On nature’s shoulders

Abstract

The use of counterfactual methods in the evaluation of policy interventions has been accepted today as the best approach in the estimation of a program’s performance. However, the simplest evaluations are often quite demanding in terms of the resources and the time needed to be implemented. In this article, we study the economic impact of a tourism media campaign launched in Nazaré, an old fishing community on the west coast of Portugal, to make big waves visible to the world. The campaign provided the required “informational media infrastructure” that created the public awareness necessary to boost tourism in the region. To measure the economic impact of that campaign on the local economy, we show how a counterfactual analysis can be implemented using regional statistical data on domestic and international tourist arrivals. We show how the method can be adapted to account for the presence of potential spillover effects that may have occurred, as neighboring municipalities could also have been affected by the intervention. We further compare the estimated impact on revenues with the costs incurred by the local municipality in the marketing campaign. Based on our empirical findings, we discuss policy implications to the municipalities in the region.

Keywords

big waves counterfactual analysis impact evaluation nature uniqueness tourism

Introduction

There are many studies in the literature that estimate the impact of natural or cultural attractions (i.e., parks, wildlife, heritage, waves, etc.), or of the campaigns undertaken to make them known to the public, on local economies. However, many of the studies that attempt to evaluate these impacts ignore the baseline scenario, that is, they do not take into account what would have happened in the absence of those attractions or media campaigns.¹ In contrast, counterfactual analysis is today accepted as the best approach in policy evaluation since it aims at establishing the cause-and-effect relationship between a particular policy intervention and the resulting outcomes. However, even the simplest evaluations are often quite demanding in terms of the resources and the time needed to be implemented, which may explain why formal evaluation studies are still uncommon (see Curzon and Kontoleon, 2016). In this study, we show how a counterfactual analysis can be implemented using regional statistical data on domestic and international tourist arrivals.

An important contribution of this article is to show how a policy intervention related to a unique characteristic of a region was successful by significantly increasing the number of visitors. We look at a particular case study: the impact of a media campaign on big waves on the local economy of Nazaré, an old fishing community in the western coast of Portugal. We also investigate how the campaign has contributed to reduce seasonality in the municipality, an important concern of the Portuguese and EU policy makers for the tourist sector (see Eurostat, 2016; Turismo-2020, 2013, 2015).² We go beyond the traditional impact evaluation analysis in the literature and compare the revenues to the costs incurred with the media campaign.³ Based on our empirical findings, we discuss policy implications to the Oeste region in Portugal where Nazaré is located.

The remainder of the article is organized as follows. Section 2 reviews the literature, while Section 3 presents the case study. Section 4 describes the data and the methodology. Estimation results are discussed in Section 5. Finally, Section 6 concludes the article. Ancillary tables are presented in the Online Appendix.

Literature review

The use of counterfactual methods in the evaluation of policy interventions is currently accepted as the best approach to estimate a program’s performance. Yet, the use of counterfactual analyses remains overlooked in tourism economics.⁴ Some examples are provided by Mykerezi and Kostandini (2016), who estimate the impact of a Labor Day on family summer vacation in the USA using a differences-in-differences approach, O’Brochta (2017) that examines the impact of international tourism on the autonomy of a region in 10 European countries using regression discontinuity, and Aroca et al. (2017) that show how to improve the accuracy of tourism data using propensity score matching.

All counterfactual analyses require a baseline scenario, that is, what would happen with the outcome of interest without the policy intervention. The difference between the observed outcomes and counterfactual ones establishes the causal effects of the policy intervention. The main challenge of such approach is the construction of a counterfactual baseline scenario based on different assumptions that are difficult to confirm statistically. Yet, as mentioned by Angrist and Pishke (2009), the Asian Development Bank (2011), and Khandker et al. (2009), a counterfactual baseline scenario is required to conduct a rigorous impact evaluation. If the baseline scenario is ignored, then no conclusion can be taken about the policy impact even though ex-post outcomes of policy intervention are observed. That is to say, a simple regression analysis that only controls for policy intervention without a baseline scenario does not necessarily estimate the policy impact.

The selection of a particular counterfactual approach is conditional on the structure of available data. In fact, while some counterfactual analyses, such as propensity score matching and regression discontinuity, perform better with micro data (i.e., individual, household, and firm level data), others work better with macro data (i.e., region and country level data).

