Eurostat CROS

  • Sign in with the EU Login
  • More about the EU Login

Tourism Satellite Accounts (TSA) - 2024

Tourism Satellite Accounts - in Europe 2019 edition - Europa EU

  • Download HTML
  • Download PDF

Tourism Satellite Accounts - in Europe 2019 edition - Europa EU

  • IT & Technique

Building profitable customer relationships with data mining - Herb Edelstein, President Two Crows Corporation

  • Uncategorized

Ghost City Extraction and Rate Estimation in China Based on NPP-VIIRS Night-Time Light Data - MDPI

  • Hobbies & Interests

Package 'shazam' September 20, 2018 - CRAN.R-project.org

  • World Around

Data Communities on AT&T Network 3.0 Indigo - The Policy ...

  • Arts & Entertainment

Unemployment Rates During the COVID-19 Pandemic - Updated August 20, 2021 - FAS ...

  • Current Events

Transparency, Reproducibility and Ethics (TRE) Policy September 2021 (Version 2) - 3ie

  • Government & Politics

Putting Data Science Pipelines on the Edge

  • Cars & Machinery

How to Make Your Word 2010 Documents 508-Compliant - Centers for Medicare & Medicaid Services "Making 508 Easy" Continuous Improvement Initiative ...

  • PDF FRONTPAGE

Sammenfatning

  • 1. Tourism in recent decades—growth and the economy

2. The importance of developing regional tourism satellite accounts

3. the history and role of tourism satellite account development, 3.1 opportunities and challenges in economic measurement using tourism satellite accounts, 3.2 constructing regional tourism satellite accounts.

  • 4. Guidelines and manuals for developing TSAs from major international organizations
  • 5. Nordic regional tourism satellite accounts—description and main tables by country
  • 5.1 Denmark

5.2 Finland

  • 5.3 Iceland
  • 5.6 Faroe Islands
  • 5.7 Greenland
  • 6. Expert statements on TSAs—advantages and disadvantages

6.1 Common Regional TSA accounting analysis and method for the Nordic countries

6.2 possible next steps in developing rtsas in the nordic region, 6.3 steps for developing a nordic rtsa, 6.4 comparable or independent rtsas in the nordic countries, appendix ii, about this publication.

  • PDF Back cover

Moreover, at around the same time, Nordic citizens had more opportunities to travel to sunny locations. For example, Danish tourism to Spain took off, enabled by technology and scheduled direct charter flights. Instead of traveling for days by bus back and forth, sunny destinations could now be reached in few hours. The sublime mountainscapes of Norway became a magnet, as did more remote attractions such as Cape North, and the range of rural tourism products widened over time (Müller, 2013). In the first and second decade of this century, tourism has grown steadily, albeit with regional variation, but in many cases, it has become an established sector of Nordic economies in terms of both employment and revenue.

While the Nordic model of regional economic impacts reflects its time, this urban–rural, domestic inbound–outbound mobility dynamic has always been associated with the economics of tourism. Prior to 2000, the two most common methods used to understand the impact of tourism, the Nordic Model and the input–output method, were advocated because they linked supply and demand and focused on the money flow from tourists to tourism enterprises, including circulation within the tourism supply sector. However, these methodologies were subject to criticism, as they gave little consideration to the contribution of local factors to the volume and quality of tourism (Paajanen, 1997). Tourism satellite accounts (TSAs), with their conceptual framework and manual, gradually became the internationally acknowledged approach to understanding the economic impact of tourism (United Nations Statistical Office, 2010; Frechtling & Smeral, 2010).

  • ^ ”Sommargästerna åt sin sida framhöll att de bidrog till kustorternas bästa genom att de gav ett bättre kundunderlag åt affärarerna vid kusten” (DN 7.October, 1978).

Tourism has played a growing role in the last two decades in the economic development of many Nordic countries until the Covid-19 pandemic hit and the tourism sector suffered from the effects of reduced travel desire and restrictions. After relief, tourist influx will resurrect and again affect local economies around the Nordic region. Tourism has economic effects.

When people travel, they pay for goods and / or services such as accommodation, food, souvenirs and activities. They may be shopping in preparation for their trip or as part of their return trip. Before, during and after the trip, their expenses are directly related to the tourism activity which generates profits, rent, tax revenue, investment and employment. Tourism also has indirect economic effects, for example on hotels, restaurants and other service providers who shop from other companies to meet demand from tourists or by employees in the tourism industry using their income to pay rent, insurance or merchandise. These trickle-down effects seep down and support the economic development of regions where tourism develops and flourishes.

Exact quantification of the contributions and costs associated with tourism is challenging for many different reasons. The Nordic countries have individually (except the Faroe Islands and Greenland) prepared satellite accounts to get an overview of the economic effects of tourism, but to varying degrees worked with regional satellite accounts which can provide insight into the difference in the importance of tourism's economic contribution to regional economies. That is what this report is about.

We have prepared a report whose purpose is to introduce the potential of Regional Tourism satellite accounts and describe their function and weaknesses in estimating the effects of tourism on regional economies. We also assess whether there are preconditions for developing a joint Nordic tourism account by virtue of the recognized satellite methods. Part two of the report contributes with an overview of available tourism statistics and the status of the regional tourism accounts today in the individual Nordic countries. On the basis of this overview, we draw up perspectives for future development opportunities associated with using regional tourism accounts in the joint collaboration on tourism development in the Nordic countries in expert opinions in collaboration with Åland's research and statistics bureau ÅSUB and Center for regional and tourism research, CRT, Bornholm.

Turisme har spillet en voksende rolle i de to sidste årtier i mange nordiske landes økonomiske udvikling, men efter at pandemien Covid-19 ramte har turismesektoren lidt under effekterne af minsket rejselyst og restriktioner. Forhåbentlig vil turismen kunne genrejses og igen have positive effeter for lokaløkonomien rundt omkring i den nordiske region og med den også de mange afledede økonomiske effekter af turismen.

Når folk rejser køber de varer og/eller tjenester som for eksempel overnatning, mad, souvenirs og aktivitieter. De handler måske ved forberedelsen af deres rejse (f.e. tasker, tøj og udstyr) eller i forbindelse med returrejsen. Før,under og efter rejsen er deres udgifter direkte forbundet med turismeaktivitieter som genererer direkte indtægter til virksomhederne, skatteindtægter til det offentlige, investeringer i nye strukturer og beskæftigelse. Turisme har også indirekte økonomiske effekter, for eksempel på hoteller, restauranter og andre tjenesteydere som handler i andre virksomheder for at møde efterspørgselen eller ved at ansatte i turismebranchen anvender sine indkomster til at betale leje, forsikringer eller handelsvarer. Disse trickle-down effekter diffunderer ud i andre sektorer og støtter den økonomiske udvikling i regioner hvor turismen udvikles og florerer. 

En konkret kvantificering af bidragene og omkostningerne forbundet med turisme er udfordrende at beregne af forskellige årsager. De nordiske lande har hver for sig (foruden Færøerne og Grønland) udarbejdet satellitregnskaber for at få overblik over turismens økonomiske effekter, men kun i varierende grad arbejdet med regionale satellitregnskaber som kan give indblik i forskellene mellem turismens økonomiske bidrag til de enkelte regionale økonomier. Nærværende rapport belyser dette. 

I rapporten er formålet at analysere Regionale Turisme satellitregnskabers potentiale og beskrive deres funktion og svagheder i estimeringen af turismens effekter på regionaløkonomien. Vi ser også på om der er grobund for at udvikle et fælles nordisk turismeregnskab med de anerkendte metoder for satellitregnskaber. Rapportens anden del  bidrager med en oversigt over tilgængelig turisme statistik og de regionale turismeregnskabers status i dag i de enkelte nordiske lande. På baggrund af denne oversigt giver vi perspektiver for fremtidige udviklingsmuligheder ved at anvende regionale turismeregnskaber i et nordisk samarbejde. Perspektiverne baserer sig på ekspertudtalelser fra både Ålands forsknings og statistik bureau og Center for regional og turisme forskning Bornholm som hver især udvikler regionale turismeregnskaber.

1. Tourism in recent decades—growth and the economy

This report provides an account of the increasing importance of tourism as an economic sector in most countries in the past two decades by considering data availability in the Nordic countries when it comes to describing tourism growth in the past 20 years and ways to measure economic impacts.

Prior to the coronavirus disease 2019 (COVID-19) pandemic, tourism had been one of the fastest growing economic sectors in the world over the past two decades (UNWTO, 2020). The Nordic countries were part of this trend, and tourist numbers increased enormously in some locations. The boom has offered both challenges and opportunities for the Nordic region. The challenges include the risk of environmental damage, deteriorating infrastructure, pollution, overcrowding and increased rents and property prices in popular areas (see Bogason, Karlsdóttir & Broegaard, 2020), whereas the benefits include job creation and incomes for the local economy in tourist areas (Jones & Munday, 2004). The question of how to manage tourism to benefit from its opportunities while limiting the negative consequences will be high on the agenda as the pandemic prompts a re-examination of the feasibility of tourism development (Ionnaides & Gyimóthy, 2020).

Tourism offers opportunities for rural areas in the Nordic Region facing population decline and job loss. In some of these regions, increased tourism may create valuable jobs, provide resident populations with new economic perspectives and prevent negative development spirals with the declining and ageing population (Almstedt, Lundmark & Petterson, 2016). At the same time, the strong seasonality of tourism flows, the prevalence of low-paid service jobs in the tourism sector and capacity constraints on capital and labour constitute particular challenges in these areas (see discussions by e.g. Kauppila et al., 2009; Saarinen, 2003; Muller, 2013). While tourism is an increasingly important topic in regional development strategies, there are not always sufficient data and other quantitative evidence to estimate the economic cost and benefit returns comprehensively. Before the COVID-19 pandemic, this was the situation in the Nordic countries and the autonomous regions.

The local economic effect of tourism in Denmark was considerable, in that tourists spent a total of 132.5 billion DKK in 2018, and tourism returns created around 169 thousand jobs the same year (VisitDenmark, 2020).

In Norway, tourists spent 186 billion NOK in 2018 and tourism created 7.1% of total employment (SSB, 2020). In Sweden, foreign visitors’ spending generated 306 billion SEK,  or 33% of the total consumption in the country in 2019 (for explanation of the consumption calculations see Cañada 2013, p.42-43). The export value of tourism was 100 billion SEK and tourism provided employment for 126 thousand people in the tourism sector (Tillväxtverket/Swedish Agency for Economic and Regional Growth and SCB, 2020).

In 2018, tourism employed 142 thousand people in Finland, with regional variations. Areas outside of the most populous urban areas accounted for over 57 thousand jobs (VisitFinland, 2020a; Statistics Finland, 2020). North Ostrobothnia and Lapland had the most people employed in tourism industries relative to the regions’ working-age populations. The numbers of passengers at Finnish airports decreased by 91% in late 2020, while domestic tourism in relation to accommodation nights by residents only decreased by 15% (Statistics Finland, 2020). While tourism rose in terms of numbers of foreign arrivals before 2020, travel in 2020 was characterised by residents holidaying at home in the summer.

Tourism in Iceland has increased enormously during the past decade. Between 2010 and 2016, the number of tourist arrivals more than tripled (Mandle 2018), peaking in 2018 at over 2 million visitors. By the end of 2019, 852 companies in rural Iceland (Landsbyggð) had built their economy on tourism and 9707 people were in full-time tourism work (of a total of 26,000—aviation not included). However, debt was on the rise and the prospects of economic returns from tourism were declining, although tourism generated at least one third of the income of the national economy. By late 2020, over 12% of the working-age population was unemployed, the highest number since the establishment of the republic.

Åland's economy is highly dependent on tourism from ferry traffic in the Baltic Sea. Tourism is also one of Åland’s most important export industries, with a total export value of EUR 330 million. Every fifth Ålander in the private sector works in tourism, and tourism indirectly contributes to jobs in industries that subcontract to the tourism industry (VisitAland, 2019). With the impact of COVID-19, Ålanders faced the highest unemployment rate in many decades with the highest rate at 13% in early summer 2020. In the autumn it had declined slowly to around 9.3-9.9% by end of that year. Youth unemployment (under 25 years) is highest by rate and as the pandemic situation extends long term unemployment is becoming a significant challenge (ÅSUB, 2020, ÅSUB 2020a). Tourism has risen in the Faroe Islands as it has for Greenland, and has increased in economic importance in both autonomous regions.

The COVID-19 pandemic has hit the tourism sector across co-operating Nordic regions and countries hard, and in some cases, the economy has plummeted, with rising unemployment. Owing to the sudden shift in tourism because of the COVID-19 pandemic, impacts, travel restrictions and hindrances to the country-level development of tourism have been in flux (UNWTO, 2020; OECD, 2020), requiring new knowledge. Given this situation, analyses of the economic effects of tourism are as relevant as ever in the Nordic context.

We ask: is it feasible to develop a common set of indicators measuring economic impacts on tourism on a regional level and how should we do it with the most commonly used and acknowledged methods at hand?

Even if the tourism sector and tourism businesses are severely hit, some prospects should not be forgotten. One such prospect is that while urban tourism, accommodation and restaurant services have encountered hardships during this period, the flow of domestic travellers has breathed life into more remote destinations and less densely populated places. However, as mentioned above, there is insufficient quantitative evidence to estimate the precise costs of investments and benefits of economic returns from increased tourism.

Regional tourism satellite accounts (RTSAs) may fill some of these knowledge gaps. RTSAs have become an established tool used internationally to measure the impact of tourism on regional economies. RTSAs can measure supply and demand generated by tourism in various sectors and their contribution to macroeconomic indicators such as gross domestic product (GDP) or employment.

Against this backdrop, this report is intended first to introduce RTSAs and describe their function, strengths and weaknesses in estimating the impact of tourism on regional economies (a comparison with other methods is provided in the Appendix). The second part provides an overview of RTSAs and tourism statistics currently available in the Nordic region. Based on this overview, in the third section, perspectives for future development and the use of RTSAs in the Nordic Region are discussed in expert statements in cooperation with ÅSUB and CRT.

This project was built on original work by the Nordic Working Group for Sustainable Regional Development in the Arctic (2013–2016) but evolved in discussions between members of the Nordic Thematic group on Sustainable Rural Regional Development (2017–2020). This group described key developments in tourism management in the northern parts of Norden. These include analyses of how these areas have targeted key tourism segments, developed priorities and organized destination management. This project extends this analysis and investigates the role and impact of tourism on rural areas across the Nordic region (Bogason, Karlsdóttir, & Broegaard, 2020).

  • ^ A ‘usual environment’ is defined as ‘the geographical area […] within which an individual conduct his/her regular life routine’ (Frechtling, 2010).

