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THE ECONOMIC IMPORTANCE OF TOURISM

Tourism in Australia continues to be a driver of growth for the Australian economy, with domestic and international tourism spend totalling $122 billion in 2018-19.

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In the financial year 2018–19, Australia generated $60.8 billion in direct tourism gross domestic product (GDP). This represents a growth of 3.5 per cent over the previous year – faster than the national GDP growth. Tourism also directly employed 666,000 Australians making up 5 per cent of Australia’s workforce.

44 cents of every tourism dollar were spent in regional destinations and tourism was Australia’s fourth largest exporting industry, accounting for 8.2 per cent of Australia’s exports earnings.

There are now more than 1.4 billion international travellers globally, spending US$1.5 trillion per year. In 2018-19, 9.3 million international visitors arrived in Australia, an increase of 3.0 per cent compared to the previous year. Australia is currently one of the highest yielding destinations in the world, with international visitors spending $44.6 billion in 2018-19 compared to the previous year, a growth of 5 per cent.  

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Australian National Accounts: Tourism Satellite Account

Estimates of tourism’s direct contribution to the economy including GDP, value added, employment and consumption by product and industry

• Australian National Accounts: Tourism Satellite Account Reference Period 2021-22 financial year
• Australian National Accounts: Tourism Satellite Account Reference Period 2020-21 financial year
• Australian National Accounts: Tourism Satellite Account Reference Period 2019-20 financial year
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Key statistics

• Tourism gross domestic product (GDP) rose 60.1% to $57.1b in chain volume terms in 2022-23 but remains below the 2018-19 peak of $63.4b.
• Tourism's contribution to economy GDP rose to 2.5% in 2022-23 but remains below the 2018-19 level of 3.1%.
• Domestic tourism consumption rose by $34.9b to $124.9b in 2022-23 while international tourism rose by $17.7b to $23.6b in chain volume terms.
• Tourism filled jobs rose to 626,400 in 2022-23 but remains below the 2018-19 peak of 700,900 filled jobs.
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(a) As the reference period for chain volume measures is 2021-22, chain volume measures and current prices are identical in 2021-22.

Direct tourism

All references to "tourism" are referring to "direct tourism" unless otherwise specified. A direct tourism impact occurs where there is a direct (physical and economic) relationship between the visitor and producer of a good or service. For more information, refer to the Methodology section.

Gross Domestic product

• In current price terms, tourism GDP rose 76.6% to $63.0b in 2022-23 to be above the 2018-19 level of $60.3b. Of this, tourism GVA was $57.2b and tourism net taxes on products $5.7b.
• In chain volume terms, tourism GDP rose 60.1% in 2022-23 but stands at 90.1% of its 2018-19 level.

Consumption

• In purchasers' price terms, domestic consumption increased 53.7% to $138.4b in 2022-23, the highest level in the time series.
• In chain volume terms , domestic consumption increased 38.8% to $124.9b in 2022-23, the highest level in the time series. 
• In purchasers' price terms, international consumption increased from $5.9b to $26.1b in 2022-23 but remains well below the 2018-19 level of $39.3b. 
• In chain volume terms, international consumption increased from $5.9b to $23.6b in 2022-23 but remains well below the 2018-19 level of $42.5b. 

Industry gross value added, current prices

• The accommodation industry's GVA increased to $7.7b in 2022-23 which is 25.5% higher than the 2018-19 level of $6.2b. 
• The cafes, restaurants and takeaway food services industry's GVA increased to $7.0b which is 17.6% higher than the 2018-19 level of $5.9b.
• The travel agency and information centre services industry's GVA increased to $6.1b which is 7.8% higher than the 2018-19 level of $5.7b.
• The air, water and other transport industry's GVA increased to $7.1b but remains 9.2% below the 2018-19 level of $7.9b. 
• The education and training industry's GVA increased from $1.2b to $3.2b but remains 47.9% below the 2018-19 level of $6.1b.

Tourism employment

• Tourism accounted for 4.1% of the filled jobs in the whole economy in 2022-23 but this is still lower than the 5.1% of filled jobs in 2018-19.
• The greatest increases in filled jobs in 2022-23 occurred in cafes, restaurants and takeaway food services (up 58,100 jobs), retail trade (up 32,500 jobs), accommodation (up 22,900 jobs) and education and training (up 19,600 jobs).
• Increases were recorded in both full-time filled jobs (up 46.0% to 317,600 jobs) and part-time filled jobs (up 37.2% to 308,800 jobs) in 2022-23.
• In 2022-23, filled jobs worked by females increased more than those filled by males with increases of 42.9% to 345,500 jobs and 39.9% to 280,900 jobs respectively.

Key considerations in data interpretation

Tourism estimates.

The International Visitor Survey (IVS) data sourced from Tourism Research Australia (TRA) is one of the key inputs to this account. Due to the COIVD-19 pandemic, IVS interviews were paused from June quarter 2020 to June quarter 2022 and data were imputed. Full sampling interviewing returned from March quarter 2023. Following a review by the TRA of the imputation method and changes to ABS Overseas Arrivals and Departures data used for IVS benchmarking, data for 2021-22 has been revised.

For more information see  International Visitor Survey Methodology and Overseas Arrivals and Departures . 

Changes in this issue

New process to derive economic measures.

This publication includes a methodological update. This update was undertaken to modernise the processing system and enhance the methodology. Consequently, the estimates for the 2019-20, 2020-21 and 2021-22 periods, which were previously published, have been revised. For an overview of the updated methodology, please refer to the Methodology page.

Status in employment

The term ‘status in employment’ has been changed to full-time and part-time employment to be consistent with  Labour Force, Australia . 

Updated job distribution in transport

The jobs that were previously reported under rail transport are now included in the air, water, and other transport industry.

Analysis of results

The contribution of tourism to the Australian economy has been measured using the demand generated by visitors and the supply of tourism products by domestic producers.

The diagram below provides a graphical depiction of the flow of tourism consumption through the Australian economy in 2022-23. What the diagram highlights is that, unlike traditional ANZSIC industries in the Australian National Accounts, tourism is not measured by the output of a single industry, but rather from the demand side i.e. the activities of visitors. It is the products that visitors consume that define what the tourism economy produces. The diagram shows how the value of internal tourism consumption (as measured by the sum of international and domestic tourism consumption in purchaser's prices, i.e. the price the visitor pays) is disaggregated to either form part of tourism GVA/tourism GDP, is excluded as it forms part of the "second round" indirect effects of tourism, or is output that was not domestically produced.

Flow of tourism consumption through the Australian Economy (a)(b)(c)

A flow chart representing the flow of tourism consumption through the Australian economy, year ending June 2023. Note, totals may not add due to rounding; tourism consumption is measured in purchasers’ prices unless otherwise specified. Other monetary aggregates are measured in basic prices; all figures in this diagram are in current price terms unless otherwise specified. Domestic tourist consumption to the value of $138,423 million is comprised of business and government, to the value of $25,433 million, and household, to the value of $112,990 million. International tourism consumption, to the value of $26,105 million, combines with domestic tourist consumption to create internal tourism consumption, to the value of $164,528 million. Internal tourism consumption splits into three values; internal tourism consumption at basic prices, to the value of $138,492 million; cost to retailers of imported goods sold directly to visitors, to the value of $13,506 million, and net taxes on tourism products to the value of $12,530 million. Internal tourism consumption at basic prices is comprised of cost to retailers of domestic goods sold directly to visitors, including wholesale and transport margins supplied domestically, to the value of $24,667 million; and direct tourism output, to the value of $113,825 million. Direct tourism output flows into two values; intermediate inputs used by tourism industries, to the value of $56,595 million; and direct tourism value added, to the value of $57,230 million. Cost to retailers of domestic goods sold directly to visitors and intermediate inputs used by tourism industries connect to second round (indirect) effects to supplier industries. Net taxes on tourism products flows into two values; net taxes on tourism products (in the case of goods, this will only include the net taxes attributable to retail trade activities), to the value of $5,720 million; and net taxes on indirect tourism output to the value of $6,810 million. Direct tourism value added and net taxes on tourism products combine to create direct tourism GDP, to the value of $62,950 million. Direct tourism value added is used to estimate total tourism employed persons, to the value of 626,400 tourism filled jobs.

Revisions are a necessary and expected part of accounts compilation as data sources are updated and improved over time. This issue includes revisions to tourism aggregates from 2019-20 to 2021-22.  Revisions in the 2022-23 release include:

• Revisions to both domestic and international tourism expenditure as a result of the TSA annual balancing and confrontation process. This is particularly the case for tourism products where the estimates have been modelled using a range of source data.
• Replacing modelled 2021-22 net taxes, imports and margins data with the latest issue of Australian National Accounts: Supply Use Tables (available on a T-1 basis) for 2021-22. 
• Revisions related to the new process to derive economic measures.
• Revisions to international tourism consumption due to the incorporation of updated 2021-22 data from Tourism Research Australia and updated data from the Survey of International Trade in Services for 2020-21 and 2021-22. 

Please note, the revisions to the chain volume level estimates across the time series are an expected part of re-referencing the indexes to 100 in the reference year.

Data downloads

Australian national accounts: tourism satellite account, create your own tables and visualisations.

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Caution: Data in Data Explorer is currently released after the 11:30am release on the ABS website. Please check the reference period when using Data Explorer. For information on Data Explorer and how it works, see the  Data Explorer user guide .

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Bulletin – December 2022 Australian Economy The Recovery in the Australian Tourism Industry

8 December 2022

Angelina Bruno, Kathryn Davis and Andrew Staib [*]

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The Australian tourism industry is gradually recovering from the COVID-19 pandemic that brought global travel to an unprecedented standstill. International tourism fell sharply in early 2020 and has only slowly recovered since restrictions were lifted in the first half of this year. By contrast, domestic tourism spending bounced back quickly as local restrictions eased and is now above pre-pandemic levels. This article outlines the recovery in the Australian tourism industry following the pandemic, the challenges the industry has faced in reopening, and the uncertainties around the outlook for the tourism industry over the next few years.

Introduction

Restrictions to contain the spread of COVID-19 and precautionary behaviour by consumers significantly disrupted the movement of people both domestically and internationally during the pandemic period. This had a devastating impact on many Australian businesses that provided services to domestic or international tourists. Nevertheless, many of these businesses have shown considerable resilience and flexibility, aided by a range of government support packages, and are now expanding to service the recovery.

This article presents a snapshot of the tourism industry through the pandemic, before focusing on the recovery over the past year. While international tourism is recovering only slowly, domestic tourism spending has rebounded strongly – to above pre-pandemic levels – as many Australians have chosen to take domestic rather than overseas holidays. The article draws on information from the Bank’s regional and industry liaison program to discuss the challenges the tourism industry has faced in meeting this sudden increase in demand, and the outlook for tourism activity over the next few years. Many tourism businesses have found it difficult to quickly scale up to meet demand, and these supply constraints have limited tourism activity and led to higher prices. Looking ahead, a continued recovery in tourism activity is expected as supply-side issues are gradually resolved and international tourism picks up further. However, there are a number of uncertainties around the timing and extent of this recovery.

International tourism

The onset of the COVID-19 pandemic led to a sharp drop in international tourism, as governments around the world implemented travel and border restrictions (Graph 1). In April 2020, international tourism arrivals declined globally by around 90 per cent and Australia’s international tourist arrivals effectively came to a standstill for several months.

The timing and extent of the recovery in international tourism has been uneven across the world, as national governments removed restrictions at a different pace. Globally, international tourism arrivals picked up to be around three-quarters of their pre-pandemic levels by September 2022. In Australia, international tourist arrivals rose slightly in mid-2021 under the temporary operation of the Australia–New Zealand travel bubble, and also in November 2021 as border restrictions eased in some parts of the country. However, it wasn’t until February 2022 – when Australia removed border restrictions for vaccinated persons – that arrivals began to substantially pick up. Since July 2022, people have been able to travel to and from Australia without being required to declare their vaccination status.

Short-term overseas arrivals to Australia (which include tourists but also those visiting for less than 12 months for business, education and employment purposes) picked up to be around half of pre-pandemic levels by September 2022 (Graph 2). However, short-term departures of Australian residents have picked up more quickly than short-term arrivals of overseas visitors, and so the net outflow of travellers has been larger than pre-pandemic levels in recent months.

Reasons for travel

The recovery in short-term travel to and from Australia has been particularly pronounced among those visiting friends and relatives (VFR) (Graph 3). VFR accounted for just over half of all international visitors’ spending over the year to June 2022, whereas it accounted for just under one-fifth in 2019 (Table 1). Short-term travel for business and education purposes has also picked up. However, the recovery in outbound business travel (including conventions and conferences) has outpaced inbound business travel, with relatively few major business events held in Australia in 2022. Short-term travel for employment reasons has almost fully recovered to its 2019 levels. By contrast, the number of visitors arriving in Australia for holidays has picked up only slightly, to be around one-third of its pre-pandemic level (holiday visitors accounted for only 10 per cent of international visitor spending over the year to June 2022, compared to nearly 40 per cent in 2019).

Working holiday makers and international students who are in Australia for more than a year are not included in the short-term arrivals data, but they make a significant contribution to tourism spending. According to Hall and Godfrey (2019), visitors who state the main purpose of their trip as education stay longer and spend more than leisure and business tourists. International students and individuals on working holiday visas have a high propensity to travel within Australia, and often their friends and relatives come to visit. The number of international students and working holiday visa holders in Australia has risen to be around two-thirds and one-half of their pre-pandemic levels in the September quarter of 2022, respectively.

The recovery in international visitors to Australia has been uneven across source countries, reflecting both travel restrictions and the quicker recovery in VFR relative to other types of travel (Graph 4). The recovery in the number of visitors from India, New Zealand and the United Kingdom has been faster than for other countries, possibly due to the close relationships residents from those countries have with Australian residents (in the 2021 Census, England and India were the top two countries of birth for Australian residents, other than Australia). While there has been a notable pick-up in people from India visiting friends and relatives, there has also been a pronounced recovery in the number of Indian students coming to Australia. By contrast, the number of Chinese visitors remains more than 90 per cent below pre-pandemic levels, due to ongoing travel restrictions to control the spread of COVID-19 in China. This is significant for the Australian tourism sector as, prior to the pandemic, Chinese visitors were the largest source of tourist spending and contributed around 20 per cent of total leisure travel exports in 2019 (or nearly 30 per cent if education-related travel is included).

Domestic tourism

Domestic tourism activity was severely disrupted by the COVID-19 pandemic, due to the introduction of strict restrictions on household mobility (‘lockdowns’) across the country in March 2020 (Graph 5). At the same time, a number of states and territories implemented interstate border restrictions and quarantine arrangements. As a result, domestic tourist visitor numbers declined sharply. By April 2020, domestic tourist numbers were less than 20 per cent of pre-pandemic levels.

The first lockdown ended for most parts of the country by the end of May 2020, although some restrictions on household activity and state border closures remained in place for an extended period of time. Melbourne re-entered lockdown for much of the second half of 2020. By the end of that year, however, a number of states and territories had eased restrictions and reopened domestic borders, allowing domestic visitor numbers to recover to around 80 per cent of pre-pandemic levels over the 2020/21  summer and the 2021 Easter holidays (Graph 6).

A third major disruption emerged in mid-2021, as a sharp rise in the number of Delta-variant cases led to the reintroduction of lockdowns in New South Wales, Victoria and the ACT. Around half of the Australian population were under significant restrictions for most of the September quarter of 2021 and domestic visitor numbers declined to around 40 per cent of pre-pandemic levels.

Domestic tourism numbers rebounded again during the 2021/22  summer holidays as health restrictions eased once more, but not to the levels of the previous year; the Omicron outbreak in early 2022 tempered activity somewhat. As concerns about Omicron abated, domestic visitor numbers again recovered, and have been around 85 per cent of pre-pandemic levels since Easter 2022.

While domestic visitor numbers remain below pre-pandemic levels, total domestic tourism spending and the average spend per visitor have been above pre-pandemic levels since March 2022. Some liaison contacts report that domestic travellers are staying longer than they did before the pandemic and spending patterns have become more like those on overseas holidays, with domestic tourists spending more on tours and experiences to explore Australia. This higher spending also reflects an increase in domestic travel prices (see below).

The recovery in domestic tourism spending in 2022, to around or above pre-pandemic levels, is evident in all states and territories (Graph 7). Naturally, states that experienced longer and stricter COVID-19 restrictions had much more significant declines in tourism activity over 2020 and 2021. Western Australia experienced the least disruption to the tourism industry, partly due to having fewer restrictions on movement, but also because the closed state border meant that more Western Australians were holidaying in their own state. In recent months, the Northern Territory and Queensland have been the recipients of domestic tourism spending well above 2019 levels, perhaps because these travel destinations are regarded as closer substitutes for overseas holidays.

Travel to regional areas recovered more quickly and fully than travel to capital cities (Graph 8). Regional areas were less affected by lockdowns and liaison suggests that travellers preferred to avoid more densely populated areas. There was also a shift towards driving holidays, which has greatly benefited regions within two to three hours’ drive from capital cities.

Challenges in reopening the Australian tourism industry

While pandemic-related declines in domestic and international tourism weighed heavily on the Australian tourism industry, many businesses have proved resilient and have experienced a strong rebound in demand from domestic tourists in recent months. Nevertheless, many businesses have found it difficult to scale up to meet this demand, and supply constraints have acted to limit tourism activity and led to higher prices.

In 2022, the biggest constraint on the recovery in tourism activity has been difficulty finding sufficient labour to service tourism demand. The tourism industry lost a large number of experienced staff during the pandemic – and so when domestic tourism recovered, the sector had to rapidly hire workers in a tight labour market. Online advertisements for tourism jobs rose to record highs by mid-2022 (Graph 9). These jobs have been difficult to fill. Liaison contacts have suggested that many of the Australians who had worked in the tourism industry prior to the pandemic have since found jobs in other industries. Moreover, many tourism-related jobs had previously been filled by international students and, particularly in regional locations, working holiday makers – many of whom left Australia during the pandemic and have been slow to return. On top of the difficulties in attracting and retaining staff, illness-related absenteeism has been elevated more broadly through 2022.