Nevertheless, each of the methods mentioned above presents its own limitations. For instance, the differences-in-differences approach controls for important unobserved characteristics that do not vary over time. However, these characteristics may change over time (see O’Brochta, 2017) and may be confounded with the policy intervention, leading to biased results. Note that a counterfactual scenario in this approach is referred as a control group, while the observed one, which is affected by the policy intervention, is referred as a treatment group. Moreover, it does not allow for spillover effects. That is, the outcome of interest in a control group should not be affected by the outcome in a treatment group which is often the case in tourism economics. For instance, organized events in a particular region may attract tourist visitors to that region, and most likely, these visitors may also visit adjacent regions (see O’Brochta, 2017). This makes it impossible to use adjacent regions as a proper control group.

Regarding propensity score matching, one of its main attractive features is that it only makes use of a single variable, the propensity score, that can be computed from many variables that predict the probability of receiving a treatment and is used to match treated and non-treated cases. However, a main criticism of the propensity score matching is that, as in the case of regression analysis, it can only control for observable covariates. Finally, the propensity score matching and the regression discontinuity are rather demanding in terms of data. In particular, they require a large number of observations before and after the policy intervention.

Case study

Nazaré is located about 120 km to the north of Lisbon and 220 km to the south of Oporto (see Figure 1), corresponding to an area of about 95.7 km². Its population is 12,810 inhabitants (INE, 2015). In this Atlantic region, the climate is temperate. It has a low-thermic amplitude throughout the year. The summer months are usually dry, while the winter months are rainy. This town is located in a typhonic valley and has long beaches along the bay.

Figure 1.

Nazaré’s location.

The Nazaré Canyon cuts into the relatively narrow continental shelf at the Western Iberian Margin, between 39°20′ and 39°40′ N, and is oriented roughly perpendicular to the coast (running therefore in the East–West direction). This is one of the largest canyon systems in Europe with depths from 100 m to 5000 m in the Atlantic Ocean, affecting all ecosystems in Nazaré (Quaresma et al., 2007; Relvas et al., 2007; Vitorino et al., 2002).

In the past, tourism demand in Nazaré was driven by religious beliefs, attracting many pilgrims to the Baroque Sanctuary of Our Lady of Nazaré, whose history dates back to the 14th century. Nazaré has become a popular seaside resort with its traditional and cultural charm.

Praia do Norte is a well-known beach because of its big waves, which are due to the Nazaré Canyon, a seafloor feature that contributes to the uniqueness of the region. Over the centuries, the big waves have been considered a threat to fishermen. However, recently the big waves have become a touristic attraction. Figure 2 reports the gradual increasing trend in Nazaré’s tourism in recent years.

Figure 2.

Number of tourist arrivals in Nazaré.

In 2007, the Nazaré municipality established a municipal company, Nazaré Qualifica, to promote regional tourism and increase its competitiveness with respect to other worldwide tourist destinations. In 2010, Nazaré Qualifica and the municipality of Nazaré launched a 3-year media campaign involving private and public institutions to promote the big waves and tourism in the region. After this marketing media campaign, the site became a more popular tourist destination by providing the required “informational media infrastructure” that campaign allowed for the worldwide recognition of the value of the big waves.⁵ The purpose of this study is to estimate the economic impact of that campaign on the local economy of Nazaré, using the number of arrivals in hotels between 2011 and 2014.

In 2009, Nazaré hosted for the first time the National Surfing Championship and the national bodyboard competition, “Sumol Nazaré Special Edition.” While the bodyboard competition was focused on the big waves of Nazaré, the National Surfing Championship was focused on normal size waves. According to Nazaré Qualifica, the bodyboard event was more successful in attracting tourists than the National Surfing Championship. For that reason, Nazaré Qualifica focused on promoting Nazaré as a destination where the big waves are advertised as a unique feature of nature.