TSAs were first developed and used in the 1980s and 1990s. Canada was a pioneer, developing one of the first TSAs in 1994. Other countries followed, including France, New Zealand, Austria, Poland, Singapore and Sweden (Frechtling, 2010; Jones et al., 2009; Rütter & Berwert, 1999; Smeral, 2006).   However, these statistical/accounting instruments are not analytical models per se. They are used in various TSA approaches and must be continuously updated because no widely accepted and common approach has been provided.

Over time, actors in several countries and institutions, such as the World Tourism Organisation (WTO, now the UNWTO) and Organisation for Economic Co-operation and Development (OECD), elaborated and refined the approach until a common methodological framework and standard could be agreed upon. This process culminated in 2008, when the United Nations Statistical Commission, UNWTO, OECD and Eurostat adopted two documents that define the core concepts, classifications and accounting rules for constructing a TSA—Tourism Satellite Account: Recommended Methodological Framework (2008 TSA:RMF)—which constituted a guideline for statistical offices to develop TSAs as well as RTSAs. This document plays a central role in most countries, as does the 2008 document International Recommendation for Tourism Statistics (see also Frechtling, 2009). These two documents now form a reference framework that countries and regions can use to compile tourism statistics and develop TSAs (Frechtling, 2010; for a recent overview of national-level TSAs in Europe, see Eurostat, 2017). Canada, Australia and Denmark are among the pioneers in applying these at the regional level (UNWTO, 2013). In addition to Canada and Australia, the Nordic countries developed TSAs or RTSAs earlier than many other industrialized countries.

TSAs are a static set of accounts to measure the size or configuration of the tourism sector (i.e. a distinctive set of activities in which visitors participate) in an economy. They are designed to complement the System of National Accounts (SNA), where the term ‘satellite is derived from Kronenberg (2014) and Frent (2016). In other words, a TSA measures the direct contribution of a predefined tourism industry to the overall economy in a manner consistent with the SNA. There are also transport satellite accounts, health satellite accounts and environmental satellite accounts (SCB, 2018; Eurostat, 2020).   The term ‘account’ refers to the characteristics of a TSA, including a set of tables that record transactions, sources and uses of resources by institutions (e.g. households) and sectors.

Tourism plays an increasingly significant role in the economic development of many Nordic regions. Despite the sudden collapse of tourism because of the COVID-19 pandemic, it is likely to rise again and have a significant impact on local economies in the Nordic region. When people travel, they pay for goods and/or services such as accommodation, food, souvenirs and activities. They may also buy goods or services in preparation for their trip (e.g. suitcases) or on their return (e.g. to replace goods lost during the trip). In all three cases, their expenditure is directly linked to tourism activity, which generates profits, rent, tax revenue, investment and employment (Frechtling, 1999, 2009). Tourism has also indirect economic effects, for instance, on hotels, restaurants and other service providers purchasing from other companies to meet tourist demand or by having local employees of tourism companies spend their salary on rent, insurance or retail goods (Jones & Munday, 2004). These trickle-down effects support economic development in tourist regions.

Exact quantification of the contributions and costs of tourism is challenging for several reasons. First, precise data are not always available (Jones & Munday, 2004). While the productivity of sectors such as agriculture or manufacturing can be measured based on output, tourism is more appropriately determined by demand (Smeral, 2006; Madsen & Zhang, 2010). Furthermore, while other sectors can be defined as distinct industries, tourism is not a discrete and separately measurable industrial sector. Instead, a range of goods and services produced by a range of sectors are consumed by tourists (Rütter & Berwert, 1999; Jones et al., 2009; Smeral, 2006). Many of these may also be consumed by locals (Smeral, 2006). Conversely, many goods and services consumed by tourists, such as clothing, groceries and books, may not have been produced specifically for this target group. The economic impact of tourism on regional development is therefore difficult to grasp and can easily be estimated incorrectly (Jones & Munday, 2004).

To assess the economic effects of tourism, different methods have been developed and used by tourism researchers, including impact models, cost–benefit models, social accounting matrices (SAMs) and computable general equilibrium (CGE) models, each with its own strengths and weaknesses (see Frechtling, 2009; Madsen & Zhang, 2010; Rossouw & Saayman, 2011; and Dwyer et al., 2007). The Appendix provides a brief account of various applied methods. However, in recent years, TSAs have been increasingly used as the standard tool to measure the direct economic contributions of tourism (Cañada, 2013; Dwyer et al., 2007).

SNAs can be thought of as a series of input–output spreadsheets listing the various sectors or industries that comprise the economy, the commodities produced and their annual value. Other spreadsheets list the annual value of the commodities consumed by each industry. A third type of spreadsheet lists private and public demand, investment and consumption (Smeral, 2006). TSAs can be considered to be a subset of these spreadsheets that ‘claim’ some of the goods and services recorded in the SNA for tourism (Pham & Dwyer, 2013). Hence, TSAs identify industry outputs that are consumed or purchased for tourism as well as their contribution to key macroeconomic indicators such as GDP, national income and employment (Frechtling, 2010; Jones et al., 2009). In this way, it is possible to evaluate the role of tourism in various industrial sectors and the overall economy of a country and to analyse its links with other economic activities (Dwyer et al., 2007; Smeral, 2006; Jones & Munday, 2004). TSAs also facilitate international comparisons of tourism activities and allow changes to be tracked over time (Dwyer et al., 2007, 2008; Frechtling, 1999). TSAs are usually based on industry data, input–output tables in the SNA and/or visitor surveys (Pham & Dwyer, 2013).

The role and uses of RTSAs may be as follows (Laimer, 2017). They help to benchmark the success of tourism policies, can provide a basis on which to evaluate tourism development in relation to the rest of the economy, work as fact base for tourism policy issues and can serve as an initial basis on which to justify and subsidize tourism activities. Most importantly, they provide data on various aspects of tourism.

According to this established reference framework, a TSA should consist of 10 tables, six of which constitute the core of each TSA. The first four tables measure tourist consumption (inbound tourism expenditure, domestic tourism expenditure, outbound tourism expenditure and internal tourism consumption), the fifth measures the output of tourism industries and the sixth connects the previous ones and estimates the gross value added by each tourism supply industry. The four remaining tables measure employment in tourism industries, investment in productive capital, collective tourist consumption and tourism flows/characteristics of enterprises (Cañada, 2013). Because of its value in analysing the economic impact of tourism, increasing efforts have been made in recent years to adapt the TSA methodology for sub-national regions (hereafter, regional TSAs or RTSAs).

The input–output structure of TSAs is not without challenges, in particular, when they are applied in a regional context. First, extensive data and statistical capacity are required for their construction, and these are not always readily available (Cañada, 2013; OECD, 2016). Many tourism-related activities may be undertaken by very small businesses which may not always be legally required to register detailed business accounts. Owners of micro-businesses may also not always explicitly draw or register a salary from their work, which may hamper endeavours to assess tourism-related labour inputs and outcomes. Reliable statistics for the construction of TSAs may also be delayed, when timeliness is usually of crucial importance for users (OECD, 2010). Second, not all tourist activities may be easily assigned to a specific region. For instance, if tourism services are provided by central governments or by multinational or multiregional companies, it may be difficult to assign transactions or outputs to a specific territory (Frechtling, 2009, 2010; Cañada, 2013). Third, tourism and hence employment opportunities may be seasonal, and labour statistics do not always reflect this (Jones et al., 2003). Some of these data gaps can be filled, for instance, through tourist surveys, but these may be costly and time consuming to develop and implement (Jones & Munday, 2004).

Finally, TSAs do not capture the full impact of tourism on a region. For instance, the indirect or intermediate economic effects of tourism, such as those triggered by the delivery linkages in the economy, are not typically included in a TSA (Smeral, 2015). Importantly, TSAs also do not usually measure the environmental or social costs of tourism. For a full appreciation of the effects of tourism on regional development, these non-economic effects must also be considered. Modelling approaches can be used to extend TSAs and capture more fully non-market commodities such as carbon emissions or natural resource consumption, but these are methodologically more challenging and demanding in terms of both time and cost (Jones & Munday, 2007; Madsen & Zhang, 2010; Frenţ, 2018). Whereas the RTSA tables provide a benchmark for the current situation and aid in the description of historical development, model analyses are needed to make ex-ante calculations of future development. With the modelling tools, all kinds of ‘what if’ questions can be studied. Thus, TSAs have a limited role in tourism accounts themselves because they must be combined with regional accounts, input–output or CGE models to analyse different policy options (for a brief descriptions of data requirements and limitations and the possibilities of various other methods for the economic impacts of tourism, see the Appendix).

Figure 1. TSA table requirements (adapted from Frechtling, 2010).

The role of RTSAs can be problematized. The clear advantages of a satellite account are that it supplements the national accounts and gives detailed accounting of one specific area, such as tourism and the environment. The disadvantages are that it is costly and the data requirements are very high. Nonetheless, TSAs have many advantages : they are relatively straightforward to interpret if linked to key economic indicators, so they are easy for policymakers, national tourism organizations, statistical offices, businesses and other actors to use (Jones et al., 2003). Especially in depopulated or economically challenged regions, there can be value in understanding the contribution of tourism to economic development and to resolving underemployment issues. RTSAs could also assist comparisons of similar regions and show the benefits of tourism (Frechtling, 2009). TSAs can identify particularly profitable types of tourist activities, which could then be promoted by policy initiatives (Frenţ, 2018; OECD, 2010).

The top-down approach involves regionalizing a national TSA. Key results from national TSAs must be broken down and allocated to different regions. For instance, the allocation could be based on survey results, a key indicator or statistics that can be disaggregated to the regional level. The advantages of this method are that it can be undertaken at low cost, in particular, if good-quality data and/or business, tourism or household surveys that can easily be regionalized are available. RTSAs that rely on such statistics may also be relatively easy to update when new data become available. If the approach includes all regions of the country, it can also produce results that are comparable and consistent. Owing to the structure and data requirements of such an approach, national statistical offices should be involved in the process of regionalizing a national TSA.

Challenges may arise if centrally collected production and/or consumption data cannot be easily allocated to specific regions. Moreover, because a central set of definitions and/or classifications will be used for the whole country, it may not always be possible to measure regional specificities adequately in terms of tourist activities or consumption patterns (Jones et al., 2009). Therefore, the results of the top-down approach may be less useful to local policymakers and stakeholders (Jones & Munday, 2010).

The bottom-up approach can avoid such conceptual shortcomings. An RTSA is developed for a specific region. One of the main advantages of this approach is that it can be tailored to the characteristics and specificities of tourism activities in that region. For instance, regional surveys that provide input to the RTSA can be tailored to specific policy interests and regional circumstances. The downsides and potential barriers to the bottom-up approach are that it requires large amounts of data and can cost considerable time and money. Its results may also not be directly comparable with those of other regions in the same country or abroad (Jones et al., 2009). Therefore, Cañada (2013) stresses that the national perspective and connection to the country’s overall TSA framework should always be retained and indeed be ‘an obligatory reference point for regional TSAs’ (Cañada, 2013, p.5).

• internal tourism consumption, • production accounts of characteristic industries, • supply and internal tourism consumption, • employment in the tourism industries, and • gross fixed-capital formation of tourism industries.

  • ^ Cañada (2013) refers to these as the ‘interregional approach’ and the ‘regional approach’, respectively.
  • ^ See also Jones and Munday (2010) for a simplified approach to constructing RTSAs where regional input–output tables are not available.

4. Guidelines and manuals for developing TSAs from major international organizations

The UNWTO (United Nations World Tourism Organization) is an intergovernmental organization with a secretariat based in Madrid, Spain. The UNWTO has 159 member states, six associate members, two observers and over 500 affiliate members worldwide. The secretariat is led by the Secretary-General and organized into departments covering issues such as sustainability, education, tourism trends and marketing, sustainable development, statistics and TSAs, destination management, ethics and risk and crisis management. Since 1999, the UNWTO has published reports on the conceptual framework of TSAs. To provide a sound basis for the international comparison of the economic impacts of tourism, the 1999 publication included comprehensive recommendations for countries wishing to implement TSAs. TSAs were presented as a tool for anyone interested in the economic importance of tourism despite the development of many other methods of measuring economic impacts. It included the basic system of classifications, general guidelines, definitions, tables and aggregates linked to the standard tables of the United Nations System of National Accounts. This ongoing TSA process of measuring the economic importance of different segments of tourism entailed consideration of the information sources and methods required to include employment (UNWTO, 2008). In 2014, the UNWTO held a global meeting on the application of RTSAs following the publication of methodological recommendations (Cañada, 2013).  

It has been consistent in recommending a set of 10 summary tables of underlying data:

  • inbound domestic tourism and outbound tourism expenditure,
  • internal tourism expenditure,
  • production accounts of tourism industries,
  • gross value added (GVA) and gross domestic product (GDP) attributable to tourism,
  • employment,
  • investment,
  • government consumption, and
  • non-monetary indicators.

(TSA data provide a better understanding of the place of tourism in an economy and enable a range of economic analyses (see UNWTO, 2008). For example, it is possible to apply economic modelling techniques (such as input–output analyses) to TSA data to estimate the indirect and induced effects of tourism in an economy.)

The principles of the Tourism Satellite Account: Recommended Methodological Framework 2008 (United Nations, 2010) are mostly designed for the national level and thus have limitations when applied at the regional level. The UN statistical office was thus part of this development in parallel with the UNWTO.

The OECD and Statistical Office of the European Communities (Eurostat) co-operated with UNWTO and UN statistical office on the recommended methodological framework in the 2008 publication (UNWTO, 2008). Eurostat disseminates national results for a set of key TSA indicators for countries in the European Union and European Free Trade Association that have compiled TSAs in recent reference years. The most recent publication was a follow-up of the 2016 Tourism Satellite Accounts in Europe (Eurostat, 2019).

The Nordic model was stipulated by the Nordic Council of Ministers and used for the evaluation of the economic impacts of tourism in the Nordic peripheries (Rinne & Saastamoinen, 2005; Saarinen, 2003). Only older tourism literature refers to it and mostly from Finland, so it has not been widely applied for over 15 years in the Nordic region. The strength of this input–output model with direct, indirect and induced income, as well as employment impact at the local or regional levels, was that it was developed to track income leakage. Why this model was abandoned remains unclear. The most likely reason is that TSAs were established as the international standard for calculating the economic impacts of tourism (Frechtling & Smeral, 2010)  and once they had been adopted in individual countries and gradually more countries followed, it became the standard.

One of the shortcomings of these tourism-related economic impact approaches and their relevance in current times is that they do not really address how patterns of consumption (tourism demand) and production (tourism supply) affect the environment. In recent years, Eurostat has been involved in developing methodological frameworks (Eurostat, 2020), and the Swedish Statistical Bureau is developing a link between TSAs and the environment (SCB, 2018).

In the following section, we summarize the developments towards TSAs and RTSAs in each Nordic country and region. In the final section, these efforts are evaluated and recommendations for next steps are provided in two expert statements that have been combined into one.