Tourism businesses in many regional areas have had additional difficulties attracting staff, partly due to a shortage of housing. An increase in net migration to these areas has contributed to very low rental vacancy rates in many popular tourist areas. In response, some holiday accommodation providers have resorted to housing their own staff.

There have also been some changes in consumer behaviour resulting from the pandemic that have made it harder for tourism businesses to plan and have sufficient staff available to meet demand. Trends such as increased working from home and a reduction in business-related day trips have created a larger gap between peak and off-peak periods for many tourism businesses. There are also sharper peaks and troughs in demand because there are fewer international tourists, who often travel at different times to domestic travellers (e.g. filling accommodation mid-week and outside school holidays). Booking lead times substantially shortened during the pandemic, though there is some evidence that perhaps these are lengthening out again. Nevertheless, booking lead times have always been shorter for domestic travel than international travel, so the change in the composition of travellers has made it more difficult for tourism businesses to plan ahead.

While labour has been a constraint across most of the tourism industry, a lack of capital equipment has been an additional constraint for some businesses. Many tourism-related businesses sold off or retired vehicles, boats, aircraft and other equipment during the pandemic when they could not operate and were in need of cash (Grozinger and Parsons 2020). The sudden and stronger-than-anticipated recovery in domestic tourism in 2022, combined with supply chain issues delaying the manufacture and delivery of new equipment and vehicles, has meant that many businesses did not have the capital equipment they need to service the increase in demand.

These supply-side constraints (in both labour and capital) have limited the tourism industry’s ability to ramp up to meet demand. Liaison suggests many tourism operators are operating below their previous capacity – for example, many have had to limit their operating hours because of lack of staff, and some accommodation providers have not been able to offer all their rooms for booking as they do not have enough staff to service them. Labour shortages and supply chain delays have also weighed on aviation capacity and contributed to a decline in domestic airlines ‘on-time performance’ over 2022 (Graph 10).

Similar constraints are also weighing on the recovery in international tourism. Contacts suggest that the recovery has been held back by limited flight availability, the higher cost of travel insurance and, in many cases, the higher cost of flights. Liaison contacts have indicated that delays in visa issuance in 2022 have also been a barrier for those seeking to travel to Australia. Over the past few months, however, visa processing times have shortened somewhat, and visa processing for applicants located overseas – including applicants for visitor, student and temporary skilled visas – have been given higher priority to allow more people to travel to Australia (Department of Home Affairs 2022).

The supply-side constraints in the tourism industry, combined with a strong pick-up in domestic demand and the higher cost of inputs such as fuel, have led to a sharp increase in domestic travel prices (Graph 11). Liaison contacts suggest that consumers have been relatively accepting of price rises for services essential to travel, such as accommodation. However, smaller operators – particularly in highly discretionary services, such as tours – have had less scope to increase their prices, and their margins have been squeezed by the higher costs of inputs such as food, fuel, energy and insurance costs. Prices for overseas travel have also increased significantly in recent quarters, as demand for flights has outstripped capacity, alongside rising jet fuel costs and increases in prices for international tours (ABS 2022).

The outlook

Looking ahead, tourism activity is expected to continue to recover as supply-side issues are slowly resolved and international tourism picks up further. Most liaison contacts suggest a full recovery will not occur until at least mid-2023; many expect it to take a few more years. There are a number of factors that will affect the timing and extent of the ongoing recovery in tourism, including:

• The easing of supply-side constraints : It is unclear how long it may take for some of the supply-side constraints in the industry to ease, including whether planned changes in flight availability will be sufficient to meet changes in demand, and whether the sector will be able to fill more job vacancies over time and as migration returns.
• The return of international students and working holiday visas : Many people have recently had working holiday visas approved and are expected to arrive over the coming year. Liaison contacts also expect international student numbers to increase over the next few years. The return of working holiday and student visa holders will increase demand for tourism services, and will likely alleviate labour shortages as they take jobs in the sector.
• Australians’ preferences for domestic and international travel : Demand for Australia’s tourism services may decline if Australians’ preference for overseas rather than domestic holidays picks up before international inbound tourism demand increases further. It is possible that cost-of-living pressures, combined with the higher cost of international travel, could lead Australian households to continue to prefer domestic holidays for a time. Nevertheless, many households have significant savings and pent-up demand for international travel after planned trips have been deferred over the past few years.
• The global economic outlook : Global economic conditions and the exchange rate affect decisions about whether to travel the long distance to Australia (as they have in the past) (Dobson and Hooper 2015). Financial concerns and the rising cost of living could make expensive, long-haul travel less attractive.
• The timing and extent of recovery in Chinese tourism : As noted above, China accounted for a large share of tourism spending prior to the pandemic. The outlook for Chinese tourism (and international students from China) remains highly uncertain and will depend on a number of factors, including China’s policies to restrict the spread of COVID-19 , the outlook for the Chinese economy and the travel preferences of Chinese tourists more generally.

Restrictions to contain the spread of COVID-19 and precautionary behaviour significantly disrupted the movement of people both domestically and internationally throughout the pandemic. Since restrictions have eased, international travel has been slow to recover, but domestic tourism spending has rebounded to be above pre-pandemic levels and many tourism service providers are currently operating at capacity. Looking ahead, tourism activity is expected to continue to recover, as supply-side issues are slowly resolved and international tourism picks up further. Australia remains an attractive destination for both domestic and international tourists, and the resilience and flexibility demonstrated by Australian tourism businesses in recent years bode well for the opportunities and challenges that lie ahead.

The authors are from the Regional and Industry Analysis section of Economic Analysis Department. The authors are grateful for the assistance provided by others in the department, in particular Aaron Walker and James Holloway. [*]

ABS (Australian Bureau of Statistics) (2022), ‘Main Contributors to Change’, Consumer Price Index , June.

Department of Home Affairs (2022), ‘Visa processing times’, viewed 14 November 2022. Available at <https://immi.homeaffairs.gov.au/visas/getting-a-visa/visa-processing-times>.

Dobson C and Hooper K (2015), ‘ Insights from the Australian Tourism Industry ’, RBA Bulletin , March, pp 21–31.

Grozinger P and Parsons S (2020), ‘ The COVID-19 Outbreak and Australia’s Education and Tourism Exports ’, RBA Bulletin , December.

Hall R and Godfrey A (2019), ‘Edu-tourism and the Impact of International Students’, International Education Association of Australia, 3 May.

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Wish You Were Here? The Economic Impact of the Tourism Shutdown from Australia’s 2019-20 ‘Black Summer’ Bushfires

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• Published: 30 January 2024
• Volume 8 , pages 107–127, ( 2024 )

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Tourism, including education-related travel, is one of Australia’s top exports and generates substantial economic stimulus from Australians travelling in their own country, attracting visitors to diverse areas including World Heritage rainforests, picturesque beachside villages, winery townships and endemic wildlife. The globally unprecedented 2019-20 bushfires burned worst in some of these pristine tourist areas. The fires resulted in tourism shutting down in many parts of the country over the peak tourist season leading up to Christmas and into the New Year, and tourism dropped in many areas not physically affected by the fires. Our research quantified the cost of the short-term shock from tourism losses across the entire supply chain using input-output (IO) analysis, which is the most common method for disaster analysis; to this end, we also developed a framework for disaggregating the direct fire damages in different tourism sectors from which to quantify the impacts, because after the fires, the economy was affected by COVID-19. We calculated losses of AU$2.8 billion in total output, $1.56 billion in final demand, $810 million in income and 7300 jobs. Our estimates suggest aviation shouldered the most losses in both consumption and wages/salaries, but that accommodation suffered the most employment losses. The comprehensive analysis highlighted impacts throughout the nation, which could be used for budgeting and rebuilding in community-and-industry hotspots that may be far from the burn scar.

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Introduction

Australia’s 2019-20 bushfires were unprecedented globally, burning through more than one-fifth of its temperate broadleaf and mixed-forest biome (Boer et al. 2020 ) over several months, and including every State and Territory. Starting in what was then Australia’s hottest and driest year on record (Norman et al. 2021 ), in a nation used to increasing extremes (Gergis 2018 ), the fires killed or displaced an estimated three billion animals (van Eeden et al. 2020 ) in addition to at least 33 people (Royal Commission into National Natural Disaster Arrangements 2020 ). At its peak, Australia’s worst fire, the Gospers Mountain mega-fire that formed from the convergence of six fires, was one day away from spreading from bushland to the built-up Sydney suburb of Hornsby (McDonald 2020 ), where 20,000 homes lie within 100 m of the bush (Hannam 2016 ). The ferocity of the fires has also raised questions about cumulative or irreversible damage, for example to rainforest dating back to the Jurassic Period, including cultural heritage (Australian Government Department of Agriculture, Water and Environment 2020 ); animals (Murphy and van Leeuwen 2021 ) such as the koala becoming endangered in New South Wales (NSW), Queensland (QLD) and the Australian Capital Territory (ACT) (Dalton 2022 ); and potentially climate targets as a result of greenhouse gases emitted from the fires (van der Velde et al. 2021 ). The fires resulted in about 830 million tonnes of carbon dioxide-equivalent emissions (Australian Government Department of Industry  2020 ), which is one-and-a-half times Australia’s annual emissions for the previous year to March 2019, of 538.9 Mt C0 2 -e (Australian Government Department of Industry & Resources  2019 ). The Australian government (2020) noted that bushfires tend to result in a carbon sink in future years as a result of regrowth, however, concerns have been raised regarding the extent of Australia’s 2019–2020 fires in terms of post-fire recovery (Boer et al. 2020 ).

The bushfires (also called wildfires) started in mid-2019; in the nation’s north, what became known as the Queensland bushfires between September to December 2020, marked the start of a catastrophic season. The QLD fires affected a number of tourism areas, including the World Heritage Lamington National Park, where the historic Binna Burra Lodge was destroyed, along with Parks and road infrastructure (Binna Burra 2022 ; Queensland Government 2020 ). A State of Emergency had been declared briefly in November. In December the fires intensified in NSW, VIC and South Australia (SA) in the lead-up to Christmas and in the early New Year period, disrupting the peak tourist season, with many tourists stranded, evacuated or cancelling trips. A “Tourist leave zone” was set up in NSW, extending 500 km from Batemans Bay along the coast to the VIC border in the first week of January. The Rural Fire Service warned of upcoming weekend fires “the same or worse” than the devastating New Year’s Eve fires and encouraged holiday-makers to get out of harm’s way and allow emergency workers to focus on protecting the local communities (BBC 2020 ). Tourism Australia paused its advertisement Matesong , which focused on celebrity Kylie Minogue (Bourke 2020 ) and an image of the spots of bushfires over a month on a map of Australia was Tweeted by singer Rhianna and went viral, giving the impression that the whole of the country was on fire simultaneously (Rannard 2020 ). In Australia’s 4th -most visited island, SA’s Kangaroo Island, catastrophic conditions resulted in evacuations and the death of two people before the fires were brought under control in late January (Kangaroo Island Council 2020 ). With conditions improving in some areas such as the NSW Blue Mountains, Australia’s capital, the ACT became the worst-hit region in February (Tourism Research Australia 2020a , b ), experiencing the most hazardous air quality in the world (Norman et al. 2021 ). Melbourne was also affected by hazardous air-quality levels and smog from the fires made its way across the globe (Rodriguez 2020 ), before the bushfire season ended in March 2020.

In some regions directly affected by fires, business takings were reduced by more than 70% in the important summer holiday period; in addition to losses from tourism, residents also spent less because of safety- and supply-chain disruptions (Indigo Shire Council 2020 ; McIlwain 2020 ). Research showed that at its peak, awareness about the fires was close to 100% across all markets (Tourism Australia 2020 ), and the government’s export arm noted that tourism and education was its most-impacted industry (Austrade 2020 , p. 2).

The federal government provided an AU$76 million Rebuilding Australian Tourism package and among other initiatives, Tourism Australia executed a successful “Holiday here this year” campaign after some of the worst of the fires, in January, encouraging Australians to return to bushfire-affected areas and support local communities across the country. In February an international campaign was launched, called “There’s still nothing like Australia”, building on a pre-fire campaign, “There’s nothing like Australia”; however, all marketing was stopped because of increasing coronavirus travel restrictions, and Australia comprehensively closed its international borders on 20 March 2020.

What has been referred to as Australia’s “Black summer” could be a sign of things to come (Canadell et al. 2021 ; Handmer et al. 2018 ; Norman et al. 2021 ; Van Oldenborgh et al. 2021 ) in a continent already subject to heatwaves and drought, which is being exacerbated by climate change (Gergis 2018 ). In particular, bushfires have been increasing their share compared to other natural hazards; this trend has been noted in Australia as well as globally (Handmer et al. 2018 ; Swiss Re 2021 ).

This is, to our knowledge, the first supply-chain analysis of the cost of the 2019-20 bushfire tourism damages on the Australian economy and is based on the popular technique input-output (IO) analysis. Drawing on surveys by Tourism Research Australia about the direct impact of the bushfires, we calculate losses across the entire supply chain, uncovering hotspots in particular sectors and regions.

This paper is set out as follows: Brief overviews of IO analysis, as well as the IO disaster analysis stream and its application to this study are detailed in the Methods section. Key findings are set out in the Results, risks to long-term tourism as well as future research recommendations are outlined in the Discussion, and we then conclude.

Overview of Input-Output Analysis

This study draws on input-output (IO) analysis, a methodology that is globally standardised and enables impact analysis along the entire supply chain. In comparison to production-based accounting, where impacts are relegated to the producer or territory responsible, IO underpins consumption-based accounting because it traces the impact of intermediate industry demand in addition to the impact of final demand from the consumption of a good or service (Afionis et al. 2017 ). In this way, IO analysis facilitates comprehensive impact analysis such as carbon footprints that include all scope-3 emissions. Furthermore, IO analysis facilitates researcher and policy expert insights, through the ability to provide highly disaggregated information at the sectoral and regional levels and across a wide range of indicators (Wiedmann 2009 ); outputs range from headline figures on gross domestic product (GDP) and environmental impacts to a breakdown of employment impacts in specific regions or sectors.

IO analysis was developed by economist Wassily Leontief during the 1930s and 1940s to enable practitioners to quantify the relationship between inputs into, and outputs of economic activity, including pollution (Leontief 1936 ). With the methodology demonstrating the relationships between consumption and production and enabling the identification of supply-chain hotspots (Leontief 1966 ), IO analysis increased in popularity during the 1970s oil shocks, winning Leontief a Nobel Prize (The Nobel Prize 1973 ).

Because it is based on the economic structure of nations, Leontief’s prize-winning formula overcomes barriers such as data collection from indirect suppliers faced in traditional life-cycle assessment (LCA). Traditional LCA tends to be limited to direct (on-site) impacts or else typically does not extend beyond direct suppliers or suppliers of direct suppliers. However, hybrid IO-LCA studies can make use of LCA’s bottom-up data while benefitting from the calculation of higher orders of production via IO’s top-down approach. The structure of IO analysis additionally lends itself to numerous applications related to economic activity (Wiedmann 2009 ), extending to environmental and social indicators and answering complex and novel research questions (for a recent example, see Malik et al. ( 2022 ).

Multi-region input-output (MRIO) models were expanded globally by research collaborations (Lenzen et al. 2017a , b , 2013 ; Malik et al. 2019 ; Tukker and Dietzenbacher 2013 ). These developments were supported by increased data availability and improvements in high-performance computing that enables the analysis of billions of supply chains.

Global, multi-regional analysis, also referred to as GMRIO draws on data issued regularly by more than 100 statistical agencies around the world and is routinely employed by organisations such as the OECD, the European Commission and the World Bank. Recently, IO analysis was used to build an open-access database on behalf of the UN for the measurement of countries’ economic, social and environmental indicators against the Sustainable Development Goals (SDGs), for standardised reporting and hotspot analysis (Lenzen et al. 2022 ).

IO analysis draws on input-output tables (IOTs) from countries’ statistical agencies as part of the almost universal System of National Accounts 2008 framework (European Commission et al. 2009 ). IO analysis also draws from international data providers such as Eurostat and sources such as UN Comtrade, the data from which can be used to build inter-country supply-and-use-tables that form the basis of IOTs. Just as the System of National Accounts has facilitated international comparisons across significant economic activities, so too has IO and its extended environmental, social and disaster analysis facilitated comparisons of impacts across companies, industries and regions; IO analysis is governed by standards set by the United Nations (UN Statistics Division 1999 ).

In this study, negative entries in the final-demand and value-added blocks of the pre-disaster MRIO tables were removed by mirroring, as described in Sect. 4 of Lenzen et al. ( 2014b ).

Disaster Analysis Sub-Stream of IO

Research focusing on quantifying the impacts of disasters was not common until a string of disasters in the decade from the 1990s, including the Kobe earthquake in 1995, the Indian Ocean earthquake and tsunami in 2004 and Hurricane Katrina in 2005 (Okuyama 2007 ). The need for routine, effective and efficient quantification of economic impacts, in order to adapt and mitigate against catastrophic disasters, is now considered urgent (Okuyama and Santos 2014 ). An increasing focus on quantifying disasters, assisted by increased data availability has led to the development and advancement of empirical research methodologies including econometric models, social accounting matrix (SAM), computable general equilibrium (CGE) and IO disaster analysis as well as hybrid models (for example, as proposed by Oosterhaven ( 2017 ). The relative strengths and applicability of various approaches have been well-discussed in the disaster analysis literature; CGE and IO models are commonly used (Galbusera and Giannopoulos 2018 ; Steenge and Bočkarjova 2007 ; Zhou and Chen 2021 ), with IO analysis increasingly popular in recent years (Bočkarjova et al. 2004 ; Li et al. 2013 ; Schulte in den Bäumen et al. 2015 ) to become the most commonly employed method for disaster impact analysis (Okuyama and Santos 2014 ). For example, IO analysis has been used recently to quantify the impacts of cyclone Debbie in Australia (Lenzen et al. 2019 ), earthquakes in Taiwan (Faturay et al. 2020a ), COVID-19 (Lenzen et al. 2020 ) and the Venezuelan energy crisis (Li et al. 2022 ).