As mentioned above, the big waves gained greater public awareness only after 2010, when Nazaré Qualifica and the municipality of Nazaré launched a media campaign to promote them. This surfing competition was mainly sponsored by a telecom company, ZON, and was held three times between 2010 and 2012.⁶ High-profile surfers, such as Garrett McNamara, were invited to surf those waves. Those elite surfers broke the Guinness World Records 2011⁷, and earned many “The XXL Big Wave Awards” nominations from the World Surf League (WSL). Moreover, from 2016 on, Nazaré has been included in the World Surf League Tour.⁸

After these municipal campaigns, Nazaré was recognized as a worldwide spot for big wave surfing, increasing its popularity as a tourist destination. This can be confirmed using the Google search for the Nazaré destination. The Google Trends search for “Nazaré Portugal” between 2006 and 2015 is in Figure 3, showing the number of searches relative to the highest number of searches over the period examined herein.

Figure 3.

Public interest trend “Nazaré Portugal.”

As shown in Figure 3, an upward trend of searches started after 2011, that is, when the Guinness World Record by Garrett McNamara was registered. The peak occurred in January 2013, when the Second World Record in Nazaré by Garrett McNamara was submitted (though not yet registered). Overall, this upward trend of searches may suggest that the campaign launched in 2010 has contributed to the worldwide recognition of the value of the big waves provided by the ecosystem in Nazaré. This can also be confirmed using Google Trends for the search term “Nazaré Big Waves” between 2006 and 2015, in which searches are observed only after 2010 (see Figure 4).

Figure 4.

Google Trends on “Nazaré Big Waves.” Source: www.google.com/trends, 27th June 2016.

In 2013, the Portuguese Government’s strategic plan for tourism also included the “Big Waves” in Nazaré as a potential attribute to increase the country’s competitiveness with respect to other world destinations (PENT, 2012). The program entitled “The National Strategic Plan for Tourism 2013-2015” (PENT, 2012) aimed at promoting sustainable growth in the tourism sector, and in particular at developing and promoting tourism with a focus on recreational and aesthetic services such as sun, beaches, gastronomy, health, and nautical tourism. It was later replaced by the Turismo-2020 program. Its main goal is to promote Portugal as one of the top 10 tourist destinations in the world. Currently, according to the Travel and Tourism Competitiveness Index,⁹ Portugal is in 15th place, following Canada, Singapore, Austria, Hong Kong, the Netherlands, among others.

Methodology and data

In this study, we use data from Statistics Portugal (INE) from 2004 to 2014 (INE, 2015). These data account for arrivals at different types of establishments such as hotels, hostels, pensions, and others.¹⁰

In order to estimate the impact of the Big Waves on the local economy, we compare the evolution of tourism in Nazaré with and without the media campaign. Since it is not possible to observe what would have happened without the campaign, we use a statistical methodology known as counterfactual analysis.

The general objective of a counterfactual analysis for policy evaluation is to establish a cause-and-effect relationship between a particular intervention and the resulting outcomes. In this study, the intervention is the media campaign on the big waves and the outcome is the number of tourist arrivals in Nazaré. Counterfactual scenarios are used to estimate the number of tourists that Nazaré would have attracted in the absence of the media campaign. A retrospective analysis prior to the media campaign is undertaken by selecting particular comparison groups that provide suitable counterfactual baselines representing the hypothetical situation without intervention. Note that our methodology is similar to a differences-in-differences approach since the counterfactual scenario corresponds to a control group, while the observed number of visitors corresponds to the treatment group. As mentioned above, the media campaign started in the autumn of 2010 and ended in 2012. Thus, we estimate the impact of the Big Waves since 2011.

We consider two counterfactual scenarios. Our first counterfactual analysis uses as a comparison group all the coastal municipalities in the Oeste region, excluding Nazaré. This selection is based on three reasons. First, these municipalities have the same distinguishing attractive factors as in Nazaré namely sun, sand, and surf, except for big waves. Figure 5 presents the evolution in the number of visitors over time. The solid line stands for the number of visitors in the Oeste coastal municipalities excluding Nazaré, while the dashed line stands for the total number of visitors in Nazaré. As can be seen, both lines move upward together and the Nazaré visitors contribute significantly to the total number of tourists visiting the region.

Figure 5.

Total number of visitors in the Oeste region (excluding Nazaré) and in Nazaré.

A second reason for using the Oeste coastal municipalities as a comparison group is that they are also located between the popular tourist route between Lisbon and Oporto, the two largest cities in Portugal, and the most important urban tourism areas in the country.¹¹ The number of visitors in Lisbon and Oporto accounts for about 30% of the total visitors in Portugal. When tourists travel between Lisbon and Oporto, a distance of 300 km, using rented cars or tourist buses, it is possible that they visit Nazaré or any other Oeste region municipality and stay overnight.