5. Nordic regional tourism satellite accounts—description and main tables by country

This section summarizes the main TSA studies and datasets available in each country. Particular emphasis has been placed on identifying endeavours towards the calculation of RTSAs in Nordic countries.

The studies and data sources presented below were obtained through the following strategies. For each Nordic country and region (the Faroe Islands, Greenland and Åland), a search on Google.com and Google Scholar with the keywords “name of country/region + tourism satellite account” was conducted to identify the academic and grey literature on TSAs. In addition, the webpage and online databases of the national statistical institute of each country and region were searched for relevant statistics and datasets on tourism and/or TSAs. In some countries, relevant datasets were not available on the statistics institute databases, but on the databases of national tourism organizations; these were consulted as well. All of this research was conducted in English; in the case of Sweden and Åland, some publications written in Swedish were included. The search was also conducted in the second part of June 2019 and May 2020 with Danish and Norwegian as the search languages.

5.1   Denmark

Among the Nordic countries, Denmark currently appears to have the most advanced system and the most extensive experience in calculating RTSAs. The Institute for Local Government Studies (AKF), the Danish Tourism Board, VisitDenmark and Statistics Denmark developed the first national-level TSA for the reference year 2000 in 2003/2004. The first RTSAs for the period 2000 to 2004 were published in 2006. In the same year, the Centre for Regional and Tourism Research (CRT) assumed responsibility for compiling TSAs from the AKF and now collaborates with VisitDenmark (Eurostat, 2009). Since then, RTSAs have been published on VisitDenmark’s webpage on a yearly basis. These are consistent with the Danish national accounts and in line with international documents and recommendations for the construction of TSAs (Zhang, 2019). Methodological changes and improvements have been made in recent years, so the RTSA results are not fully comparable over time.

The Danish RTSA uses the ‘bottom-up’ method. The RTSA is based on a regional model, LINE. The latter is an interregional macroeconomic CGE model based on a SAM framework (Zhang, 2001). The RTSA provides information on tourism consumption by categories of visitors, production accounts of different tourism industries and employment in the tourism industry at the municipal level, among others (Zhang, 2001, 2014). It can capture the direct, indirect and induced economic effects of tourism (Zhang et al., 2007). The RTSAs are based on statistics provided by Statistics Denmark (e.g. accommodation facilities, census data, national accounts data, regional production data, register data), as well as on a tourism survey, Tøbbe, conducted every 3 years (Zhang, 2019; Zhang, 2018; OECD, 2016). More than 10,000 visitors are interviewed in each survey round covering topics such as destination choices, consumption and satisfaction with their travels (VisitDenmark, 2018).

Statistics Denmark has published the following tourism-related datasets on its online database on hotels, holiday centres and youth hostels, holiday dwellings, camping sites, marinas and holiday and business trips (see Appendix 2 for the tables, indicator name, details and reference period). The available regional statistics are in almost all datasets on accommodation (hotels and guesthouses and holiday houses/cottages back to either 1992 or 2004, in some of the campsite statistics and on nights spent at marinas).   The following maps illustrate the results of RTSAs processed by CRT (Zhang 2018, 2019) for VisitDenmark (2018) on tourism consumption by region and economic importance in relation to GDP and employment..

According to the latest RTSA figures, the average job generation effect in Denmark was 1,700 full-time jobs per municipality, with great variation between municipalities (see Maps 4 and 5). This is calculated as total employment from tourism including direct, indirect and induced effects (VisitDenmark, 2019). As the maps above and TSA results show, a large share of tourism accumulates in a small number of municipalities. The 10 largest municipalities received 48% of tourism consumption. Århus and the Capital region are the largest recipients of tourism income, but coastal municipalities such as Varde, Ringkøbing-Skjern, Frederikshavn, Jammerbugt, Bornholm and Hjørring accounted for 32.8% of tourism consumption in 2018.

Statistics Finland and Travel Development Finland, Ltd., first published a preliminary TSA for 1999. After this first endeavour, Statistics Finland developed a consistent method for satellite accounts and produced final TSA tables for 1995 to 2001 (Statistics Finland, 2004). Since then, national-level TSAs have been published annually (Eurostat, 2009).

  • ^ Åland is not part of this survey. Accommodation statistics and a survey conducted by Statistics and Research Åland provide comparable information (Konttinen, 2006).
  • ^ Compensated business trips and free use of personal residences.

Table 1. Tourism Satellite Account Finland.

Finland has additional studies using other methods to study the economic impact of tourism. Paajanen (1997) worked on a method of economic impact analysis for tourism in the years around the turn of the millennium. That method was designed for local/regional environments where the analysis primarily served local tourism planning. In addition, Metsähallitus and Parks and Wildlife—the authority for managing national parks and other state-owned protected areas in Finland—estimates the socio-economic benefits of visits to national parks and protected areas. The authority does not use RTSAs for this purpose, but rather, a model originally developed for the US National Park Service and based on a visitor monitoring system and surveys (for more information, see OECD, 2016). Tohmo (2018) estimated the value of economic tourism in Central Finland with a regional input–output analysis. It is interesting that in recent years (since 2011), Finland has systematically published cultural satellite accounts that are also relevant to TSAs (Statistics Finland, 2020a). The results show that the share of GDP from cultural activities was 3.3% in 2018, which had decreased slightly (by 0.1%) from 2017.

5.3 Iceland

In addition, Frenţ (2014a) calculated TSA aggregates for Iceland as a whole (tourism gross fixed-capital formation and tourism collective consumption). According to these estimations, before the impacts of the COVID-19 pandemic were felt, the tourism industry had become a larger contributor to the Icelandic economy than the fishing industry, which is traditionally one of the core economic activities of Icelanders (Frenţ, 2018).

At the regional level, Rögnvaldsdóttir (2014, 2016) studied available tourism data for Þingeyjarsýslur (now Norðurþing), a region in northern Iceland with a population of approximately 4,800, with a focus on the effects of the inbound tourism of foreign visitors but did not take domestic tourism into account. Rögnvaldsdóttir consulted a range of available statistics for her studies, and conducted company interviews and an inbound visitor survey in the region during from 2013 to 2015. She estimated tourist numbers and overnight stays in the region, total turnover by tourism industries and tourist consumption in the region, as well as the indirect effects of tourism, employment and municipal revenues.

Rögnvaldsdóttir (2014) notes that according to Eurostat’s NUTS classification, the number of separate entities in Iceland is small. This is mainly due to population size—other European countries have a higher population density than Iceland, which has prompted a more detailed division of other territories into individual units. In Iceland, by contrast, the NTUS-3 classification only distinguishes between the capital area around Reykjavík and the rest of the country. At the LAU1 level, there are eight statistical units (regions) in Iceland and 74 municipalities at the LAU2 level. These differences in statistical classification between Iceland and the rest of Europe (including other Nordic countries) have considered in determining the appropriate geographic level for RTSAs to be calculated. The Tourist Board of Iceland has recommended distinguishing between five main tourist destination regions in Iceland (see Rögnvaldsdóttir, 2014).

  • ^ undefined

An overview of tables showing tourism statistics currently available on the online database of Statistics Iceland can be found in the Appendix. More specific statistical studies can be found on the website of the Icelandic Tourism Board, which is also responsible for the tourist survey. However, in recent years, analyses of economic prospects have relied more heavily on banks’ analytical units (Icelandic Tourism Board, 2020). As noted above, where data are available at the regional level, this has been highlighted in bold. In her study, Rögnvaldsdóttir (2014) concluded that the lack of regional data ‘makes statistical analysis of tourism at the regional level in Iceland difficult and expensive’. This conclusion still seems to hold. Frenţ (2013, 2014b) makes a series of recommendations to improve Icelandic statistics to meet international standards and provide better information on the tourism sector in Iceland.

In addition to the datasets (in the Appendix), Statistics Iceland has also published the results of a travel survey conducted by the Tourism Council from 2007 to 2018. Indicators include the number of tourists according to gender, age and household income, number, average length and main purpose of inbound and outbound trips, and types of accommodation. The survey was conducted among residents of Iceland only, so it does not include foreign tourists. Only a few of the available datasets include regional information (e.g. destination of inbound trips by region, domestic trips in each season, region and unit, type of transport for domestic trips in each season).

Statistics Iceland has published the number of people employed in the capital region and the rest of the country in workplaces such as hotels and restaurants, and for the whole country, in what it designates ‘characteristic tourism occupations’. Information on the numbers of employees each month are available from 2008 to 2020 in transport, accommodation and restaurants, motorized vehicle rentals, leisure and sport equipment rentals, travel agencies, travel planners and other booking services (Hagstofa Íslands, 2020). Owing to the unexpected cessation of tourism due to the COVID-19 pandemic, the Icelandic Tourism Council, in co-operation with KPMG, conducted a special analysis of the financial state of the tourism industry at the end of 2019 (Iceland Tourism Board & KPMG, 2020). That analysis revealed a rather bleak state of affairs in many tourism enterprises, declining economic returns from tourism and increased debt rates of larger as well as small-to-medium‐sized enterprises in the tourism industry. A resurgence of tourism, and hence income and jobs, remains uncertain.

5.4   Norway

Compared with other countries, Norway implemented international guidelines on the development of TSAs relatively early. The Statistical Office of Norway published TSAs from 1988 (Brændvang et al., 2001). Since then, several revisions of the national accounts system have been implemented, so the TSAs are not fully comparable over time. They are currently consistent with the national accounts system, aligned with international TSA standards and revised on an annual basis (Statistics Norway, 2019).

The Norwegian TSA builds on statistics from different sources, including Structural Business Statistics, accounting statistics, trade statistics, household consumer surveys, tourist expenditure surveys and labour statistics. The TSA takes stock of tourism consumption by domestic tourists (residents of Norway) and inbound tourists (non-residents of Norway). Business travel is also taken into account. The Norwegian TSA quantifies the supply of a variety of characteristic tourism products, in addition to output, value added, gross fixed-capital formation and employment in tourism industries (Statistics Norway, 2019).

Parts of the TSA concerning regional output, value added and employment in tourism industries are also published in some years. In 1997 and 2007, Statistics Norway published tourism consumption data for regions (Statistics Norway, 2019). In addition, the Norwegian Institute for Urban and Regional Research, Statistics Norway and the Institute of Transport Economics conducted a pilot project on RTSAs in Norway between 1999 and 2001. The results of this project were published in various reports, including one on the data, concepts, methods, and applications of RTSAs in Norway (Brændvang et al., 2001). In their project, the authors aimed to develop a simple simulation model to construct RTSAs for the Norwegian context. Brændvang et al. (2001) treated each county of Norway as a ‘small nation‘, to which they applied the principles of the national accounts and the national-level TSA. Their study focused on tourist consumption, which was understood to include all consumption in a county by non-residents (i.e. including residents of other counties of Norway). Brændvang et al. (2001) used existing regionalized national accounts for their study and built on the national TSA and tourist surveys. Tourist consumption as measured by the national TSA was broken down to the regional level by product according to various types of keys.

Table 2. Overview of outcomes from Norwegian national TSA 2020 (SSB, 2020).

Currently, the Statistics Norway database contains a section on ‘Tourism Satellite Accounts’ with the number of available datasets in 2018 last updated in 2020. Only two are available at the regional (county) level.

In addition to the above-mentioned datasets, Statistics Norway has published additional data and statistics in a section on ‘Tourism’, some of which are available at the regional (county) level. These encompass the following measures: nights in each type of accommodation—hotels, guesthouses and campsites—by guests’ country of residence, as well as structural business statistics on hotels and restaurants and accommodation and food service activities.

The Statistics Norway database also contains a section on ‘Regional accounts’ with indicators such as the number of people employed in each sector, gross fixed-capital formation or value added at current basic prices. Nonetheless, tourism is not included as a separate industry or sector in these tables. Only tourism-related sectors such as accommodation and food service activities appear (see an overview of the tables in the Appendix).

5.5   Sweden

The first TSA for Sweden was calculated in 1985, focusing solely on the supply side of tourism (Nordström, 1996). Later on, Nordström (1996) estimated consumption expenditures for the years 1992 to 1993, but focused only on internal visitors to Sweden. Statistics Sweden then started to produce national-level TSAs in 1995 at the request of the Swedish Tourist Authority. The authority wanted to have a more precise estimate of the contribution of tourism to the Swedish economy than the national accounts could deliver. Since the first publication of TSAs, some methodological changes have been implemented, partly in response to changes in international guidelines.

The Swedish Agency for Economic and Regional Growth (Tillväxtverket) is currently in charge of tourism industry issues in Sweden. On its behalf, Statistics Sweden has published national-level estimates concerning issues such as employment by industry and tourism value added to GDP on an annual basis since the mid-1990s (Tillväxtverket, 2019a). These are integrated with the Swedish national accounts system in line with international TSA standards. Accommodation statistics (including information on the number of nights spent and revenue from the accommodation sector) have been published on a regional (Län) level in several publications (for instance, see Tillväxtverket, 2019b). Full regional TSAs are not currently available, but Kronenberg et al. (2018) recently published a tourism input–output analysis for the Jämtland region (see also Junkka, 2009 for an early RTSA study on Jämtland). Tillväxtverket is working on further harmonization of touristic consumption data gathered from traveller surveys, thereby facilitating future work on RTSAs (correspondence with Frederik Junkka, 2019). This means that some calculations have been modified in the 2019 TSA and consumption now includes taxes (Tillväxtverket, 2020b). Open data is available in ten tables from 2019, 2018 and 2017 (Tillväxtverket. 2020).

Table 3. Overview of outcomes from Swedish national TSAs 2017, 2018 and 2019. Source: Tillväxtverket & SCB, 2020.

5.6  F aroe   Islands

TSAs have not yet been published for the Faroe Islands. On the database of the Statistical Office of the Faroe Islands, a limited range of tourism statistics are available under the category of ‘Accommodation’. These consist of several datasets on overnight stays by type of accommodation, region, purpose and/or country of residence (Hagstova Forøya, 2020). These are the only specifically tourism-related statistics that could be identified besides more general calculations of the export value of services in Búskaparfrágreidingar, the quarterly economic outlook reports by the Economic Council of the Faroe Islands (i.e. Búskaparáðið, 2018).

5.7   Greenland

Greenland has not yet published a TSA account (VisitGreenland, 2017). Nonetheless, the Statistics Greenland database contains a ‘Tourism’ section with statistics that offer insights into the sector; these are summarized below. Only the datasets on ‘overnight stays’ provide information at the regional level (highlighted in bold). Statistics on flight passengers and cruises are available for all individual airports and ports, respectively, in Greenland.