With IO models previously established as the major tool of impact analysis that assesses more than one region (Richardson 1985 ), this methodology plays a crucial role in tracing the indirect, flow-on effects from large-scale disasters in an increasingly globalised world (Steenge and Bočkarjova 2007 ). IO post-disaster analysis calculates impacts from direct damages data rather than relying on expected future trends as inputs to the model. In addition to its universality, IO disaster assessment because of its relatively straightforward structure, has also enabled integrative approaches where IO is incorporated with other models to enable them to assess higher-order (indirect) effects, such as for CGE (Koks et al. 2016 ; Rose 1995 ) and transportation networks (Okuyama 2007 ). In comparison, CGE’s approach in simulating future states is more flexible, which can be a weakness. In a meta-analysis of CGE studies, Zhou and Chen ( 2021 ) concluded that variability in results because of practitioner assumptions inherent in the modelling remain a challenge. An assumption that the market produces optimal outcomes and the economy re-adjusts towards equilibrium over the longer term can provide an underestimation of losses, particularly where a large disruption occurs in a short timeframe (less than a year), which typifies natural hazards (Rose 2004 ). Oosterhaven ( 2022 ) details a new approach, which has been referred to as IO/SU non-linear programming and allows for substitutability, as well as price rises, which minimise business disruption; however, it may be less suitable for quantifying the impacts of complex disasters where shortages are common, along with business shutdowns. Recognising the imbalance that exists in the aftermath of a disaster and the new situation the economy faces as a result of spillover impacts along supply chains, Steenge and Bočkarjova ( 2007 ) built on the concept of a basic equation, using IO analysis, to describe the pre- and post-disaster economies, with the idea that governments can use the model to determine market interventions and analyse alternate pathways to the desired post-catastrophe equilibrium.

We follow the approach by Steenge and Bočkarjova to determine the short-term post-disaster loss for the economy, which has been built on in recent studies to improve the disaster model. Limitations of IO disaster analysis have included the fact that the rigid structure requires constant prices and does not take account of real-world behaviour such as substitution of goods and services; however, advances have gone some way to addressing several limitations. Steenge and Bočkarjova described a “basic equation” that can be represented as \(\stackrel{\sim}{\mathbf{x}}=\left(\mathbf{I} -\widehat{\varvec{\upgamma }} \right)\mathbf{x}\) – where the potential maximum production of each sector of the impacted economy \(\stackrel{\sim}{\mathbf{x}}\) takes into account the event matrix of losses placed on the diagonal, gamma hat ( \(\widehat{\varvec{\upgamma }}\) ), of proportionate production losses that shinks the pre-disaster economy \(\mathbf{x}\) , so that losses in total output are the difference between this new output level and the initial output (Bočkarjova et al. 2004 ; Steenge and Bočkarjova 2007 ). Total output is determined according to standard IO anaysis: \(\mathbf{x}={(\mathbf{I} -\mathbf{A})}^{-1}\mathbf{y}\) , where \(\mathbf{I}\) is an identity matrix of 1’s on the diagonal and 0’s elsewhere; the \(\mathbf{I}\) matrix is the same dimensions as the direct requirements matrix \(\mathbf{A}\) to which it relates, which is a “production recipe” of the selected sector groupings comprising the economy, with the inputs into each sector are a fraction adding up to $1 (or other monetary unit as relevant) worth of production; \(({\mathbf{I} -\mathbf{A})}^{-1}\) being the famous Leontief inverse \(\mathbf{L}\) that includes the entire supply chain, and demand from end-consumers \(\mathbf{y}\) (also referred to as final demand or consumption) being equal to \(\left(\mathbf{I} -\mathbf{A}\right)\mathbf{x}\) . A relaxation of Steenge’s approach is described by Schulte in den Bäumen et al. ( 2014 ). Developed to be used in instances when the “unbound” constant production recipe approach results in negative final demand ( \(\mathbf{y}\) ) values, this method assumes that very small, marginal inputs to production, in the \(\mathbf{A}\) matrix, are substitutable, meaning intermediate demand can shoulder some of the shock to ensure no negative final demand in order to reflect better the real world. To achieve this, marginal inputs in \(\mathbf{A}\) are reduced to zero to ensure the post-event final demand sectors in \(\mathbf{y}\) are either zero or positive.

An alternative to removing marginal inputs in \(\mathbf{A}\) was developed by Faturay et al. ( 2020a ) because small values may nonetheless be important in complex supply-chain interactions; this approach uses optimisation coding in MATLAB to determine the maximum total output losses. Given the disaster “basic equation” \(\stackrel{\sim}{\mathbf{x}}=\left(\mathbf{I}-\widehat{\varvec{\upgamma }} \right)\mathbf{x}\) , with \(\mathbf{x}={(\mathbf{I}-\mathbf{A})}^{-1}\mathbf{y}\) , the optimisation approach to determining the post-disaster economy enables changes in intermediate demand ( \(\mathbf{A}\) ), final demand \(\mathbf{y}\) and total output ( \(\mathbf{x}\) ) in order to meet the constraints of no negative values in final demand ( \(\mathbf{y}\) ). This model was used in a comprehensive footprint of the first COVID-19 lockdown (Lenzen et al. 2020 ) and more recently in projections of climate impacts on the Australian food system (Malik et al. 2022 ). A new “minimum-disruption” approach to modelling the post-disaster transition has also been proposed by Li et al. ( 2022 ), who apply priority weights to essential sectors to guard against the economic shock. In this novel study of the tourism impacts of Australia’s 2019-20 mega-fires, we use the optimisation approach developed by Faturay et al. ( 2020a ) described above, because of its application to numerous recent disasters.

Data Collection

Tourism Research Australia (TRA) published a range of data in the National Visitor Survey ( 2020b ) and International Visitor Survey ( 2020a ); in order to provide a more comprehensive understanding of the losses from the bushfires, TRA provided, upon request, quarterly expenditure including day trips (personal communication, 31 August, 2022). Only data from January-March 2020 was used because expenditure only started falling in that quarter. By the following quarter, the fires had been brought under control and it would not be possible to determine if any bushfire tourism losses flowed through to the following quarter because non-essential travel was banned because of the coronavirus pandemic. TRA also provided the underlying data from surveys that sought to determine the proportion of tourists who were impacted by the bushfires (personal communication, 10 & 14 June, 2022). These percentages were applied to the March quarter losses to ensure no losses because of the coronavirus were included. In order to disaggregate losses by sector, the proportionate representation of tourism- and tourism-related sectors from TRA’s 2018-19 State Tourism Satellite Accounts (TSA) (Austrade & Tourism Research Australia  2020 ) was applied to the 2019-20 losses (Austrade & Tourism Research Australia  2021 ). The UN World Tourism Organization and Australian Bureau of Statistics definitions of tourism relate to expenditure by visitors to an area where the visit is for less than a year; TSAs, which comprise expenditure on tourism and related activities of nations, include business- and education-related travel, in other words, any visits, as opposed to long-term moves. Online Resource 1 SI 2.7 provides further details about the calculations of direct damages.

The Event (Gamma) Matrix

Losses were divided across eight regions (each State and Territory) and 39 sectors, which included the most-affected sectors as well as other key primary, secondary and tertiary sectors. The post-disaster losses were then compared with the pre-disaster total output for the year, for the relevant sectors and regions in the MRIO and converted into a proportion. A separate gamma matrix of capital damages was also compiled, with the treatment of infrastructure, including depreciation, following the approach described in previous IO disaster studies (Faturay et al. 2020a ; Lenzen et al. 2019 ) (see Online Resource 1 SI 2.6 for details); added together, these make up the final gamma matrix of proportionate losses for the economy. For example, 0.02 for South Australian Accommodation means that income in the accommodation sector in SA reduced 2% for the year; areas where no known direct damage occurred are 0. Table  1 shows the final gamma matrix ( \(\varvec{\upgamma }\) ) of direct losses and capital damages.

As can be seen in Table  1 , no losses were recorded for Tasmania (TAS) because that State recorded increased tourism expenditure (of $1.1 million). This study quantified the total impact from direct losses, across the supply chain, but did not quantify the impact of gains (in Tasmania); in the same way, insurance paid out can be seen as an economic stimulus, as can hospitalisations in providing money for the healthcare sector; these are also not included in IO disaster-analysis calculations. In this way, a standardised approach is followed in quantifying the short-term economic cost of the losses from each impacted sector.

MRIOs are based on countries’ input-output tables (IOTs) in the National Accounts so the aggregated sectors were selected from 1284 sectors in the Australian Industrial Ecology Virtual Laboratory ( http://www.ielab.info/ ), which are based on the Input-Output Product Classification in the Australian National Accounts (Australian Bureau of Statistics 2009 ). The States and Territories were aggregated from the 2214 Statistical Area level 2 (SA2) regions (Australian Bureau of Statistics 2011 ). A concordance matrix to aggregate the sectors and regions was converted into a MRIO of the Australian economy in the IELab. The IELab developed at the University of Sydney (Lenzen et al. 2014a ) was Australia’s first such collaborative cloud-based platform for IO analysis. Such platforms overcome the time-consuming nature of MRIO compilation through an open-source approach, with the source data updated regularly. IELabs have now been built for Indonesia (Faturay et al. 2017 ), Japan (Wakiyama et al. 2020 ), Taiwan (Faturay et al. 2020a ), China (Wang 2017 ) and the United States (Faturay et al. 2020b ), and the Global MRIO Lab infrastructure was used to build GLORIA on behalf of the UN International Resource Panel as the database for the open-access global Sustainable Consumption and Production Hotspot Analysis Tool (Lenzen et al. 2022 ).

Indicators for Impact Analysis and Unravelling supply Chains Through Production Layer Decomposition

The satellite account attached to the tailored MRIO was selected during the MRIO compilation in the IELab, with matrix calculations then carried out in MATLAB. In this study, the satellite account employment (in addition to the related indicator, income) was selected as an indicator for impact analysis, to be quantified along with the post-event total output ( \(\mathbf{x}\) ) and final demand ( \(\mathbf{y}\) ).

The change in final demand ( \(\varDelta \mathbf{y})\) is used to calculate the employment and income impacts of the disaster using the formula \(\mathbf{q}\mathbf{L}\mathbf{y}\) , where \(\mathbf{q}\) is the multiplier derived by dividing the desired indicator by pre-disaster total output \(\mathbf{x}\) , and \(\mathbf{L}\) represents the entire supply chain \({(\mathbf{I}-\mathbf{A})}^{-1}\) . Income data is extracted from the first row of the value-added block of the MRIO ( \(\mathbf{v}\) ), while the aggregated total employment data is contained in the 24th row of the employment satellite account in the IELab. In both instances, the \(\mathbf{q}\) matrix is calculated using element-wise multiplication so that the intensity sectors/multipliers align with the final demand sectors, enabling production layer decomposition (PLD) for a disaggregated view of impacts. The entire impact \(\mathbf{q}\mathbf{L}\mathbf{y}\) is unravelled at each production layer through the following decomposition:

where \(\mathbf{q}\mathbf{y}\) is the direct impact (first layer in the PLD), \(\mathbf{q}\mathbf{A}\mathbf{y}\) is the additional impact from direct suppliers involving the \(\mathbf{A}\) matrix of direct requirements, \(\mathbf{q}{\mathbf{A}}^{2}\mathbf{y}\) is the impact from suppliers of the direct suppliers and so on, to infinite (n) layers/orders of production i.e., direct suppliers as well as all indirect suppliers.

Limitations

Our results may be conservative because it is possible that tourists would have spent even less than anticipated in the Tourism Research Australia surveys on which this bushfire research is based, had it not been for the first COVID-19 lockdown, which then became the primary reason for slashed tourism expenditure. We calculated bushfire-related tourism expenditure losses from the National Visitor Surveys and International Visitor Surveys that were carried out from 21 January to 15 March (personal communication, 15 & 17 June, 2022), which asked tourists about the extent to which their changed behaviour occurred because of the bushfires. Had it not been for the pandemic, the bushfire impact on tourism may have measured more post-fire, without being mixed up with losses from concurrent disasters, meaning we would have identified potentially higher bushfire losses. As well, direct bushfire damages data were only available for regions, not sectors, apart from tourism-related infrastructure. Although sectoral expenditure is available in the 2019-20 ABS Tourism Satellite Account, this period included COVID-19; therefore, assumptions had to be made about bushfire-specific direct sectoral losses, based on the usual proportionate representation of tourism spend, which were then used to calculate total losses including indirect impacts (see Online Resource 1 SI 2.7 for details about the calculation of the direct damages data).

From the Tourism Research Australia quarterly data and bushfire surveys, we calculated direct losses in tourism expenditure of $1629.9 million nationwide, in addition to $112.6 million in depreciated infrastructure (in other words, $1742 million direct losses for the year, including infrastructure). In terms of regional breakdown, these direct losses (including infrastructure) were: NSW - $760.5 million, VIC - $347 million, QLD - $343.7 million, SA - $113.8 million, Western Australia (WA) - $135.6 million, TAS - $0, ACT - $22.2 million and Northern Territory (NT) $19.7 million. This triggered losses across the entire supply chain totalling $2801.6 million in total output, $1561.8 million in consumption, $809.4 million in income, and employment losses of more than 7292 full-time equivalent (FTE), which impacted sectors and regions in different ways. Taking the total output losses into account as a proportion of the pre-fire total output, in 2018-19, the losses were worst in NSW, closely followed by SA, which experienced significant fires not only in the Adelaide Hills winery and day-trip region near the State’s capital but also in Kangaroo Island, where almost half the island burned (Kangaroo Island Council 2020 ). Next in terms of proportionate losses was NT, despite the fact that this region did not suffer catastrophic fire conditions.

Geographic Distribution of the Employment Losses

The geographical spread of losses in employment are similar to losses in the other indicators measured in this study. Figure  1 shows that almost half of the 7292 jobs lost were experienced in NSW, the most populous State, which is also where the fires were worst.

Losses in full-time equivalent (FTE) jobs across Australia resulting from the tourism losses because of the 2019-20 fires. The most populous State, New South Wales (NSW), suffered about twice as many losses in employment as its neighbouring eastern States, equivalent to 3171 full-time jobs. The Northern Territory (NT), although not suffering catastrophic fires, nonetheless lost 75 jobs from the short-term shock. Nationwide, more than 7292 jobs were lost. Other regions: Victoria (VIC), Queensland (QLD), South Australia (SA), Western Australia (WA), Tasmania (TAS), Australian Capital Territory (ACT)

Figure 1  shows that although most of the employment losses were concentrated around Australia’s east-coast States that also suffered the most direct tourism losses, spillovers were experienced across the nation. QLD and VIC suffered about half as much job losses as NSW, at 1499 and 1430 respectively, and SA experienced about one sixth of NSW’s losses, at 516, followed by WA at 479. Tasmania, despite not suffering direct tourism damages, lost 13 jobs because of supply-chain impacts resulting from the contraction in consumption. The ACT lost substantially more jobs (110), closely followed by the NT (75 jobs).

Sectoral and Regional Hotspots

As can be seen in Fig.  2 that compares losses in consumption (final demand) and related income and employment, from an industry perspective, hospitality and transport were the worst hit overall, with the recreation and educational sectors also significantly impacted.

Losses in consumption, income and employment, across Australia’s eight States and Territories and disaggregated by broad sector groupings, because of the tourism shutdown from the 2019-20 bushfires. Hospitality and transport suffered the most losses. Regional abbreviations: New South Wales (NSW), Victoria (VIC), Queensland (QLD), South Australia (SA), Western Australia (WA), Tasmania (TAS), Australian Capital Territory (ACT), Northern Territory (NT)

The “Accommodation” and “Cafes, restaurants and take-away” study sectors, which make up our aggregated hospitality grouping, together suffered the most losses in the consumption, income and employment indicators. However, disaggregating into our 39 individual sector groupings in this study, the aviation-led “Air, water and other transport” sector was the worst-hit in consumption and income (but not in employment, where “Accommodation” dominated), losing $292 million and $159 million respectively.

NSW shouldered the most losses, including 44% of both consumption and income impacts; NSW differed somewhat from the other regions in that the single most-impacted sector, out of the 39 sector groupings in this study, was “Cultural and recreational services” across consumption, income and employment (reducing by $148 million, $73 million and 662 jobs respectively), although when considering “Accommodation” and “Cafes, restaurants and take-away” together as hospitality, the hospitality industry dominated NSW consumption, income and employment losses. The particularly large NSW losses in “Cultural and recreational services” is in part a reflection of the destruction of more than $200 million in Crown Lands and National Park infrastructure, (which was then depreciated - see Methods ). These impacts including on areas such as the World Heritage Blue Mountains National Park (where approximately 82% was burnt (Australian Government Department of Agriculture, Water and the Environment 2020 ) would also have resulted in flow-on impacts to the local community, as well as more broadly, in areas such as reduced consumption of lodgings, restaurant meals and transport. Differences can also be seen between indicators for regions that suffered similar total losses. These include: VIC suffered more losses than QLD in consumption but the reverse was the case for related income and employment, with a key driver being greater losses in VIC’s consumption of education and training ($37 million loss compared to $20 million). As well, WA experienced more losses than SA in consumption ($118 million compared to $102 million) and income ($60 million compared to $52 million) but not in employment (479 jobs lost compared to 516), where SA suffered particularly more losses in hospitality (229 jobs compared to 179. SA hospitality losses included from the Kangaroo Island destination the Southern Ocean Lodge, which was destroyed by the fires and for which the rebuild was estimated at $50 million (Boisvert 2022 ). From a per-capita perspective, the NT was particularly impacted; for example, the NT had the smallest population in Australia in March 2020, at 245,400 people, which was more than half the TAS population of 539,600 (Australian Bureau of Statistics 2020 ), however, the NT lost more income, at $9.3 million compared to $1.4 million. The underlying data on losses is in Online Resource 1 .

Chain Reactions Along Supply Chains

In the following analysis, we discuss the impact on income and employment, which was triggered by the contraction in consumption.

Figure 3  shows that almost all the impacts were felt within about six or seven layers in the upstream supply chain, after which the additional losses per layer particularly start to level off.

