1 (very dissatisfied) to 10 (very satisfied). Different aspects of the trip include the
hospitality and friendliness of the people, cities and works of art, the landscape and natural
environment, hotels and other accommodations, food and beverage, prices and the cost of living,
the quality and variety of products offered in stores, information and tourist services, and safety.
Of the 806,377 Italian tourists observed over the period 2007-2017, we focused on travelers that move
for leisure reasons as holidays or fun (40.76% of the total). To better control for satisfaction and
expenditure at each destination, data were also adequately cleaned (see Appendix A); thus, the final
sample consists of about 282,751 Italian tourists.
Table 1 shows some descriptive statistics about the characteristics of the travelers and of the journey
referring to the destinations that Italians reach. The most visited countries are France (10.11%) Spain
(12.38%) USA (9.73%), Germany (5.02%), UK (4.72%) and Austria (5.35%) so we considered these as
the main countries, while all the other countries have been grouped by continents.
The destinations mainly chosen by young people are UK and Spain, while the oldest (more than 65
years old) prefer France (14.16% of people visiting France is aged more than 65). USA, America and
Oceania are mostly visited by people aged 25-34 (36.96%, 37.49% and 43.96% of their total,
respectively). France and Austria are the destinations preferred mainly by people aged 45-64.
Employees, self-employees and students are the job position that travel more. In particular,
employees prefer destinations like USA, America, Africa and Asia; while the majority of students
travel to Spain (20.69%) and UK (24.70%). Retired spent their holiday in France and Austria.
Insert Table 1
Concerning accommodation, Italians prefer staying in hotel, touristic village, farmhouse or bed and
breakfast, in particular in Spain, USA, Asia, Africa, America and Oceania. Houses for rent are mainly
chosen in Spain, Europe, America and Oceania. 35.09% of Italians visiting France has a house of
property or it is hosted by relatives or friend. Even in Germany and UK, Italians are often guests of
friends or relatives or they have a house of property. 18.91% of people visiting Austria do not spend
the night away.
Regarding the average length of the travel, people spent more nights in USA (13.89), America (19.34),
Asia (18.05) and Oceania (42.50), which are the more distant destinations. The average length of the
travel referring to all leisure tourists is 10.60 nights.
Table 2 shows mean total expenditure and mean expenditure for the different categories of expense
in each destination. Referring to all leisure travelers and to all destinations the average expenditure
is €1346.14, with a mean per-day expenditure of 170.80. Tourists spend more money in Oceania
(€3267.02), America (2051.24) and USA (2468.45) while for Italians Austria is the cheaper
destination (average expenditure is €645.49).
The category in which tourists allocate the majority of their expenditure is accommodation, in
particular the share of expenditure for accommodation is bigger in that countries in which tourist
have a higher total expense. France has the lowest share of expenditure for accommodation (33.50%
compared to a medium level of 42.53%), on the other side France has the biggest share of expenditure
for restaurant (32.44% compared to the medium level of 24.28%). Conversely, Africa has the biggest
share of expenditure for accommodation (48.20%) and the lowest for restaurant (14.92%). The
destinations in which tourists prefer spending for shopping are UK (17.96%), USA (17.43%) and
France (16.66%).
Insert Table 2
Table 3 shows the average satisfaction of tourists for various features of the journey (i.e., standard
deviations are reported in brackets). In general, Italian tourists are very satisfied of their journey
because overall satisfaction’s score is more than 8 in each destination. Considering overall
satisfaction, the destinations that travelers appreciate more are Oceania (8.70), Austria (8.54), USA
(8.53) and Spain (8.49) while Africa has the lowest score of 8.20. The others categories present quite
high scores, with the exception of prices that is always above 6; in particular prices are evaluated as
insufficient in UK (5.58). So, satisfaction about prices is often the category with the lowest scores
instead the category that most impresses tourists is environment, in fact it takes very high scores in
all the destinations (the minimum score is 8.35 for UK). Tourists mainly appreciate artistic and
cultural offer in France (8.67), Austria (8.69) and UK (8.74); while they are very satisfied of safety in
Oceania (8.79), Austria (8.92), Germany (8.69) and USA (8.71). Tourists mostly appreciate courtesy
in Oceania (8.64) and America (8.63) while the worst score is that of France (7.66). The highest score
for accommodation is the one of Austria (8.36) while UK has the lowest (7.41). Food in general is not
really appreciated; all scores are under 7.72 that is the score assigned to Spain. In particular, the
countries that are less appreciated for food are USA (6.91) and UK (6.38). The destination that has a
score sensibly higher than other destinations for shopping is USA (8.41) considering a medium score
for shopping of 7.66, while Africa has the lowest score of 6.94. All scores for information are quite
high and Oceania reaches the highest level (8.51).
Insert Table 3
Our analysis mainly concentrates on the relationship between tourists’ expenditure and satisfaction,
so it is useful to analyze their dynamics. Figure 1 (first panel) shows the total expenditure of Italian
tourists from 2007 to 2017. It can be noticed that there is a very strong decrease (-14.30%) of the mean
expenditure in the years of the economic recessions from 2008 to 2012; in particular between 2011
and 2012 it can be observed the strongest annual decrease (-5.39%) in tourism expenditure due to
the crisis of the sovereign debt. As the Italian economic condition improved, the expenditure started
to increase, confirming that international tourism is a luxury good for Italian households (Bernini &
Cracolici, 2015). In fact, from the end of the crisis (2012-2013) to 2017 mean expenditure has
augmented of 30.38% at a quite constant annual rate. The mean overall satisfaction is increasing in
time; from 8.17 in 2007 it has reached 8.51 in 2017 (+4.16%). The only period in which travelers
experienced a decrease in the level of overall satisfaction was from 2010 to 2013, the same years
during which the average expenditure was at the minimum level (-0.58%). In particular the decrease
in the level of satisfaction was more intense between 2012 and 2013 (-0.44%) than in the previous
years.
Insert Figure 1
Figure 1 also presents the dynamics of expenditure and satisfaction for the other categories
considered in the analysis (i.e, accommodation, restaurant and shopping). In general, the dynamics
observed for the total expenditure is reproduced for the other expenditure categories; to note that
shopping reveals to be the expenditure most hidden by the crises (from 2008 to 2012 the reduction
equals 16.45%). As for satisfaction, differently from the overall satisfaction all categories exhibit a
reduction in the last years covered by the analysis.
Figure 2 shows mean overall satisfaction in the different quantiles of the total tourism expenditure
as well as the mean satisfaction in the different quantiles of the tourism expenditure distribution for
the different categories. Overall, tourists with higher expenditure results to be more satisfied. This
evidence is also confirmed for satisfaction for accommodation and shopping, even if there are some
exceptions for some quantiles of expenditure. Only the satisfaction for restaurants remains quite
stable across the expenditure distribution. These results support our interest in modelling the role
of satisfaction over the quantile distribution of tourism expenditure.
Insert Figure 2
4. The Model
4.1 The expenditure model
The analysis of the relationship between tourism expenditure and satisfaction of tourists is based on
the estimation of quantile regression (QR) models (Koenker & Bassett, 1978). The most appealing
feature of QR is its ability to estimate quantile-specific effects that describe the impact of covariates
not only on the center but also on the tails of the outcome distribution. In presence of heterogeneous
effects of satisfaction, this approach is expected to offer a more ample representation of the spending
behavior because each determinant's effect is allowed to vary over the whole spectrum of the
distribution. More specifically, one may argue that the marginal effect of tourist satisfaction can be
different at different quantiles of tourist expenditure. This feature enriches the understanding of
what determines heterogeneity in tourists spending behavior, which is a relevant information for
policy makers and destination managers (Marrocu et al, 2015).
We model the relationship between tourism expenditure (TourExp) and satisfaction (Satis) of the
individual i at time t as a double-logarithmic specification within a quantile approach, as follows
  τ  τ   τ  (1)
where refers to a set of socio-demographic and trip characteristics (i.e sex, age classes, student,
area of provenience, hotel, inclusive package, travelling alone, destinations as Spain, France, USA,
UK and Austria, dummies for the duration of the travel and dummies that identify the years of the
economic recession and the crisis of the sovereign debt) observed for tourist i at time t;  is the
corresponding error; and τ is the specific quantile considered, with 0 < τ < 1.
Rewriting Eq. (1) in general form as  
τ , the estimator of parameters τ
is derived by minimizing the function in (2) by applying linear programming methods:
τ= 
τ

+   
τ

(2)
The main issue in estimating Eq. (1) is whether the satisfaction is endogenous, in the sense that there
is a simultaneity problem; i.e., while tourist satisfaction may influence tourist spending, the latter
may affect the former as well. In this case, parameters’ estimates are biased and inconsistent, which
in turn are not a good base for policy and decision making. To handle with the endogeneity problem,
in this study we suggest using an Instrumental Variable approach adapted for QR models
(Chernozhukov & Hansen, 2008). The Instrumental Variable Quantile Regression (IVQR) estimator
proposed by Chernozhukov & Hansen (2008) has several appealing features. First, it is a robust
inference procedure for an instrumental variables model. Second, the asymptotic properties of the
estimator are derived under suitable conditions. In addition, it is robust to weak and partial
identification and remains valid even in cases where identification fails completely. Moreover, it can
be computed through a series of conventional quantile regression steps and so will be
computationally convenient in many cases encountered in practice (for more details, see Appendix
B).
To derive the IVQR estimator we can start defining the weighted ordinary QR objective function as
follow:

 
  
    (3)
where D is a vector containing the endogenous variables (in our case satisfaction), X is a vector
including the control variables and Z contains the instrumental variables. So, we can define the
instrumental variable or inverse quantile regression (IVQR) estimator as:

      (4)
To find an estimate for , we will search for the value that makes  as close to 0 as possible.
The IVQR approach allows for particular tests that we used in the postestimation stage
(Chernozhukov & Hansen, 2006), that are:
1. No effect test: the null hypothesis is that   for all in , that is to say that satisfaction
has no effect on tourists’ expenditure in each quantile of expenditure.
2. Location shift test: the null hypothesis is that   for all   , which asserts that
is constant across all   So the null hypothesis is the hypothesis of constant effect of
satisfaction across expenditure’s quantile. The alternative hypothesis is that the effect of
satisfaction varies across quantiles.
3. Dominance test: the null hypothesis is that   , for all  , versus the nondominance
alternative   , for some   . So, if we accept the null hypothesis, we will conclude
that satisfaction do not influence negatively tourist’s expense for each quantile of
expenditure.
4. Exogeneity test: in the case of absence of endogeneity, the effect of satisfaction on
expenditure’s quantiles can be estimated using the conventional quantile regression without
instrumenting (RQ). The difference between IVQR estimates,
, and QR estimate,
, can
be used to formulate a Hausman test that tests the null hypothesis of exogeneity:
  
for each   . So if we accept the null hypothesis we will conclude that
satisfaction is exogenous, while if RQ estimations are different from IVQR one, we will
conclude that we have a problem of endogeneity in our model, so instrumental variables are
necessary to obtain consistent estimations.