Finally, a third reason for using the Oeste coastal municipalities as a comparison group is that they also shared in the recent boom in tourism in Portugal between 2010 and 2014. As shown in Figure 6, the trend of tourism in Portugal is very similar to that observed in the coastal municipalities of the Oeste region (including Nazaré). Thus, to disentangle the impact of the Big Waves in Nazaré from the effect that might be due to the recent tourism boom in Portugal, the constructed comparison group should also reflect that recent change in trend.

Figure 6.

Number of visitors in Portugal and the Oeste region (excluding Nazaré).

In the first counterfactual analysis, we use the Oeste municipalities, excluding Nazaré, as the comparison or baseline group. The counterfactual number of tourists that would have visited Nazaré in case the media campaign had not taken place is estimated as the projected number of tourists in Nazaré given its past trend plus a correction of the change in trend that occurred after 2009 due to factors other than the big wave media campaign (mainly explained by the recent boom in tourism in Portugal). This change in trend is calculated from the observed change in trend in the number of tourists in the Oeste region. More specifically, we start using data on tourist arrivals in Nazaré before the media campaign, that is, from 2004 to 2009, in order to obtain projections for the subsequent years. To make the projections, we use the following equation:

ln (N u m T o u r i s t_{t}) = β_{0} + β_{1} t r e n d + u_{t}

where $ln (N u m T o u r i s t_{t})$ is the natural logarithm of the number of tourists in Nazaré in year t while trend stands for a linear trend, and u_t is an error term. Next, we apply the same procedure but using data for the Oeste coastal municipalities, excluding Nazaré, and obtain projections of the corresponding number of tourists for the same years. The above-mentioned correction of the change in the trend is then calculated for each year from 2011 to 2014 as follows¹²:

Δ_{t}^{Oeste} = ln (N u m T o u r i s t_{t}^{Observed Oeste}) - ln (N u m T o u r i s t_{t}^{Projected Oeste})

where $ln (N u m T o u r i s t_{t}^{Observed Oeste})$ and $ln (N u m T o u r i s t_{t}^{Projected Oeste})$ are the natural logarithms of the observed and projected numbers of tourists in the Oeste coastal municipalities excluding Nazaré in year t, respectively. Finally, the estimated impact of the media campaign on the number of tourist arrivals in Nazaré for the period 2011–2014 is calculated as the difference between the observed number of tourists in Nazaré and the projected values, including the correction for the change in trend, as follows:

{Impact}_{t} = N u m T o u r i s t_{t}^{Observed Nazare} - (1 + Δ_{t}^{Oeste}) \times N u m T o u r i s t_{t}^{Projected Nazare}

where $N u m T o u r i s t_{t}^{Observed Nazare}$ represents the observed number of tourists in Nazaré in year t, $N u m T o u r i s t_{t}^{Projected Nazare}$ is the projected numbers of tourists in Nazaré in year t obtained from equation (1), and $Δ_{t}^{Oeste}$ is the correction for the change in trend obtained from equation (2).

Our second counterfactual analysis extends the previous one by accounting for a problem common to any counterfactual analysis: the presence of potential spillover effects occurring when the comparison group is also affected by the intervention. In our case, it may be the case that the estimated Oeste coastal trend was also affected by the Nazaré big waves campaign, even though the Nazaré’s visitors were excluded from the comparison group. For instance, those who visited Nazaré because of the big wave could also have visited the neighboring coastal municipalities in Oeste. That is to say, there may exist a positive spillover effect of the big waves’ media campaign in Nazaré on the adjacent coastal municipalities in Oeste such that

Δ_{t}^{Oeste} = Δ_{t} + {Spillover}_{t}^{Oeste}

where Δ_t is the Oeste coastal municipality change in trend that would occur without the big wave intervention and without any spillover effects, and Spillover_t is the spillover effect caused on the Oeste coastal municipalities because of the Nazaré big wave campaign. To isolate this spillover effect, we first estimate the recent change in the growth rate of tourism in coastal municipalities that are located between Lisbon and Oporto but are not part of the Oeste region, as follows:

Δ_{t}^{Coastal} = ln (N u m T o u r i s t_{t}^{Observed Coastal}) - ln (N u m T o u r i s t_{t}^{Projected Coastal})

where $ln (N u m T o u r i s t_{t}^{Observed Coastal})$ and $ln (N u m T o u r i s t_{t}^{Projected Coastal})$ are the natural logarithms of the observed and projected numbers of tourists in coastal municipalities between Lisbon and Oporto excluding those from the Oeste region in year t, respectively.¹³ Since these municipalities are far from Nazaré, we may reasonably assume that in this case there is no spillover effect, that is, ${Spillover}_{t}^{Coastal} \approx 0$ , implying that

Δ_{t}^{Coastal} \approx Δ_{t}

where $Δ_{t}^{Coastal}$ and Δ_t stand as above. Finally, we calculate the estimated impact of the big wave media campaign as:

{Impact}_{t} = N u m T o u r i s t_{t}^{Observed Nazare} - (1 + Δ_{t}^{Coastal}) \times N u m T o u r i s t_{t}^{Projected Nazare}

where $Δ_{t}^{Coastal}$ is as in equation (5). This estimate properly accounts for any spillover effects that may have occurred.

Finally, note that the number of tourists before the policy intervention in 2010 follows a linear trend (Figure 2); thus, omitted factors are negligible in our study. If that were not the case, the model is flexible enough to accommodate additional factors in equation (1).

Estimation results

In this section, we present and discuss the estimation results of the economic impact of the media campaign on the big waves on the local economy of Nazaré under the two scenarios described in Section 3. We start by examining the impact on domestic visitors, followed by that on international visitors.

Domestic visitors

The results for domestic visitors are presented in Figure 7, where the solid line indicates the observed number of visitors in Nazaré and the dashed and dotted lines indicate the estimated number of tourists in Nazaré under scenarios 1 and 2, respectively. The differences between the solid line (observed data) and each other line (dashed or dotted line) illustrate to the impact of the media campaign. We also computed the estimated number of visitors for each scenario in Table 1.

Figure 7.

Estimation results for the number of domestic visitors.

Table 1.

Estimation results for the number of domestic visitors.

	2011	2012	2013	2014	Total
Scenario 1	13,434	10,682	15,671	13,903	53,690
Scenario 2	14,194	14,869	18,279	20,770	68,112
Observed number of domestic visitors	30,080	33,993	39,922	42,161	152,156

Note that the projection of the number of domestic visitors to Nazaré in the absence of the media campaign in scenario 1 is based on past information (2004–2009) and accounts for the coastal municipality trend. The projection in scenario 2 also takes into account the coastal municipality trend but excludes any spillover effect, as discussed in Section 3.

We observe a significant difference in the estimated number of domestic visitors to Nazaré depending on the different scenarios. The difference between the solid and dashed lines (scenario 1) corresponds to 53,690 domestic visitors for 2011–2014, while the difference between the solid and dotted lines (scenario 2) corresponds to 68,112 domestic visitors, respectively.

The greatest impact on the number of domestic visitors attracted by the Big Waves is obtained under the second scenario, indicating that a considerable drop in the number of domestic visitors to Nazaré would have occurred without the media campaign, when compared to the number of domestic tourists that would have been attracted in the first scenario.

We also test for the difference in the projected number of visitors in the absence of the media campaign by conducting t-tests for differences in means. The null hypothesis is that the means of the projected number of domestic visitors between scenarios 1 and 2 are not different from each other. The null hypothesis is rejected at a 10% significance level (p value = 0.06), suggesting the presence of a spillover effect.

International visitors

The results for international visitors are reported in Figure 8. The interpretation is similar to that of Figure 7. The solid line indicates the observed number of visitors in Nazaré and the dashed and dotted lines correspond to the constructed comparison groups under scenarios 1 and 2, respectively. Interestingly enough, the data on visitors (solid line) suggest that the Big Waves in Nazaré reversed in the following years the observed negative trend between 2008 and 2010. The estimated numbers of visitors for each scenario are presented in Table 2.

Figure 8.

Estimation results for the number of international visitors.

Table 2.

Estimation results for the number of international visitors.