Production layer decomposition (PLD) of regions ( a ) and broad sector groupings ( b ). Layer 1 represents the impact from the direct tourism losses, layer 2 represents the impact from direct suppliers and so on, with the cumulative losses up to 10 layers depicted, which represent most of the losses. Employment losses measured in full-time-equivalent (FTE) jobs. Regions: New South Wales (NSW); Victoria (VIC); Queensland (QLD); South Australia (SA); Western Australia (WA); Tasmania (TAS); Australian Capital Territory (ACT); Northern Territory (NT)

The least-impacted regions tended to have a longer tail of losses because of supply-chain spillovers. In comparison, the most-impacted regions, the eastern States of NSW, VIC and QLD, experienced more losses directly or within a few orders of production.

Similarly, key industries such as transport and hospitality experienced more losses earlier on, while “Other services”, which includes sectors not directly impacted such as “Finance, property and other business services”, continued to experience significant losses further along the supply chain.

Regional Case Studies

Losses in the most-impacted State, NSW, followed a similar trend to the national results so in this section we highlight examples of divergence from the aggregated results, in the Australian Capital Territory and Tasmania. Additional disaggregation for regions and sectors and the underlying data are in Online Resource 1 SI 4 .

The dominance of losses in accommodation and the aviation-led transport sector in Australia’s capital may in part be explained by the “fly-in-fly-out” economy (Fig. 4 ).

Production layer decomposition of the impact of tourism losses from the 2019-20 bushfires in the Australian Capital Territory, for income and full-time equivalent (FTE) employment in broad sector groupings. Although the number of upstream supply-chain interactions is theoretically infinite, results are illustrated for up to 10 orders of production, which comprise most of the losses

The ACT experienced the biggest income impact in the transport industry, led by the “Air, water and other transport” sector, which lost $3.4 million. These losses are in part because of the extreme bushfire smoke that the ACT’s capital Canberra experienced, which resulted in the airport being closed for hours on one of the worst days (Foster 2020 ). “Accommodation”, as part of the hospitality industry, experienced substantially more employment losses than other sectors, equivalent to 30 jobs.

Despite Tasmania not experiencing an overall loss in direct tourism expenditure, losses from other regions flowed throughout Tasmania’s economy.

Production layer decomposition, across 10 broad sector groupings, of the impact of tourism losses from the 2019-20 bushfires in Tasmania. The losses are illustrated in terms of income and full-time equivalent (FTE) employment, up to 10 orders of production

As Fig.  5 shows, the losses from elsewhere in Australia flowed through Tasmania across the primary, secondary and tertiary sectors, with significant losses continuing to accumulate in upstream layers of production, particularly in the services sectors. TAS’s employment indicator is notable because although the manufacturing industry in aggregate was substantially impacted in TAS, out of the 39 sectors in this study, the “Accommodation” hospitality sector suffered the most, experiencing 2 job losses in TAS.

Tourism has been a critical driver of economic output and risks damage from climate change, particularly in countries such as Australia that are vulnerable to disasters. Tourism spend in the year prior to the fires was more than AU$120 billion, being responsible for the employment of 5% of Australians overall and 8.1% in rural areas, or almost one in 12 people (Tourism Australia n.d. ), and the bushfires burned worst outside of major cities because of tree cover. From a global perspective, Australia was one of the highest-yielding tourism destinations in 2018-19, with international visitors spending $44.6 billion (Tourism Australia n.d. ). Education-related travel services was Australia’s fourth-biggest export in 2018-19 and, when combined with personal travel, was beaten only by iron ore and coal and was responsible for more export income than natural gas (Australian Government Department of Foreign Affairs and Trade 2020 , p. 19); in fact, the federal export arm Austrade reported that its two most-impacted industries from the bushfires were tourism and education ( 2020 , p. 2). It should be noted that tourists are defined as any visitors who will stay for less than a year; standardised tourism satellite accounts (TSA) of tourism and related activities of nations include business- and education-related travel, meaning the official tourism statistics include not only holidaymakers but also the large and growing area of air travel generally. In Australia prior to the bushfires, “Air, water and other transport” was the main component of tourism travel, responsible for expenditure of $23.278 billion (compared to just $1.090 billion for rail transport, $1.252 billion for taxi transport, $1.854 billion for other road transport and $1.839 for motor vehicle hiring (Austrade & Tourism Research Australia  2020 ).

With bushfires/wildfires increasing compared to other natural hazards (Handmer et al. 2018 ) and natural hazards generally projected to intensify under climate change (IPCC 2022 ), it is important for countries such as Australia to quantify the economic impact of disasters as part of routine practice, that take account of supply-chain spillovers. As our research demonstrates, by including the entire supply chain, using IO analysis, total output losses identified were a 61% increase on top of the direct damages.

Our highly disaggregated results enabled us to identify differences in impacts along supply chains, which was important because the impacts were unevenly distributed. For example, in addition to the key industries of transport, hospitality and cultural and recreational services, the education sector was significantly impacted. Therefore, universities and other providers could consider planning for potential cuts to expenditure on their services in the longer term if major shutdowns to tourism become more commonplace because of increasing natural hazards in particular regions or perceptions that Australia may be unsafe. As well, although we found that the hospitality industry was the most affected overall, with “Accommodation” experiencing the most job losses, followed by “Cafes, restaurants and take-away”, in terms of consumption and income, the aviation-led “Air, water and other transport” sector suffered the most out of the 39 sectors that we studied, indicating that different approaches may be taken by the government depending on policy priorities, for example in terms of jobs or income. From a regional perspective, although the States that were declared bushfire catastrophes also instigated State inquiries to help guide responses, we found that some other regions suffered significant impacts compared to their pre-fire total output. As well, supply-chain spillovers rendered some smaller regions more vulnerable to shouldering the impacts from a per-capita perspective, and this was particularly the case for the remote NT, which has the smallest population. These disaggregated results may help decision-makers in investigating certain hotspots, not only for re-building post-fire but also in terms of preparing for the next disaster.

It is also worth considering the losses suffered by “Cultural and recreational services”, largely because of extensive infrastructure destruction, and spillover impacts, in National Parks that are key drawcards for tourists, for example to the World Heritage Blue Mountains in Greater Sydney. From infrastructure damage and destruction before even accounting for supply-chain impacts, we identified $275 million in losses, although these direct damages were then depreciation for the purposes of our impact analysis (see Online Resource 1 SI2.6 Summary of infrastructure damage). These infrastructure losses are borne by the State governments and their repair, which would be paid by public funding, is an investment in tourism in addition to nature-based recreation generally. However, similar damages in poorer countries could be much more difficult to rectify efficiently ahead of upcoming holiday seasons, particularly in developing nations with weak local municipalities. Therefore, natural hazards may increase economic inequalities, with the burden of climate adaptation and mitigation adding to the costs of governments already struggling under business-as-usual.

Although the losses from the tourism damage that we calculated only represented a small fraction of the nation’s economic output, Australia’s reputation as a pristine destination could become permanently damaged in the longer term under global warming, with fewer people travelling in Australia in our peak summer holiday season; similarly, people may start to avoid other countries and regions that are increasingly in the media for their wildfires and other natural hazards. The aviation-led transport sector, which suffered among the most losses, may expect a double-hit from future impacts of climate change, with carbon-intensive industries such as air travel set to become more expensive in the low-carbon transition, making a trip “down under” less attractive. Our findings have broader implications for other nature-based destinations particularly in the Asia Pacific, which is the most disaster-prone and populous region (United Nations Office for the Coordination of Humanitarian Affairs 2017 ). Countries reliant on tourism and in particular remote nations, where aviation plays a major role, are advised not only proactively to adapt their economies to worsening climate-fuelled natural hazards but also to prepare for the impacts of the necessary global transition to a low-carbon world. On the other hand, aviation globally has been increasing because of growing affluence (Lenzen et al. 2018 ) and it is possible that in the near future this trend will continue.

This is the first IO analysis applied to Australia’s 2019-20 bushfires, with a focus on the supply-chain impacts of the reduction in tourism expenditure. Future IO studies could calculate the impact of other megafire-affected areas such as forestry or estimate the economic impact of the fires overall, from this globally unprecedented event.

Our novel research into the losses from the tourism shutdown resulting from Australia’s 2019-20 fires found that flowing on from direct impacts of AU $1.7 billion, indirect impacts along supply chains resulted in $2.8 billion in total output losses and $1.6 billion in reduced consumption. The short-term drop in consumption from the unprecedented bushfires, in terms of reduced tourism expenditure during the peak holiday season, also triggered a reduction in income of $809 million and the shedding of 7292 full-time-equivalent jobs nationwide. Hospitality and the emissions-intensive transport sector were the most impacted, the latter of which is one of Australia’s top exports. In particular, the accommodation sector within hospitality stood out as suffering the most job losses.

By incorporating the entire supply chain, using IO analysis, we calculated significant spill-over costs, with total output losses being an increase of 61% on top of the direct damages identified. As well, invisible impacts of the fires were identified, such as in Tasmania, which did not suffer a direct loss in tourism but nonetheless lost 13 jobs overall, with its manufacturing sectors among the most impacted, because of tourism losses suffered in other parts of the country.

This sort of comprehensive supply-chain analysis is particularly important not only in Australia but also in other nations in the disaster-prone Asia Pacific, and other regions vulnerable to fires worldwide. In line with findings that fires are increasing disproportionately because of global warming, countries that rely on nature-based tourism are among those with the most to gain from climate-change mitigation but these countries must also prepare for the impacts to community-and-industry hotspots that will result from future fires, in an era that has been referred to as the Pyrocene.

Data Availability

The datasets generated and analysed during the study are available from the corresponding author on request.

Afionis S, Sakai M, Scott K, Barrett J, Gouldson A (2017) Consumption-based carbon accounting: Does it have a future? WIREs Clim Change 8(1):e438. https://doi.org/10.1002/wcc.438

Austrade (2020) Lessons to be learned in relation to the Australian bushfire season 2019-20: Submission 127. Commonwealth of Australia, Parliament of Australia. https://www.aph.gov.au/DocumentStore.ashx?id=5cbb91b2-9635-4a97-a2af-7c2cff40898c&subId=684327 . Accessed 12 Sept 2023

Austrade & Tourism Research Australia (2021) Appendix: State tourism satellite accounts, 2019-20. Commonwealth of Australia, Tourism Research Australia. https://www.tra.gov.au/en/data-and-research.html . Accessed 11 Sept 2023

Austrade & Tourism Research Australia (2020) Appendix: State tourism satellite accounts, 2018–19. Commonwealth of Australia, Tourism Research Australia. https://www.tra.gov.au/en/data-and-research.html . Accessed 11 Sept 2023

Australian Bureau of Statistics (2011) 1270.0.55.001 - Australian Statistical Geography Standard (ASGS): Volume 1 - Main structure and greater capital city Statistical Areas, July 2011. Archived Issue. https://www.abs.gov.au/ausstats/[email protected]/Previousproducts/88F6A0EDEB8879C0CA257801000C64D9?opendocument . Accessed 10 Sept 2023

Australian Bureau of Statistics (2020) National, state and territory population. Commonwealth of Australia, Population – States and Territories. https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/mar-2020/310104.xls . Accessed 11 Sept 2023

Australian Bureau of Statistics (2009) 5215.0.55.001 - Australian National Accounts: Input-Output Tables (product details), 2009-10. Australian Bureau of Statistics, Archived Issue. https://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/5215.0.55.001Main+Features12009-10?OpenDocument . Accessed 10 Sept 2023

Australian Government Department of Agriculture, Water and Environment (2020) Gondwana rainforests of Australia: State of conservation update: April 2020. Commonwealth of Australia, Canberra

Australian Government Department of Agriculture, Water and the Environment (2020) Greater blue mountains area state of conservation update: April 2020. Commonwealth of Australia, Canberra

Australian Government Department of Foreign Affairs and Trade (2020) Trade and investment at a glance 2020. Commonwealth of Australia, Canberra

Australian Government Department of Industry, Science, Energy and Resources (2019) Quarterly update of Australia’s national greenhouse gas inventory: March 2019. Commonwealth of Australia, Canberra

Australian Government Department of Industry, Science, Energy and Resources (2020) Estimating greenhouse gas emissions from bushfires in Australia’s temperate forests: Focus on 2019-20 – technical update. Commonwealth of Australia, Canberra

BBC (2020) Australia fires: New South Wales declares week-long emergency. BBC News. https://www.bbc.com/news/world-australia-50969088 . Accessed 25 Aug 2023

Binna Burra (2022) QLD Government will provide funding support to rebuild the historic Binna Burra Lodge. Binna Burra Lodge. https://www.binnaburralodge.com.au/news/qld-government-will-provide-funding-support-to-rebuild-the-historic-binna-burra-lodge/ . Accessed 24 Jun 2022

Bočkarjova M, Steenge AE, van der Veen A (2004) On direct estimation of initial damage in the case of a major catastrophe: Derivation of the basic equation. Disaster Prev Manage 13(4):330–336. https://doi.org/10.1108/09653560410556555

Boer MM, Resco De Dios V, Bradstock RA (2020) Unprecedented burn area of Australian mega forest fires. Nat Clim Change 10(3):171–172. https://doi.org/10.1038/s41558-020-0716-1

Article   ADS   Google Scholar  

Boisvert E (2022) Southern Ocean Lodge rebuild on Kangaroo Island starts two years after devastating bushfire. ABC. https://www.abc.net.au/news/2022-02-18/southern-ocean-lodge-rebuild-on-kangaroo-island-starts/100842806#:~:text=The%20lodge%20was%20destroyed%20in,its%20replacement%2C%20worth%20%2450%20million . Accessed 25 Sept 2022

Bourke L (2020) Out of respect’: Kylie Minogue Matesong Tourism Australia ad pulled amid bushfire coverage. Sydney Morning Herald. https://www.smh.com.au/world/europe/out-of-respect-kylie-minogue-matesong-tourism-australia-ad-pulled-amid-bushfire-coverage-20200103-p53opl.html . Accessed 25 Aug 2023

Canadell JG, Meyer CP, Cook GD, Dowdy A, Briggs PR, Knauer J, Pepler A, Haverd V (2021) Multi-decadal increase of forest burned area in Australia is linked to climate change. Nat Commun 12(1):6921. https://doi.org/10.1038/s41467-021-27225-4

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Dalton J (2022) Koalas declared endangered in Australia after devastating wildfires. The Independent. https://www.independent.co.uk/news/world/australasia/koalas-endangered-species-australia-extinction-b1998320.html . Accessed 29 Aug 2022

European Commission, International Monetary Fund, Organisation for Economic Co-operation and Development, United Nations, World Bank (2009) System of National Accounts 2008. United Nations, New York

Faturay F, Lenzen M, Nugraha K (2017) A new sub-national multi-region input–output database for Indonesia. Econ Syst Res 29(2):234–251. https://doi.org/10.1080/09535314.2017.1304361

Article   Google Scholar  

Faturay F, Sun Y-Y, Dietzenbacher E, Malik A, Geschke A, Lenzen M (2020a) Using virtual laboratories for disaster analysis: a case study of Taiwan. Econ Syst Res 32(1):58–83. https://doi.org/10.1080/09535314.2019.1617677

Faturay F, Vunnava VSG, Lenzen M, Singh S (2020b) Using a new USA multi-region input output (MRIO) model for assessing economic and energy impacts of wind energy expansion in USA. Appl Energy 261:114141

Foster A (2020) Canberra Airport reopens after fires forced shut down. news.com.au. https://www.news.com.au/travel/travel-updates/incidents/too-late-to-leave-bushfires-flare-up-as-temperatures-soar/news-story/6932587f0297dd9e23eacceb4014bd34 . Accessed 6 Jan 2023

Galbusera L, Giannopoulos G (2018) On input-output economic models in disaster impact assessment. Int J Disaster Risk Reduct 30:186–198. https://doi.org/10.1016/j.ijdrr.2018.04.030

Gergis J (2018) Sunburnt country: The history and future of climate change in Australia. Melbourne University Press, Melbourne

Handmer J, Ladds M, Magee L (2018) Updating the costs of disasters in Australia. Austral J Emerg Manag 33(2):41–46. http://classic.austlii.edu.au/au/journals/AUJlEmMgmt/2018/36.html . Accessed 30 July 2022

Hannam P (2016) The 10 Sydney regions most exposed to bushfire risk. The Sydney Morning Herald. https://www.smh.com.au/environment/the-10-sydney-regions-most-exposed-to-bushfire-risk-20161107-gsk08y.html . Accessed 29 Aug 2022

Indigo Shire Council (2020) Exhibit 10-027.001 - ISC.500.001.0001 - Indigo Shire Council response to NTG-HB3-601. Royal Commission into National Natural Disaster Arrangements, Canberra. https://naturaldisaster.royalcommission.gov.au/system/files/exhibit/ISC.500.001.0001.pdf . Accessed 25 Aug 2023

IPCC (2022) Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press, Cambridge and New York. https://doi.org/10.1017/9781009325844

Kangaroo Island Council (2020) Kangaroo Island Council Annual report 2019-20

Koks EE, Carrera L, Jonkeren O, Aerts JCJH, Husby TG, Thissen M, Standardi G, Mysiak J (2016) Regional disaster impact analysis: Comparing input–output and computable general equilibrium models. Nat Hazards Earth Syst Sci 16(8):1911–1924. https://doi.org/10.5194/nhess-16-1911-2016

Lenzen M, Moran D, Kanemoto K, Geschke A (2013) Building Eora: A global multi-region input-output database at high country and sector resolution. Econ Syst Res 25(1):20–49. https://doi.org/10.1080/09535314.2013.769938

Lenzen M, Geschke A, Wiedmann T, Lane J, Anderson N, Baynes T, Boland J, Daniels P, Dey C, Fry J, Hadjikakou M, Kenway S, Malik A, Moran D, Murray J, Nettleton S, Poruschi L, Reynolds C, Rowley H et al (2014a) Compiling and using input–output frameworks through collaborative virtual laboratories. Sci Total Environ 485–486:241–251. https://doi.org/10.1016/j.scitotenv.2014.03.062

Article   ADS   CAS   PubMed   Google Scholar  

Lenzen M, Moran DD, Geschke A, Kanemoto K (2014b) A non-sign-preserving RAS variant. Econ Syst Res 26(2):197–208. https://doi.org/10.1080/09535314.2014.897933