5. Results
Statistical tests for model’s specification are presented in Table 4. The Hausman test for endogeneity
shows that overall satisfaction is endogenous to total expenditure. In fact, we reject at a confidence
level of 1% the null hypothesis of exogeneity of satisfaction. Referring at location shift test, we reject
at a confidence level of 1% the null hypothesis that the effect of satisfaction is constant across all
expenditure’s quantiles. This justify the use of a quantile estimator that allows us to study the effect
of perceived satisfaction for the different levels of tourists’ expenditure. Finally, no effect test rejects
the null hypothesis that the effect of satisfaction on total expenditure is equal to zero; and the
dominance test does not reject the null hypothesis that the effect of satisfaction on total expenditure
is positive for all quantiles.
Test results are similar for all the expenditure categories, confirming that satisfaction is endogenous
in every model estimated, that the effect of satisfaction on expenditure is positive and it varies across
expenditure’s quantiles. Then, IVQR estimator is used in estimating the consumption-satisfaction
models in overall case and for the expenditure’s categories of accommodation, shopping and
restaurants (Tables 5-8); OLS and QR model estimates are presented in Appendix C.
Insert Table 4
Satisfaction with specific characteristics of the destination is found to be significant in affecting the
amount of money spent by tourists within the different expenditure categories and in the total
budget spent. The elasticity of expenditure with respect to overall satisfaction is on average 0.76
(which is 0.50 percentage points higher than the estimate by OLS). Specifically, for a one percentage
increase in overall satisfaction we expect to see on average a 0.76% increase in total tourist spending.
However, over the entire distribution of tourism expenditure, the impact of overall satisfaction
exhibits an inverted U-shape profile. Overall satisfaction at the destination boots expenditure for
low amounts of the tourism expenditure; after the third quantile, the effect of satisfaction is still
positive but decreases as the tourism expenditure augments (Table 5). A similar pattern is detected
for the relationship between expenditure and satisfaction for accommodation; that is, satisfaction
with accommodation exerts a positive but not linear effect on the propensity to spend for the
accommodation (Table 6). While the median impact of satisfaction is 0.68, in the first and last
quantile of accommodation’s expenditure the impact of satisfaction reduces to 0.40 and 0.55,
respectively. For shopping, results suggest that expenditures increase by satisfaction but at a
decreasing rate. The satisfaction for shopping reduces its impact on the shopping expenditure
progressively from the first quantile (1.03) to the 9th quantile (0.39), also evidencing that the
propensity to spend for shopping is highly sensitive to satisfaction (Table 7). Conversely, the role of
satisfaction for restaurants on the corresponding expenditure increases from the first quantile (0.06)
to the 9th quantile (0.20). Then, there is a strict correlation between restaurant satisfaction and the
expenditure for restaurants. The more tourists are satisfied with the food and beverages offered at
the destination, the more they will spend on in restaurants (Table 8).
Figure 3 provides a visual demonstration of the relationship between expenditures and satisfactions.
The solid line in blue traces the coefficient estimates of satisfaction based on the 0.100.90 quantile
regression models. The dotted lines define the 95% confidence region of the coefficients estimates.
The IV estimates are shown by the yellow solid horizontal line; yellow dotted lines delimit the
confidence interval.
Insert Figure 3
The estimated effects of the control variables are discussed only for the overall satisfaction-
expenditure model (Table 5 and Figure 4); similar results are obtained for the other expenditure’s
categories (Tables 6-8).
The coefficients related to tourists socio-demographic characteristics (i.e., age, gender, education,
area of residence) are always significant, apart from the effect of originating from the south of Italy
or from the islands on total expenditure, which is not significantly different from zero. In particular,
we can notice from Table 4 that young tourists and students tend to spend less money than adults
while older tourists (people aged more than 65) have a high variable spending behavior across
expenditure’s quantiles. Travelers originating from the north tend to spend less money than other
travelers and this effect rises in absolute value across expenditure’s quantiles. Finally, referring to
gender, men tend to spend slightly more than women.
The number of nights spent at the destination significantly affects the amount of money spent. In
particular, the higher the number of nights spent at the destination is, the higher the amount spent
for the whole trip become. However, the impact decreases as we move to the highest quintiles of the
expenditure distribution. Regarding accommodation, staying in a hotel positively boots the total
expenditure but the effect decreases as the total expenditure for the holiday increases. Conversely,
having bought an all-inclusive package has an increasing effect on the expenditure across quantiles.
Insert Figure 4
As regards the composition of the travel group, tourists who are travelling alone largely reduce the
total amount of the expenditure, but the effect becomes negligible at the highest quantiles of the
distribution. As regards the holiday destination, the lower the distance between the place of
residence and the place visited is, the lower is the amount of money spent for the whole trip. Tourists
having a holiday in Spain and France spend less than tourists going to UK; while tourists directed
to USA register the highest increase in expenditure. In general, these impacts tend to reduce for the
highest quantiles of the expenditure’s distribution. As expected, the two recessions have a negative
effect on expenditure, especially for the tourists who spend less (first quantile) and most (ninth
quantile).
Insert Table 5 8
In the model for accommodation’s expenditure, the effect of the control variables is similar to the
effect previously described for the overall expenditure model. Conversely, for shopping expenditure
we can notice some differences: women tend to spend more money than men for shopping, the effect
of originating from the south in this case is positive (and not equal to zero as is the previous models),
the crisis of 2008-2009-2010 did not affect negatively shopping’s expenditure as for the other
expenditure’s categories, while accommodating in hotel has not a significant effect on shopping’s
expenditure for some expenditure’s quantiles. For restaurants expenditure, model’s estimations are
very similar to the one of models for overall expenditure and accommodation’s expenditure. The
only difference is that, travelers that bought an inclusive package and that spend few moneys for
restaurants (until quantile 30) tend to spend less money than others, than the effect of having bought
an inclusive package on the restaurant’s expenditure become positive.
6. Conclusions
The main aims of this study are to analyze the impact of satisfaction with the different attributes of
the destination on tourists’ spending behavior and to determine to what extent this impact varies
across quantiles of the tourist’s expenditure’s distribution. Moreover, the present study investigates
whether satisfaction may be endogenous to expenditure, making estimates of its effect biased and
inconsistent.
Using a huge dataset on Italian tourists travelling abroad for personal purposes over the period
2007-2017, we verified that the relation between tourism expenditure and satisfaction is affected by
the issue of endogeneity; thus an IVQR estimator is used to obtain unbiased and consistent estimates.
Satisfaction with specific characteristics of the destination is found to be significant in affecting
tourists expenditure behavior, and this effect differs among quantiles and expenditure categories.
These results confirm the theory that satisfaction is a predictor of expenditure are they are in line
with Bernini et al. (2016) that affirms that: “Increasing the grade of satisfaction has a clear implication
in terms of higher tourism expenditures and higher incomes in the area. This fact explains strong
political interest in tourists’ satisfaction levels."
The study improves previous literature by determining the relationship between satisfaction with
the different aspects of the destination and the corresponding expenditure category acquired by the
tourists for the different quantiles of expenditure. The elasticity of expenditure with respect to
overall satisfaction is high and equal on average to 0.76; but, the impact of overall satisfaction over
the tourism expenditure distribution shows an inverted U-shape profile. Besides, satisfaction with
accommodation exerts a positive but not linear effect on the propensity to spend for the
accommodation. For shopping, results suggest that expenditures increase by satisfaction but at a
decreasing rate; while, the more tourists are satisfied with the food and beverages offered at the
destination, the more they will spend on in restaurants.
These results confirm that expenditure is significantly and positively related to the standard of the
service offered in line with Disegna & Osti (2016) that conclude that “dis/satisfaction with food and
beverages directly influences expenditure on food and beverages; similarly, dis/satisfaction with
products sold determines the amount of money spent on shopping and dis/satisfaction with the
friendliness of the local people influences expenditure on accommodation. These results show that
expenditure at the destination (and therefore the profit of the single services located at the
destination) is intimately linked to the standard of the service offered.”
Thus, destination mangers and policy makers firstly should improve the overall satisfaction of the
low-spending tourists, for whom satisfaction has the highest impact on their expenditure. Second,
hotel managers should mainly focus to tourists in the segment of low- and medium quality
accommodation, who are very sensitive in terms of satisfaction. The enlargement and improvement
of the quality of local goods may be a useful strategy for taking advantage of the role of satisfaction
for shopping on the corresponding expenditure. Similarly, it should be recommended to
restaurateurs that satisfaction and therefore the standard of the food and beverage they offer, has a
relevant impact on Italian tourists who results to be very sensitive to the quality of the services
offered in respect to the amount of money that they spent for restaurants.
Further researches should be dedicated to deepening the understanding about the relationships of
total expenditure not only on the overall satisfaction but also with respect to the other expenditure
and satisfaction categories, simultaneously. It would be also interesting to investigate whether the
results obtained for the whole International destinations, are still valid at specific destination.
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APPENDIX A. Data description
The initial sample was made up of 806377 observations. We carefully cleaned it up obtaining a final
sample of 282751 observations using these methods:
- We delated from the sample all the tourist for which the total expenditure was lower than 20
euros (3.7%) and all the tourist that expended more than 25000 euros (0.11%). Making this
cleaning procedure we obtained a sample of 775546 observations.
- We delated all the observations that had missing values in all the scores of satisfaction
(10.55%) so 693745 observations left.
- We considered only Italians that travel for “tourism, holiday and leisure” (40.76%).
APPENDIX B. The Instrumental Quantile Estimator (IVQR)
Following Chernozhukov & Hansen (2008), we suppose a structural relationship defined by
Y =D′α(U)+X′β(U), U|X,ZUniform(0,1) (C1)
D = δ(X, Z, V), where V is statistically dependent on U (C2)
τ → D′α(τ) + X′β(τ) strictly increasing in τ (C3)
where Y is the dependent variable, U is a scalar random variable that aggregates all of the
unobserved factors affecting the outcome equation. D is a vector of endogenous variables
determined by (C2), where V is a vector of unobserved disturbances determining D and correlated
with U, Z is a vector of instrumental variables, and X is a vector of included control variables.
The observed variables consist of (Y, D, X, Z), and due to the dependence between V and U, D is also
sampled depending on U.
We shall refer to the function
SY (τ|d, x) = d′α(τ) + x′β(τ) (C4)
as the Structural Quantile Function (SQF) in order to emphasize that it is in general a different object
than the conditional quantile function QY(τ|d,x). The structural quantile function SY(τ|d,x)
describes the quantile function of the latent outcome variable Yd = d′α(U) + X′β(U) obtained by
fixing D = d and sampling the disturbance U U(0,1) (all conditional on X). This notion of sampling
corresponds to independent sampling of D and U, which is generally not feasible outside
experimental settings. Instead the sampled variable D is determined via (C2). Nevertheless, it is still
possible to estimate or make inference on the structural quantile function SY (τ|d,x) through the use
of instrumental variables Z which induce variation in D but are themselves independent of U.