5.8   Åland

Statistics and Regional TSAs for Åland are included in the database of Statistics Finland and VisitFinland (see section on Finland above). In addition, the Statistics and Research Åland (ÅSUB) database provides several tourism-related datasets, which are summarized below. Every 5 years, ÅSUB also publishes a report on the socio-economic role of tourism in Åland. This includes information and data on the consumption and expenditure of different tourist groups, as well as calculations of the share of tourism in Åland’s economy and its effect on employment. The latest report is available for 2018 (ÅSUB, 2019).

Åland has also published SAMs for the years 2007, 2010 and 2015, in which tourist expenditure is broken down by commodity for two groups: domestic (mainland Finnish) tourists and foreign tourists. Tourist expenditure includes expenditure on board Åland-owned cruise ships on their way to and from Åland, as well as their land-based consumption. The SAMs are used as a central part of the database for a CGE model for Åland that has been used to analyse tourism’s contribution to the local economy.

In addition to the 5-year studies, Statistics Åland publishes an annual calculation of tourism’s share of GDP at factor prices as a part of the national accounts statistical leaflet. ÅSUB also publishes a monthly indicator of wages and turnover for tourism in its statistical databases. The annual and monthly calculations use the results of the quinquennial studies.

Table 4. Tourism Satellite Account Åland. Source: TSAs Finland, VisitFinland, 2020.

6. Expert statements on TSAs—advantages and disadvantages

Measuring tourism economic effects is in general a complex procedure because it requires collecting data from both supply and demand services related to tourism. With TSA it is possible to compare different tourist segments performance and calculate the ratio between demand and supply to obtain the direct value added for tourism. However, measuring the effect of tourism on a lower aggregation level (e.g. regional level) represents a more demanding procedure than measuring at national level. If the same data sources are used for the measurement of tourism at national level, the results of a regional analysis may be incorrect. 

Compared with other models, satellite accounts actually use accounting methods; they are used for not only tourism, but also transport, health, culture and the environment. The advantages of satellite accounts are that they clearly supplement national accounts and provide detailed accounting for specific areas. A disadvantage should also be mentioned, which is that TSA work is clearly costly and requires a large amount of data. Concerning the final point on RTSA methods, the report has provided a detailed description of two approaches: top-down and bottom-up. In relation to the methods and approaches in developing the Nordic RTSA. While Jie Chang our Denmark expert prefers the bottom-up method, as it provides a more detailed and concrete description of tourism statistics and development, our Åland and Finland experts Jouko Kinnunen and Katarina Fellman argue for the necessity to speak for dual approach, both national top-down studies, and whenever necessary and feasible, region-specific studies that follow as much as possible the national guidelines and solutions. However, they also argue, that these RTSAs should be allowed to deviate in the issues that are of upmost importance to the region. Every country must decide on an approach according to data availability.

Nordic countries appear to have experienced different processes in developing RTSAs. However, except for some regions like the Faroe Islands and Greenland, all the Nordic countries have developed RTSAs with varying frequency.  It would be nice to see what RTSA tables are available from each country and to compare their results.

Prospects and different approaches for developing regional TSAs

While there is general agreement regarding benefits that a TSA can provide in analysing tourism, there is less clarity regarding the most appropriate structure of such accounts. It is worth mentioning that the construction of a TSA has potentially significant implications, both during initial construction and for ongoing maintenance.

Regional accounts are needed, together with the national TSA as a framework for successful compilation of accounts from the Åland perspective. However, from experience we know that the national initiatives may not be fully suited for region-specific studies. There are important differences starting from data coverage (e.g. which establishments are included) and methods (e.g. how second-home usage is taken into account) between the national Finnish and regional Åland tourism statistics. The national methods should be defined in such a manner that enables flexibility in the definitions and coverage. For example, the number of typical industries that can have a share of tourism should be as large as possible to cater for regional idiosyncrasies.

Each Nordic country has its own national accounts and regional production accounts. It would be nearly impossible to have one unified system for the Nordic RTSAs; therefore, producing independent RTSAs is the best option. However, there may be ways to merge some of core RTSA numbers into one spreadsheet for comparison.

As a starting point for this project, RTSAs for the Nordic Countries were to have a unified definition of tourism. For example, what should be included in the tourism statistics? Should both domestic and inbound same-day visitors be included in the RTSA? If so, there must be a specific definition of domestic same-day visitors (e.g. Are they from across regional borders? How long should they be away from home?).

For which geographical level should RTSAs be compiled? Should it be NUTS-2, NUTS-3 or LAU2 (NUTS 5)? As one of the main objectives for the RTSA project is to describe tourism development in the regional economy and tourism’s contribution to the regions, some important tourism data are required (described in next section). We suggest that the suitable geographical level for the Nordic countries is the NUTS-2 level. If the most disaggregated level, such as municipality, is used, much work will be required to compile the data. For future work we should primarily concentrate in each country on the NUTS level for which necessary regional accounts exist.

Tourism products—country-specific products?

Which tourism products should be included in the project? Should there be a unified list of tourism products? As we all know, each country has specific tourism products. For example, in Norway, Sweden and Finland, winter ski tourism is an important part of tourism. However, in Denmark and other regions, ski tourism does not exist. Therefore, ski tourism should be on the list of country-specific tourism products. 

Tourism industries

Is it possible to have a unified list of tourism industries, like the UNWTO list 10 important industries?

There is also the issue of cross-checking, as the Nordic countries are neighbours. The Danish inbound tourists from Norway, Sweden and Finland must be outbound tourists from these countries. Is it possible to cross-check after the Nordic RTSA tables are created?

The Nordic RTSAs have some differences, for example in the treatment of business tourism. In the future Nordregio could take as a task to report those figures and aspects for tourism that can be found from all the regions. In addition, Nordregio could develop initial estimates e.g. for tourism’s share of regional GDP for the regions that do not have official RTSAs compiled yet (i.e. Sweden). The results can be presented in terms categories, which masks the lower reliability of estimated results.

If we were to develop a common and comparable RTSA for the Nordic region, we should, in general, follow the UNWTO/OECD/Eurostat document (UNWTO, 2008) for the seven key TSA tables. However, the UNWTO TSA tables focus on tourism consumption by inbound and domestic tourists. In general, the more data can be divided into subgroups with the goal of breaking down more aggregate results into smaller segments, the better. We suggest that we include the numbers of same-day visitors and tourist nights at destinations in different types of accommodations. Therefore, besides TSA Tables 1–4, we should develop TSA Table 1a to show numbers of inbound same-day visitors and overnight tourists, TSA Table 2a for the numbers of domestic same-day visitors and overnight tourists and TSA Table 4a for the number of total (inbound and domestic) same-day visitors and overnight tourists. I recommend breaking these tables down by NUTS-2 region (see map below). That is, if one country has five NUTS-2 regions, then it should have five TSA tables: 1a, 2a and 4a, etc. TSA Table 5 should include production accounts for sector and product, and there should be a similar table for each region. TSA table 6 is simply a combination of Tables 4 and 5. It should be noted that the important indicator from TSA Table 6 is ‘tourism ratio of supply’—that is, the share of demand for each tourism product supplied. As tourism demand is normally presented by purchase prices, but tourism supply is normally in basis prices, we also need to transform the supply into purchase prices. This is quite difficult, as most figures for production supply are given in basis prices in the national accounts. In Åland growing problems have been identified with recognizing difference between tourists and local customers for established businesses and surveys conducted among businesses may not be sufficient sources of information. For example, we see a growing role for second-home owners in our tourist interviews. Another problematic group from information gathering point of view are accommodations in private homes, either provided through platform services like Airbnb’s or through some other means. All in all, we want to stress the importance of triangulation of information from different sources considering how to address this issue.

TSA Table 7 is employment accounts—it is believed that most countries have these numbers, which can be broken down by sector (tourism versus non-tourism sectors) and by gender, education or other factors. Previous reviews have found that most countries have difficulty providing TSA Tables 8 and 9. I suggest that we omit these two tables at present. As we have already added Tables 1a–4a, we do not require TSA Table 10.

One question concerns the steps required to develop RTSAs in the Nordic countries. If the short term is defined as 1 year, the medium term as 3–5 years and the long term 7–10 years, then Jie Zhang recommend starting with the short term to construct a single-year Nordic RTSA, and then prepare for the medium and long terms. In other words, even if the work is prepared for a short period, the framework should be prepared for the long term; that is, it should allow the system to be updated in the future. In the case of financial support, it is not possible to update the Nordic RTAS every year; this can maybe be done flexibly every 2–3 years.

While the creation of comparable RTSAs is our target, we reckon this is not easy to achieve. The intention would be in helping responsible agencies demonstrate the scale and scope of tourism and aide them in policy planning with a tool with clear value in an accounting and economic modelling sense.  As each country has its own national accounts and tourism products—even specific tourism industries—a unified system for the Nordic RTSA will be challenging.

The best option is to establish one or two unified spreadsheets for every country to deliver according to requirements. Other tables should be allowed to differ; for example, there may be different tourism products or industries. Comparison target 1 is ‘tourism ratio on supply’ in hotels and restaurants, while target 2 can be the share of GDP contributed by tourism in each region.

Cohesive Nordic regional Tourism Satellite Accounts may for now be out of reach other than within limited set of comparisons across countries of regions.  Compiling RTSAs is closely related to regional accounts and regional input-output tables. The report shows clearly that the data underlying theses statistical products are also needed in the compilation of RTSAs. Therefore, either very close cooperation and (micro) data sharing or outright joining of forces is needed between compilers of main regional accounts and regional tourism satellite accounts. Tourism bodies should e.g. help in guaranteeing that the number of regional tourist interviews is sufficiently large to enable compilation of regional RTSAs. And data gathering is very time consuming and costly, coordination between regional accounting and RTSAs is needed to reach the best possible results with the existing resources. In addition, the national and regional bodies should be involved in lobbying for increasing the resources.

In the future, Nordregio could also gather and publish experiences (and manuals) for different ways of compiling top down RTSAs, which we see as a good way to start creating accounts for the regions lagging behind in publishing accounts. For example, the same methods that are being used in the creation of regional supply and demand tables for CGE models or in the creation of regional input-output tables, starting from national counterparts, can be adjusted to produce the most rudimentary versions of the RTSAs containing production and employment by industry/product as well as share of GDP. Nordregio could conduct such studies with interested counterparts. Also, the mapping competence of Nordregio should be used in the comparison and surveying of the RTSAs results.

Broader considerations also remain. When implementing analysis of economic impact, it should be possible to illustrate which effects of tourism are particularly important for society and not just for the supply side of the tourism industry (Kronenberg et.al, 2014). This could also include a definition of the sectors that earn the most from tourism (e.g., hotels, real estate, trade) and furthermore the extent to which these industries are important to society (e.g., number of jobs generated, added value, growth development). In this context, it is relevant that the interests of different stakeholders are identified and considered. For this reason, specific key figures and impact indicators for the various interest groups should be established. These important indicators enable stakeholders to control the extent to which the tourism industry contributes to meeting their objectives. While indicators for measuring the profits of private enterprises are set in financial performance measures, the profits look different on the public side (i.e., the municipal area). They, in turn, are more interested in tourism's contribution to taxes, while politicians are primarily interested in gaining the support of the population and potential voters (i.e., the positive attitude of the inhabitants towards tourism).

Almstedt, Å., Lundmark, L. & Pettersson, Ö., (2016). Public spending on rural tourism in Sweden. FENNIA—International Journal of Geography , 194(1), 18–31.

Búskaparráðið (2018). Búskaparfrágreiðingar. Retrieved from https://www.setur.fo/fo/setrid/samstarv/buskaparradid/buskaparfragreidingar/

Brændvang, A. K., Dybedal, P., Johansen, S. and Sørensen, K. (2001). Regional satellite accounts for tourism. Data, concepts, methods and applications, Paper for the 41st European Congress of the E-RSA , Zagreb, August–September 2001.

Cañada, A. (2013). Regional Tourism Satellite Account, Statistics and TSA: Issue Paper Series, Madrid: UN World Tourism Organizatio n.

Chenguang, W., Liu, J., Song, H., Li, A., & Fui, H. (2019). Developing a Web-based Regional Tourism Satellite (TSA) Information System, Tourism Economics , 25(1), 67–84. https://journals.sagepub.com/doiregional-tourism-satellite-accounts-for-the-nordic-countries.pdf10.1177/1354816618792446

Dwyer, L., Forsyth, P., and Spurr, R., (2007). Contrasting the uses of TSAs and CGE models: measuring tourism yield and productivity, Tourism Economics , vol. 13, no. 4, pp. 537–551.

Dwyer, L., Forsyth, P., Spurr, R. and Ho, T.V. (2008). Tourism’s economic contribution versus economic impact assessment: Differing roles for Satellite Accounts and Economic Modelling, in: A.G. Woodside and D. Martin, Tourism management: Analysis, behaviour and strategy , Wallingford: CAB International, pp. 459–469.

Eurostat (2009). Tourism Satellite Accounts in the European Union. Volume 1: Report on the implementation of TSA in 27 EU Member States , Eurostat: Luxembourg.

Eurostat (2016). Tourism Satellite Accounts in Europe. 2016 edition, Luxembourg: Publications Office in the European Union.

Eurostat (2019). Tourism Satellite Accounts in Europe—2019 edition, retrieved 11.November 2020 from https://ec.europa.eu/eurostat/documents/7870049/10293066/KS-FT-19-007-EN-N.pdf/f9cdc4cc-882b-5e29-03b1-f2cee82ec59d?t=1575909526000

Eurostat (2020). Environmental Accounts—establishing the links between the environment and the Economy, Retrieved 1.November 2020 https://ec.europa.eu/eurostat/statistics-explained/index.php/Environmental_accounts_-_establishing_the_links_between_the_environment_and_the_economy

Fornesbech-Sandberg, M., & Rich, R. (2019). Turismens økonomiske betydning 2018. VisitDenmark I samarbejde med CRT, retrieved 11.November 2020 https://www.visitdenmark.dk/corporate/videncenter/turismens-oekonomiske-betydning

Frechtling, D. C. (2009). Measurement and analysis of tourism economic contributions for sub-national regions through the Tourism Satellite Account. Enzo Paci Papers on Measuring the Economic Significance of Tourism , vol. 6, pp. 189–206.

Frechtling, D. C. (2010). The tourism satellite account. A primer. Annals of Tourism Research , vol. 37, no. 1, pp. 136–153.

Frechtling, D.C. & Smeral, E. (2010). Measuring and Interpreting the Economic Impact of Tourism: 20/20 Hindsight and Foresight, in: Douglas G. Pearce and Richard W. Butler (2010), Tourism Research: A 20-20 Vision , Oxford, England: Goodfellow Publishing.

Frechtling, D. C. (1999). The tourism satellite account: foundations, progress and issues. Tourism Management , vol. 20, pp. 163–170.

Frenţ, C. (2013). The economic benefits of tourism in Iceland: Boosting the Icelandic Tourism Satellite Account development—Icelandic Tourism Satellite Account (TSA)—A conformity assessment with United Nations standards for TSA—Part I, Akureyri: Icelandic Tourism Research Centre.