Lenzen M, Geschke A, Abd Rahman MD, Xiao Y, Fry J, Reyes R, Dietzenbacher E, Inomata S, Kanemoto K, Los B, Moran D, Schulte In Den Bäumen H, Tukker A, Walmsley T, Wiedmann T, Wood R, Yamano N (2017a) The global MRIO lab – Charting the world economy. Econ Syst Res 29(2):158–186. https://doi.org/10.1080/09535314.2017.1301887

Lenzen M, Geschke A, Malik A, Fry J, Lane J, Wiedmann T, Kenway S, Hoang K, Cadogan-Cowper A (2017b) New multi-regional input–output databases for Australia: enabling timely and flexible regional analysis. Econ Syst Res 29(2):275–295. https://doi.org/10.1080/09535314.2017.1315331

Lenzen M, Sun Y-Y, Faturay F, Yuan-Peng T, Geschke A, Malik A (2018) The carbon footprint of global tourism. Nat Clim Change 8(6):522–528. https://doi.org/10.1038/s41558-018-0141-x

Lenzen M, Malik A, Kenway S, Daniels P, Ka Leung L, Geschke A (2019) Economic damage and spillovers from a tropical cyclone. Nat Hazards Earth Syst Sci 19(1):137–151. https://doi.org/10.5194/nhess-19-137-2019

Lenzen M, Li M, Malik A, Pomponi F, Sun Y-Y, Wiedmann T, Faturay F, Fry J, Gallego B, Geschke A, Gómez-Paredes J, Kanemoto K, Kenway S, Nansai K, Prokopenko M, Wakiyama T, Wang Y, Yousefzadeh M (2020) Global socio-economic losses and environmental gains from the Coronavirus pandemic. PLoS ONE 15(7):e0235654. https://doi.org/10.1371/journal.pone.0235654

Article   PubMed   PubMed Central   Google Scholar  

Lenzen M, Geschke A, West J, Fry J, Malik A, Giljum S, Milà I, Canals L, Piñero P, Lutter S, Wiedmann T, Li M, Sevenster M, Potočnik J, Teixeira I, Van Voore M, Nansai K, Schandl H (2022) Implementing the material footprint to measure progress towards sustainable development goals 8 and 12. Nat Sustain 5(2):157–166. https://doi.org/10.1038/s41893-021-00811-6

Leontief W (1936) Quantitative input and output relations in the economic systems of the United States. Rev Econ Stat 18(3):105–125. https://www.jstor.org/stable/pdf/1927837.pdf . Accessed 13 Jun 2023

Leontief W (1966) Input-output economics. Oxford University Press, Oxford. https://global.oup.com/academic/product/input-output-economics . Accessed 23 August 2022

Li J, Crawford-Brown D, Syddall M, Guan D (2013) Modeling imbalanced economic recovery following a natural disaster using input-output analysis. Risk Anal 33(10):1908–1923. https://doi.org/10.1111/risa.12040

Article   PubMed   Google Scholar  

Li M, Lenzen M, Pedauga LE, Malik A (2022) A minimum-disruption approach to input-output disaster analysis. Spat Econ Anal 1–25. https://doi.org/10.1080/17421772.2022.2056231

Malik A, McBain D, Wiedmann TO, Lenzen M, Murray J (2019) Advancements in input-output models and indicators for consumption-based accounting. J Ind Ecol 23(2):300–312. https://doi.org/10.1111/jiec.12771

Malik A, Li M, Lenzen M, Fry J, Liyanapathirana N, Beyer K, Boylan S, Lee A, Raubenheimer D, Geschke A, Prokopenko M (2022) Impacts of climate change and extreme weather on food supply chains cascade across sectors and regions in Australia. Nat Food 3(8):631–643. https://doi.org/10.1038/s43016-022-00570-3

McDonald P (2020) Anatomy of a mega-fire: Black Summer [special report]. ABC. https://www.youtube.com/watch?v=SlGmatigAy4 . Accessed 29 Aug 2022

McIlwain K (2020) 'We’re sorry': Plea for South Coast tourists to return after mass evacuation. Canberra Times. https://www.canberratimes.com.au/story/6618649/were-sorry-plea-for-south-coast-tourists-to-return-after-mass-evacuation/ . Accessed 27 Aug 2023

Murphy H, van Leeuwen S (2021) Australia state of the environment 2021: Biodiversity, independent report to the Australian Government Minister for the Environment, Commonwealth of Australia, Canberra. https://doi.org/10.26194/ren9-3639

Norman B, Newman P, Steffen W (2021) Apocalypse now: Australian bushfires and the future of urban settlements. Npj Urban Sustain 1(2). https://doi.org/10.1038/s42949-020-00013-7

Okuyama Y (2007) Economic modeling for disaster impact analysis: Past, present, and future. Econ Syst Res 19(2):115–124. https://doi.org/10.1080/09535310701328435

Okuyama Y, Santos JR (2014) Disaster impact and input-output analysis. Econ Syst Res 26(1):1–12. https://doi.org/10.1080/09535314.2013.871505

Oosterhaven J (2017) On the limited usability of the inoperability IO model. Economic Systems Research 29(3):452–461. https://doi.org/10.1080/09535314.2017.1301395

Oosterhaven J (2022) Rethinking input-output analysis a spatial perspective negative IO supply shock analyses: when substitution matters. Springer International Publishing, Cham, pp 105-121

Queensland Government (2020) Binna Burra Road reopening marks key recovery milestone [Press release]. https://statements.qld.gov.au/statements/90603 . Accessed 6 July 2022

Rannard G (2020) Australia fires: Misleading maps and pictures go viral. BBC. https://www.bbc.com/news/blogs-trending-51020564 . Accessed 25 Aug 2023

Richardson HW (1985) Input-output and economic base multipliers: looking backward and forward. J Reg Sci 25(4):607–661. https://doi.org/10.1111/j.1467-9787.1985.tb00325.x

Rodriguez A (2020) Dark smoke from Australia fires is circling the Earth, NASA says. USA Today. https://www.usatoday.com/story/news/world/2020/01/15/australia-fires-google-earth-nasa-tracks-smoke-around-world/4476126002/ . Accessed 25 Aug 2023

Rose A (1995) Input-output economics and computable general equilibrium models. Struct Change Econ Dyn 6(3):295–304. https://doi.org/10.1016/0954-349X(95)00018-I

Rose A (2004) Economic principles, issues, and research priorities in hazard loss estimation. In: Okuyama Y et al (eds) Modeling spatial and economic impacts of disasters. Springer-Verlag, Berlin Heidelberg, pp 13–36. https://doi.org/10.1007/978-3-540-24787-6_2

Chapter   Google Scholar  

Royal Commission into National Natural Disaster Arrangements (2020) Royal Commission into National Natural Disaster Arrangements: Report. Commonwealth of Australia, Canberra

Schulte in den Bäumen H, Moran D, Lenzen M, Cairns I, Steenge A (2014) How severe space weather can disrupt global supply chains. Nat Hazards Earth Syst Sci 14(10):2749–2759. https://doi.org/10.5194/nhess-14-2749-2014

Schulte in den Bäumen, H, Többen, J, Lenzen, M (2015) Labour forced impacts and production losses due to the 2013 flood in Germany. J Hydrol 527:142–150. https://doi.org/10.1016/j.jhydrol.2015.04.030

Steenge AE, Bočkarjova M (2007) Thinking about imbalances in post-catastrophe economies: An input–output based proposition. Econ Syst Res 19(2):205–223. https://doi.org/10.1080/09535310701330308

Swiss Re (2021) Natural catastrophes in 2020: Secondary perils in the spotlight, but don’t forget primary-peril risks. Sigma(1/2021). Swiss Re Management Ltd, Zurich

The Nobel Prize (1973) The prize in Economic Sciences in memory of Alfred Nobel to the father of input-output analysis [Press release]. https://www.nobelprize.org/prizes/economic-sciences/1973/press-release/ . Accessed 31 Aug 2023

Tourism Australia (2020) Lessons to be learned in relation to the Australian bushfire season 2019-20: Submission 28. Commonwealth of Australia, Parliament of Australia. https://www.aph.gov.au/DocumentStore.ashx?id=f1225b83-21dd-48ac-832d-b49c5204a74b&subId=680468 . Accessed 12 Sept 2023

Tourism Australia (n.d.) The economic importance of tourism. https://www.tourism.australia.com/en/insights/tourism-statistics/the-economic-importance-of-tourism.html#:~:text=In%20the%20financial%20year%202018,per%20cent%20of%20Australia's%20workforce . Accessed 25 Aug 2023

Tourism Research Australia (2020a) International visitors in Australia: Year ending March 2020 [Summary]. Commonwealth of Australia. https://www.tra.gov.au/en/data-and-research.html . Accessed 25 Aug 2023

Tourism Research Australia (2020b) Travel by Australians: Year ending March 2020 [Summary]. Commonwealth of Australia. https://www.tra.gov.au/en/data-and-research.html . Accessed 25 Aug 2023

Tukker A, Dietzenbacher E (2013) Global multiregional input–output frameworks: An introduction and outlook. Econ Syst Res 25(1):1–19. https://doi.org/10.1080/09535314.2012.761179

UN Statistics Division (1999) Handbook of input-output table compilation and analysis. United Nations, New York

United Nations Office for the Coordination of Humanitarian Affairs (2017) Disaster response in Asia and the Pacific: a guide to international tools and services. OCHA, Bangkok

van der Velde IR, van der Werf GR, Houweling S, Maasakkers JD, Borsdorff T, Landgraf J, Tol P, van Kempen TA, van Hees R, Hoogeveen R, Veefkind JP, Aben I (2021) Vast CO2 release from Australian fires in 2019–2020 constrained by satellite. Nature 597(7876):366–369. https://doi.org/10.1038/s41586-021-03712-y

van Eeden L, Nimmo D, Mahony M, Herman K, Ehmke G, Driessen J, O’Connor J, Bino G, Taylor M, Dickman C (2020) Impacts of the unprecedented 2019-20 bushfires on Australian animals. Report prepared for WWF-Australia, Ultimo

Van Oldenborgh GJ, Krikken F, Lewis S, Leach NJ, Lehner F, Saunders KR, Van Weele M, Haustein K, Li S, Wallom D, Sparrow S, Arrighi J, Singh RK, Van Aalst MK, Philip SY, Vautard R, Otto FEL (2021) Attribution of the Australian bushfire risk to anthropogenic climate change. Nat Hazards Earth Syst Sci 21(3):941–960. https://doi.org/10.5194/nhess-21-941-2021

Wakiyama T, Lenzen M, Geschke A, Bamba R, Nansai K (2020) A flexible multiregional input–output database for city-level sustainability footprint analysis in Japan. Resour Conserv Recycl 154:104588. https://doi.org/10.1016/j.resconrec.2019.104588

Wang Y (2017) An industrial ecology virtual framework for policy making in China. Econ Syst Res 29(2):252–274. https://doi.org/10.1080/09535314.2017.1313199

Article   MathSciNet   Google Scholar  

Wiedmann T (2009) Editorial: Carbon footprint and input-output analysis – an introduction. Econ Syst Res 21(3):175–186. https://doi.org/10.1080/09535310903541256

Zhou L, Chen Z (2021) Are CGE models reliable for disaster impact analyses? Econ Syst Res 33(1):20–46. https://doi.org/10.1080/09535314.2020.1780566

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Acknowledgements

Tourism Research Australia provided crucial survey and expenditure data, without which this study would not have been possible. The authors thank Sebastian Juraszek for expertly managing our advanced computation requirements.

Open Access funding enabled and organized by CAUL and its Member Institutions This work was financially supported by the Australian Research Council (ARC) through its Discovery Projects DP0985522, DP130101293, DP200103005, DP200102585, DE230101652, LP200100311 and IH190100009, and the University of Sydney SOAR Funding. IELab infrastructure is supported by ARC infrastructure funding through project LE160100066, and through the National eResearch Collaboration Tools and Resources project (NeCTAR) through its Industrial Ecology Virtual Laboratory VR201. NeCTAR are Australian Government projects conducted as part of the Super Science initiative and financed by the Education Investment Fund. This research is also supported by federal government Research Training Program Stipend Scholarships. Manfred Lenzen was financially supported by the Hanse-Wissenschaftskolleg in Delmenhorst, Germany through its HWK Fellowships.

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ISA, School of Physics A28, The University of Sydney, Sydney, NSW, 2006, Australia

Vivienne Reiner, Navoda Liyana Pathirana, Manfred Lenzen & Arunima Malik

Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia

Navoda Liyana Pathirana

Business School, The University of Queensland, Brisbane, QLD, 4072, Australia

Hanse-Wissenschaftskolleg, Lehmkuhlenbusch 4, 27753, Delmenhorst, Germany

Manfred Lenzen

Business School, The University of Sydney, Sydney, NSW, 2006, Australia

Arunima Malik

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V.R. and A.M. conceptualised the study; V.R. performed scenario analysis and drafted the manuscript, which was initially reviewed by A.M. and M.L. Coding for the model was designed by N.L.P and A.M. Y-Y.S advised on tourism calculations and all authors edited the manuscript.

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Reiner, V., Pathirana, N.L., Sun, YY. et al. Wish You Were Here? The Economic Impact of the Tourism Shutdown from Australia’s 2019-20 ‘Black Summer’ Bushfires. EconDisCliCha 8 , 107–127 (2024). https://doi.org/10.1007/s41885-024-00142-8

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Tourist bucks weigh in with record economy boost

Travel and tourism is expected to contribute more to Australia’s economy in 2024 than any previous year on record.

Four years after COVID-19 brought the sector to its knees with border closures and widespread restrictions on people movement, it’s poised to surpass its 2019 peak by generating $265.5 billion, according to World Travel and Tourism Council forecasts.

The projection represents 10 per cent of the nation’s economy and follows the industry’s long-awaited bounce back to pre-pandemic levels in 2023.

The council, which will host its 24th international summit in Perth in October, predicts the robust growth spurt will extend over the next decade.

In line with global trends, it says the sector’s contribution to the national economy should exceed $345 billion by 2034. More than two million Australian jobs would be supported, representing 12 per cent of the country’s workforce.

Employment in travel and tourism surged nearly 10 per cent last year, hitting 1.42 million or one in 10 jobs, and is expected to exceed 2018’s peak by 2026.

“Australia is set to break tourism records,” World Travel and Tourism Council president Julia Simpson said.

“The Perth summit will highlight its dynamic growth, reflecting travel and tourism’s broader economic recovery and rising employment trends.”

Ratings agency Fitch believes a full recovery of international tourism visitor numbers in the Asia-Pacific region will materialise in the first half of next year.

“However, we expect those prospects to remain vulnerable to multiple risks, such as a slow restoration of international air traffic, elevated airfares and energy prices and heightened geopolitical tensions,” it said.

In Victoria, tourism and aviation is set for a targeted boost with the introduction of additional non-stop flights between Shanghai and Melbourne in a move expected to create almost 1200 jobs and amass more than $200 million for the state’s economy annually.

This after Melbourne became Australia’s first capital city airport to exceed pre-pandemic international capacity in December and with global travellers generating $6.4 billion in expenditure across the state last year, according to Jobs and Industry Minister Natalie Hutchins.

Inbound travel across the country is on a slow and steady recovery, with improvements month-on-month, says Australian Tourism Export Council chief Peter Shelley.  

“While this is slower than we’d like overall, there is still a growth trend which, if it continues, should see us back to 2019 levels towards the end of this year or early 2025,” he said.

International holiday maker arrivals are at 74 per cent of 2019 levels. But Australians are heading overseas for holidays at a remarkable rate, surpassing numbers in April five years ago.

Google data reveals Bali as the top destination. London is next most popular, followed by Tokyo, Rome and Los Angeles. Melbourne ranks eighth and Sydney 10th.

The search engine behemoth has identified the top-five travel trends making waves in 2024: immersive cultural experiences, exploring nature, mindful escapes (read wellness retreats and food tours), day tripping and turning to AI to help plan trips.

Last year, domestic visitors set a record for total spending in Australia of $146 billion. The World Travel and Tourism Council predicts this figure will reach nearly $148 billion in 2024 and soar to almost $180 billion in 2034.

Despite reopening its border later than many other major destinations around the world in 2023, spending by overseas visitors surged nearly 195 per cent to $31.6 billion, ranking Australia 10th globally for growth.

It’s likely it will near $35 billion this year and set a new record in 2025, and should reach more than $50 billion over the next decade.

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COVID-19 impacts of inbound tourism on Australian economy

Tien duc pham.

a Griffith Institute for Tourism, Griffith Business School, Griffith University, 170 Kessels Road, Nathan, QLD 4111, Australia

Larry Dwyer

b University of Technology, Sydney, Broadway, Sydney 2007, Australia

The pandemic COVID-19 has severely impacted upon the world economy, devastating the tourism industry globally. This paper estimates the short-run economic impacts of the inbound tourism industry on the Australian economy during the pandemic. The analysis covers effects both at the macroeconomic as well as at the industry and occupation level, from direct contribution (using tourism satellite accounts) to economy-wide effects (using the computable general equilibrium modelling technique). Findings show that the pandemic affects a range of industries and occupations that are beyond the tourism sector. The paper calls for strong support from the government on tourism as the recovery of tourism can deliver spillover benefits for other sectors and across the whole spectrum of occupations in the labour market.

Introduction

Tourism has for some decades experienced rapid growth worldwide, serving as an important source of export income for many countries, accounting for around 10% of global GDP ( World Travel and Tourism Council, 2020 ). Tourism becomes the main driver of growth in many countries and regions. With a strong social interaction nature, the industry is prone to recession, terrorism, natural disasters and infectious diseases. The outbreak of the coronavirus disease in late 2019 (hereafter, COVID-19) has severely and rapidly impacted human life on a global scale with respiratory illness that has effected more than 67 million infected cases and more than one and half million of deaths at the time of writing, an unprecedented crisis. Governments across the globe have taken wartime-like actions to curtail the spread of the illness and deaths by imposing strong restrictions on travel, social gathering and social distancing regulations. The social distancing measures constrain both the demand and supply sides of tourism services, causing significant flow-on effects throughout affected countries ( OECD, 2020a , OECD, 2020b ) with large reductions in employment and losses to household income. Even if a vaccine is available soon, with demand side recovery aided by progressive lifting of travel and social distancing restrictions, tourism supply chains may take years to adjust to the new circumstances of the travel experience ( Gössling et al., 2020 ).