Under the conditions of (C1) and (C2), the problem of dependence between U and D is overcome
through the presence of instrumental variables, Z, that affect the determination of D but are in-
dependent of U. In program evaluation studies with imperfect compliance, a simple example of an
instrument is random assignment to the treatment group, which is done independently of the
potential values of U. The presence of the instrumental variable leads to a set of moment equations
that can be used to estimate the parameters of (C1). From (C1) and (C3), the event {Y ≤ SY (τ|D,X)}
is equivalent to the event {U ≤ τ}. It then follows from (2) that
P[Y ≤ SY (τ|D,X)|Z,X] = τ (C5)
Equation (C5) provides a useful statistical restriction that can be used to estimate the structural
parameters α and β. It is important to notice that the equation P[Y SY (τ|D,X)|Z,X] = τ differs
from the conventional estimating equation
P[Y ≤ QY (τ|D,X)|D,X] = τ (C6)
used to estimate the conditional quantile function of Y given D and X.
Recall from Koenker & Bassett (1978) that the ordinary quantile regression (QR) is formulated as
finding the best predictor of Y given W under the asymmetric least absolute deviation loss ρτ (u) :=
(τ − 1(u < 0))u. In other words, assuming integrability, the τth conditional quantile of Y given W
solves the problem:
QY (τ|W) = argmin E[ρτ(Y −f(W))] fF (C7)
where F is the class of measurable functions of W (restricted in applications to be a set of flexible
parametric functions). Laplaces median regression function QY (.5|W) is a solution of this problem
with τ = 1/2 so that ρτ (u) = 1 |u|. The function QY (τ |D, X ) solves the above problem with 2W =
(D,X) and can be estimated using the finite sample analog of the above equation.
The moment equation given in (C5) is equivalent to the statement that 0 is the τ-th quantile of
random variable Y −SY (τ|D,X) conditional on (Z,X):
0=QY−SY(τ|D,X)(τ|Z,X) a.s.for each τ. (C8)
Thus, we may pose the problem of finding α(τ) and β(τ) solving equation (C5) as the instrumental
variable or inverse quantile regression (IVQR). This problem is to find an SY (τ|D,X) such that 0 is
a solution to the quantile regression of Y −SY (τ|D,X) on (Z,X):
0=argmin Eρτ [(Y −SY(τ|D,X)−f(Z,X))], fF (C9)
where F is the class of measurable functions of (X, Z) (which will be restricted in applications). The
term inverse emphasizes an evident inverse relation of this problem to the conventional quantile
regression (C7).
APPENDIX C. OLS QR MODEL ESTIMATES
Insert Table C1. Model RQ estimates: total expenditure
Insert Table C2. Model RQ estimates: accommodation expenditure
Insert Table C3. Model RQ estimates: shopping expenditure
Insert Table C4. Model RQ estimates: restaurant expenditure
Insert Table C5. Tests for RQ
Insert Figure C1. OLS and RQ estimates of satisfaction parameters
Insert Figure C2. OLS and QR estimates of the total expenditure model
TABLES
Table 1. Descriptive statistics
Spain
Germany
UK
America
Oceania
% of total tourists
12.38
5.02
4.72
9.81
1.54
% of females
42.34
37.07
44.96
30.94
33.84
Age
15-24
25-34
35-44
45-64
65+
22.97
35.91
23.21
15.31
2.60
17.61
31.67
25.71
21.49
3.51
23.00
36.02
23.42
16.05
1.51
6.97
37.49
31.17
21.82
2.55
10.65
43.96
26.58
17.45
1.35
Job Title
Employed
Self-employed
Student
Housewife
Retired
Unemployed
Other
No response
56.11
14.12
20.69
1.95
3.84
2.59
0.53
0.19
56.81
14.56
17.44
2.22
5.21
2.66
0.43
0.68
54.12
12.64
24.70
1.87
2.31
3.36
0.50
0.50
58.36
26.73
5.52
1.51
4.46
3.04
0.31
0.06
55.62
23.67
10.06
1.38
2.39
6.52
0.32
0.05
Accomodation
House for rent
House of property
Hotel, village, B&B
Other
No overnight stay
13.90
11.14
67.94
6.98
0.04
4.93
23.21
62.32
8.71
0.83
6.37
23.90
62.45
7.24
0.03
11.06
17.11
66.90
4.63
0.31
12.01
18.23
59.57
10.19
0
Number of travelers
1.73
1.79
1.61
1.58
1.58
Average number of
nights
8.01
5.97
8.16
19.34
42.53
Table 2. The expenditure profile
Average expenditure
(€)
France
Spain
USA
Germany
UK
Austria
Europe
America
Africa
Asia
Oceania
TOT
OVERALL
824.53
1064.73
2468.45
774.76
1035.11
645.49
988.22
2051.24
1474.97
1865.84
3267.02
1346.14
s.d.
845.15
890.78
2209.97
723.74
1054.37
899.71
999.22
1890.10
1380.82
1718.05
3051.83
1505.43
SHARE FOR TRANSPORTS
12.17%
8.05%
7.21%
9.91%
8.40%
16.11%
9.79%
12.66%
13.33%
11.67%
13.76%
10.63%
s.d.
0.15
0.09
0.07
0.11
0.08
0.21
0.11
0.11
0.09
0.10
0.11
0.12
SHARE FOR
ACCOMODATION.
33.50%
43.51%
43.45%
42.18%
42.21%
37.59%
42.89%
44.68%
48.20%
44.84%
45.30%
42.53%
s.d.
0.25
0.17
0.17
0.20
0.18
0.27
0.19
0.20
0.18
0.18
0.18
0.20
SHARE FOR RESTAURANTS
32.44%
25.99%
22.76%
27.04%
24.16%
23.99%
26.03%
19.96%
14.92%
21.94%
17.61%
24.28%
s.d.
0.32
0.15
0.12
0.16
0.14
0.19
0.16
0.16
0.13
0.13
0.12
0.16
SHARE FOR SHOPPING
16.66%
12.88%
17.43%
14.73%
17.96%
15.12%
12.83%
11.07%
10.86%
11.84%
11.32%
13.69%
s.d.
0.19
0.12
0.14
0.15
0.15
0.20
0.13
0.12
0.11
0.11
0.12
0.15
SHARE FOR OTHER
5.22%
9.57%
9.16%
6.15%
6.27%
7.20%
8.46%
11.63%
12.70%
9.71%
12.00%
8.88%
s.d.
0.09
0.11
0.10
0.09
0.09
0.14
0.11
0.12
0.12
0.10
0.10
0.11
TOTAL DAILY EXPEDITURE
s.d.
161.9829
.90
162.9688
.63
238.0165
1.19
168.2629
1.56
181.0683
1.18
193.0439
1.77
158.3527
.50
155.4559
.78
162.6909
.78
157.8435
1.00
160.2494
2.36
170.7997
.28
Table 3. Satisfaction scores with respect to travel destinations
France
Spain
USA
Germany
UK
Austria
Europe
America
Africa
Asia
Oceania
TOT
Courtesy
7.66
8.49
8.36
7.80
7.83
8.21
8.01
8.63
8.01
8.38
8.64
8.15
s.d.
1.55
1.36
1.35
1.69
1.61
1.64
1.65
1.44
1.71
1.59
1.48
1.59
Art
8.67
8.51
8.48
8.41
8.74
8.69
8.29
7.70
7.56
8.01
7.90
8.31
s.d.
1.22
1.41
1.50
1.31
1.27
1.29
1.48
1.97
2.09
1.74
2.03
1.58
Environment
8.52
8.59
8.54
8.43
8.35
9.12
8.73
9.10
8.74
8.69
9.46
8.71
s.d.
1.22
1.29
1.45
1.36
1.50
1.12
1.32
1.23
1.50
1.58
1.16
1.37
Accomodation
7.86
7.82
7.96
7.93
7.41
8.36
7.78
7.99
8.01
7.92
7.99
7.88
s.d.
1.36
1.56
1.45
1.45
1.78
1.41
1.62
1.60
1.63
1.60
1.65
1.57
Food
7.43
7.72
6.91
7.10
6.38
7.64
7.37
7.68
7.37
7.62
7.25
7.38
s.d.
1.62
1.66
1.90
1.78
2.08
1.77
1.81
1.74
1.95
1.73
1.93
1.82
Price
6.33
7.30
6.77
7.02
5.58
7.40
7.09
7.68
7.84
8.09
6.76
7.13
s.d.
2.15
1.74
2.03
1.67
2.30
1.80
1.99
1.87
1.68
1.86
2.33
2.03
Shopping
8.03
7.76
8.41
7.90
8.05
8.10
7.47
7.09
6.94
7.52
7.45
7.66
s.d.
1.29
1.47
1.49
1.36
1.60
1.41
1.58
1.93
1.93
1.74
1.95
1.65
Info
8.06
8.19
8.45
8.20
8.46
8.36
7.81
7.49
7.59
7.70
8.51
7.98
s.d.
1.39
1.42
1.40
1.52
1.38
1.61
1.71
1.99
1.93
1.99
1.81
1.68
Security
8.24
8.32
8.71
8.69
8.57
8.92
8.19
7.78
8.00
8.56
8.79
8.32
s.d.
1.21
1.43
1.19
1.22
1.23
1.17
1.62
1.98
1.73
1.65
1.62
1.54
Overall
8.25
8.49
8.53
8.28
8.34
8.54
8.28
8.40
8.20
8.41
8.67
8.37
s.d.