Frenţ, C.(2014a). The economic benefits of tourism in Iceland. New developments for the Icelandic Tourism Satellite Account: Tourism Gross Fixed Capital Formation and Tourism Collective Consumption, Akureyri: Icelandic Tourism Research Centre.

Frenţ, C. (2014b). The economic benefits of tourism in Iceland. Boosting the Icelandic Tourism Satellite Account Development, Icelandic Tourism Satellite Account (TSA)—A Conformity Assessment with United Nations standards for TSA—Part II, Akureyri: Icelandic Tourism Research Centre. Retrieved May 2018 from http://www.rmf.is/en/reports/index/skyrslur-reports/the-economic-benefits-of-tourism-in-iceland-boosting-the-icelandic-tourism-satellite-account-development-icelandic-tourism-satellite-account-tsa-a-conformity-assessment-with-united-nations-standards-for-tsa-part-ii

Frenţ, C. (2015). The new compilation of the Tourism Satellite Account in Iceland for 2009–2013. Data sources, methodology and results, Akureyri: Icelandic Tourism Research Centre.

Frenţ, C. (2018). Informing tourism policy with statistical data: The case of the Icelandic Tourism Satellite Account. Current Issues in Tourism , vol. 21, no. 9, pp. 1033–1051.

Gustavsson, A. (2018). Turisternas möte med lokalbefolkning. Ojämlikhet kontra jämlikhet i ett förändringsperspektiv. I Kolbe, W & Gustavsson, A. (2018). Turismhistoria i Norden , Acta Academiae Gustavi Adolphi CL, Uppsala: Kunglig Gustav Adolfs Akademien, 33–47.

Hagstova Forøya, (2020). Ferðavinna. Retrieved from: https://hagstova.fo/fo/vinna/taenastuvinna/ferdavinna Icelandic Tourist Board (2020). Útgefið efni—Gagnabanki. Umfang og áhrif. Retrieved 8.december 2020 from https://www.ferdamalastofa.is/is/tolur-og-utgafur/utgefid-efni/umfang-og-ahrif?itemCount=-1

Icelandic Tourist Board & KPMG (2020). Fjárhagsgreining—Staða íslenskrar ferðaþjónustu í árslok 2019. 3.December 2020. Retrieved from: https://www.ferdamalastofa.is/static/files/ferdamalastofa/Frettamyndir/2020/desember/fjarhagsgreining-stada-ferdathjonustufyrirtaekja-2019.pdf

Ionnades, D., & Gyimóthy, S. (2020). The COVID-19 crisis as an opportunity for escaping the unsustainable global tourism path. Tourism Geographies , https://doi.org/10.1080/14616688.2020.1763445

Jóhannesson, G.Th., Huijbens, E.H. and Sharpley, R. (2010). Icelandic tourism: Past directions—future challenges. Tourism Geographiers , vol. 12, no. 2, pp. 278–301.

Jones, C. and Munday, M. (2004). Evaluating the economic benefits from tourism spending through input–output frameworks: issues and cases. Local Economy, vol. 19, no. 2, pp. 117–133.

Jones, C. and Munday, M. (2007). Exploring the environmental consequences of tourism: A satellite account approach. Journal of Travel Research , vol. 46, no. 2, pp. 164–172.

Jones, C. and Munday, M. (2010). Tourism satellite accounts for regions? A review of development issues and an alternative.: Economic Systems Research , vol. 22, no. 4, pp. 341–358.

Jones, C., Munday, M. and Roberts, A. (2003). Regional tourism satellite accounts: A useful policy tool? Urban Studies , vol. 40, no. 13, pp. 2777–2794.

Jones, C., Munday, M. and Roberts, A. (2009). Top down or bottom up? Issues in the development of sub-national tourism satellite accounts. Current Issues in Tourism , vol. 12, no. 4, pp. 301–313.

Junkka, F. (2009). Regionala turism räkenskaper. En studie över möjligheterna att framställa regionala turismräkenskaper i Sverige, Arbetsrapport 2009-06-12, Östersund: Myndigheten för tillväxtpolitiska utvärderingar och analyser.

Kauppila, P., Saarinen, J. and Leinonen, R. (2009). Sustainable tourism planning and regional development in peripheries: A Nordic view. Scandinavian Journal of Hospitality and Tourism , vol. 9, no. 4, pp. 242–435.

Kolbe, W., & Gustavsson, A. (2018). Turismhistoria i Norden , Acta Academiae Gustavi Adolphi CL, Uppsala: Kunglig Gustav Adolfs Akademien.

Konttinen, J.P. (2006). Regional Tourism Satellite Account (RTSA) in Finland—Data, concepts, methods and key results, Conference paper, 46th Congress of the European Regional Science Association: ‘Enlargement, Southern Europe and the Mediterranean ‘, August 30–September 3 2006, Volos (Greece).

Kronenberg, K., Lexhagen, M., & Fuchs, M. (2014). Ekonomiska spridningseffekter inom turism—Forskningsöversikt och praktiska metoder . ETOUR Report 2014:4.

Kronenberg, K., Fuchs, M. and Lexhagen, M. (2018). A multi-period perspective on tourism’s economic contribution—a regional input–output analysis for Sweden. Tourism Review , vol. 73, no. 1, pp. 94–110.

Madsen, B. and Zhang, J. (2010). Towards a new framework for accounting and modelling the regional and local impacts of tourism. Economic Systems Research , vol. 22, no. 4, pp. 313–340.

Mandle, J. R. (2018). Tourism and the future of the Iceland economy, Paper prepared for presentation at the University of Iceland, March 2, 2018.

Müller D.K., (2013). Rural Tourism in the Nordic Countries—A Short Assessment, in: Fredricsson C., & Smas L. (eds). Small-scale tourism in rural areas: trends and research in Nordic countries, 41–46. Nordic Working group 1B: future rural areas. Nordregio Working paper 2013:3. Nordregio, Stockholm. http://www.nordregio.se/en/Publications/Publications-2013/Small-scale-Tourism-in-Rural-Areas/

Nielsen, A.M., Zhang, J., & Javakshishvili-Larsen, N. (2019). Regional Economic Effects of Coastal and Marine Tourism in Denmark. Centre for Regional and Tourism Research. https://crt.dk/wp-content/uploads/2019/02/Regional-economic-effect-of-coastal-and-maritime-tourism-in-Denmark_01022019.pdf

Nordström, J. (1996). Tourism Satellite Account for Sweden 1992-1993. Tourism Economics , vol. 2, no. 1, pp. 13–42.

OECD (2010). OECD tourism trends and policies 2010, Paris: OECD.

OECD (2016): An OECD review of statistical initiatives measuring tourism at subnational level, OECD Tourism Papers 2016/01, Paris: OECD Publishing.

Paajanen, M. (1997 ). The Economic Impact Analysis of Tourism—Towards Methodological Development , 37th European Congress of the Regional Science Association, August 26–29, 1997, Rome, Italy, Parallel Session N3: History, Culture, Arts and Regional/Urban Economic Development.

Pham, T. D. and Dwyer, L. (2013). Tourism Satellite Accounts and their applications in CGE modelling, in: Clement A. Tisdell (Ed.), Handbook of tourism economics: Analysis, new applications and case studies , New Jersey: World Scientific, pp. 493–521.

Rinne, P & Saastamoinen, O. (2005). Local Economic Role of Nature‐based Tourism in Kuhmo Municipality, Eastern Finland, Scandinavian Journal of Hospitality and Tourism , 5 (2), 2005, 89–101.

Rossouw, R. and Saayman, M. (2011). Assimilation of tourism satellite accounts and applied general equilibrium models to inform tourism policy analysis. Tourism Economics , vol. 17, no. 4, pp. 753–783.

Rögnvaldsdóttir, L. B. (2014). Economic effects of tourism in Þingeyjarsýslur. Analysis at the sub-national level in Iceland, Akureyri: Icelandic Tourism Research Centre.

Rögnvaldsdóttir, L. B. (2016). Tourism data collection. Analysis at the sub-national level in Iceland, Akureyri: Icelandic Tourism Research Centre.

Rütter, H. and Berwert, A. (1999). A regional approach for tourism satellite accounts and links to the National Account. Tourism Economics , vol. 5, no. 4, pp. 353–381.

Saarinen, J. (2003). The regional economics of tourism in Northern Finland: The socio-economic implications of recent tourism development and future possibilities for regional development. Scandinavian Journal of Hospitality and Tourism , vol. 3, no. 2, pp. 91–113.

SCB (2018). The Tourism Satellite Account & the Environment—Method Development, SCB Regioner och Miljö, MIR 2018:1.

Smeral, E. (2006). Tourism Satellite Accounts: A critical assessment. Journal of Travel Research , vol. 45, pp. 92–98.

Smeral, E. (2015). Tourism Satellite Accounts as a policy tool—some critical reflections, in: Harald Pechlander and Egon Smeral (eds.), Tourism and leisure. Current issues and perspectives of development, Wiesbaden: Springer Gabler, pp. 65–71.

SSB (2020). Tourism satellite accounts. https://www.ssb.no/en/nasjonalregnskap-og-konjunkturer/statistikker/turismesat

Statistics Finland (2004). Final report of the Tourism Satellite Account project, available at: http://ktm.elinar.fi/ktm_jur/ktmjur.nsf/All/4A4961275CDE38B6C2256F6D0026AEE1/$file/englanninkielinen_ratu8mos_2004.pdf

Statistics Finland (2020). Transport and Tourism. https://www.stat.fi/til/lii_en.html

Statistics Finland (2020a). Statistics: Culture satellite accounts [e-publication]. ISSN=2323-9905. Helsinki: Statistics Finland [referred: 01.12.2020]. Access method: http://www.stat.fi/til/klts/index_en.html

Statistics Norway (2019). Tourism satellite accounts. About the statistics. Available from: https://www.ssb.no/en/turismesat

Statistics Iceland/ Hagstofa Íslands (2020) Fjöldi launþega í einkennandi atvinnugreinum ferðaþjónustu 2008-janúar 2020, https://px.hagstofa.is/pxis/pxweb/is/Atvinnuvegir/Atvinnuvegir__ferdathjonusta__ferdaidnadurhagvisar/SAM08051.px

Tillväxtverket (2019a). Turism, available at: https://tillvaxtverket.se/statistik/turism.html

Tillväxtverket (2019b). Fakta om svensk turism 2018, Stockholm: Tillväxtverket.

Tillväxtverket (2020). Turismens årsbokslut 2019, Stockholm: Tillväxtverket och SCB. https://tillvaxtverket.se/statistik/vara-undersokningar/resultat-fran-turismundersokningar/2020-09-30-turismens-arsbokslut-2019.html

Tillväxtverket (2020b). Om turist­räkenskaperna. Stockholm: Tillväxtverket, SCB, https://tillvaxtverket.se/statistik/turism/turismens-omsattning/om-turistrakenskaperna.html

Tohmo, T. (2018). The economic impact of tourism in Central Finland: A regional input–output study. Tourism Review , vol. 73, no. 4, pp. 521–547.

UNWTO (1999). Tourism Satellite Account (TSA)—The Conceptual Framework, Madrid: UNWTO. ISBN 978-92-844-0317-2.

UNWTO (2008). Sources and Methods: Labour Statistics—Employment in the Tourism Industries (Special Edition) Madrid: UNWTO.

United Nations Statistical Office (2010). Manual on Statistics of International Trade in Services 2010, Economy & Society, New York: United Nations retrieved from: https://unstats.un.org/unsd/tradeserv/TFSITS/msits2010/docs/MSITS%202010%20M86%20(E)%20web.pdf

VisitFinland (2020). Key figures in regional tourism account by Indicator, Year and Region. http://visitfinland.stat.fi/PXWeb/pxweb/en/VisitFinland/VisitFinland__Alueellinen_matkailutilinpito/010_amtp_tau_101.px/?rxid=ea589d71-c7bb-4fc4-9520-4842a4a00535

VisitFinland (2020). Regional Tourism Accounts, Retrieved from: http://visitfinland.stat.fi/PXWeb/pxweb/en/VisitFinland/VisitFinland__Alueellinen_matkailutilinpito/010_amtp_tau_101.px/table/tableViewLayout1/?rxid=ea589d71-c7bb-4fc4-9520-4842a4a00535

VisitFinland (2020a). Boosting the Finnish travel industry. Retrieved from: https://www.businessfinland.fi/en/for-finnish-customers/services/travel/travel

Visit Greenland (2017). Tourism Statistics Report 2016, available from: http://www.tourismstat.gl/resources/reports/en/r8/GREENLAND%20TOURISM%20REPORT%202016.pdf

VisitDenmark (2020). Videnscenter -Følg med i turismens udvikling, turisterne i Danmark og internationale tendenser inden for turismen. https://www.visitdenmark.dk/corporate/videncenter

VisitDenmark (2020a). Turismens økonomiske betydning 25.25.2020. retrieved from https://www.visitdenmark.dk/corporate/videncenter/turismens-oekonomiske-betydning

VisitÅland (2019). Turismen på Åland. Retrieved from: https://www.visitaland.com/app/uploads/sites/3/2020/02/Turismrapport-2019_print-.pdf

Zhang, J. (2019). Documentation on Regional Tourism Satellite Accounts in Denmark, Bornholm/Copenhagen: Center for Regional and Tourism Research. https://crt.dk/wp-content/uploads/2019/01/rtsa-documentation_2018_revised-from-2005-1.pdf

Zhang, J. (2018). Documentation on Regional Tourism Satellite Accounts in Denmark, Bornholm/Copenhagen: Center for Regional and Tourism Research.

Zhang, J. (2014). Tourist attraction development in Denmark and its impact on regions. Management Studies , vol. 2, no. 4, pp. 254–268.

Zhang, J. (2001). Tourism impact analysis on Danish regions, Paper presented at 41 Congress of the European Regional Science Association: ‘European regional development issues in the new millennium and their impact on economic policy’, 29 August–1 September 2001, Zagreb (Croatia).

Zhang, J., Madsen, B. and Jensen-Butler, C. (2007). Regional economic impacts of tourism: The case of Denmark. Regional Studies , vol. 41, no. 6, pp. 839–854.

ÅSUB/Statistics and Research Åland (2020). Ekonomisk översikt hösten 2020. Översikter och indikatorer 2020:5. Published 09.10.2020 retrieved at https://www.asub.ax/sites/www.asub.ax/files/reports/o20205_ekonomisk_oversikt_hosten_2020_-_uppdaterad_0.pdf

ÅSUB/Statistics and Research Åland (2020a). Arbetslöshetssituationen December 2020a. Statistiskmeddelande. Arbetsmarknad. 2020:13, retrieved at https://www.asub.ax/sites/www.asub.ax/files/statistics/arblos_12_2020_0.pdf

ÅSUB (2019): Turismens samhällsekonomiska betydelse för Åland 2018. Rapport 2019:2, Mariehamn: ÅSUB.