Among all other countries, the Australian tourism industry is inevitably a victim to the outbreak, losing billions of dollars each month that the disease persists. Australia's tourism industry associations have united in new demands for support measures. These organisations include the Tourism and Transport Forum, the Accommodation Association, Cruise Lines International Association, the Australian Federation of Travel Agents the Restaurant and Catering Australia and the Business Events Council of Australia. Facing similar situations in respect of business closures, plummeting sales, losing jobs and incomes, these associations have acknowledged their dependence on government support to soften the effects of the pandemic both for current and future business operations. In a joint statement to the Prime Minister, the association group argued the case for the tourism industry's bigger businesses to be front and centre of any new economic lifeline package describing them as providing the scaffolding for the tourism sector and for business events. Claiming that the tourism industry will be critical to the Australian economy as it manages through the current survival phase and later into the eventual economic recovery phase, the peak group stated that:

The tourism industry is losing almost A$ 9bn every month that the global pandemic continues and is forecasting job losses of well over 300,000 so we are calling on government to recognise the urgency of providing these employers with sector-specific financial assistance. We acknowledge all of the steps taken by the Federal and State and Territory Governments are entirely necessary to ensure the health and wellbeing of Australians, but we are now at a point where our industry and its people are in the fight for survival. ( Colston, 2020 )

Included in the statement was a list of ‘sensible reforms’ that will help to ensure that Australia's tourism industry can survive the current crisis and become a stronger and more resilient industry. These reforms include investment incentives, tax concessions, rent abatements, and utility payments relief.

Without prejudging the appropriateness or otherwise of the suggested reforms, it is clear that their efficacy can only be determined in a context where the economic impacts of COVID-19 on the Australian tourism industry have been estimated. Since the effects of the pandemic are still unfolding, it is extremely difficult to predict with an accuracy what the ultimate health and economic impacts will be and what reform measures are most efficient and effective. The effects of the pandemic encompass many different aspects, including the health costs, human suffering, consumer behaviour and losses of tourism demand. All of these are important aspects of changes, and each warrants separate research on its own merit. This paper, however, focuses on the economic aspect of the pandemic only.

This paper will undertake what we believe to be the first detailed assessment of the economic impacts of COVID-19 on the Australian international tourism industry. The model employed has been substantially developed to include explicitly eleven international markets and three domestic markets to allow for full interaction between tourism and non-tourism demands by both international and domestic consumers. This is the first time that the full tourism satellite account (TSA) framework is incorporated into the tourism computable general equilibrium (CGE) modelling in order to reflect tourism markets explicitly and to allow flexibility for implementing individual shocks. Impacts are explained from direct to flow-on effects explicitly and results capture employment effects by occupation. This comprehensive approach is rare in the literature. The full details of the extension, as discussed below, provide rich sectoral results that have not been captured in tourism modelling previously.

The paper will review previous studies specifically of epidemics/pandemics on tourism, followed by a brief account of the pre-COVID-19 conditions of the world and Australian tourism sector. The paper then presents the adopted modelling framework, measures of the direct and flow-on effects on the pandemic. The final section will discuss in broad terms some strategies to reduce the effects of COVID-19 on the Australian tourism industry currently and in the future.

Review of previous studies

The literature of tourism economic impact analysis is very broad, a review can be found in Dwyer (2015) . This section will focus specifically on economic impact studies of pandemics of infectious diseases such as Severe Acute Respiratory Syndrome (SARS), Avian flu, Foot and Mouth Disease and recently COVID-19. The modelling approaches encompass a wide range of techniques for different objectives, including tourism demand assessment using the econometric technique ( Kuo et al., 2008 ; Kuo et al., 2009 ; McAleer et al., 2010 ; Liu, Moss and Zhang, 2011 , and Page et al., 2012 ), the market evaluation approach assessing impacts on the consumption and production sides separately (Australian Bureau of Statistics or ABS hereafter, 2020 ; OECD, 2020a , OECD, 2020b ; United Nations Conference on Trade and Development, 2020a ); macro-econometric modelling ( Jonung & Roeger, 2006 ; Keogh-Brown, Wren-Lewis, et al., 2010 ; Kohlscheen et al., 2020 ); the Input-Output multiplier approach ( Hai, Zhao, Wang and Hou, 2004 ), dynamic stochastic general equilibrium ( Yang et al., 2020 ), and the computable general equilibrium modelling ( Blake et al., 2003 ; Dwyer et al., 2006 ; Lee & McKibbin, 2004 ; Maliszewska et al., 2020 ; McKibbin & Fernando, 2020 ; McKibbin & Sidorenko, 2006 ; Keogh-Brown, Smith, et al., 2010 ; Park et al., 2020 ; PricewaterhouseCoopers, 2020 ; Smith et al., 2011 ; World Bank, 2014 : and Yang & Chen, 2009 ).

As pandemics affect economies on both supply and demand sides simultaneously ( Boissay & Rungcharoenkitkul, 2020 ), most economy-wide studies employ the CGE technique to reveal the impacts of pandemics at the industry as well as the macro aggregate level for both world and national economies under the influence of changes in prices and resource re-allocation. The initial direct effects of a pandemic reduce labour supply due to losses of workers through sickness and mortality. Further impacts are prompted by fear . Prophylactic absenteeism of workers is due to fear of being infected by asymptomatic co-workers, thus effecting an additional loss to the productive workforce. Government's public health policy imposes restriction on social distancing, social gathering, school closure, international border closure for fear of the virus spread ( World Bank, 2014 , p. 6); The combined effect of prophylactic absenteeism and school closure is the essential driving force of economic costs of a pandemic ( Keogh-Brown, Wren-Lewis, et al., 2010 ). Both health effect and fear factor cut labour supply significantly. Impact studies at the early stage of pandemics often have to base on assumptions of clinical attack rates and case fatality ratio in order to work out the reduction of labour supply (e.g. Keogh-Brown, Wren-Lewis, et al., 2010 ; McKibbin and Fernando, 2020 ; PricewaterhouseCoopers, 2020 ), which alters the relative prices of capital and labour and subsequently depresses rates of return significantly in the medium to long term, thus drives down investment ( Jordà et al., 2020 ). With border closure, regions and countries are locked down, production is shut down, leading to losses of household consumption. It appears that the literature focuses on reduced productive workforce mainly from the supply side, which might not cover employment losses due to production cut prompted by reduced demand for goods and services. Fiscal expansion is urgently recommended to governments to prop the economy through both supply and demand ( IMF, 2020 ). Previous studies all share a common modelling approach that incorporates shocks such as (i) reduced labour supply, (ii) reduced household consumption, (ii) changed production technology, (iv) increased government expenditure (higher budget deficit), and (v) increased risk premium or loss of capital productivity (e.g. McKibbin & Fernando, 2020 ; PricewaterhouseCoopers, 2020 ).

With all of the above shocks, past studies aim to project the position of the economy accounting for the overall economic impacts of the pandemics on the economy. The adverse impacts range from −0.1 to −6% for global GDP ( Boissay et al., 2020 ). Comparing across countries, previous studies indicate that developing countries tend to suffer more than developed countries ( Burns et al. 2006 ). For COVID-19, statistics from the IMF (2020) show the reverse, where impacts on developed countries (−8%) are much worse than the world average (−4.9%).

Given the importance of the tourism industry in the Australian economy, the industry is particularly vulnerable to an infectious pandemic. The question then arises as to the extent to which the tourism industry, alone, has impacted on the rest of the Australian economy. Answer to such question has valuable policy implications for the tourism industry during the recovery and is the motivation of this paper.

As the downturn of the domestic sector has not been completely settled, different states have applied different border closure schedules between themselves, this is not all that clear for a robust impact assessment. On the other hand, the international border closure is consistent, and the international tourism segment plays a crucial role in attracting foreign exchange to the Australian economy, an economic impact assessment of the pandemic on the international tourism market will provide valuable inputs for policy makers.

Tourism before and after outbreak of COVID-19

The effect on tourism worldwide.

Forecasts of the United Nations World Tourism Organization (2011) , hereafter UNWTO, projected international tourist arrivals to increase by 43 million annually on average to reach 1.8 billion by 2030, equivalent to 3.3% per year during 2010–2030. In 2019, 1.5 billion of international tourist arrivals were recorded globally, representing a 4% growth on the previous year. The report contained optimistic prospects for 2020, confirming tourism, in the UNWTO view, as a ‘leading’, ‘resilient’ and ‘reliable’ economic sector ( UNWTO, 2020a ).

The spread of COVID-19 worldwide has up-ended all tourism forecasts globally for all inbound, outbound and domestic travel. Acknowledging this, UNWTO issued a series of reports from January to May 2020, outlining in broad terms the impact of the pandemic on the global tourism industry. A key message of these reports is that the spread of COVID-19 represents an unparalleled, rapidly evolving pandemic with a substantial challenge to estimation of its impacts on tourism. Preliminary estimates are that international tourism could drop back to levels of 2012–2014. In its May Report (UNWTO, 7/5/2020), the UNWTO estimated international tourist arrivals could decline between 850 and 1.1 billion international tourists equivalent to between 60% to 80% loss of arrivals in 2020. This would translate into a loss of US$910 billion to US$1.2 trillion in international tourism receipts (exports) and 100 to 120 million direct tourism jobs at risk. Similarly, the World Travel and Tourism Council (WTTC) estimated that the COVID-19 pandemic could result in a loss of 75.2 million jobs worldwide in the travel and tourism industry in 2020 alone. The WTTC (2020) also warned that it could take up to 10 months or longer for the industry to recover, an estimate that now seems to be unduly optimistic. These estimates must be interpreted with caution. The pandemic could result in a 70% or greater decline in the international tourism economy in 2020, depending on its duration and the speed with which travel and tourism rebounds ( OECD, 2020a , OECD, 2020b ). As more data emerges regarding destination management strategies, estimates of the short- and longer-term losses to world tourism will become more accurate.

The Australian international tourism industry

Tourism has been one of Australia's fastest growing industries for some decades. Fig. 1 visualises the historical development of international arrivals in Australia over time. While the path has fluctuated over the whole period of nearly three decades, all the dips in arrivals prior to 2016 were due major shocks that cut arrival growth rates below the long-term average (5.2%). Since then, however, the overall growth of international arrivals to Australia has weakened but not due to any apparent shocks. Arrival growth rates have gradually dwindled down for the last four years and submerged below the long-term average in the last two years. In the absence of COVID-19, international tourism to Australia was forecast to grow in annual visitation from 9.4 million visitors to 14.6 million between 2018 and 19 and 2028–29 ( TRA, 2020 ).

Annual arrival growth in Australia (ABS, Cat no. 3401.0).

Over time, the origin country shares comprising Australia's inbound tourism markets have shifted; in favour of some markets (e.g. China) with stronger growth than the others. Collectively the top ten origins in Table 1 delivered 71.4% of the inbound visitation numbers to Australia and 70% of the revenue. While China and New Zealand contribute the most in terms of visitor arrivals, China by far has the largest revenue share among all countries.

Profiles of international markets in Australia in 2018/19.

The spread of COVID-19 has been described as an ‘economic wrecking ball’ for the Australian tourism sector. While the domestic tourism market can begin the early recovery as social gathering is relaxed, restrictions on international travel may be expected to continue for much longer, constraining the international tourism market severely.

High levels of uncertainty attend estimates of reductions in tourism numbers and the associated reductions in expenditure, given the ongoing development of the pandemic. The modelling estimates the likely outcome of the losses of international visitors as the international border closure is approaching the end 2020, making it a complete year of international isolation.

Modelling the economic impact of COVID-19

The aim of this paper is to quantify the economic effects of the pandemic on the international tourism market and subsequently on all other industries of the Australian economy. In the present study, we employ the computable general equilibrium (CGE) modelling technique, enabling us to ‘drill down’ to assess effects on different industries and to determine ‘inter-industry effects’.

As the CGE modelling technique has been described widely in the literature ( Burfisher, 2017 ; Cardenete et al., 2012 ; Dixon et al., 1982 ; Dwyer, 2015 ) we herein provide a brief summary only. A typical CGE model encompasses both supply (industries) and demand (all users) of an economy embedded entirely in an input-output (IO) database. An industry's cost structure includes wages, rental to capital and all other intermediate inputs. On the demand side, industry outputs are purchased by final users such as household consumption, investment, government consumption and exports. Decisions regarding both supply and demand are modelled following the microeconomic optimisation theory using a constant elasticity of substitution (CES) functional form. This allows goods and services to be sourced from a cheaper source among all available supplies, for example domestic versus imported sources. For a given market price of the output, producers will minimise their production costs by selecting cheapest inputs; and, the household sector will select a bundle of goods and services to maximise their ‘satisfaction’ (or precisely, utility in the micro-economic theory) subject to their income constraint.

Algebraically, a CGE model can be presented as:

where X 1 is a set of n endogenous variables determined by the n differentiable equations F(.) while X 2 is another set of m variables determined exogenously. Examples of endogenous variables are household income, household consumption and industry output while import prices, consumer taste, input mix in industry production and expenditure pattern of visitors are common exogenous variables.

Typically, the equation system in F(.) reflects:

• • Demands for goods and services by industries, investment, household, government and exports (product markets);
• • Market clearing equations for each industry (total output equals total sales);
• • Demands for labour, capital, and land by industry (factor markets), reflecting explicitly resource constraints in CGE models;
• • Production costs by industry (supply); and,
• • Pricing system with all components of production costs, import costs, net commodity taxes, and margins to provide relative price movements.

The tourism CGE model in this study is adapted from The Enormous Regional Model, hereafter TERM, ( Horridge et al., 2005 ). The model was developed by the Centre of Policy Studies using all available published and unpublished data and information compiled by the ABS. The model database is regularly updated to the latest data by the modelling team at the Centre. The platform of the model has been applied across many countries and widely used by economists in both government departments and academia; it is a well-tested model and a sound basis for the modelling undertaken. Use of this model allows us to focus on the development of the tourism module specifically. The database was expanded to include eleven international markets and three domestic markets (day trip, intra-state and inter-state overnight trips) to allow for full interaction between (1) tourism and non-tourism demand for the same commodity in the final demand and (2) among individual markets in response to shocks.

The rationale for such development is due to the fact that within each commodity, apart from the amount consumed by tourists, there is also another proportion of non-tourism consumption. This non-tourism consumption exists in both household consumption final demand (related to domestic tourists) and exports demand (related to international tourists). Without an explicit separation of tourism and non-tourism components in the final demands, shocks imposed on the model to reflect changes in tourism demand will effectively have no impacts on the non-tourism demand component. This would be an undesirable approach as the shock can have a different impact on the non-tourism component, and is complicated under the influence of income and macro effects. For example, if the shock is an increase in demand for “food, alcohol and other beverages” products by international visitors, it will (i) increase the domestic production costs of these products and at the same time (ii) it will make the exchange rate appreciate. Both changes will have an adverse impact on exports of the non-tourism component of these commodities. If not separated, the adverse impacts will be overlooked. The separation of tourism and non-tourism components is sparsely captured in the literature.

On the second aspect, given the different speeds of virus spread across countries, changes in international visitor numbers of all markets were also different. It is important to capture the actual decline in visitor number from each market so that changes in each market can be reflected accurately, as each market has a specific expenditure pattern. For this reason, the international tourism segment was further disaggregated down into eleven markets: the top ten and the rest of the world. Similarly, the domestic tourism segment was modelled with three different expenditure patterns of day trip, intra-state overnight and inter-state overnight markets. Tourism expenditure data for each market was carefully developed using the tourism satellite account (TSA) framework to provide a comprehensive coverage of goods and services consumed by visitors. Following the CGE modelling framework that explicitly incorporated TSA data for the tourism sector ( Pham et al., 2010 ; Pham & Dwyer, 2013 ), the stylised TSA data for each market was embedded into the model database. In comparison, the model development in this study is far more comprehensive, offering more advanced features for policy applications, as earlier models only cover domestic and international tourism at the aggregate level.

The type of model developed in this paper provides rich sectoral results that have not been captured in tourism modelling previously. Although the model can be used for both international and domestic shocks, the on-and-off imposition of the social distancing and social gathering due to the resurgence of the virus makes impact analysis on the domestic segment very difficult. As such, this paper focuses mainly on the international markets.

The structure of the comprehensive tourism model is presented in Fig. 2 . Each individual international tourism market is represented by the etour and domestic tourism markets ( day trip and domestic overnight markets) are represented by dtour in the figure. The model was run using GEMPACK ( Horridge et al., 2018 ). The original database of the model is large. The full dimensions of the database are not always needed in simulations and can make the interpretation of results more complicated unnecessarily. Thus, we focussed on only 75 commodities and 8 regions. The practice of using an aggregated database is very common among all TERM users. This does not compromise the coverage of the model in our analysis. The set of 75 commodities selected for this paper is appropriate for the Australian tourism industry.

Model structure of the tourism CGE model.

The version of the TERM model database was in 2012/13. The database was then updated to the latest year (2018/19) in this study. At the macro level, the update targets aggregate household consumption, government consumption, investment and exports, published by the Australia Bureau of Statistics (2020). The update also targets some important commodities for exports selected for the micro level. Exports of mining commodities are obtained from the Department of Industry, Science, Energy and Resources (2020) while export data for agricultural commodities are obtained from the Department of Agriculture, Water and the Environment (2020) . All individual tourism markets were updated to 2018/19 levels using the latest tourism expenditure data from Tourism Research Australia, or TRA hereafter ( TRA, 2020 ) to calibrate the latest expenditure patterns of all markets. The method allows us to estimate the impacts on the economy from lost inbound visitor numbers compared to the benchmark year 2018/19. The shock is a decrease in the demand of international tourism. Therefore, the original expenditure patterns of the international visitors are crucial in order to reflect accurately the loss in economic activity in 2020. The pandemic may potentially change visitor expenditure patterns once the international border closure is lifted and visitors start travelling again. Such longer-term changes are important in the impact analysis of the recovery, but are beyond the scope of this study. As this study examines the losses compared to what we had before COVID-19, the pattern of 2018/19 is most suitable and will provide accurate estimates.