0.99
1.07
1.02
1.05
1.09
1.11
1.15
1.23
1.34
1.16
1.13
1.14
N
28548
34968
27481
14176
13320
15110
71252
27700
23822
21655
4356
282751
Table 4. Tests IVQR model
H0: No effect
H0: Location shift
H0: Dominance
H0: Exogeneity
Test statistic value
Test statistic value
Test statistic value
Test statistic value
Overall
19.97***
3.90***
0
14.22***
Accommodation
18.09***
3.69***
0
12.29***
Shopping
14.19***
7.27***
0
8.56***
Restaurant
9.52***
3.51***
0
7.85***
Table 5. Model IVQR estimates: total expenditure
Total expenditure
IV
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Overall Satisfaction
0.76
(0.02)***
0.58
(0.05)***
0.64
(0.04)***
0.68
(0.04)***
0.67
(0.04)***
0.66
(0.03)***
0.63
(0.03)***
0.60
(0.03)***
0.53
(0.03)***
0.48
(0.03)***
Male
0.01
(0.00)***
0.02
(0.01)***
0.02
(0.00)***
0.01
(0.00)***
0.01
(0.00)***
0.01
(0.00)**
0.00
(0.00)
0.00
(0.00)
0.00
(0.00)
0.01
(0.01)**
Age15to25
-0.18
(0.01)***
-0.27
(0.01)***
-0.28
(0.01)***
-0.28
(0.01)***
-0.27
(0.01)***
-0.25
(0.01)***
-0.23
(0.01)***
-0.21
(0.01)***
-0.19
(0.01)***
-0.16
(0.01)***
Age25to34
-0.10
(0.00)***
-0.15
(0.01)***
-0.16
(0.01)***
-0.16
(0.00)***
-0.15
(0.00)***
-0.15
(0.00)***
-0.14
(0.00)***
-0.14
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
Age45to64
0.01
(0.00)*
..08
(0.01)***
0.09
(0.01)***
0.09
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
0.11
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
Agemorethan65
-0.32
(0.01)***
-0.06
(0.02)***
-0.05
(0.01)***
-0.04
(0.01)***
-0.03
(0.01)**
-0.02
(0.01)**
0.00
(0.01)
0.01
(0.01)
0.02
(0.02)
0.07
(0.02)***
South-islands
-0.00
(0.00)
0.01
(0.01)*
0.01
(0.01)*
0.01
(0.01)**
0.01
(0.01)*
0.00
(0.01)
0.00
(0.01)
0.01
(0.01)*
0.01
(0.01)
0.03
(0.01)***
North
-0.19
(0.00)***
-0.04
(0.01)***
-0.06
(0.00)***
-0.06
(0.00)***
-0.08
(0.00)***
-0.09
(0.00)***
-0.10
(0.00)***
-0.10
(0.00)***
-0.11
(0.01)***
-0.10
(0.01)***
Inclusive Package
0.29
(0.00)***
0.24
(0.01)***
0.24
(0.00)***
0.24
(0.00)***
0.25
(0.00)***
0.25
(0.00)***
0.26
(0.00)***
0.26
(0.00)***
0.27
(0.01)***
0.27
(0.01)***
Hotel
0.44
(0.00)***
0.23
(0.01)***
0.21
(0.00)***
0.20
(0.00)***
0.20
(0.00)***
0.19
(0.00)***
0.18
(0.00)***
0.17
(0.00)***
0.14
(0.01)***
0.09
(0.01)***
Student
-0.12
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.15
(0.01)***
-0.16
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.17
(0.00)***
-0.16
(0.01)***
-0.15
(0.01)***
Alone
-0.16
(0.00)***
-0.22
(0.01)***
-0.20
(0.01)***
-0.20
(0.01)***
-0.20
(0.01)***
-0.18
(0.01)***
-0.16
(0.01)***
-0.15
(0.01)***
-0.10
(0.01)***
-0.02
(0.01)
Spain
0.03
(0.00)***
0.08
(0.01)***
0.06
(0.01)***
0.04
(0.01)***
0.02
(0.01)***
0.01
(0.01)**
-0.01
(0.01)***
-0.04
(0.01)***
-0.07
(0.01)***
-0.09
(0.01)***
France
-0.25
(0.01)***
0.11
(0.01)***
0.09
(0.01)***
0.08
(0.01)***
0.07
(0.01)***
0.05
(0.01)***
0.04
(0.01)***
0.02
(0.01)***
0.00
(0.01)
-0.04
(0.01)***
USA
0.60
(0.01)***
0.58
(0.01)***
0.54
(0.01)***
0.52
(0.01)***
0.51
(0.01)***
0.50
(0.01)***
0.49
(0.01)***
0.49
(0.01)***
0.49
(0.01)***
0.51
(0.01)***
UK
0.12
(0.01)***
0.18
(0.01)***
0.17
(0.01)***
0.15
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.10
(0.01)***
0.08
(0.01)***
0.06
(0.01)***
0.02
(0.01)*
Austria
-0.67
(0.01)***
-0.26
(0.02)***
-0.23
(0.01)***
-0.22
(0.01)***
-0.19
(0.01)***
-0.18
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.15
(0.01)***
-0.13
(0.01)***
Night 1-7
-0.55
(0.00)***
-0.66
(0.01)***
-0.67
(0.00)***
-0.66
(0.00)***
-0.67
(0.00)***
-0.68
(0.00)***
-0.68
(0.00)***
-0.71
(0.00)***
-0.73
(0.01)***
-0.78
(0.01)***
Nights 16-31
0.43
(0.01)***
0.25
(0.01)***
0.25
(0.01)***
0.27
(0.01)***
0.27
(0.01)***
0.28
(0.01)***
0.27
(0.01)***
0.25
(0.01)***
0.22
(0.01)***
0.17
(0.01)***
Years 08-09-10
-0.03
(0.00)***
-0.08
(0.01)***
-0.07
(0.01)***
-0.06
(0.00)***
-0.06
(0.00)***
-0.05
(0.00)***
-0.05
(0.00)***
-0.06
(0.00)***
-0.07
(0.01)***
-0.09
(0.01)***
Years 11-12-13
-0.09
(0.00)***
-0.08
(0.01)***
-0.08
(0.00)***
-0.08
(0.00)***
-0.08
(0.00)***
-0.08
(0.00)***
-0.09
(0.00)***
-0.09
(0.00)***
-0.10
(0.01)***
-0.12
(0.01)***
Intercept
5.37
(0.05)***
5.27
(0.10)***
5.41
(0.08)***
5.53
(0.08)***
5.71
(0.08)***
5.89
(0.07)***
6.11
(0.07)***
6.35
(0.07)***
6.72
(0.07)***
7.19
(0.07)***
Table 6. Model IVQR estimates: accommodation expenditure
Accomodation expenditure
IV
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Accomodation satisfaction
0.56
(0.02)***
0.48
(0.05)***
0.54
(0.04)***
0.61
(0.03)***
0.65
(0.04)***
0.68
(0.04)***
0.63
(0.04)***
0.59
(0.03)***
0.56
(0.03)***
0.55
(0.04)***
Male
-0.05
(0.00)***
-0.02
(0.01)***
-0.03
(0.01)***
-0.03
(0.01)***
-0.04
(0.00)***
-0.03
(0.00)***
-0.04
(0.00)***
-0.03
(0.00)***
-0.03
(0.01)***
-0.03
(0.01)***
Age15to25
-0.24
(0.01)***
-0.28
(0.02)***
-0.28
(0.01)***
-0.29
(0.01)***
-0.29
(0.01)***
-0.28
(0.01)***
-0.26
(0.01)***
-0.26
(0.01)***
-0.21
(0.01)***
-0.14
(0.02)***
Age25to34
-0.16
(0.00)***
-0.17
(0.01)***
-0.18
(0.01)***
-0.18
(0.01)***
-0.18
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.16
(0.01)***
-0.15
(0.01)***
Age45to64
0.10
(0.00)***
0.10
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.12
(0.01)***
0.12
(0.01)***
0.13
(0.01)***
0.14
(0.01)***
Agemorethan65
-0.03
(0.01)***
-0.12
(0.02)***
-0.07
(0.02)***
-0.04
(0.02)***
-0.04
(0.02)**
-0.02
(0.02)
0.00
(0.02)
0.01
(0.01)
0.02
(0.02)*
0.07
(0.02)***
South-islands
-0.00
(0.00)
0.02
(0.01)*
0.01
(0.01)*
0.00
(0.01)
0.01
(0.01)
0.00
(0.01)
0.00
(0.01)
0.00
(0.01)
0.00
(0.01)
0.03
(0.01)***
North
-0.09
(0.00)***
-0.03
(0.01)***
-0.04
(0.01)***
-0.05
(0.01)***
-0.06
(0.01)***
-0.07
(0.01)***
-0.08
(0.01)***
-0.09
(0.01)***
-0.09
(0.01)***
-0.09
(0.01)***
Inclusive Package
0.37
(0.00)***
0.28
(0.01)***
0.26
(0.01)***
0.26
(0.01)***
0.27
(0.01)***
0.28
(0.01)***
0.29
(0.01)***
0.31
(0.01)***
0.33
(0.01)***
0.33
(0.01)***
Hotel
0.31
(0.00)***
0.41
(0.01)***
0.37
(0.01)***
0.34
(0.01)***
0.33
(0.01)***
0.30
(0.01)***
0.28
(0.01)***
0.25
(0.01)***
0.21
(0.01)***
0.16
(0.01)***
Student
-0.13
(0.01)***
-0.11
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.13
(0.01)***
-0.13
(0.01)***
Alone
-0.17
(0.00)***
-0.19
(0.01)***
-0.20
(0.01)***
-0.20
(0.01)***
-0.19
(0.01)***
-0.17
(0.01)***
-0.16
(0.01)***
-0.13
(0.01)***
-0.07
(0.01)***
-0.01
(0.01)
Spain
0.01
(0.00)
0.08
(0.01)***
0.07
(0.01)***
0.04
(0.01)***
0.03
(0.01)***
0.02
(0.01)***
0.01
(0.01)*
-0.01
(0.01)**
-0.04
(0.01)***
-0.07
(0.01)***
France
-0.00
(0.01)
0.11
(0.01)***
0.13
(0.01)***
0.11
(0.01)***
0.09
(0.01)***
0.07
(0.01)***
0.06
(0.01)***
0.04
(0.01)***
0.03
(0.01)***
-0.01
(0.01)
USA
0.50
(0.01)***
0.61
(0.01)***
0.58
(0.01)***
0.55
(0.01)***
0.52
(0.01)***
0.51
(0.01)***
0.49
(0.01)***
0.49
(0.01)***
0.49
(0.01)***
0.52
(0.01)***
UK
0.11
(0.01)***
0.19
(0.01)***
0.16
(0.01)***
0.16
(0.01)***
0.14
(0.01)***
0.12
(0.01)***
0.10
(0.01)***
0.08
(0.01)***
0.07
(0.01)***
0.04
(0.01)***
Austria
-0.24
(0.01)***
-0.26
(0.03)***
-0.21
(0.02)***
-0.19
(0.02)***
-0.16
(0.01)***
-0.15
(0.01)***
-0.11
(0.01)***
-0.10
(0.01)***
-0.05
(0.02)***
-0.03
(0.02)*
Night 1-7
-0.78
(0.00)***
-0.73
(0.01)***
-0.73
(0.01)***
-0.72
(0.01)***
-0.73
(0.01)***
-0.73
(0.01)***
-0.74
(0.01)***
-0.76
(0.01)***
-0.78
(0.01)***
-0.83
(0.01)***
Nights 16-31
0.21
(0.01)***
0.18
(0.01)***
0.21
(0.01)***
0.23
(0.01)***
0.25
(0.01)***
0.26
(0.01)***
0.26
(0.01)***
0.24
(0.01)***
0.21
(0.01)***
0.14
(0.01)***
Years 08-09-10
-0.16
(0.00)***
-0.16
(0.01)***
-0.15
(0.01)***
-0.15