ÅSUB (2015) https://www.asub.ax/sv/statistik/socialrakenskapsmatris-aland-2015

ÅSUB (2010) https://www.asub.ax/sv/statistik/alands-socialrakenskapsmatris-2010

ÅSUB (2007) https://www.asub.ax/sv/statistik/alands-socialrakenskapsmatris-2007

ÅSUB (2016) National accounts statistics (in Swedish): https://www.asub.ax/sites/www.asub.ax/files/statistics/bnp_meddelande_2016.pdf

Many approaches to understand economic impacts of tourism

There are various approaches to economic impacts analysis of tourism and applied techniques. Few of them will be mentioned here as a point of comparison. 

According to UNWTO (2013) there are identified four key areas that should be considered when analysing economic effects: 1. Scope 2. Aggregation level 3. Time dimension 4. Geographic area. 

The first attempt to develop Regional Tourism satellite accounts was in Australia (Kronenberg et.al., 2014). There is a range of descriptive tourism analysis tools, i.e. Tourism Benchmarking (i.e. Tyrolean Tourism Barometer) and shift-share analysis. While they have advantages i.e. that only small amount of data is needed for the benchmarking and it considers spatial variations the data requirements for benchmarking are small amount of input data but the weakness is that data input is average prices on accommodation rooms, so no sub-markets are considered in this methodology.  The benefits of shift-share is that it enables to illustrate each hosting region´s growth in relation to growth in i.e. Northern Europe. However very little data is required to obtain knowledge with high potential for managerial implications of tourism enterprises and thus it is mainly recommended as a support tool to strategic decision for the industry perspective rather than the political dimension (Kronenberg et.al., 2014).

Keynesian Multiplier models focusing on multiplication as the marginal propensity to consume and the marginal propensity to import, have been used to support taxation and spending policies in order to stimulate demand. The application to the tourism industry includes two additional components. This is the propensity of consumption by different visitor segments and shares of visitor spending in different industries.  Input-output models’ basic idea is to describe the flow of goods and services between all sectors of an economy over a period of time in the context of one table. The system quantifies the mutual interrelationship among the sectors. Input output models are rather incomplete and ignore key aspects of economy also in relation to tourism. Some of its elements are strongly simplified, i.e. labour markets. Thus illustrate poorly dynamics of tourism in that i.e. all jobs created are new jobs and there are no productivity changes, wages are fixed, no commutes from outside the region are hired  and there are no seasonal variations or differences between skilled and unskilled jobs or people holding multiple jobs( highly rigid perspective in relation to tourism) (Kronenberg et.al., 2014). 

One widely used IO model in Economic impact analyses is the IMPLAN model which is based on the theoretical conditions of input-output in its fundamental assumptions. i.e. it has been applied to analyse the impact of tourists ‘expenditure for a regional economy and understand changes in industrial output, employment, income and taxes. An example of how this has been applied is in Vermont, US a study analysed the impact of Vermont tourists’ expenditure on the state economy, annually and seasonally. The economic impact of tourism comprised changes in industrial output, employment, income and taxes. Both direct and secondary effects could be measured. The IMPLAN required three different types of data sources combined for conducting a regional tourism EIA. These were visitor surveys, business surveys for selected tourism related businesses; lodging, eat &drink and ski areas, supplied by national average data and Data about the States economy for a certain year (1996) (further reading UOV, 1999). 

A more recent study from Central Finland (Tohmo, 2018) applied input output analysis to understand the economic impact of tourism in the region. The author’s regional input–output analysis reveals that tourism has a substantial impact on production in Central Finland (including the direct and indirect effects of consumption by tourists in different sectors). Moreover, the effects of tourism expenditures on employment and residents’ incomes in tourism-related sectors in Central Finland are quite significant. However, there were many limitations of this study that stem from the assumptions of the input–output model. Other limitations relate to the analysis of the impacts of tourism on household taxes, savings, consumption, and net income. They used average figures, which risks overstating the effect of tourist expenditures on taxes because tourism jobs are often low paying. For the practical implications however, the study yielded results that can be used to frame regional policy. Results like that may be useful for policymakers in planning for tourist attractions. Furthermore, local authorities may use the results to guide decisions regarding infrastructure investments or improvements to the operating environment of tourism industries (Tohmo, 2018).

Several countries and regions, i.e. Australia, Brazil, China, Turkey, Florida and more have applied the social account matrix (SAM) to analyse the impact of international tourism. The method is based on extending the IO-table by considering more detailed transactions in a certain economy. It thus further disaggregates relationships among suppliers, purchasers and factors of production. The complexity however is a limitation in that each matrix is individually developed and cannot be replicated into a common universal structure transferable from one region to another (Kronenberg et.al., 2014).

Commonly used techniques to approach economic impact analysis in a tourism context, such as Input-Output analyses and multiplier effects, are recognized to have some major weaknesses (e.g. no resource limitations, fixed prices, wages and profits, or omitted tax variables). CGE models (Computable General Equilibrium models) attempt to overcome many of these previously mentioned approaches, e.g. the estimation of the impact of a variety of changes in policies across sectors or the implication of limited resources in the economy.

The CGE can incorporate existing Tourism satellite accounts defining Tourism as an own sector. They are used increasingly in tourism analysis, though they have distinctly different functions. The first of these involves developing measures of profitability and productivity of the Australian tourism industry – the national TSA was used to provide the database for this exercise. The second involves measuring the yield of different types of tourists to the tourism industry and the economy as a whole. TSAs provide an appropriate technique to estimate economic yield at the industry level, while the CGE approach is used to estimate the yield to the economy as a whole (Dwyer, Forsyth & Spurr, 2007). 

More recently the Regional Tourism satellite Accounts (TSA) are being developed into a web-based information system. So far only in China (Chenguang et.al., 2019).

Available tourism related data sets from each Nordic Country

Table 1. Hotels, holiday centres and youth hostels​

Table 2. Holiday dwellings

Table 3. Camping sites

Table 4. Marina

Table 5. Holiday and business trips

Table 6. Accommodation Statistics

Table 7. Regional tourism accounts

Table 8. Statistics on rental cottages

Table 9. Tourism accounts (national level)

Table 10. Travel-related credits and debits

Table 11. Accomodation

Table 12. Statistics on Passengers

Table 13. Tourism Satellite Accounts

Table 14. Short term indicators in tourism

Table 15. International Visitors in Iceland – Summer 2016

Table 16. Accommodation

Table 17. Accommodation and food service activities, structural business statistics

Tbale 18. Tourism satellite accounts

Table 19. Overnight stays

Table 20. Cruises

Table 21. Flight passengers

Åland

Table 22. Tourism

Regional Tourism Satellite Accounts for the Nordic Countries 

Authors:  Anna Karlsdóttir and Nora Sánchez Gassen Contributors:  Jie Zhang, Jouko Kinnunen and Katarina Fellman

This publicaiton is a cooperation between Nordregio, the Statistics and Research Åland (ÅSUB) and the Centre for Regional and Tourism Research (CRT).

Nordregio Report 2021:2 ISBN:  978-91-8001-010-8 ISSN : 1403-2503 DOI : http://doi.org/10.6027/R2021:2.1403-2503

© Nordregio 2021

Cover photo: Maria Michelle, Pixabay Layout: Marija Zelenkauskė, Nordregio

Book cover

Evolution of Destination Planning and Strategy pp 149–171 Cite as

Implementation of Tourism Satellite Account: Assessing the Contribution of Tourism to the Croatian Economy

  • Neven Ivandić 4 &
  • Zrinka Marušicś 4  
  • First Online: 25 November 2016

1276 Accesses

1 Citations

Compiling the indicators of tourism consumption and the output of tourism industries, Tourism Satellite Account (TSA) provides a framework for internationally harmonized measurements of direct macroeconomic contribution of tourism. Ivandić and Marušić provide a detailed methodological approach for the transfer of TSA theoretical concepts to the assessment of tourism economic contribution on the case of the Croatia. Giving that the TSA compilation is still characterized by a surprisingly wide range of ‘styles’ used, the chapter contributes to a better understanding of the issues related to measurement of direct tourism impacts. It also gives a set of baseline criteria for resource allocation within tourism policy and the further evaluation of its effectiveness.

  • System of tourism statistics
  • Tourism Satellite Account
  • Direct economic contribution of tourism
  • Unregistered tourism flows

This is a preview of subscription content, log in via an institution .

Buying options

  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
  • Available as EPUB and PDF
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
  • Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Ahlert, G. (2007). Methodological aspects of preparing the German TSA, empirical findings and initial reactions. Tourism Economics, 13 (2), 275–287.

Article   Google Scholar  

Alriquet, G. & Herbecq, J.M. (1979). The tourism satellite account: Presentation of accounting tables and the first estimation of domestic tourism expenditure. In: World tourism organization (2001). The tourism satellite account as an ongoing process: Past, present and future developments , Madrid, Spain: World Tourism Organization.

Google Scholar  

Blažević, B. (2007). Turizam u gospodarskom sustavu , 2. izmijenjeno i dopunjeno izdanje [Tourism in the Economic System, 2nd ed.]. Opatija, Croatia: Faculty of Tourism and Hotality Management, University of Rijeka.

Car, K., Cicvarić, A., Radnić, A., & Sekulić, M. (1975). Neki ekonomski efekti inozemnog turizma u Jugoslaviji [Some economic effects of inbound tourism in Yugoslavia]. Economic Review, 26 (9–10), 509–548.

Commission of the European Communities, International Monetary Fund, Organization for Economic Cooperation and Development, United Nations & World Bank. (1993). System of national accounts 1993 . Brussels/Luxembourg: Commission on the European Communities.

Commission of the European Communities, Organisation of Economic Co-operation and Development, United Nations & World Tourism Organization. (2001). Tourism satellite account: Recommended methodological framework . Brussels/Luxembourg, Paris, New York, Madrid: Authors.

Croatian Bureau of Statistics. (2011). Hotels and restaurants. Statistical reports . www.dzs.hr . Date assessed 4 October 2013.

Croatian Bureau of Statistics. (2012). Tourism in 2011. First release , from 4.4.2/11. www.dzs.hr . Date assessed 4 October 2013.

Croatian Bureau of Statistics. (2013a). Annual gross domestic product for 2011. First release , 12.1.6. www.dzs.hr . Date assessed 24 March 2014.

Croatian Bureau of Statistics. (2013b). Input-output table for 2004 and supply and use tables for 2004 and 2005. First release , 12.1.4. www.dzs.hr . Date assessed 24 March 2014.

Diakomihalis, M. N., & Lagos, D. G. (2008). Estimation of the economic impacts of yachting in Greece via the tourism satellite account. Tourism Economics, 14 (4), 871–887.

Dwyer, L., Deery, M., Jago, L., Spurr, R., & Fredline, L. (2007). Adapting the tourism satellite account conceptual framework to measure the economic importance of the meetings industry. Tourism Analysis, 12 (4), 247–255.

European Union. (2011) Regulation (EU) No 692/2011 of the European Parliament and of the Council of 6 July 2011. Official Journal of the European Union , L 192/2011. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:192:0017:0032:EN:PDF . Date accessed 10 May 2014.

Eurostat. (2009). Tourism satellite accounts in the European Union. Methodologies and working papers , Luxembourg: Publications Office of the European Union.

Eurostat. (2012). Methodological manual for tourism statistics, Version 1.2. Methodologies and working papers , Luxembourg: Publications Office of the European Union.

Eurostat. (2013). Tourism satellite accounts (TSAs) in Europe . Statistical working papers, Luxembourg: Publications Office of the European Union.

Frangialli, F. (2006). The TSA’s relevance for policy-makers . In: Tourism Satellite Account (TSA) – Implementation Project Enzo Paci Papers on Measuring the Economic Significance of Tourism Vol. 5, Madrid, Spain: World Tourism Organization.

Frechtling, D.C. (2006). An assessment of visitor expenditure methods and models. Journal of Travel Research , 45 (1), 26–35.

Frechtling, D. C. (2009). Measurement and analysis of tourism economic contributions for sub-national regions through the tourism satellite account. Enzo Paci Papers , Volume 6, UNWTO, 189–206.

Frechtling, D.C. (2010). The tourism satellite account: A primer. Annals of Tourism Research , 37 (1), 136–153.

Frechtling, D.C. (2013). The Economic impact of tourism: Overview and examples of macroeconomic analysis , UNWTO Statistics and TSA Issue Paper Series STSA/IP/2013/03 (Online). http://statistics.unwto.org/en/content/ papers. Date assessed 7 November 2014.

Frent, F. (2008). The economic importance of vacation homes from the Tourism Satellite Account (TSA) perspective. Tourism Review , 64 (2), 19–27.

Gatti, P. (2013). Tourism, welfare and income distribution: The case of Croatia. Tourism , 61 (1), 53–71.

Horak, S., Marušić, Z. & Radnić, A. (1999). Potrošnja inozemnih putnika u Hrvatskoj i domaćih putnika u inozemstvu u 1998. godini [Expenditures of inbound and outbound tourists in Croatia in 1998]. Zagreb, Croatia: Croatian National Bank.

Institute for Tourism. (2003). Turistička aktivnost domaćeg stanovništva u 2002 [Tourist Activity of Population of Republic of Croatia in 2002] . Zagreb, Croatia: Institute for Tourism.

Institute for Tourism. (2007). Satelitski račun turizma Republike Hrvatske – Studija izvedivosti [Tourism Satellite Account of Republic of Croatia – Feasibility Study]. Zagreb, Croatia: Institute for Tourism.

Institute for Tourism. (2008). Eksperimentalni satelitski račun turizma Republike Hrvatske u 2005. godini [Experimental Tourism Satellite Account of Republic of Croatia for 2005]. Zagreb, Croatia: Institute for Tourism.

Institute for Tourism. (2010). Eksperimentalna TSA 2007 prema metodologiji Svjetske turističke organizacije: Izravni i neizravni učinci turizma u RH [Experimental TSA 2007 according to UNWTO methodological framework: Direct and Indirect Impacts of Tourism in the Republic of Croatia]. Zagreb, Croatia: Institute for Tourism.

Institute for Tourism. (2011). Stavovi i potrošnja turista u Hrvatskoj – TOMAS Ljeto 2010 [Attitudes and Expenditures of Tourist in Croatia – Tomas Summer 2010]. Zagreb, Croatia: Institute for Tourism.

Institute for Tourism. (2012). Turistička aktivnost domaćeg stanovništva u 2011 [Tourist Activity of Population of Republic of Croatia in 2011] . Zagreb, Croatia: Institute for Tourism.