	2011	2012	2013	2014	Total
Scenario 1	10,148	12,235	11,774	16,952	51,109
Scenario 2	12,532	14,850	16,228	21,222	64,832
Observed number of international visitors	28,006	27,257	31,434	35,500	122,197

The results from counterfactual analysis in Table 2 suggest that the Big Waves attracted additional 51,109 and 64,832 international visitors between 2011 and 2014, depending on the scenario. As with domestic visitors, we also test for the difference in the projected number of visitors in the absence of the media campaign by conducting t-tests for the difference in means. The p value for the difference between scenarios 1 and 2 indicates that they are statistically different. The results suggest that the presence of spillover effects in the case of international visitors is even more statistically significant since the p value is smaller (=0.00). In summary, the statistical tests comparing the observed data to the projected data for both domestic and international visitors indicate that the media campaign has significantly contributed to the recognition of the region (p value = 0.00 for all scenarios).

Economic impact of the big waves

In order to compute the impact of the media campaign in euros, we obtained an estimate of the average individual expenditures per trip for international and domestic tourists in Nazaré from 2010 to 2014 by conducting an online survey to managers of hotel establishments in Nazaré. The data obtained from this survey from five hotels (out of 11 in 2010) are shown in Table 3. The average individual expenditures per trip include all the payments at the hotel, including even payments for services to other companies such as car rentals, ticket sales for different activities, and so on. These data do not include expenditures outside the hotel establishments such as in souvenirs’ shops or restaurants, and can therefore be considered as lower bound estimates.

Table 3.

Average expenditure per visitor per trip in Nazaré (euros).

Year	International tourists	Domestic tourists
2010	68	51
2011	68	58
2012	74	68
2013	92	72
2014	92	72

The results related to the impact of the media campaign are shown in Table 4. The overall estimated economic impact of the Big Waves is about 7.91 million euros (scenario 1), and 10.08 million euros (scenario 2), in 2012 prices, for the period 2011–2014.¹⁴ As shown in this table, the largest estimates obtained are in scenario 2, in which the recent coastal municipality change in trend in tourism and the spillover effect of Nazaré are taken into account.

Table 4.

Estimated economic impact in euros.

	2011	2012	2013	2014	Total
Scenario 1	1,469,236	1,631,766	2,211,520	2,560,600	7,907,921
Scenario 2	1,675,428	2,109,992	2,809,064	3,447,864	10,081,267

To give a sense of scale, the total impact estimates from Table 4 are compared to the total revenues of local hotel establishments. The results are presented in Table 5. The estimated impact of the Big Waves ranges between 32.2% and 41% of the total revenue of hotel establishments for 2011–2014, depending on the scenario.

Table 5.

Contribution of the Big Waves to the local economy when compared to total revenues of hotel establishments in %.

	2011	2012	2013	2014	Average
% Change (scenario 1)	25.0	28.1	36.7	38.1	32.2
% Change (scenario 2)	28.5	36.3	46.6	51.4	41.0

Also note that the impact estimates obtained should be considered as lower bound estimates. First, the data on tourist arrivals do not account for those who informally rent apartments, rooms, bungalows, and so on. Second, the average expenditures used for the calculation of those estimates do not include expenditures outside hotel establishments. Third, Nazaré may still continue to benefit from this media campaign. Moreover, as mentioned above, the tourists attracted by the media campaign may also visit nearby municipalities, contributing to their economies. All these issues can be addressed in future research.

Public expenditures on the Big Waves

Besides estimating the revenues that can be associated with the media campaign, we also collected information on its costs (see Table A1 in the Online Appendix). For that purpose, we conducted face-to-face interviews to stakeholders responsible for promoting the Big Waves campaign in order to obtain information about the financial support provided by public and private institutions between 2010 and 2013 that sponsored the campaign. Since the private companies that invested have most likely also benefited from that campaign, by advertising and promoting their brands and products to Nazaré’s visitors, when accounting for the costs we consider only the expenditures incurred by the local municipality.¹⁵

Overall, the total reported expenditures related to Big Waves were 283,847 euros during 2010–2013 of which 26,948 euros were public expenditures, that is, investment of the local municipality.¹⁶ Even though public expenditures are less than the private ones, the involvement of the public sector in organizing events has the potential to attract visitors and businesses, as pointed out by Felsenstein and Fleischer (2003).