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.13
(0.01)***
-0.15
(0.01)***
-0.17
(0.01)***
Years 11-12-13
-0.14
(0.00)***
-0.12
(0.01)***
-0.12
(0.01)***
-0.11
(0.01)***
-0.11
(0.01)***
-0.12
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.17
(0.01)***
Intercept
5.29
(0.05)***
4.38
(0.11)***
4.61
(0.09)***
4.71
(0.07)***
4.85
(0.09)***
4.98
(0.08)***
5.29
(0.08)***
5.58
(0.07)***
5.89
(0.07)***
6.29
(0.07)***
Table 7. Model IVQR estimates: shopping expenditure
Shopping
expenditure
IV
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Shopping satisfaction
0.77
(0.04)***
1.03
(0.10)***
0.89
(0.08)***
0.94
(0.07)***
0.95
(0.07)***
0.84
(0.06)***
0.77
(0.06)***
0.66
(0.05)***
0.43
(0.05)***
0.39
(0.06)***
Male
-0.03
(0.00)***
-0.05
(0.01)***
-0.04
(0.01)***
-0.03
(0.01)***
-0.04
(0.01)***
-0.04
(0.01)***
-0.03
(0.01)***
-0.04
(0.01)***
-0.04
(0.01)***
-0.02
(0.01)***
Age15to25
-0.16
(0.01)***
-0.26
(0.02)***
-0.24
(0.01)***
-0.24
(0.01)***
-0.25
(0.01)***
-0.20
(0.01)***
-0.18
(0.01)***
-0.16
(0.01)***
-0.10
(0.01)***
-0.08
(0.02)***
Age25to34
-0.11
(0.01)***
-0.12
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.13
(0.01)***
-0.12
(0.01)***
-0.12
(0.01)***
-0.10
(0.01)***
-0.10
(0.01)***
Age45to64
0.05
(0.01)***
0.05
(0.01)***
0.05
(0.01)***
0.06
(0.01)***
0.04
(0.01)***
0.04
(0.01)***
0.05
(0.01)***
0.07
(0.01)***
0.06
(0.01)***
0.07
(0.01)***
Agemorethan65
-0.09
(0.01)***
-0.09
(0.02)***
-0.12
(0.02)***
-0.14
(0.02)***
-0.16
(0.02)***
-0.13
(0.02)***
-0.10
(0.02)***
-0.10
(0.02)***
-0.03
(0.02)***
0.01
(0.03)
South-islands
0.12
(0.01)***
0.13
(0.01)***
0.11
(0.01)***
0.10
(0.01)***
0.11
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
0.09
(0.01)***
0.09
(0.01)***
North
-0.14
(0.01)***
-0.06
(0.01)***
-0.07
(0.01)***
-0.10
(0.01)***
-0.10
(0.01)***
-0.11
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.12
(0.01)***
-0.12
(0.01)***
Inclusive Package
0.20
(0.01)***
0.20
(0.01)***
0.15
(0.01)***
0.16
(0.01)***
0.15
(0.01)***
0.13
(0.01)***
0.11
(0.01)***
0.10
(0.01)***
0.07
(0.01)***
0.05
(0.01)***
Hotel
0.02
(0.00)***
0.03
(0.01)***
0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
0.01
(0.01)**
0.02
(0.01)***
0.02
(0.01)***
0.01
(0.01)**
0.01
(0.01)*
Student
-0.15
(0.01)***
-0.12
(0.02)***
-0.12
(0.01)***
-0.11
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.12
(0.01)***
-0.15
(0.01)***
-0.17
(0.01)***
-0.18
(0.02)***
Alone
-0.06
(0.01)***
-0.14
(0.01)***
-0.11
(0.01)***
-0.10
(0.01)***
-0.09
(0.01)***
-0.09
(0.01)***
-0.07
(0.01)***
-0.04
(0.01)***
0.00
(0.01)
0.05
(0.01)***
Spain
-0.02
(0.01)***
0.00
(0.01)
0.01
(0.01)*
0.00
(0.01)
-0.01
(0.01)
-0.01
(0.01)*
-0.02
(0.01)***
-0.03
(0.01)***
-0.03
(0.01)***
-0.07
(0.01)***
France
0.06
(0.01)***
0.15
(0.02)***
0.13
(0.01)***
0.14
(0.01)***
0.12
(0.01)***
0.08
(0.01)***
0.09
(0.01)***
0.08
(0.01)***
0.08
(0.01)***
0.08
(0.02)***
USA
0.75
(0.01)***
0.74
(0.02)***
0.76
(0.01)***
0.73
(0.01)***
0.74
(0.01)***
0.74
(0.01)***
0.76
(0.01)***
0.76
(0.01)***
0.79
(0.01)***
0.82
(0.02)***
UK
0.30
(0.01)***
0.33
(0.02)***
0.31
(0.02)***
0.33
(0.02)***
0.32
(0.01)***
0.30
(0.01)***
0.31
(0.01)***
0.29
(0.01)***
0.28
(0.01)***
0.27
(0.02)***
Austria
-0.36
(0.01)***
-0.36
(0.02)***
-0.29
(0.02)***
-0.27
(0.02)***
-0.31
(0.02)***
-0.23
(0.02)***
-0.21
(0.02)***
-0.22
(0.02)***
-0.13
(0.02)***
-0.14
(0.02)***
Night 1-7
-0.41
(0.00)***
-0.40
(0.01)***
-0.41
(0.01)***
-0.43
(0.01)***
-0.40
(0.01)***
-0.42
(0.01)***
-0.44
(0.01)***
-0.43
(0.01)***
-0.46
(0.01)***
-0.53
(0.01)***
Nights 16-31
0.21
(0.01)***
0.14
(0.02)***
0.16
(0.01)***
0.16
(0.01)***
0.20
(0.01)***
0.19
(0.01)***
0.17
(0.01)***
0.15
(0.01)***
0.11
(0.01)***
0.10
(0.02)***
Years 08-09-10
0.11
(0.01)***
0.13
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.10
(0.01)***
0.09
(0.01)***
0.08
(0.01)***
0.10
(0.01)***
0.09
(0.01)***
0.09
(0.01)***
Years 11-12-13
-0.04
(0.01)***
-0.01
(0.01)
0.00
(0.01)
-0.01
(0.01)
-0.01
(0.01)
-0.01
(0.01)*
-0.02
(0.01)**
0.00
(0.01)
0.00
(0.01)
-0.02
(0.01)**
Intercept
3.47
(0.07)***
1.73
(0.20)***
2.46
(0.15)***
2.65
(0.14)***
2.90
(0.14)***
3.35
(0.12)***
3.72
(0.12)***
4.17
(0.10)***
4.92
(0.10)***
5.42
(0.12)***
Table 8. Model IVQR estimates: restaurant expenditure
Restaurant
expenditure
IV
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Restaurant
satisfaction
0.19
(0.01)***
0.06
(0.03)**
0.12
(0.02)***
0.14
(0.02)***
0.18
(0.02)***
0.17
(0.02)***
0.17
(0.02)***
0.18
(0.02)***
0.19
(0.02)***
0.20
(0.02)***
Male
0.04
(0.00)***
0.06
(0.01)***
0.06
(0.01)***
0.05
(0.01)***
0.04
(0.00)***
0.03
(0.00)***
0.02
(0.00)***
0.02
(0.00)***
0.03
(0.01)***
0.04
(0.01)***
Age15to25
-0.19
(0.01)***
-0.31
(0.02)***
-0.28
(0.01)***
-0.25
(0.01)***
-0.24
(0.01)***
-0.22
(0.01)***
-0.20
(0.01)***
-0.19
(0.01)***
-0.15
(0.01)***
-0.11
(0.02)***
Age25to34
-0.09
(0.00)***
-0.14
(0.01)***
-0.11
(0.01)***
-0.13
(0.01)***
-0.13
(0.01)***
-0.13
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.13
(0.01)***
-0.11
(0.01)***
Age45to64
0.02
(0.01)***
0.02
(0.01)*
0.05
(0.01)***
0.07
(0.01)***
0.07
(0.01)***
0.09
(0.01)***
0.09
(0.01)***
0.10
(0.01)***
0.11
(0.01)***
0.13
(0.01)***
Agemorethan65
-0.24
(0.01)***
-0.27
(0.03)***
-0.19
(0.03)***
-0.17
(0.02)***
-0.12
(0.02)***
-0.06
(0.02)***
-0.02
(0.02)*
0.00
(0.02)
0.04
(0.02)**
0.08
(0.03)***
South-islands
0.01
(0.01)
0.01
(0.01)
0.02
(0.01)**
0.00
(0.01)
0.01
(0.01)
0.00
(0.01)
0.01
(0.01)
0.01
(0.01)**
0.02
(0.01)***
0.04
(0.01)***
North
-0.18
(0.00)***
-0.09
(0.01)***
-0.10
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.12
(0.01)***
Inclusive Package
0.00
(0.00)
-0.19
(0.01)***
-0.06
(0.01)***
-0.01
(0.01)**
0.01
(0.01)**
0.04
(0.01)***
0.07
(0.01)***
0.08
(0.01)***
0.09
(0.01)***
0.08
(0.01)***
Hotel
0.30
(0.00)***
0.25
(0.01)***
0.20
(0.01)***
0.18
(0.01)***
0.16
(0.01)***
0.15
(0.01)***
0.14
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.07
(0.01)***
Student
-0.15
(0.01)***
-0.12
(0.01)***
-0.15
(0.01)***
-0.15
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.18
(0.01)***
-0.18
(0.01)***
-0.17
(0.01)***
Alone
-0.17
(0.00)***
-0.28
(0.01)***
-0.25
(0.01)***
-0.24
(0.01)***
-0.23
(0.01)***
-0.21
(0.01)***
-0.19
(0.01)***
-0.17
(0.01)***
-0.15
(0.01)***
-0.11
(0.01)***
Spain
0.11
(0.01)***
0.13
(0.01)***
0.09
(0.01)***
0.08
(0.01)***
0.08
(0.01)***
0.07
(0.01)***
0.07
(0.01)***
0.06
(0.01)***
0.04
(0.01)***
0.01
(0.01)*
France
-0.01
(0.01)**
0.21
(0.01)***
0.16
(0.01)***
0.15
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
0.07
(0.01)***
USA
0.55
(0.01)***
0.63
(0.01)***
0.54
(0.01)***
0.52
(0.01)***
0.49
(0.01)***
0.48
(0.01)***
0.48
(0.01)***
0.47
(0.01)***
0.45
(0.01)***
0.44
(0.01)***
UK
0.16
(0.01)***
0.17
(0.02)***
0.16
(0.01)***
0.16
(0.01)***
0.16
(0.01)***
0.15
(0.01)***
0.14
(0.01)***
0.14
(0.01)***
0.12
(0.01)***
0.09
(0.01)***
Austria
-0.68
(0.01)***
-0.52
(0.02)***
-0.48
(0.02)***
-0.37
(0.02)***
-0.33
(0.02)***
-0.28
(0.01)***
-0.25
(0.01)***
-0.22
(0.01)***
-0.23
(0.01)***
-0.22
(0.02)***
Night 1-7
-0.51
(0.00)***
-0.53
(0.01)***
-0.56
(0.01)***
-0.57
(0.01)***
-0.57
(0.01)***
-0.60
(0.01)***
-0.62
(0.01)***
-0.64
(0.01)***
-0.67
(0.01)***
-0.73
(0.01)***
Nights 16-31
0.34
(0.01)***
0.27
(0.02)***
0.25
(0.01)***
0.25
(0.01)***
0.24
(0.01)***
0.25
(0.01)***
0.23
(0.01)***
0.23
(0.01)***
0.22
(0.01)***
0.18
(0.01)***
Years 08-09-10
-0.07
(0.00)***
-0.13
(0.01)***
-0.12
(0.01)***
-0.11
(0.01)***
-0.08
(0.01)***
-0.07
(0.01)***