Direct impacts of COVID-19 from the international tourism market

The impacts of COVID-19 from the international tourism market are measured through two stages. In the first stage, the tourism satellite account (TSA) approach is used to measure the economic impacts on industries providing goods and services directly to visitors. The second stage measures how far the direct impacts can permeate through the inter-industry linkages to generate further effects on other industries in the whole economy using the tourism CGE model.

Estimating the shocks

The base year of the model database is in 2018/19. However, as the time frame of the pandemic is currently spreading over the calendar year 2020, covering two financial years of 2019/20 and 2020/21, for convenience, the impacts are estimated for the calendar year 2020 on the basis of expenditure patterns and industry structure for 2018/19.

Table 2 presents the historical data of visitor arrivals to Australia in 2018/19 and period between January to September of 2020 by inbound market. Arrivals from overseas started to decline significantly in February. The numbers of arrivals from all markets effectively ended in April ( ABS, 2020 ). All inbound markets experienced significant declines compared to the same period the year previously. Losses of visitor arrivals are calculated for individual markets. For example, over the first nine months of 2020 there were only 206,690 visitors from China, or just 14% of the 2018/19 base. This implies a loss of 86% of Chinese visitors for nearly the whole 2020. All individual markets are estimated to experience a major downturn for 2020, losing at least 73% of their visitors. The percentage declines are displayed as (negative) shocks in the right-hand column of Table 2 .

Effects of COVID-19 on estimated losses of visitor arrivals.

Direct impacts

Tourism revenue is assumed to change proportional to the change in visitor number for individual markets estimated in Table 2 . Taking China for example, 86% less inbound tourists means 86% less inbound tourism expenditure, equivalent to A$10,062 million as presented in Table 3 . Tourism expenditure is measured at purchasers' prices that include values of goods and services produced by domestic industries as well as imports from overseas, net taxes payable to the government and margins to bring goods and services to visitors. To measure the direct impacts, expenditure measured at purchasers' prices is decomposed so that only values contributed by domestic industries providing goods and services directly to visitors are reflected ( Pham et al., 2009 ).

Direct impacts of COVID-19 from the international tourism market in Australia.

Based on TRA's unpublished TSA data ( TRA, 2020 ) on tourism revenue and tourism contribution of each market to the Australian economy in terms of gross value-added, gross domestic product and numbers employed in tourism, the COVID-19 direct impacts of those international markets are calculated on the pro-rata basis of the revenue losses for those international markets for 2020. The total loss is estimated to be more than A$31.8 billion, equal to 81.2% of the total international tourism revenue in 2018/19. This translates into $A14.5 billion of lost tourism gross domestic product (TGDP). Total loss of direct tourism employment from these international tourism markets is estimated as 152,000 employed persons, which adds 1.15 percentage points of unemployment to the current unemployment at the national level. Relatively, the direct impacts are greater in terms of lost tourism employment (1.2%) than reduced tourism GDP (0.75%), as tourism is a labour-intensive industry.

The estimated effects above were calculated using a strong assumption that Australia will not open up the international border until 2021 at the earliest, as the number of active cases and daily new cases are still increasing across many countries, reducing the likelihood of resurgence without a vaccine. The loss of tourism revenue from China is estimated to be the largest loss to Australia compared to other markets. The loss from the China market alone contributes a dominant share of 26% of the total loss in Australia's international tourism revenue in 2018/19. Such impact is significant and warrants a separate study of the effects of market dependency and strategies to overcome this.

Of the total 152,000 estimated job losses presented in Table 3 , we extended the standard TSA framework to disaggregate the employment impacts by tourism-related industries and by occupation. The TSA base data of 2018/19 for employment was first further disaggregated into individual markets by tourism-related industry to give the distribution of tourism impacts by sector ( Fig. 3 ).

Distribution of direct impacts on employment by sector (per cent).

The definition of tourism by the ABS includes education where visitors attend short courses, workshops or students who spend less than twelve months on their visits to Australia. While most countries have a very small proportion of education in their total tourism expenditure, education accounts for nearly 35% of total tourism expenditure in Australia for visitors from China, taking up slightly more than 50% of the total tourism expenditure on education in Australia ( TRA, 2019a, unpublished data ). This explains the significant impact of 30% on employment accounted for from education in Fig. 3 . Restaurants and bars, retails and hotels are the three sectors that account largely for the total loss of employment, as expected, 53%.

The results show that the employment effects of COVID-19 extend across many tourism relevant industries, with education the most badly affected, followed by restaurants and bars, retail trading and hotels. The results reinforce the fact that, given its links with other industries, a downturn in tourism will adversely affect many other sectors. An implication of this is that rescue strategies directed at tourism can deliver spillover benefits for other sectors along tourism's value chain where the links with tourism may not be immediately evident ( Song, 2012 ).

The industries listed in Fig. 3 , are then mapped back to the ANZSIC industries. Given the occupation structure by the ANZSIC industry provided by the ABS (2020, Cat. 6291.0) , the employment impacts of the international tourism markets are then translated into occupations as seen in Fig. 4 .

Distribution of direct impacts on employment by occupation (per cent).

Among all occupations affected by the international tourism market, nearly 57% are among the low-skilled and basic-skilled groups. Managers, professionals and technicians and trades account for 43% in total job losses. Relatively, the direct impacts have more effect on the low-income groups of workers. The results also indicate that a downturn in tourism has adverse effects on employment in many occupations that may not be obviously thought of as ‘tourism related’. In addition to sales and service workers, conventional thinking of tourism workforce, the COVID-19 crisis affects employment among professionals, managers and technicians. This reflects the widespread effects that tourism has on employment along its value chain ( Song, 2012 ).

Economy-wide impacts of the international tourism market

The magnitude of the COVID-19 impact can potentially render long-term changes in expenditure patterns, behaviours among industries and consumers that require careful attention in modelling tasks. For example, the losses of employment so far have triggered a lower propensity to consume for all households. Using the (high) value of the old parameter for propensity to consume to estimate sales revenue during and post-COVID19 will likely overestimate the industry sales revenue, as consumers are not prepared to spend as much as previously. This is a challenge for Treasury Departments world-wide in their preparation for upcoming budgets. In contrast, estimates of industry output losses from COVID-19 will be underestimated when imposing a lower value of the new parameter for the propensity to consume in the model. The losses must be based on the income level, and subsequently the associated behavioural parameters, before the crisis event. Depending on the objectives of analysis, either a projection or an impact assessment, a certain set of parameters, ex-post or ex-ante respectively, would be required specifically. It is not necessarily that all economic analyses must now adopt new parameters. This really depends on what effects we are trying to capture.

As the literature reveals, pandemics induce a wide range of changes to the economy including an unplanned large fiscal expansion from the government, changes in household consumption and the associated expenditure pattern, new relationship among industries and changes in labour supply. These are important factors in projecting where the economy is on its trajectory going through the pandemic or predicting tax revenue for government budget purposes.

This paper has a different objective. It focuses solely on the costs of losing the inbound segment to provide insights into the path that the Australian Government can assist the industry in its fight for survival . Therefore, the modelling scenarios are conducted in a ceteris paribus condition so that impacts from the losses of the inbound segment are clearly isolated from impacts of all of the aforementioned factors. Results in this paper are strictly due to the international border closure, and subsequently the losses of international arrivals.

This explains the rationale in our approach not to modify model parameters nor to include the fiscal expansion of billions of dollars that the Australian Government has injected into the economy. If such fiscal expansion policy or parameters were to be incorporated, results would be distorted, thus would not, and cannot, be interpreted as the impacts of the losses of the inbound tourism markets on the Australian economy due to COVID-19.

Macro results

The direct impacts of reduced inbound tourism will have further effects on other industries in the rest of the economy through the inter-industry linkages that generates larger impacts on the economy. The tourism CGE model was applied to estimate the flow-on economic impacts of COVID-19 in 2020. Given the comparative nature of the model, results are not traced explicitly on any time path. We adopt a standard short-run scenario, usually within a year. The short-run results are of particular relevance as they will help the Australian Government to understand the likely immediate impacts on the economy through losses to tourism so that relevant policies can be put in place to support the industry. In the short run, nominal wages are assumed to be fixed while changes in demand for labour lead to fluctuations of employment numbers. For the capital market, capital stocks are normally fixed in the short run as buildings and equipment take time to build up, while the rates of return will vary in response changes in demand for capital. Investment, however, is assumed to respond to the prevailing conditions in the economy. If the income from capital is growing faster than the costs of investment, this will entice more investment. The benefits of having more capital stocks will materialise beyond the short-run timeframe. In contrast, when the costs of investment are growing faster than the income from capital, this implies a decline in the rates of return, thus discouraging investment. This could lead to reduction of capital stocks and affect the supply side of industries in the longer run. Although the Australian Government has applied a fiscal stimulus package to the economy, the stimulus is not incorporated in the analysis as doing so will dilute the impacts of the travel restrictions on visitor flows to the country. Government consumption is held constant in this paper. Finally, the exchange rate is set exogenously as a numeraire in this study.

Although the direct impacts ( Table 3 ) were estimated for each market individually, the economy-wide impacts are measured for the international tourism market as a whole. The losses of international visitor arrivals in the percentage form in Table 2 were imposed onto the model simultaneously to generate the overall simulations of impacts.

The reduced tourism demand will have adverse impacts on the tourism industry, and as a result, the tourism industry will release its resources to the rest of the economy. This, in effect, can reduce the cost pressures on production and can help to increase exports of other industries. However, given the current condition that almost all of countries are focusing on fighting the pandemic for the rest of 2020, it is likely that the released resources might not be utilised to the full extent, particularly when the tension between the Chinese Government (Australia's major trading partner) and the Australian Government has escalated due to the call for an enquiry into the origin of COVID-19. Potentially, the reduced production costs could be used for trade diversion strategy so that the Australian exports can reach markets other than China. This could help Australia's traditional exporting industries such as coal, mining and basic metal products. Thus, this study examines the loss of international tourism demand in both scenarios, with and without export increases from other industries.

Table 4 shows the macro results in percentage change form and values measured at 2018/19 prices. Columns 1 and 3 are results of the scenario with ‘increased exports’ from the traditional exporting sectors, while columns 2 and 4 are results of the ‘without increased exports’ scenario. We begin our explanation of results with the most stringent scenario in columns 2 and 4, assuming ‘no exports’. In the absence of the responses of the traditional export sectors, the travel restrictions associated with the international tourism sector are estimated to result in a decline of 6.84% of total exports or a total loss of A$31.802 billion, purely from the international tourism sector as previously indicated in Table 3 . This reduction in tourism revenue will directly lower demand for goods and services of tourism, thus reducing employment and income for those working in tourism-related industries such as hotels, restaurants, travel agencies and retail trade. The income losses of tourism employees will further result in lower demands for output of other industries, and lower returns on investment, driving down investment by nearly 3.38% (or A$15.2 billion).

The COVID-19 impacts of the international market on the Australian economy.

The overall reduction in demand from the domestic economy reduces demands for imports by 3.28% (A$14.487 billion). The reduction in imports could also be influenced by the fact that domestic products are relatively cheaper than those from overseas, domestic consumers shift toward domestically produced goods and services. Cheaper products from the domestic economy are reflected by the decline of 2.76% in the consumer price index (CPI) from the demand side, or 2.63% of GDP deflator from the supply side.

The net effect on output is estimated to result in a large reduction in demand for labour across all industries by 3.58%. While nominal wages are constant, real wages actually increase for those who are still employed, due to the reduction in the CPI. Nevertheless, the job losses dominate the effect of lower income for the household sector leading to lower household consumption in real terms by 0.9%, equivalent to A$9.6 billion, as seen in Table 4 .

Overall, reduced inbound tourism is estimated to shrink the Australian economy by 2.2%, equivalent to A$42.1 billion, compared to the base 2018/19. The downturn of the international tourism markets is estimated to cut 456,500 jobs across all industries, adding 3.45 percentage points of unemployment to the current level of unemployment.

In the event that the released resources (primarily labour) from the tourism-related industries can be utilised in the traditional exporting industries, the loss of international tourism revenue is offset by a modest increase of A$1.8 billion in traditional exports due to lower production costs, resulting in a total decline of exports of A$29.9 billion, or 6.4% reduction. The adverse impacts are softened slightly for all macro variables in columns 1 and 3 of Table 4 . Household consumption is estimated to reduce by A$8.8 billion, investment by A$13.5 billion and GDP by A$39.2 billion. The number of job losses is slightly smaller compared to the No Trade case, estimated to be approximately 423,500 jobs or 3.2 percentage points of unemployment nationally.

The exogenous setting of the exchange rate for the short-run closure restricts reallocation of resources across industries in the domestic economy to suit the current conditions of the pandemic. The magnitude of the offset can be larger within a longer-term setting that allows for greater labour mobility. Nevertheless, the results highlight an opportunity for Australia to broaden its trade portfolio in order to minimise risks by reducing dependency on just one or two main trading partners for its traditional exporting industries.

Sectoral results

Among all industries, as expected, tourism-related industries including accommodation, air, rail and road transport, and restaurants are primarily the hardest hit as seen in Table 5 . The output losses of accommodation and air and rail transport industries range between 12% to 17%. The impacts on employment are even greater, between 20% to 23%, since these industries are labour intensive. These results displayed in Table 5 reinforce the importance of tourism for the output of a large range of industries and demonstrate that the tourism effects of the pandemic extend across almost all industry sectors.

Impacts on industry output.

An important note for industries in Table 5 is that the result for construction masks its significant impact of the industry. Given its very larger output base, and labour intensiveness, the range of output losses in construction between 2.5 and 2.8% is significant for the economy. This output reduction is induced by the decline in investment as seen in Table 4 .

Occupations

Fig. 4 provides the distribution of the employment impacts by occupations using the ABS classification. The distribution was derived by applying the simulation results of labour demand by occupation on the actual level occupations for 2018/19 ( ABS, 2020, Cat 6291.0 ). The differences of employment impacts between the two scenarios on the proportion basis are marginal, thus Table 6 provides a representative composition of occupations for both scenarios (with and without trade). For comparison, Table 6 reproduces the composition/distribution of occupations from the direct impacts displayed in Fig. 4 and also includes the national profile of occupations for 2018/19 – the base year. While the pattern of the direct effect highlights the typical nature of employment in tourism with large shares of employment of service workers, sales workers and labourers, the distribution of employment effects in the economy-wide impacts tends to resemble broadly the structure of occupations across all industries in 2018/19. The impacts of COVID-19 are not only on the low-skilled groups, workers in the skilled labour groups (managers, professional and technicians and trades) are also affected. Since the skilled labour groups tend to have higher wage rates, the absolute income loss is relatively more for the skilled labour groups.

Distribution of the international tourism effects by occupation (negative per cent).

Conclusions

The COVID-19 pandemic is still developing and its incidence varies greatly by destination. Policy responses are highly specific to country's economic and public health contexts. Despite the industry's proven resilient capability, the depth and breadth of the pandemic impacts on tourism and the wider economy imply that an early recovery is unlikely. This paper thus focuses on only the short-term impacts for 2020 on the Australian economy.

The results of our study for Australia are instructive. Not surprisingly, the pandemic affects tourism directly with a decline in output and employment not only in characteristic tourism industries such as accommodation, restaurants, and transportation, but also in a range of many other industries. The study highlights the significance of Australia's inbound tourism industry, which is estimated to result in an immediate decline of between A$39-A$42 billion in GDP. The results show direct job losses of around 152,000 in tourism, extending to between 423,000 and 456,000 across many industries along the tourism value chain. As a labour-intensive industry, the impacts on the basis of percentage change of employment is estimated to be greater than the reduction in national GDP. This paper confirms the pattern of long-term declining investment and depressed rates of return, as observed from past pandemic studies ( Jordà et al., 2020 ). If this is not addressed adequately, the industry will lose its economy of scale during a slow recovery in tourism demand, lowered output with higher prices might be the outcome at the end, a long and steep road ahead for tourism businesses. To what extent JobSeeker and JobKeeper programs ( Australian Government, 2020 ) are required remains an important question for the Australian government.

Tourism industry stakeholders, public and private, should be aware of the fact that the tourism effects of COVID-19 extend beyond the direct impacts on a narrow set of (characteristic) industries related to tourism. Among industries, education is the industry that most suffers from the decline in inbound visitor expenditure. The study reveals that the tourism downturn has adverse effects on direct employment in many occupations that may not be obviously thought of as ‘tourism related’, including professionals, managers and technicians. These consequences reinforce the depth and complexity of tourism's value chain. It is important for the government to provide support evenly and equally across all groups of labour occupations in society, as the pandemic affects employment widely over a lengthy period.

While resources released from the tourism industry can be re-employed by other industries, it is unlikely that these resources can be taken up significantly by non-tourism industries in present conditions. But, potentially, the released resources could be used, to some extent, for trade diversion strategy supporting other exporting industries. The study explored differences in the results between ‘no trade’ and ‘with trade’ scenarios. Impacts generally are softened in the ‘with trade’ assumption compared to the alternative. The reduced losses experienced when trade remains open indicates the potential gains to the Australian economy of diversifying its export industries in a post COVID world.

As the pandemic unfolds, Australian governments, from state to national level, are taking aggressive and co-ordinated policy action to maintain employment levels and reduce business closures. The economy-wide stimulus package targets three areas: individuals and households, businesses, flow of credit ( Australian Government, 2020 ). Within the overall economic stimulus package, specific strategies have been directed at the tourism and hospitality industries to ensure business survival. These include reduced fees and charges for tourism businesses across several sectors; taxation relief for domestic airlines; and targeted measures to boost domestic tourism after the crisis. The crisis has revealed the need for sharing crucial and timely data and information, such as the extent and pattern of the impacts, among all tourism stakeholders to support informed decision making, and for national, regional and local destination managers to adopt an integrated governmental and all -industry approach so that their own response measures are consistent and complementary to achievement of accepted macroeconomic goals ( OECD, 2020a , OECD, 2020b ). The findings of this study concerning both the macroeconomic, sectoral and occupational effects of reduced inbound tourism to Australia can help to formulate specific policies to stimulate the industry. Further, industry interactive effects between tourism and other industries identified in this study indicate that policies directed at Australia's tourism recovery can deliver spillover benefits to other areas of economic activity. As tourism output increases, so too will the outputs of many connected industries.