Conclusions

We contribute to the literature on impact evaluation by providing evidence of the successful experience led by the municipality of Nazaré in attracting a rising number of visitors in recent years namely, how an old fishing community can successfully promote its unique natural attributes by investing resources in making them visible to the world. Overall, the costs incurred with the Big Waves campaign were relatively small as compared to the estimated revenues obtained. The successful experience of Nazaré can be an example to the other coastal municipalities that face similar challenges and have unique or featured natural or cultural attributes that may attract visitors at different times of the year.

Figure 9 shows the availability of different nature-related attributes in different municipalities, thus providing evidence of the spatial diversity of the region. The nature-related attributes are divided into two main groups namely, seascape and terrestrial landscape related ones (see the left and right parts of Figure 9, respectively). The seascape-related attributes include ocean and beach, waves (for different type of surfing), and marine-protected areas, while the terrestrial landscape-related attributes include forest and vegetation, fresh water system (including beach), wetlands, hills and bare rocks, caves, and terrestrial-protected areas. The majority of coastal municipalities offer beaches, marine-protected areas, and waves. Also, the majority of municipalities present at least four terrestrial landscape-related attributes, out of six. Thus, we may conclude that there may exist potential in the region to be developed in the future.

Figure 9.

Seascape (left part) and terrestrial landscape (right part) attributes. Source: Authors’ construction.

Not only can seasonality be reduced by increasing the number of visitors in low season, but adjacent regions can also benefit from positive spillover effects. Seasonality is an important concern of EU policy makers (see Eurostat, 2016), and Portugal is no exception. As reported in Eurostat (2016), the number of nights spent in 2014 during the peak month (August) was 4.9 times greater than the number of nights spent in the off-peak month (January). Among the 28 European countries (from highest to lowest), Portugal is ranked in the eighth position, after, for instance, Denmark, Italy, and France. In the case of Nazaré, visitors are attracted by beaches in the region and all related recreational activities (generic interests) in the summer, as in other coastal regions in the country. However, by attracting visitors with specific interests, the worldwide recognition of the big waves contributed positively to reduce off-peak unused capacity of the hotels in Nazaré, as the waves occur only in the autumn–winter period. As shown in Figure 10, the annual number of nights (solid line) in Nazaré increases, while the share of nights spent (dashed line) in July–September decreases. This suggests that tourists are visiting Nazaré for the whole year and not only in high season. Therefore, we may conclude that capitalizing on specific and/or unique local features may help to diversify the touristic offer, increasing the number of visitors throughout the year.

Figure 10.

Share and number of nights in hotel establishments in Nazaré.

Finally, we identify possible avenues for future research. First, even though the existence of attractive attributes in a region is crucial, there are other factors that may influence the capacity of the municipalities to exploit their potential, such as the availability and quality of the infrastructure network and the institutional framework, namely related to the public/private sector interaction. Second, note that the short distances between the municipalities in the case of Portugal make policy coordination even more important in order to avoid wasting resources by competing against each other. Although the desirable degree of policy coordination across the different municipalities to increase efficiency when promoting adjacent destinations can be high, it also may contribute to weaken accountability of municipalities toward the citizens under their jurisdiction. While these are important political issues, they are beyond the scope of this article. Moreover, in order to increase the chances of success, it is crucial to understand how visitors value different local attributes, that is, their preferences. A better understanding of tourists’ preferences in their whole diversity would definitely contribute to increase efficiency when promoting those destinations.

Supplemental material

Supplementary_material - On nature’s shoulders: Riding the big waves in Nazaré

Supplementary_material for On nature’s shoulders: Riding the big waves in Nazaré by Maria A Cunha-e-Sá, Rita Freitas, Luis Catela Nunes, and Vladimir Otrachshenko in Tourism Economics

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors gratefully acknowledge financial support from Fundação Calouste Gulbenkian, FCT –Fundação para a Ciência e a Tecnologia under the project Ref. UID/ECO/00124/2013 and POR Lisboa under the project LISBOA-01-0145-FEDER-007722. This research work was developed in the context of the project entitled “The Economic Valuation and Governance of Marine and Coastal Ecosystem Services (MCES).” Vladimir Otrachshenko wishes to thank financial support from Fundação para a Ciência e a Tecnologia (FCT), Portugal (SFRH/BPD/122946/2016).

Supplemental material

Supplementary material for this article is available online.

Notes

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