Institute for Tourism. (2013). Stavovi i potrošnja nautičara u Hrvatskoj – TOMAS Nautika jahting 2012 [Attitudes and Expenditures of Yachtsmen in Croatia – Tomas Nautica Yahting 2012]. Zagreb, Croatia: Institute for Tourism.

Ivandić, N., & Marušić, Z. (2009). Je li sustav statistike turizma u Hrvatskoj spreman za izradu satelitskog računa turizma? [Is the system of tourism statistics in Croatia ready to create a tourism satellite account?]. Tourism, 57 (2), 185–205.

Ivandić N., Marušić Z., Šutalo I. & Vuglar, J. (2014). Satelitski račun turizma RH za 2011. godinu i izračun neizravnih i ukupnih učinaka turizma u RH [Tourism Satellite Account of the Republic of Croatia for 2011 and Estimation of Indirect and Total Impacts of Tourism] . Zagreb, Croatia: Institute for Tourism.

Ivandić, N., & Radnić, A. (1997). Neslužbeno gospodarstvo u turizmu i ugostiteljstvu [The grey economy in tourism and catering]. Financial Theory and Practice, 21 (1-2), 231–240.

Jones, C., & Munday, M. (2008). Tourism satellite accounts and impact assessments: Some considerations. Tourism Analysis, 13 (1), 53–69.

Kenneally, M., & Jakee, K. (2012). Satellite accounts for the tourism industry: structure, representation and estimates for Ireland. Tourism Economics, 10 (5), 971–997.

Kesar, O. (2006). Ekonomski učinci turističke potrošnje, doktorska disertacija [The Economic Effects of Tourism Consumption, dissertation], Zagreb, Croatia: Faculty of Economics and Business, University of Zagreb.

Lapierre, J. (1991). A proposal for a Satellite Account and Information System for Tourism. In: World Tourism Organization (2001). The tourism satellite account as an ongoing process: Past, present and future developments . Madrid, Spain: World Tourism Organization.

Libreros, M., Massieu, A., & Meis, S. (2006). Progress in tourism satellite account implementation and development. Journal of Travel Research, 45 (1), 83–91.

Los, B., & Steenge, A. E. (2010). Tourism studies and input–output analysis: Introduction to a special issue. Economic Systems Research, 22 (4), 305–311.

Lück, M. (2007). Nautical tourism: Concepts and issues . New York: Cognizant Communication Corporation`

Lukovic, T. (Ed.). (2013). Nautical tourism . Wallingford, UK: CABI.

Marušić, Z., Ivandić, N. & Horak, S. (2014). Nautical tourism within TSA framework: Case of Croatia, 13th Global Forum on Tourism Statistics, 17–18 November 2014, Nara, Japan. http://naratourismstatisticsweek.visitors.jp/global/ pdf/full_paper/4-4.pdf. Date assessed 22 February 2015.

Ministry of Tourism. (2013). Croatian tourism development strategy to 2020 . Official Gazette of the Republic of Croatia 55/2013. http://narodne-novine.nn.hr/clanci/sluzbeni/2013_05_55_1119.html . Date accessed 20 November 2014.

Munday, M., Turner, K., & Jones, C. (2013). Accounting for the carbon associated with regional tourism consumption. Tourism Management, 36 , 35–44.

Organisation for Economic Cooperation and Development. (1991). Manual on tourism economic accounts . Paris: Organisation for Economic Cooperation and Development.

Radnić, A. (1990). Strukturna analiza turističke potrošnje u Jugoslaviji , doktorska disertacija [Structural Analysis of Tourism Consumption in Yugoslavia, dissertation], Zagreb, Croatia: Faculty of Economics and Business, University of Zagreb.

Radnić, A., & Ivandić, N. (1999). War and tourism in Croatia – Consequences and the road to recovery. Tourism, 47 (1), 43–54.

Sainaghi, R. (2012). Tourist expenditures: The state of the art. Anatolia, 23 (2), 217–233.

Smeral, E. (2006). Tourism satellite accounts: A critical assessment. Journal of Travel Research, 45 (1), 92–98.

Song, H., Dwyer, L., Li, G., & Cao, Z. (2012). Tourism economics research: A review and assessment. Annals of Tourism Research, 39 (3), 1653–1682.

Stynes, D. J., & White, E. M. (2006). Reflections on measuring recreation and travel spending. Journal of Travel Research, 45 (1), 8–16.

Šutalo, I., Ivandić, N., & Marušić, Z. (2011). Ukupan doprinos turizma gospodarstvu Hrvatske: input-output model i satelitski račun turizma [Total contribution of tourism to Croatian economy: Input-output model and tourism satellite account]. Economic Review, 62 (5-6), 267–285.

Šutalo, I., Vuglar, J., & Ivandić, N. (2012). Importance of theoretical value added tax for Croatia’s fiscal capacity in the context of the European Union. Financial Theory and Practice, 36 (3), 297–320.

United Nations, World Tourism Organization, Eurostat – Commission of the European Communities & Organisation for Economic Co-operation and Development. (2010a). Tourism satellite account: Recommended methodological framework 2008. Studies in methods , Series F, No. 80/Rev.1, Luxemburg, Madrid, New York, Paris: Authors.

United Nations & World Tourism Organization. (2010b). International recommendations for tourism statistics 2008. Studies in methods , Series M, No. 83/Rev.1, New York: Authors.

Vizek, M. (2014). Cijena neuređene države [The Cost of Inefficient State], Jutarnji list. http://www.jutarnji.hr/cijena-neuredene-drzave/1200673/ . Date assessed 30 December 2014.

Wilton, J. J., & Nickerson, N. P. (2006). Collecting and using visitor spending data. Journal of Travel Research, 45 (1), 17–25.

World Tourism Organization. (1983). Determination of the importance of tourism as an economic activity within the framework of the national accounting system. In: World Tourism Organization (2001). The tourism satellite account as an ongoing process: Past, present and future developments . Madrid, Spain: World Tourism Organization.

Download references

Acknowledgments

This paper is based on the results of project Tourism Satellite Account for Croatia for 2011 and Estimation of Indirect and Total Contribution of Tourism in Croatia conducted by the Institute for Tourism and entirely supported by Ministry of Tourism of the Republic of Croatia in 2013 and 2014.

Author information

Authors and affiliations.

Institute for Tourism, Zagreb, Croatia

Neven Ivandić & Zrinka Marušicś

You can also search for this author in PubMed   Google Scholar

Editor information

Editors and affiliations.

University of Ljubljana, Woolloomooloo, Australia

Larry Dwyer

Renata Tomljenović

Sanda Čorak

Rights and permissions

Reprints and permissions

Copyright information

© 2017 The Author(s)

About this chapter

Cite this chapter.

Ivandić, N., Marušicś, Z. (2017). Implementation of Tourism Satellite Account: Assessing the Contribution of Tourism to the Croatian Economy. In: Dwyer, L., Tomljenović, R., Čorak, S. (eds) Evolution of Destination Planning and Strategy. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-42246-6_8

Download citation

DOI : https://doi.org/10.1007/978-3-319-42246-6_8

Published : 25 November 2016

Publisher Name : Palgrave Macmillan, Cham

Print ISBN : 978-3-319-42245-9

Online ISBN : 978-3-319-42246-6

eBook Packages : Business and Management Business and Management (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Publish with us

Policies and ethics

  • Find a journal
  • Track your research

UN Tourism | Bringing the world closer

UN Adopts a New Global Standard to Measure the Sustainability of Tourism

share this content

  • Share this article on facebook
  • Share this article on twitter
  • Share this article on linkedin

UN Adopts a New Global Standard to Measure the Sustainability of Tourism

  • All Regions

A groundbreaking statistical framework, developed under the leadership of UN Tourism, has been adopted by all 193 UN member states.

The Statistical Framework for Measuring the Sustainability of Tourism (MST) thus becomes the internationally agreed reference framework for measuring the economic, social and environmental aspects of tourism.

The adoption by the UN Statistical Commission at its 55th session (27 February – 1 March 2024) marks a historical milestone towards harnessing the full potential of the sector, providing a solution to the pressing need for a harmonized methodology to effectively assess the sustainability of tourism.

"Tourism is a powerful force for positive change when managed responsibly and sustainably," says Zurab Pololikashvili, UN Tourism Secretary General. "The adoption of the Statistical Framework for Measuring the Sustainability of Tourism marks a paradigm shift, going beyond GDP by enabling the measurement of what matters most to people and planet."

The adoption of the Statistical Framework for Measuring the Sustainability of Tourism marks a paradigm shift, going beyond GDP by enabling the measurement of what matters most to people and planet

Collaborative effort

This achievement is the fruit of a seven-year UN process led by Austria and Spain as co-chairs of the UN Tourism Committee on Statistics, with Saudi Arabia and Seychelles as co-vice chairs.  Under auspices of the Committee, the Framework was developed thanks to the extraordinary work of the multistakeholder Expert Group on Measuring the Sustainability of Tourism composed of 40+ countries and 30+ international and regional organizations including the UN Statistics Division, the International Labour Organization (ILO), subnational authorities and observatories, academia and others.

The work involved technical guidance from an Editorial Board chaired first by the Philippines and then by Canada, as well as extensive engagement and consultation with input from numerous pilots in countries.

The Statistical Commission expressed an overwhelmingly enthusiastic support with 34 countries, 3 world regions and international organizations taking active part in the deliberations: Antigua and Barbuda, Austria, Benin on behalf of the African Group, Cabo Verde, Canada, Chile, Colombia, Costa Rica, Croatia, Denmark, Dominican Republic, Egypt, Finland on behalf of the European Statistical System, Greece, Jamaica, India, Indonesia, Kuwait, Malaysia, Malta, Mexico, Morocco, the Netherlands, New Zealand, the Philippines, Portugal, Qatar, Saudi Arabia on behalf of the Gulf Cooperation Council, Slovenia, Spain, Tajikistan, Tanzania, United Arab Emirates, United States of America, the Committee for the Coordination of Statistical Activities and ILO.  

Looking ahead, the Commission also welcomed the future development of an implementation programme, including a compilation guide, and called on the international donor community to support the financing for measuring the sustainability of tourism.

Established in 1947, the UN Statistical Commission gathers Chief Statisticians from Member States and international organizations, and is the highest decision-making body for international statistical activities. The last time that the Commission adopted a statistical standard for tourism was in 2008, when the International Recommendations for Tourism Statistics and the Tourism Satellite Account framework were presented.

Closing the gap between policy and statistics

In the margins of the United Nations Statistical Commission, Austria, Spain and UN Tourism co-organized the high-level side event “Measuring the Sustainability of Tourism: Closing the gap between policy and statistics”, in collaboration with the UN Committee for Economic-Environmental Accounting. Austria and Spain shared their vision on the importance of the Statistical Framework for Measuring the Sustainability of Tourism for evidence-based policy and decisions, while acknowledging its significance in upholding the relevance of statistical systems worldwide and the links to key topics like data governance and stewardship.

Mexico, the Philippines and Canada reflected on their pioneering experiences with implementing the framework, showcasing the power of integrating data from different domains and sources to distil more holistic and meaningful information on tourism.

The event raised awareness of the Statistical Framework for MST and functioned as an informative preamble to the UN Statistical Commission’s formal deliberations. 

Releted links

  • Download the News Release on PDF
  • 55th Session of the United Nations Statistical Commission (all documents)
  • Report of the World Tourism Organization on tourism statistics to the 55th Session of the United Nations Statistical Commission
  • Statistical Framework for Measuring the Sustainability of Tourism as presented to the 55th Session of the United Nations Statistical Commission
  • Videos of the 55th Session of the United Nations Statistical Commission, item 4a on tourism statistics: part 1
  • Videos of the 55th Session of the United Nations Statistical Commission, item 4a on tourism statistics: part 2
  • Side Event “Measuring the Sustainability of Tourism: Closing the gap between tourism policy and statistics”
  • Measuring the Sustainability of Tourism (MST) programme of work
  • MST Governance

Related Content

no img

New Products and Experiences: an opportunity for mounta...

no img

UN Tourism reports openness is back to pre-pandemic levels

no img

UN Tourism to Make Residents Focus of Thassos Island’s ...

no img

UN Tourism Calls on Sector to #InvestInWomen

Cookies on GOV.UK

We use some essential cookies to make this website work.

We’d like to set additional cookies to understand how you use GOV.UK, remember your settings and improve government services.

We also use cookies set by other sites to help us deliver content from their services.

You have accepted additional cookies. You can change your cookie settings at any time.

You have rejected additional cookies. You can change your cookie settings at any time.

tourism satellite accounts in europe

  • Regional and local government
  • Northern Ireland

Northern Ireland Tourism Satellite Account (TSA) 2019

The NI TSA provides economic information about the demand for goods and services associated with tourism, and their contribution to the NI economy.

Northern Ireland Tourism Satellite Account 2019

https://www.nisra.gov.uk/statistics/tourism

The Department for the Economy (DFE) NI commissioned Northern Ireland Statistics and Research Agency (NISRA) to produce a Tourism Satellite Account (TSA) for NI to inform the measurement of the Tourism industry in NI and support tourism related policy development going forward. The TSA has been developed to provide policy makers and key stakeholders in Northern Ireland with credible statistics relating to the NI Tourism industry to support policy development and decision making in this sphere going forward.

Is this page useful?

  • Yes this page is useful
  • No this page is not useful

Publication detail

tourism satellite accounts in europe

Tourism satellite accounts in Europe

2019 edition, publication metadata, available languages and formats, english (en).

  • Publication details
  • Related publications
  • All editions
  • Published: 2019
  • Corporate author(s): Eurostat ( European Commission )
  • Themes: Industry, trade and services
  • Subject: impact study , tourism , tourism statistics , tourist profession , transport economics , transport statistics
  • Released on EU Publications: 2019-12-19
  • Show all issues in this serial

Document viewer

Note: The publication cannot be displayed in the document viewer. Open web version You may access it from: Download and languages

Did you know that you can annotate your document and share your annotations?

We've detected unusual activity from your computer network

To continue, please click the box below to let us know you're not a robot.

Why did this happen?

Please make sure your browser supports JavaScript and cookies and that you are not blocking them from loading. For more information you can review our Terms of Service and Cookie Policy .

For inquiries related to this message please contact our support team and provide the reference ID below.

Create an account

Create a free IEA account to download our reports or subcribe to a paid service.

Oil Market Report - March 2024

03 March

About this report

The IEA Oil Market Report (OMR) is one of the world's most authoritative and timely sources of data, forecasts and analysis on the global oil market – including detailed statistics and commentary on oil supply, demand, inventories, prices and refining activity, as well as oil trade for IEA and selected non-IEA countries.