-0.06
(0.01)***
-0.05
(0.01)***
-0.05
(0.01)***
-0.06
(0.01)***
Years 11-12-13
-0.12
(0.00)***
-0.14
(0.01)***
-0.12
(0.01)***
-0.12
(0.01)***
-0.10
(0.01)***
-0.10
(0.01)***
-0.09
(0.01)***
-0.09
(0.01)***
-0.09
(0.01)***
-0.11
(0.01)***
Intercept
5.25
(0.03)***
4.70
(0.06)***
4.98
(0.05)***
5.19
(0.04)***
5.32
(0.04)***
5.53
(0.05)***
5.71
(0.04)***
5.89
(0.04)***
6.12
(0.04)***
6.46
(0.05)***
FIGURES
Figure 1. Expenditure and satisfaction dynamics
8.00
8.10
8.20
8.30
8.40
8.50
8.60
1000
1100
1200
1300
1400
1500
1600
1700
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Overall
Expenditure Satisfaction
7.40
7.50
7.60
7.70
7.80
7.90
8.00
8.10
200
300
400
500
600
700
800
900
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Accommodation
Expenditure Satisfaction
7.20
7.30
7.40
7.50
7.60
7.70
7.80
7.90
100
140
180
220
260
300
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Shopping
Expenditure Satisfaction
6.80
6.90
7.00
7.10
7.20
7.30
7.40
7.50
7.60
200
240
280
320
360
400
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Restaurant
Expenditure Satisfaction
Figure 2. Mean satisfaction for the different quantiles of expenditure
8.05
8.10
8.15
8.20
8.25
8.30
8.35
8.40
8.45
8.50
8.55
8.60
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
Overall
7.30
7.40
7.50
7.60
7.70
7.80
7.90
8.00
8.10
8.20
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
Accommodation
7.00
7.20
7.40
7.60
7.80
8.00
8.20
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
Shopping
7.20
7.25
7.30
7.35
7.40
7.45
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
Restaurants
Figure 3. IV and IVQR estimates of satisfaction parameters
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
OVERALL
IVQR C.I. ivqr C.I. ivqr C.I. ivr C.I. ivr IVR
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
ACCOMMODATION
IVQR C.I. ivqr C.I. ivqr C.I. ivr C.I. ivr IVR
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
SHOPPING
IVQR C.I. ivqr C.I. ivqr C.I. ivr C.I. ivr IVR
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
RESTAURANTS
IVQR C.I. ivqr C.I. ivqr C.I. ivr C.I. ivr IVR
Figure 4. IV and IVQR estimates of the total expenditure model
Yellow solid line: IVR estimation
Yellow dotted line: IVR 95% confidence intervals
Blue solid line: IVQR estimation
Blue dotted line: IVQR 95% confidence intervals
5
5.5
6
6.5
7
7.5
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
INTERCEPT
-0.05
-0.03
-0.01
0.01
0.03
0.05
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
MALE
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
AGE15TO24
-0.2
-0.18
-0.16
-0.14
-0.12
-0.1
-0.08
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
AGE25TO34
-0.01
0.01
0.03
0.05
0.07
0.09
0.11
0.13
0.15
0.17
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
AGE45TO64
-0.4
-0.3
-0.2
-0.1
0
0.1
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
AGEMORETHAN65
-0.25
-0.23
-0.21
-0.19
-0.17
-0.15
-0.13
-0.11
-0.09
-0.07
-0.05
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
STUDENTS
-0.05
-0.03
-0.01
0.01
0.03
0.05
0.07
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
SOUTH-ISLANDS
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
NORTH
0.2
0.22
0.24
0.26
0.28
0.3
0.32
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
INCLUSIVE PACKAGE
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
HOTEL
-0.25
-0.2
-0.15
-0.1
-0.05
0
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
ALONE
Figure 4. IV and IVQR estimates of the total expenditure model (continued)
Yellow solid line: IVR estimation
Yellow dotted line: IVR 95% confidence intervals
Blue solid line: IVQR estimation
Blue dotted line: IVQR 95% confidence intervals
-0.77
-0.67
-0.57
-0.47
-0.37
-0.27
-0.17
-0.07
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
AUSTRIA
-0.85
-0.8
-0.75
-0.7
-0.65
-0.6
-0.55
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
NIGHTS 1-7
0.12
0.17
0.22
0.27
0.32
0.37
0.42
0.47
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
NIGHTS 16-31
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
YEARS 2008-2009-2010
-0.15
-0.14
-0.13
-0.12
-0.11
-0.1
-0.09
-0.08
-0.07
-0.06
-0.05
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
YEARS 2011-2012-2013
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
SPAIN
-0.35
-0.25
-0.15
-0.05
0.05
0.15
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
FRANCE
0.4
0.45
0.5
0.55
0.6
0.65
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
USA
-0.02
0.03
0.08
0.13
0.18
0.23
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
UK
TABLES APPENDIX
Table C1. Model QR estimates: total expenditure
Total expenditure
OLS
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Overall Satisfaction
0.26
(0.01)***
0.37
(0.02)***
0.29
(0.01)***
0.25
(0.01)***
0.24
(0.01)***
0.23
(0.01)***
0.21
(0.01)***
0.20
(0.01)***
0.18
(0.01)***
0.17
(0.02)***
Male
-0.00
(0.00)
-0.01
(0.01)**
-0.01
(0.00)
0.00
(0.00)
-0.01
(0.00)**
-0.01
(0.00)***
-0.01
(0.00)***
-0.01
(0.00)***
0.00
(0.00)
0.00
(0.00)
Age15to25
-0.19
(0.01)***
-0.24
(0.01)***
-0.24
(0.01)***
-0.25
(0.01)***
-0.24
(0.01)***
-0.24
(0.01)***
-0.22
(0.01)***
-0.21
(0.01)***
-0.19
(0.01)***
-0.16
(0.01)***
Age25to34
-0.11
(0.00)***
-0.09
(0.01)***
-0.12
(0.00)***
-0.13
(0.00)***
-0.13
(0.00)***
-0.13
(0.00)***
-0.13
(0.00)***
-0.13
(0.00)***
-0.13
(0.00)***
-0.14
(0.01)***
Age45to64
0.01
(0.00)***
-0.06
(0.01)***
-0.01
(0.01)
0.02
(0.01)***
0.03
(0.00)***
0.04
(0.00)***
0.06
(0.00)***
0.07
(0.00)***
0.08
(0.00)***
0.09
(0.01)***
Agemorethan65
-0.32
(0.01)***
-0.46
(0.01)***
-0.51
(0.02)***
-0.46
(0.02)***
-0.35
(0.01)**
-0.28
(0.01)***
-0.21
(0.01)***
-0.17
(0.01)***
-0.12
(0.01)***
-0.08
(0.01)***
South-islands
-0.00
(0.00)
0.00
(0.01)
-0.01
(0.01)
-0.01
(0.01)**
-0.01
(0.00)***
-0.01
(0.00)**
-0.01
(0.00)**
0.00
(0.00)
0.01
(0.01)*
0.03
(0.01)***
North
-0.19
(0.00)***
-0.20
(0.01)***
-0.18
(0.00)***
-0.17
(0.00)***
-0.16
(0.00)***
-0.15
(0.00)***
-0.15
(0.00)***
-0.14
(0.00)***
-0.14
(0.00)***
-0.13
(0.00)***
Inclusive Package
0.29
(0.00)***
0.32
(0.01)***
0.30
(0.00)***
0.29
(0.00)***
0.30
(0.00)***
0.29
(0.00)***
0.28
(0.00)***
0.28
(0.00)***
0.28
(0.00)***
0.27
(0.00)***
Hotel
0.45
(0.00)***
0.67
(0.01)***
0.51
(0.00)***
0.44
(0.00)***
0.39
(0.00)***
0.35
(0.00)***
0.32
(0.00)***
0.29
(0.00)***
0.25
(0.00)***
0.20
(0.01)***
Student
-0.11
(0.01)***
-0.09
(0.01)***
-0.11
(0.01)***
-0.11
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.13
(0.01)***
Alone
-0.17
(0.00)***
-0.20
(0.01)***
-0.21
(0.00)***
-0.22
(0.00)***
-0.23
(0.00)***
-0.23
(0.00)***
-0.23
(0.00)***
-0.21
(0.00)***
-0.18
(0.01)***
-0.12
(0.01)***
Spain
0.05
(0.00)***
0.14
(0.01)***
0.10
(0.00)***
0.07
(0.00)***
0.05
(0.00)***
0.04
(0.00)***
0.02
(0.00)***
-0.01
(0.00)**
-0.04
(0.00)***
-0.07
(0.01)***
France
-0.25
(0.01)***
-0.33
(0.01)***
-0.32
(0.01)***
-0.25
(0.01)***
-0.20
(0.00)***
-0.17
(0.01)***
-0.14
(0.01)***
-0.12
(0.01)***
-0.12
(0.01)***
-0.14
(0.01)***
USA
0.61
(0.01)***
0.77
(0.01)***
0.67
(0.01)***
0.61
(0.01)***
0.57
(0.00)***
0.54
(0.00)***
0.52
(0.00)***
0.51
(0.01)***
0.51
(0.01)***
0.50
(0.01)***
UK
0.13
(0.01)***
0.22
(0.01)***
0.16
(0.01)***
0.14
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.09
(0.01)***
0.06
(0.01)***
0.02
(0.01)***
Austria
-0.64
(0.01)***
-1.19
(0.01)***
-0.98
(0.02)***
-0.71
(0.02)***
-0.56
(0.01)***
-0.47
(0.01)***
-0.39
(0.01)***
-0.34
(0.01)***
-0.31
(0.01)***
-0.27
(0.01)***
Night 1-7
-0.56