  • Global oil demand is forecast to rise by a higher-than-expected 1.7 mb/d in 1Q24 on an improved outlook for the United States and increased bunkering. While 2024 growth has been revised up by 110 kb/d from last month’s Report, the pace of expansion is on track to slow from 2.3 mb/d in 2023 to 1.3 mb/d, as demand growth returns to its historical trend while efficiency gains and EVs reduce use.
  • World oil production is projected to fall by 870 kb/d in 1Q24 vs 4Q23 due to heavy weather-related shut-ins and new curbs from the OPEC+ bloc. From the second quarter, non-OPEC+ is set to dominate gains after some OPEC+ members announced they would extend extra voluntary cuts to support market stability. Global supply for 2024 is forecast to increase 800 kb/d to 102.9 mb/d, including a downward adjustment to OPEC+ output.
  • Refinery crude runs are forecast to rise from a February-low of 81.4 mb/d to a summer peak of 85.6 mb/d in August. For the year as a whole, throughputs are projected to increase by 1.2 mb/d to average 83.5 mb/d, driven by the Middle East, Africa and Asia. Refining margins improved through mid-February before receding, with the US Midcontinent and Gulf Coast as well as Europe leading the gains.
  • Global observed oil inventories surged by 47.1 mb in February. Offshore stocks dominated gains as seaborne exports reached an all-time high and shipping disruptions through the Red Sea tied up significant volumes of oil on water while onshore inventories declined. Global stocks plunged by 48.1 mb in January, with OECD industry stocks at a 16-month low.
  • ICE Brent futures rose by $2/bbl during February as ongoing Houthi shipping attacks in the Red Sea kept a firm bid under crude prices. With oil tankers taking the longer route around Africa more oil was kept on water, further tightening the Atlantic Basin market and sending crude’s forward price structure deeper into backwardation. At the time of writing, Brent was trading at $83/bbl.

Oil on water

Benchmark crude oil prices were range bound in early March, as the market had already priced in the announced extension of OPEC+ voluntary production cuts through 2Q24. North Sea Dated rose by $2.13/bbl to $84.66/bbl during February as continued tanker attacks in the Red Sea lengthened supply routes and global on-land oil inventories fell for a seventh consecutive month to reach their lowest level since at least 2016.

Global onshore oil stocks fell a further 38 mb last month, taking the draw down since July to 180 mb, according to preliminary data. Over the same period, oil on water surged. Trade dislocations from the rerouting of Russian barrels and more recently due to unrest in the Middle East, have boosted oil on water by 115 mb. In February alone, oil on water surged by 85 mb as repeated tanker attacks in the Red Sea diverted more cargoes around the Cape of Good Hope. At nearly 1.9 billion barrels as of end-February, oil on water hit its second highest level since the height of the Covid-19 pandemic.

Trade flow disruptions also boosted bunker fuel use. Longer shipping routes and faster vessel speeds saw Singapore bunkering reach all-time highs. That, along with surging US ethane demand for its petrochemical sector underpins a slight upward revision to our global oil demand expectations for this year by 110 kb/d compared with last month’s Report. World oil demand growth is now forecast at 1.3 mb/d in 2024, down sharply from last year’s 2.3 mb/d expansion.

The slowdown in growth, already apparent in recent data, means that oil consumption reverts towards its historical trend after several years of volatility from the post-pandemic rebound. A weaker economic outlook further tempers oil use, as do efficiency improvements and surging electric vehicle sales. Growth will continue to be heavily skewed towards non-OECD countries, even as China’s dominance gradually fades. The latter’s oil demand growth slows from 1.7 mb/d in 2023 to 620 kb/d in 2024, or from roughly three-quarters to half of the global total, under the gathering weight of a challenging economic environment and slower expansion in its petrochemical sector.

As in 2023, non-OPEC+ oil supply growth will eclipse the oil demand expansion by some margin. Led by the United States, non-OPEC+ production is forecast to rise by 1.6 mb/d in 2024 compared to 2.4 mb/d last year when global oil output climbed by 2 mb/d to 102 mb/d. Substantial gains will also come from Guyana, Brazil and Canada, all forecast to pump at record-highs this year. Together, the non-OPEC+ Americas quartet is set to add 1.3 mb/d of new oil production in 2024.

Iran, which last year ranked as the world’s second largest source of supply growth after the United States, is expected to increase production by a further 280 kb/d this year. Output policy for the remainder of the OPEC+ bloc will be revisited when ministers meet in Vienna on 1 June to review market conditions. In this Report, we are now holding OPEC+ voluntary cuts in place through 2024 – unwinding them only when such a move is confirmed by the producer alliance (see OPEC+ cuts extended). On that basis, our balance for the year shifts from a surplus to a slight deficit, but oil tanks may get some relief as the massive volumes of oil on water reach their final destination.

1. Includes extra voluntary curbs where announced. 2. Capacity levels can be reached within 90 days and sustained for an extended period. 3. Excludes shut in Iranian, Russian crude. 4. Angola left OPEC effective 1 Jan 2024. 5. Iran, Libya, Venezuela exempt from cuts. 6. Mexico excluded from OPEC+ compliance. 7. Bahrain, Brunei, Malaysia, Sudan and South Sudan.

Definitions of key terms used in the OMR, access the OMR Glossary here.

For more info on the methodology, download the PDF below.

  • Download the methodology circle-arrow

Previous editions

Purchase licence

  • 24 months (-10%)
  • Unlimited users
  • Multiple locations

Need help with your purchase ? Visit our help centre

See if you qualify for a discount. Learn more

Request price

Cite report

IEA (2024), Oil Market Report - March 2024 , IEA, Paris https://www.iea.org/reports/oil-market-report-march-2024

Share this report

  • Share on Twitter Twitter
  • Share on Facebook Facebook
  • Share on LinkedIn LinkedIn
  • Share on Email Email
  • Share on Print Print

Subscription successful

Thank you for subscribing. You can unsubscribe at any time by clicking the link at the bottom of any IEA newsletter.

IMAGES

  1. Tourism Satellite Accounts 2019

    tourism satellite accounts in europe

  2. Tourism satellite accounts in Europe. 2023 edition

    tourism satellite accounts in europe

  3. Tourism satellite accounts in Europe. 2019 edition

    tourism satellite accounts in europe

  4. Tourism Satellite Account (TSA)

    tourism satellite accounts in europe

  5. PPT

    tourism satellite accounts in europe

  6. Tourism Satellite Accounts in Europe

    tourism satellite accounts in europe

VIDEO

  1. Satellite accounts

  2. How to plan europe trip ? #ytshortsindia #travelhacks #budgettravel #europe

COMMENTS

  1. Tourism Satellite Accounts in Europe

    Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU and EFTA countries, submitted on a voluntary basis to Eurostat, and is a follow-up of the publication Tourism Satellite Accounts in Europe of 2019.

  2. Tourism Satellite Accounts in Europe

    This report presents an analysis of the data gathered in 2022 and is a follow-up to the 2019 edition of Tourism Satellite Accounts (TSA) in Europe(4). At this stage of development, national methodologies are not sufficiently harmonised for the data to be fully comparably across countries.

  3. Tourism Satellite Accounts (TSA)

    Tourism Satellite Accounts in Europe (2019 edition) [link] Tourism Satellite Account: Recommended Methodological Framework 2008 (TSA:RMF 2008) [link] Methodological work on Tourism Satellite Accounts in the European Union - deliverables of the 2008-2009 Eurostat project [link]

  4. Tourism satellite accounts (TSA) in Europe

    Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU, EFTA and candidate countries who have compiled TSA for recent reference years and is a follow-up of the publication "Tourism Satellite Accounts in Europe" of 2010 ...

  5. Tourism satellite accounts in Europe

    Tourism plays an important role in many countries' economies and labour markets. Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU, EFTA and candidate countries who have compiled TSA for recent reference years and is a follow-up of the publication " ...

  6. Tourism Satellite Accounts in Europe

    Publication Tourism Satellite Accounts in Europe - 2016 edition. Date February 16, 2017. Tourism plays an important role in many countries' economies and labour markets. Tourism satellite systems have been developed to quantify the importance of tourism. This publication contains key indicators from the Tourism Satellite Accounts ( TSA) for the ...

  7. Tourism Satellite Account

    The Tourism Satellite Account (TSA) is a distinctive method of measuring the direct economic contributions of tourism demand to a national economy. Its unique approach derives from employing the principles and structure of the internationally recognized System of National Accounts (SNA) to measuring the direct economic impact of tourism.

  8. Tourism Satellite Accounts in Europe

    Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU and EFTA countries who have compiled TSA for recent reference years and is a follow-up of the publication Tourism Satellite Accounts in Europe of 2016.

  9. Estimating the Economic Impact of Tourism in the European Union: Review

    The routine is then applied to selected destinations for which a minimum standard in the quality of data from Tourism Satellite Accounts and Input-Output tables is met. Methodologically, the article provides a tool for estimating the total contribution of tourism to output, gross value added, and employment. ... Tourism Satellite Accounts in ...

  10. Tourism Satellite Accounts in Europe 2019 edition

    Since 2010, the Member States and EFTA countries submit every three years available TSA data to Eurostat (2010, 2013, 2016 and 2019). This report presents an analysis of the data gathered in 2019 and is a follow-up to the 2016 edition of Tourism Satellite Accounts (TSA) in Europe(4).

  11. Tourism Satellite Accounts in the European Union : report on the

    Tourism Satellite Accounts (TSA) provide an economic measure of the importance of tourism in terms of expenditures, GDP and employment for a given country. In 2008-2009, Eurostat ran a project assessing the work done in the EU in the field of TSA and fostering the further implementation and harmonisation of TSA compilation. The key deliverables of the project are published in a set of 4 ...

  12. Tourism Satellite Accounts

    Tourism Satellite Accounts (TSA) in Europe (2019 edition) 5. Main findings 2 Analysis The analysis of the demand side (see Chapter 4) shows that domestic tourism accounted for 65 % of internal tourism expenditure on average in the EU, and 'inbound expenditure' for 35 %. In 15 out of the 27 countries for which data is available, inbound ...

  13. Regional tourism satellite accounts for the Nordic countries

    The most recent publication was a follow-up of the 2016 Tourism Satellite Accounts in Europe (Eurostat, 2019). The Nordic model was stipulated by the Nordic Council of Ministers and used for the evaluation of the economic impacts of tourism in the Nordic peripheries (Rinne & Saastamoinen, 2005; Saarinen, 2003). Only older tourism literature ...

  14. Tourism satellite accounts in Europe

    Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU and EFTA countries, submitted on a voluntary basis to Eurostat, and is a follow-up of the publication Tourism Satellite Accounts in Europe of 2019.

  15. PDF Tourism Satellite Accounts in Europe

    Tourism Satellite Account Manila, Philippines, 19 -20 June 2017 Christophe Demunter ... Dissemination of the TSA tables Tourism Satellite Accounts in Europe. 2 Outline of the presentation 1. State of affairs 2. TSA framework in EU 3. Voluntary transmission 4. Some food for thought. State of affairs Since 2000, the European Commission has actively

  16. THE TOURISM SATELLITE ACCOUNT: A Primer

    The Tourism Satellite Account (TSA) is a popular method of measuring the direct contributions of tourism consumption to a national economy. Its unique role in quantifying economic contributions of visitors in a country derives from its nature as an account rather than a model and its observance of the principles of national economic accounting ...

  17. Tourism satellite accounts in the European Union. VOL 3, Practical

    Tourism satellite accounts in the European Union. VOL 3, Practical guide for the compilation of a TSA Directory of good practices Publication metadata. How to cite. Citation style. Export format. Export Download and languages Close. Available languages and formats. Download X. Available languages and formats ...

  18. Implementation of Tourism Satellite Account: Assessing the ...

    Tourism satellite accounts (TSAs) in Europe. Statistical working papers, Luxembourg: Publications Office of the European Union. Google Scholar Frangialli, F. (2006). The TSA's relevance for policy-makers. In: Tourism Satellite Account (TSA) - Implementation Project Enzo Paci Papers on Measuring the Economic Significance of Tourism Vol. 5 ...

  19. Workshop on Measuring the economic impact of tourism in Europe: the

    2008 Tourism Satellite Account: Recommended Methodological Framework (TSA: RMF 2008) European Implementation Manual on TSA; OECD: Measuring the Role of Tourism in OECD Economies (readable for free) OECD (Alain Dupeyras) USING TSA FOR BUSINESS AND POLICY; EUROSTAT project related TSA 2008-2009, the following four reports have been published:

  20. UN Adopts a New Global Standard to Measure the Sustainability of Tourism

    A groundbreaking statistical framework, developed under the leadership of UN Tourism, has been adopted by all 193 UN member states. The Statistical Framework for Measuring the Sustainability of Tourism (MST) thus becomes the internationally agreed reference framework for measuring the economic, social and environmental aspects of tourism.

  21. Northern Ireland Tourism Satellite Account (TSA) 2019

    The NI TSA provides economic information about the demand for goods and services associated with tourism, and their contribution to the NI economy. Northern Ireland Tourism Satellite Account (TSA ...

  22. Tourism satellite accounts in Europe

    Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU and EFTA countries who have compiled TSA for recent reference years and is a follow-up of the publication Tourism Satellite Accounts in Europe of 2016.

  23. How this beautiful Spanish tourist city became the green capital of Europe

    Pedal power: Valencia in Spain has been named the Green Capital of Europe thanks to sustainability credentials burnished by projects like the Turia Park, a 9-kilometer converted riverbed that's ...

  24. Tourism Satellite Accounts in Europe

    Tourism Satellite Accounts (TSA) is a framework developed to quantify the importance of tourism. This publication disseminates national results for a set of key TSA indicators for EU and EFTA countries who have compiled TSA for recent reference years and is a follow-up of the publication "Tourism Satellite Accounts in Europe" of 2013.

  25. Tourism Satellite Accounts (TSA) in Europe

    Tourism Satellite Accounts (TSA) in Europe 6 Background and introductory comments on the data The purpose of this publication is to disseminate the results of the TSA, although for different reference years (see Table 2) in the EU, EFTA and candidate countries which were transmitted to Eurostat from

  26. Oil-Rich Abu Dhabi's $35 Billion Gamble on Egypt

    Egypt's undeveloped Mediterranean coastline is the deal's main focus. Yet the huge financial injection also speaks to Abu Dhabi's strategic aims.

  27. Tourism Satellite Accounts in Europe 6

    Tourism Satellite Accounts (TSA) in Europe (2016 edition) 6 Representing 65 % of domestic tourism expenditure and 83 % of inbound tourism expenditure on average, overnight visitors were more important than same-day visitors for internal tourism expenditure. The analysis of the supply side is based on macroeconomic variables such as gross value ...

  28. Oil Market Report

    For the year as a whole, throughputs are projected to increase by 1.2 mb/d to average 83.5 mb/d, driven by the Middle East, Africa and Asia. Refining margins improved through mid-February before receding, with the US Midcontinent and Gulf Coast as well as Europe leading the gains. Global observed oil inventories surged by 47.1 mb in February.