(0.00)***
-0.39
(0.01)***
-0.51
(0.00)***
-0.56
(0.00)***
-0.59
(0.00)***
-0.62
(0.00)***
-0.65
(0.00)***
-0.68
(0.00)***
-0.71
(0.00)***
-0.77
(0.01)***
Nights 16-31
0.44
(0.01)***
0.63
(0.01)***
0.49
(0.01)***
0.44
(0.01)***
0.40
(0.01)***
0.38
(0.01)***
0.35
(0.01)***
0.33
(0.01)***
0.28
(0.01)***
0.21
(0.01)***
Years 08-09-10
-0.03
(0.00)***
-0.01
(0.01)
-0.03
(0.00)***
-0.04
(0.00)***
-0.04
(0.00)***
-0.05
(0.00)***
-0.06
(0.00)***
-0.06
(0.00)***
-0.07
(0.00)***
-0.08
(0.01)***
Years 11-12-13
-0.09
(0.00)***
-0.05
(0.01)***
-0.08
(0.00)***
-0.09
(0.00)***
-0.10
(0.00)***
-0.10
(0.00)***
-0.10
(0.00)***
-0.11
(0.00)***
-0.11
(0.00)***
-0.13
(0.01)***
Intercept
6.42
(0.02)***
5.02
(0.04)***
5.75
(0.03)***
6.15
(0.03)***
6.42
(0.02)***
6.65
(0.02)***
6.87
(0.02)***
7.09
(0.02)***
7.37
(0.03)***
7.75
(0.03)***
Table C2. Model QR estimates: accommodation expenditure
Accomodation
expenditure
OLS
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Accomodation
satisfaction
0.23
(0.01)***
0.22
(0.01)***
0.23
(0.01)***
0.24
(0.01)***
0.24
(0.01)***
0.23
(0.01)***
0.23
(0.01)***
0.24
(0.01)***
0.22
(0.01)***
0.22
(0.01)***
Male
-0.05
(0.00)***
-0.06
(0.01)***
-0.06
(0.00)***
-0.06
(0.00)***
-0.06
(0.00)***
-0.06
(0.00)***
-0.05
(0.00)***
-0.05
(0.00)***
-0.05
(0.00)***
-0.05
(0.01)***
Age15to25
-0.26
(0.01)***
-0.29
(0.01)***
-0.29
(0.01)***
-0.30
(0.01)***
-0.31
(0.01)***
-0.30
(0.01)***
-0.30
(0.01)***
-0.27
(0.01)***
-0.25
(0.01)***
-0.19
(0.01)***
Age25to34
-0.17
(0.00)***
-0.16
(0.01)***
-0.17
(0.01)***
-0.19
(0.01)***
-0.19
(0.00)***
-0.19
(0.00)***
-0.18
(0.00)***
-0.18
(0.00)***
-0.18
(0.01)***
-0.17
(0.01)***
Age45to64
0.10
(0.00)***
0.08
(0.01)***
0.10
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.11
(0.00)***
0.11
(0.00)***
0.11
(0.01)***
0.12
(0.01)***
0.13
(0.01)***
Agemorethan65
-0.01
(0.01)
-0.07
(0.02)***
-0.05
(0.01)***
-0.04
(0.01)***
-0.02
(0.01)
-0.01
(0.01)
0.01
(0.01)
0.02
(0.01)*
0.03
(0.01)**
0.06
(0.01)***
South-islands
-0.00
(0.00)
0.00
(0.01)
0.00
(0.01)
-0.01
(0.01)
-0.01
(0.01)
-0.02
(0.01)***
-0.01
(0.01)***
-0.01
(0.01)**
0.00
(0.01)
0.01
(0.01)
North
-0.08
(0.00)***
-0.05
(0.01)***
-0.05
(0.00)***
-0.06
(0.00)***
-0.07
(0.00)***
-0.08
(0.00)***
-0.07
(0.00)***
-0.08
(0.00)***
-0.09
(0.00)***
-0.09
(0.01)***
Inclusive Package
0.37
(0.00)***
0.36
(0.01)***
0.35
(0.00)***
0.35
(0.00)***
0.36
(0.00)***
0.37
(0.00)***
0.37
(0.00)***
0.38
(0.00)***
0.38
(0.00)***
0.37
(0.01)***
Hotel
0.31
(0.00)***
0.42
(0.01)***
0.38
(0.01)***
0.37
(0.00)***
0.35
(0.00)***
0.33
(0.00)***
0.30
(0.00)***
0.27
(0.00)***
0.23
(0.01)***
0.18
(0.01)***
Student
-0.14
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.15
(0.01)***
-0.15
(0.01)***
-0.13
(0.01)***
-0.12
(0.01)***
Alone
-0.17
(0.00)***
-0.23
(0.01)***
-0.23
(0.01)***
-0.23
(0.01)***
-0.22
(0.01)***
-0.20
(0.01)***
-0.19
(0.01)***
-0.18
(0.01)***
-0.13
(0.01)***
-0.07
(0.01)***
Spain
0.00
(0.00)
0.08
(0.01)***
0.06
(0.01)***
0.04
(0.01)***
0.03
(0.01)***
0.02
(0.01)***
0.01
(0.01)
-0.02
(0.01)***
-0.04
(0.01)***
-0.07
(0.01)***
France
-0.00
(0.01)
0.02
(0.01)
0.03
(0.01)***
0.03
(0.01)***
0.02
(0.01)***
0.01
(0.01)*
0.01
(0.01)*
0.00
(0.01)
-0.01
(0.01)**
-0.04
(0.01)***
USA
0.50
(0.01)***
0.58
(0.01)***
0.54
(0.01)***
0.52
(0.01)***
0.49
(0.01)***
0.48
(0.01)***
0.47
(0.01)***
0.47
(0.01)***
0.46
(0.01)***
0.47
(0.01)***
UK
0.09
(0.01)***
0.18
(0.01)***
0.14
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.09
(0.01)***
0.07
(0.01)***
0.05
(0.01)***
0.03
(0.01)***
0.00
(0.01)
Austria
-0.22
(0.01)***
-0.45
(0.02)***
-0.36
(0.01)***
-0.29
(0.01)***
-0.25
(0.01)***
-0.20
(0.01)***
-0.17
(0.01)***
-0.12
(0.01)***
-0.08
(0.01)***
-0.02
(0.01)*
Night 1-7
-0.79
(0.00)***
-0.77
(0.01)***
-0.76
(0.01)***
-0.75
(0.00)***
-0.75
(0.00)***
-0.74
(0.00)***
-0.75
(0.00)***
-0.76
(0.00)***
-0.79
(0.01)***
-0.83
(0.01)***
Nights 16-31
0.20
(0.01)***
0.20
(0.01)***
0.22
(0.01)***
0.25
(0.01)***
0.25
(0.01)***
0.27
(0.01)***
0.26
(0.01)***
0.25
(0.01)***
0.23
(0.01)***
0.17
(0.01)***
Years 08-09-10
-0.17
(0.00)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.15
(0.00)***
-0.15
(0.00)***
-0.16
(0.00)***
-0.17
(0.00)***
-0.18
(0.00)***
-0.19
(0.00)***
-0.22
(0.01)***
Years 11-12-13
-0.15
(0.00)***
-0.11
(0.01)***
-0.12
(0.01)***
-0.12
(0.00)***
-0.13
(0.00)***
-0.14
(0.00)***
-0.15
(0.00)***
-0.16
(0.00)***
-0.18
(0.00)***
-0.21
(0.01)***
Intercept
5.96
(0.01)***
4.93
(0.02)***
5.28
(0.02)***
5.52
(0.02)***
5.73
(0.02)***
5.93
(0.02)***
6.14
(0.02)***
6.34
(0.02)***
6.64
(0.02)***
7.04
(0.03)***
Table C3. Model QR estimates: shopping expenditure
Shopping
expenditure
OLS
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Shopping
satisfaction
0.33
(0.01)***
0.39
(0.01)***
0.35
(0.01)***
0.35
(0.01)***
0.35
(0.01)***
0.33
(0.01)***
0.32
(0.01)***
0.32
(0.01)***
0.29
(0.01)***
0.27
(0.01)***
Male
-0.03
(0.00)***
-0.06
(0.01)***
-0.05
(0.00)***
-0.03
(0.01)***
-0.04
(0.01)***
-0.03
(0.00)***
-0.03
(0.00)***
-0.03
(0.01)***
-0.03
(0.00)***
-0.01
(0.01)**
Age15to25
-0.18
(0.01)***
-0.25
(0.02)***
-0.21
(0.01)***
-0.23
(0.01)***
-0.25
(0.01)***
-0.19
(0.01)***
-0.18
(0.01)***
-0.17
(0.01)***
-0.11
(0.01)***
-0.09
(0.01)***
Age25to34
-0.11
(0.01)***
-0.12
(0.01)***
-0.11
(0.01)***
-0.13
(0.01)***
-0.14
(0.01)***
-0.11
(0.01)***
-0.12
(0.01)***
-0.13
(0.01)***
-0.10
(0.01)***
-0.11
(0.01)***
Age45to64
0.05
(0.01)***
0.02
(0.01)**
0.02
(0.01)***
0.04
(0.01)***
0.05
(0.01)***
0.04
(0.01)***
0.06
(0.01)***
0.07
(0.01)***
0.06
(0.01)***
0.08
(0.01)***
Agemorethan65
-0.08
(0.01)***
-0.15
(0.02)***
-0.14
(0.02)***
-0.16
(0.02)***
-0.17
(0.01)***
-0.10
(0.02)***
-0.10
(0.02)***
-0.05
(0.02)***
0.01
(0.01)
0.05
(0.02)**
South-islands
0.12
(0.01)***
0.15
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.12
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
North
-0.11
(0.00)***
-0.06
(0.01)***
-0.07
(0.01)***
-0.10
(0.01)***
-0.11
(0.01)***
-0.10
(0.01)***
-0.12
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
-0.14
(0.01)***
Inclusive Package
0.09
(0.00)***
0.20
(0.01)***
0.13
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.09
(0.01)***
0.07
(0.01)***
0.06
(0.01)***
0.04
(0.01)***
0.01
(0.01)*
Hotel
0.02
(0.00)***
0.08
(0.01)***
0.04
(0.01)***
0.02
(0.01)***
0.01
(0.01)**
0.01
(0.01)
0.00
(0.01)
0.00
(0.01)
-0.01
(0.01)*
-0.01
(0.01)
Student
-0.14
(0.01)***
-0.14
(0.02)***
-0.12
(0.01)***
-0.10
(0.01)***
-0.15
(0.01)***
-0.15
(0.01)***
-0.12
(0.01)***
-0.15
(0.01)***
-0.16
(0.01)***
-0.18
(0.01)***
Alone
-0.07
(0.01)***
-0.10
(0.01)***
-0.10
(0.01)***
-0.09
(0.01)***
-0.09
(0.01)***
-0.10
(0.01)***
-0.08
(0.01)***
-0.06
(0.01)***
-0.04
(0.01)***
0.00
(0.01)
Spain
0.01
(0.01)
0.06
(0.01)***
0.04
(0.01)***
0.04
(0.01)***
0.03
(0.01)***
0.02
(0.01)***
0.01
(0.01)
0.00
(0.01)
-0.01
(0.01)
-0.04
(0.01)***
France
0.10
(0.01)***
0.13
(0.02)***
0.10
(0.01)***
0.11
(0.01)***
0.11
(0.01)***
0.08
(0.01)***
0.10
(0.01)***
0.10
(0.01)***
0.09
(0.01)***
0.08
(0.01)***
USA
0.81
(0.01)***
0.83
(0.01)***
0.86
(0.01)***
0.82
(0.01)***
0.82
(0.01)***
0.81
(0.01)***
0.81
(0.01)***
0.81
(0.01)***
0.81
(0.01)***
0.81
(0.01)***
UK
0.34
(0.01)***
0.40
(0.02)***
0.34
(0.01)***
0.38
(0.01)***
0.36
(0.01)***
0.35
(0.01)***
0.36
(0.01)***
0.33
(0.01)***
0.29
(0.01)***
0.28
(0.01)***
Austria
-0.33
(0.01)***
-0.45
(0.02)***
-0.42
(0.02)***
-0.32
(0.02)***
-0.37
(0.01)***
-0.34
(0.02)***
-0.23
(0.01)***
-0.26
(0.01)***
-0.21
(0.01)***
-0.19
(0.01)***
Night 1-7
-0.40
(0.00)***
-0.33
(0.01)***
-0.30
(0.01)***
-0.41
(0.01)***
-0.34
(0.01)***
-0.36
(0.01)***
-0.43
(0.01)***
-0.41
(0.01)***
-0.44
(0.01)***
-0.53
(0.01)***
Nights 16-31
0.20
(0.01)***
0.25
(0.01)***
0.26
(0.01)***
0.23
(0.01)***
0.24
(0.01)***
0.26
(0.01)***
0.20
(0.01)***
0.20
(0.01)***
0.17
(0.01)***
0.13
(0.01)***
Years 08-09-10
0.11
(0.00)***
0.12
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.10
(0.01)***
0.09
(0.01)***
0.10
(0.01)***
0.09
(0.01)***
0.10
(0.01)***
Years 11-12-13
-0.03
(0.00)***
-0.04
(0.01)***
-0.01
(0.01)**
-0.03
(0.01)***
-0.03
(0.01)***
-0.03
(0.01)***
-0.04
(0.01)***
-0.04
(0.01)***
-0.04
(0.01)***
-0.05
(0.01)***
Intercept
4.32
(0.02)***
2.91
(0.03)***
3.43
(0.02)***
3.79
(0.02)***
4.05
(0.02)***
4.34
(0.02)***
4.62
(0.02)***
4.86
(0.02)***
5.23
(0.02)***
5.70
(0.03)***
Table C4. Model QR estimates: restaurant expenditure
Restaurant
expenditure
OLS
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Restaurant
satisfaction
0.05
(0.05)***
0.09
(0.01)***
0.08
(0.01)***
0.06
(0.01)***
0.06
(0.01)***
0.05
(0.01)***
0.04
(0.01)***
0.03
(0.01)***
0.03
(0.01)***
0.02
(0.01)***
Male
0.03
(0.00)***
0.05
(0.01)***
0.04
(0.01)***
0.03
(0.00)***
0.03
(0.00)***
0.02
(0.00)***
0.02
(0.00)***
0.02
(0.00)***
0.02
(0.00)***
0.03
(0.00)***
Age15to25
-0.21
(0.01)***
-0.29
(0.01)***
-0.27
(0.01)***
-0.27
(0.01)***
-0.24
(0.01)***
-0.22
(0.01)***
-0.20
(0.01)***
-0.19
(0.01)***
-0.16
(0.01)***
-0.11
(0.01)***
Age25to34
-0.09
(0.00)***
-0.09
(0.01)***
-0.11
(0.01)***
-0.11
(0.01)***
-0.10
(0.01)***
-0.10
(0.00)***
-0.11
(0.00)***
-0.12
(0.00)***
-0.12
(0.01)***
-0.11
(0.01)***
Age45to64
0.02
(0.01)***
-0.07
(0.01)***
-0.03
(0.01)***
0.01
(0.01)
0.03
(0.01)***
0.05
(0.01)***
0.06
(0.01)***
0.07
(0.01)***
0.09
(0.01)***
0.12
(0.01)***
Agemorethan65
-0.24
(0.01)***
-0.37
(0.02)***
-0.33
(0.02)***
-0.31
(0.01)***
-0.31
(0.01)***
-0.27
(0.01)***
-0.21
(0.01)***
-0.17
(0.01)***
-0.10
(0.02)***
-0.03
(0.01)**
South-islands
-0.00
(0.01)
0.00
(0.01)
0.00
(0.01)
-0.01
(0.01)*
-0.01
(0.01)**
-0.02
(0.01)***
-0.01
(0.01)*
0.01
(0.01)
0.01
(0.01)
0.02
(0.01)***
North
-0.16
(0.00)***
-0.19
(0.01)***
-0.17
(0.01)***
-0.17
(0.00)***
-0.16
(0.00)***
-0.16
(0.00)***
-0.16
(0.00)***
-0.15
(0.00)***
-0.14
(0.00)***
-0.12
(0.01)***
Inclusive Package
0.00
(0.00)
-0.13
(0.01)***
-0.04
(0.01)***
0.00
(0.00)
0.03
(0.01)***
0.06
(0.00)***
0.07
(0.00)***
0.08
(0.00)***
0.08
(0.00)***
0.07
(0.01)***
Hotel
0.30
(0.00)***
0.50
(0.01)***
0.39
(0.01)***
0.33
(0.01)***
0.30
(0.00)***
0.26
(0.00)***
0.24
(0.00)***
0.22
(0.00)***
0.19
(0.01)***
0.14
(0.01)***
Student
-0.15
(0.01)***
-0.08
(0.01)***
-0.11
(0.01)***
-0.13
(0.01)***
-0.15
(0.01)***
-0.16
(0.01)***
-0.17
(0.01)***
-0.17
(0.01)***
-0.18
(0.01)***
-0.18
(0.01)***
Alone
-0.17
(0.00)***
-0.21
(0.01)***
-0.22
(0.01)***
-0.22
(0.01)***
-0.21
(0.01)***
-0.21
(0.00)***
-0.20
(0.01)***
-0.19
(0.01)***
-0.17
(0.01)***
-0.13
(0.01)***
Spain
0.12
(0.01)***
0.23
(0.01)***
0.17
(0.01)***
0.14
(0.01)***
0.12
(0.01)***
0.11
(0.01)***
0.09
(0.01)***
0.09
(0.01)***
0.07
(0.01)***
0.04
(0.01)***
France
-0.02
(0.01)***
0.10
(0.02)***
0.03
(0.01)***
0.00
(0.01)***
0.00
(0.01)**
-0.01
(0.01)
-0.02
(0.01)**
0.00
(0.01)
-0.01
(0.01)
-0.01
(0.01)
USA
0.53
(0.01)***
0.76
(0.01)***
0.62
(0.01)***
0.55
(0.01)***
0.50
(0.01)***
0.48
(0.01)***
0.46
(0.01)***
0.44
(0.01)***
0.43
(0.01)***
0.41
(0.01)***
UK
0.13
(0.01)***
0.26
(0.01)***
0.18
(0.01)***
0.15
(0.01)***
0.15
(0.01)***
0.13
(0.01)***
0.12
(0.01)***
0.10
(0.01)***
0.08
(0.01)***
0.04
(0.01)***
Austria
-0.68
(0.01)***
-1.00
(0.02)***
-0.94
(0.02)***
-0.86
(0.02)***
-0.67
(0.01)***
-0.58
(0.01)***
-0.49
(0.01)***
-0.42
(0.01)***
-0.39
(0.01)***
-0.37
(0.01)***
Night 1-7
-0.51
(0.01)***
-0.36
(0.01)***
-0.43
(0.01)***
-0.46
(0.00)***
-0.50
(0.00)***
-0.53
(0.00)***
-0.57
(0.00)***
-0.60
(0.00)***
-0.64
(0.01)***
-0.71
(0.01)***
Nights 16-31
0.34
(0.01)***
0.50
(0.01)***
0.41
(0.01)***
0.37
(0.01)***
0.34
(0.01)***
0.33
(0.01)***
0.30
(0.01)***
0.29
(0.01)***
0.27
(0.01)***
0.23
(0.01)***
Years 08-09-10
-0.07
(0.00)***
-0.10
(0.01)***
-0.10
(0.01)***
-0.10
(0.00)***
-0.09
(0.00)***
-0.07
(0.00)***
-0.07
(0.00)***
-0.07
(0.00)***
-0.07
(0.01)***
-0.06
(0.01)***
Years 11-12-13
-0.11
(0.00)***
-0.10
(0.01)***
-0.11
(0.01)***
-0.12
(0.00)***
-0.11
(0.00)***
-0.11
(0.00)***
-0.11
(0.00)***
-0.11
(0.00)***
-0.11
(0.01)***
-0.11
(0.01)***
Intercept
5.54
(0.01)***
4.21
(0.02)***
4.77
(0.02)***
5.15
(0.02)***
5.38
(0.01)***
5.61
(0.01)***
5.86
(0.01)***
6.11
(0.01)***
6.37
(0.01)***
6.75
(0.02)***
Table C5. Tests for RQ
Test
Overall
Accommodation
Shopping
Restaurants
q10=q20
0.0418**
0.3306
0.0000***
0.1768
q20=q30
0.0000***
0.0005***
0.3045
0.0009***
q30=q40
0.0005***
0.8156
0.0000***
0.3250
q40=q50
0.1291
0.6712
0.0183**
0.0007***
q50=q60
0.0000***
0.8975
0.0000***
0.0192**
q60=q70
0.2955
0.0000***
0.0000***
0.0000***
q70=q80
0.0000***
0.0074***
0.0000***
0.0000***
q80=q90
0.0000***
0.7922
0.0014***
0.3310
FIGURES APPENDIX
Figure C1. OLS and QR estimates of satisfaction parameters
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
OVERALL
OLS C.I. ols C.I. ols
C.I. rq RQ C.I. rq
0.15
0.17
0.19
0.21
0.23
0.25
0.27
0.29
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
ACCOMMODATION
OLS C.I. ols C.I. ols
C.I. rq RQ C.I. rq
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
SHOPPING
OLS C.I. ols C.I. ols
C.I. rq RQ C.I. rq
-0.0100
0.0100
0.0300
0.0500
0.0700
0.0900
0.1100
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
RESTAURANTS
OLS C.I. ols C.I. ols
C.I. rq RQ C.I. rq
Figure C2. OLS and QR estimates of the total expenditure model
Red solid line: OLS estimation
Red dotted line: OLS confidence intervals
Blue solid line: RQ estimation
Blue dotted line: RQ confidence intervals
5
5.5
6
6.5
7
7.5
8
1 2 3 4 5 6 7 8 9
INTERCEPT
-0.0500
-0.0300
-0.0100
0.0100
0.0300
0.0500
1 2 3 4 5 6 7 8 9
MALE
-0.3
-0.25
-0.2
-0.15
-0.1
123456789
AGE15TO24
-0.2
-0.18
-0.16
-0.14
-0.12
-0.1
-0.08
-0.06
123456789
AGE25TO34
-0.1
-0.05
0
0.05
0.1
0.15
123456789
AGE45TO64
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
1 2 3 4 5 6 7 8 9
AGEMORETHAN65
-0.2
-0.18
-0.16
-0.14
-0.12
-0.1
-0.08
-0.06
-0.04
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
STUDENTS
-0.05
-0.03
-0.01
0.01
0.03
0.05
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
SOUTH-ISLANDS
-0.25
-0.23
-0.21
-0.19
-0.17
-0.15
-0.13
-0.11
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
NORTH
0.25
0.26
0.27
0.28
0.29
0.3
0.31
0.32
0.33
0.34
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
INCLUSIVE PACKAGE
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
HOTEL
-0.3
-0.25
-0.2
-0.15
-0.1
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
ALONE
Figure C2. OLS and QR estimates of the total expenditure model (continued)
Red solid line: OLS estimation
Red dotted line: OLS 95% confidence intervals
Blue solid line: RQ estimation
Blue dotted line: RQ 95% confidence intervals
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
SPAIN
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
USA
-0.01
0.04
0.09
0.14
0.19
0.24
0.29
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
UK
-1.25
-1.05
-0.85
-0.65
-0.45
-0.25
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
AUSTRIA
-0.85
-0.8
-0.75
-0.7
-0.65
-0.6
-0.55
-0.5
-0.45
-0.4
-0.35
Q10 Q20 Q30 Q40 Q50 Q60 Q70 Q80 Q90
NIGHTS 1-7
0.15
0.25
0.35
0.45
0.55
0.65