Beyond the immediate industry focussed responses to stimulate the economy, it would be useful if the Australian policy makers can broaden up the current experiences in crisis management strategies to better prepare the country for future shocks of any types. Although productive activities need to bounce back to provide jobs and income for households, it is imperative to take this opportunity to develop inbuilt-sustainable growth for the industry because sustainability is a prerequisite condition for growth in the long run. The established mindset underpinning tourism planning, development and research is under criticism on the grounds that the ‘business as usual’ emphasis on economic growth and resource degradation is impossible to reconcile with sustainability of travel and tourism ( Bramwell & Lane, 2011 ). Ignoring this type of criticism, the majority of ‘priorities for tourism recovery’ and ‘global guidelines’ promulgated by the United Nations World Tourism Organization, 2020a , United Nations World Tourism Organization, 2020b , United Nations World Tourism Organization, 2020c are just ‘nods and tweaks’ to ‘business as usual’, with no real substance to progress sustainably in the post COVID world.

COVID-19 will forever change the way we travel and may be expected to have a substantial impact on the implementation of each of the United Nation's Sustainable Development Goals in which tourism can play a major participative role ( UNWTO, 2017 ). There is insufficient space to explore this issue here; but suffice to say that the pathways to facilitate tourism's transition to the new sustainable future paradigm have been identified ( Dwyer, 2018 ) and have substantial relevance to construction and operation of the global tourism industry post COVID-19.

Declaration of competing interest

I have no declaration of interest to make.

Biographies

Tien Pham ( [email protected] ) is an A/Prof at Griffith University, with strong interests in CGE modelling, tourism satellite accounts and demand analysis.

Larry Dwyer is Visiting Research Professor. He has published widely across many areas of tourism research including economic impact analysis and TSA.

Jen-Je Su (PhD) is a Senior Lecturer at Griffith Business School, with research interests in forecast and economic demand modelling.

Tramy Ngo (PhD; Griffith University) is an experienced tourism market analyst.

Associate editor: Haiyan Song

• Australian Bureau of Statistics . Detailed labour force data collected on a quarterly basis; July: 2020. Labour force, Australia, detailed, quarterly. https://www.abs.gov.au/statistics/labour/employment-and-unemployment/labour-force-australia-detailed-quarterly/latest-release [ Google Scholar ]
• Australian Bureau of Statistics (2020a) 3401.0 - Overseas Arrivals and Departures, Australia, July https://www.abs.gov.au/statistics/industry/tourism-and-transport/overseas-arrivals-and-departures-australia/latest-release , November 2020.
• Australian Government . Australian Treasury; 2020. Economic Response to the Coronavirus. https://treasury.gov.au/coronavirus> accessed 8/04/2020. [ Google Scholar ]
• Blake A., Sinclair M.T., Sugiyarto G. Quantifying the impact of foot and mouth disease on tourism and the UK economy. Tourism Economics. 2003; 9 (4):449–465. [ Google Scholar ]
• Boissay F., Patel N., Shin H.S. Trade Finance, and the COVID-19 Crisis. 2020. Trade credit, trade finance, and the Covid-19 Crisis. (June 19, 2020) [ Google Scholar ]
• Boissay F., Rungcharoenkitkul P. “Macroeconomic effects of Covid-19: An early review”, BIS Bulletin , no. 7. April. 2020; 2020 [ Google Scholar ]
• Bramwell B., Lane B. Critical research on the governance of tourism and sustainability. Journal of Sustainable Tourism. 2011; 19 (4–5):411–421. [ Google Scholar ]
• Burfisher M. Cambridge University Press; Cambridge: 2017. Introduction to computable general equilibrium models. [ Google Scholar ]
• Burns A., Van der Mensbrugghe D., Timmer H. World Bank; Washington, DC: 2006. Evaluating the economic consequences of avian influenza. [ Google Scholar ]
• Cardenete M.A., Guerra A.I., Sancho F. Springer; Berlin Heidelberg: 2012. Applied general equilibrium. [ Google Scholar ]
• Colston P (2020) ‘Australia's tourism industry associations united in new demands for support measures’ conference and meetings world cmw-net, march 3.
• Department of Agriculture, Water and the Environment (2020) Agricultural Outlook- March 2020 https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/mar-2020
• Department of Industry, Science, Energy and Resources (2020) Resources and Energy Quarterly – March 2020, https://www.industry.gov.au/data-and-publications/resources-and-energy-quarterly-march-2020
• Dixon P.B., Parmenter B.R., Sutton J., Vincent D.P. Contributions to economic analysis. Vol. 142. North-Holland Publishing Company; 1982. ORANI: A multisectoral model of the Australian economy. (pp. xviii + 372) [ Google Scholar ]
• Dwyer L. Computable general equilibrium Modelling: An important tool for tourism policy analysis. Tourism and Hospitality Management. 2015; 21 (2):111–126. [ Google Scholar ]
• Dwyer L. Saluting while the ship sinks: The necessity for tourism paradigm change. Journal of Sustainable Tourism. 2018; 26 (1):29–48. [ Google Scholar ]
• Dwyer L., Forsyth P., Spurr R. Effects of the SARS crisis on the economic contribution of tourism to Australia. Tourism Review International. 2006; 10 (1–2):47–55. [ Google Scholar ]
• Gössling S., Scott D., Hall C.M. Pandemics, tourism and global change: A rapid assessment of COVID-19. Journal of Sustainable Tourism. 2020:1–20. [ Google Scholar ]
• Hai W., Zhao Z., Wang J., Hou Z.G. The short-term impact of SARS on the Chinese economy. Asian Economic Papers. 2004; 3 (1):57–61. [ Google Scholar ]
• Horridge J.M., Jerie M., Mustakinov D., Schiffmann F. 2018. GEMPACK manual. (GEMPACK software) [ Google Scholar ]
• Horridge M., Madden J., Wittwer G. The impact of the 2002–2003 drought on Australia. Journal of Policy Modeling. 2005; 27 (3):285–308. [ Google Scholar ]
• IMF (2020), World Economic Outlook Update: A Crisis Like No Other, An Uncertain Recovery, June 2020.
• Jonung L., Roeger W. 2006. “The macroeconomic effects of a pandemic in Europe-A model-based assessment” ECFIN/001515 – EN, ISBN 92-79-01192-8, KC-AI-06-251-EN-C. (European Communities) [ Google Scholar ]
• Jordà, O, S Singh and A Taylor (2020), “Longer-run economic consequences of pandemics”, unpublished manuscript, March.
• Keogh-Brown M., Wren-Lewis S., Edmunds W.J., Beutels P., Smith R.D. The possible macroeconomic impact on the UK of an influenza pandemic. Health Economics. 2010; 19 :1345–1360. [ PubMed ] [ Google Scholar ]
• Keogh-Brown M.R., Smith R.D., Edmunds J.W., Beutels P. The macroeconomic impact of pandemic influenza: estimates from models of the United Kingdom, France, Belgium and The Netherlands. The European Journal of Health Economics. 2010; 11 [ PubMed ] [ Google Scholar ]
• Kohlscheen, E. B. Mojon and D. Rees (2020), “The Macroeconomic Spillover Effects of the Pandemic on the Global Economy”, BIS Bulletin, no 4.
• Kuo H.I., Chang C.L., Huang B.W., Chen C.C., McAleer M. Estimating the impact of avian flu on international tourism demand using panel data. Tourism Economics. 2009; 15 (3):501–511. [ Google Scholar ]
• Kuo H.I., Chen C.C., Tseng W.C., Ju L.F., Huang B.W. Assessing impacts of SARS and avian flu on international tourism demand to Asia. Tourism Management. 2008; 29 (5):917–928. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lee J.-W., McKibbin W. In: Learning from SARS: Preparing for the next outbreak. Knobler S., Mahmoud A., Lemon S., Mack A., Sivitz L., Oberholtzer K., editors. The National Academies Press; Washington DC: 2004. Estimating the global economic costs of SARS. (0-309-09154-3) [ PubMed ] [ Google Scholar ]
• Liu J., Moss S.E., Zhang J. The life cycle of a pandemic crisis: SARS impact on air travel. J. Int. Bus. Res. 2011; 10 (2) [ Google Scholar ]
• Maliszewska M., Mattoo A., van der Mensbrugghe D. Policy Research Working Paper no. 9211. World Bank Group; 2020. The potential impact of COVID-19 on GDP and trade. April 2020. [ Google Scholar ]
• McAleer M., Huang B., Kuo H., Chen C., Chang C. An econometric analysis of SARS and avian flu on international tourist arrivals to Asia. Environmental Modeling and Software. 2010; 25 (1):100–106. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• McKibbin W., Fernando R. CAMA Working Paper, no 19/2020. 2020. The global macroeconomic impacts of Covid-19: seven scenarios. [ Google Scholar ]
• McKibbin W., Sidorenko A. Lowy Institute Analysis; 2006. Global macroeconomic consequences of pandemic influenza. February. [ Google Scholar ]
• OECD (2020a), Tourism policy responses. Tacking coronavirus, contributing to a global effort (COVID-19), OECD Tourism Committee https://read.oecd-ilibrary.org/view/?ref=124_124984-7uf8nm95se&Title=Covid-19:%20Tourism%20Policy%20Responses .
• OECD . 2020. Evaluating the initial impact of Covid containment measures on activity. (27 March) [ Google Scholar ]
• Page S., Song H., Wu D. Assessing the impacts of the global economic crisis and swine flu on inbound tourism demand in the United Kingdom. Journal of Travel Research. 2012; 51 (2):142–153. [ Google Scholar ]
• Park C., Villafuerte J., Abiad A., Narayanan B., Banzon E., Samson J.…Tayag M. ADB Briefs. 2020. An updated assessment of the economic impact of COVID-19. no. 133, ISBN 978-92-9262-215-2; May 2020. [ Google Scholar ]
• Pham T.D., Dwyer L. In: The handbook of tourism economics – Analysis, new applications and case studies, chapter 22. Tisdell, editor. World Scientific Publishing; 2013. Tourism satellite account and its applications in CGE Modelling. [ Google Scholar ]
• Pham T.D., Dwyer L., Spurr R. Constructing a regional TSA: The case of Queensland. Tourism Analysis. 2009; 13 (5/6):445–460. [ Google Scholar ]
• Pham T.D., Simmons D., Spurr R. Climate change induced impacts on tourism destinations: The case of Australia Special Issue for Climate Change. Journal of Sustainable Tourism. 2010; 18 (3):449–473. [ Google Scholar ]
• PricewaterhouseCoopers (2020), The possible economic consequences of a novel coronavirus (COVID-19) pandemic, Australia matters.
• Smith R.D., Keogh-Brown M.R., Barnett T. Estimating the economic impact of pandemic influenza: An application of the computable general equilibrium model to the UK. Social Science & Medicine. 2011; 73 (2):235. (1982) (0277e–9536) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Song H. Routledge; NY: 2012. Tourism supply chain management. [ Google Scholar ]
• Tourism and Transport Forum (2020) Coronavirus set to hit Australian tourism industry much harder than SARS, Sydney, https://www.ttf.org.au/coronavirus-set-to-hit-australian-tourism-industry-much-harder-than-sars/
• Tourism Research Australia (2019a) Tourism Satellite Accounts 2029 , unpublished data, Canberra.
• United Nations World Tourism Organization (2011) Tourism towards 2030, Global Overview.
• United Nations World Tourism Organization (2020a) World Tourism Barometer Volume 18, Issue 1. January 2020, https://www.unwto.org/world-tourism-barometer-n18-january-2020
• United Nations World Tourism Organization (2020b), ‘ International tourism growth continues to outplace the global economy’ , 24/03/2020, available at: https://unwto.org/international-tourism-growth-continues-to-outpace-the-economy
• United Nations World Tourism Organization (2020c) Global Guidelines to Restart Tourism May 28 https://webunwto.s3.eu-west-1.amazonaws.com/s3fs-public/2020-05/UNWTO-Global-Guidelines-to-Restart-Tourism.pdf
• United Nations World Tourism Organization and United Nations Development Programme . UNWTO; Madrid: 2017. Tourism and the sustainable development goals – Journey to 2030, Highlights. [ Google Scholar ]
• World Bank . 2014. “The economic impact of the 2014 ebola epidemic: Short and medium term estimates for West Africa”, mimeo. (October) [ Google Scholar ]
• World Travel and Tourism Council (2020) Global Economic Impact and Trends, June file:///C:/Users/105893/Downloads/Global_Economic_Impact_&_Trends_2020.pdf.
• Yang H.Y., Chen K.H. ‘A general equilibrium analysis of the economic impact of a tourism crisis: A case study of the SARS epidemic in Taiwan’ Journal of Policy Research in Tourism . Leisure and Events. 2009; 1 (1):37–60. [ Google Scholar ]
• Yang Y., Zhang H., Chen X. Coronavirus pandemic and tourism: Dynamic stochastic general equilibrium modeling of infectious disease outbreak. Annals of Tourism Research. 2020 doi: 10.1016/j.annals.2020.102913. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

24 August 2022

How responsible tourism contributes to a more sustainable visitor economy

An increasing number of tourists are looking for sustainable travel experiences.

More than 70% of travellers indicate they would make more effort to travel sustainably in the coming year. This is up 10% from 2021. (Source: booking.com, Sustainable Travel Report, 2022).

The national strategy for the visitor economy,  THRIVE 2030 , recognises the importance of sustainability to the long-term growth and resilience of Australian tourism.

Tourism Ministers from the 21 Asia-Pacific Economic Cooperation (APEC) member economies, including Australia, agreed to and released the “ Policy Recommendations for Tourism of the Future: Regenerative Tourism ”. This set of policy recommendations covers concrete actions for member economies to consider. Gathered under  the theme of APEC 2022  “Open. Connect. Balance.”, they envision the future of tourism as inclusive and sustainable.

What responsible tourism means

Responsible tourism is about ‘making better places for people to live in and better places for people to visit’ (Source: Cape Town Declaration, 2002).

It asks industry, government, local communities and tourists to work together to make tourism more sustainable by:

• respecting local cultures
• protecting the environment for future generations
• making tourism accessible to people with a disability
• providing socio-economic benefits to the host community
• providing meaningful connections between visitors and local people.

Contributing to a more sustainable tourism industry

There are many ways for destinations and visitors to make tourism more sustainable. These may include:

• providing carbon-neutral travel options like electric vehicles or bicycles
• using native ingredients, sourced locally and sustainably
• using biodegradable or recyclable packaging, or no packaging wherever possible
• providing training and employment opportunities for local people
• respectfully highlighting Indigenous cultures
• using local or minority-owned suppliers, including Indigenous suppliers
• engaging early and often with local communities about future tourism development
• managing visitor numbers at environmentally or culturally sensitive areas.

Making a promise to future generations

Some destinations are even asking tourists to commit to protecting the environment, native wildlife and host culture.

Tasmania’s Maria Island, for example, asks tourists to pledge to ‘keep it wild and pristine’:

I take this pledge to respect and protect the furred and feathered residents of Maria. I will remember you are wild and pledge to keep you this way.

I promise I will respectfully enjoy the wonders of your beautiful island home, from the wharf, to the Painted Cliffs, to the Rocky bluffs, haunted bays and mystery of Maria’s ruins.

Wombats, when you trundle past me I pledge I will not chase you with my selfie stick, or get too close to your babies. I will not surround you, or try and pick you up. I will make sure I don’t leave rubbish or food from my morning tea. I pledge to let you stay wild.

I vow to explore with a sense of responsibility, adventure and kindness. I will leave your wild island as I found it, and take home memories filled with beauty and my soul filled up with wonder.

Pledges such as this are an example of responsible tourism in action. They go beyond encouraging visitors to make their visit more sustainable, to empowering them to be responsible for their actions.

Achieving sustainable growth that balances social, environmental and economic factors is one of the guiding principles of THRIVE 2030 , the industry-led, government-enabled strategy for Australia’s visitor economy. 

Growing the visitor economy

THRIVE 2030 is Australia’s national strategy for the long-term, sustainable growth of the visitor economy.

Learn about THRIVE 2030

Related analysis

Celebrating 35 years of tourism research australia.

For 35 years, Tourism Research Australia has worked with states and territories to generate data and intelligence on Australia’s visitor economy.

People with disability a valuable addition to the tourism workforce

Employing people with disability helps address shortages in the visitor economy workforce, develops skills and boosts the tourism industry.

Indigenous-owned businesses THRIVE in the visitor economy

Austrade encourages businesses in the visitor economy to work with Indigenous-owned enterprises. Read about some examples.

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• Economic contribution of tourism

Tourism is an important industry to our economy, filling 110,800 jobs and contributing $13.2 billion to WA's economy (by Gross State Product) in 2022-23. Find out the value of tourism to the regional, state and national economy below.

Economic contribution of tourism to WA

In April 2024, Tourism Research Australia released the State Tourism Satellite Accounts (TSA) 2022-23, which provides the latest data on tourism's contribution to WA's economy.

This report also outlines the economic contribution of tourism to each state and territory, in relation to Gross State Product, Gross Value Added and tourism filled jobs.

Download a summary of  The economic contribution of tourism to Western Australia in 2022-23 (PDF 672KB) .

To download the full report, visit Tourism Research Australia's website.

Economic contribution of tourism to WA's regions

In July 2023, Tourism Research Australia released the 2021-22 Regional Tourism Satellite Account, which provides the latest data on tourism's contribution to WA's five tourism regions, as well as other tourism regions in Australia.

Download a summary of The economic contribution of tourism to Western Australia's tourism regions in 2021-22 . 

Visit  Tourism Research Australia's website  to access data for each tourism region across Australia.​​

Tourism businesses in WA

Tourism Research Australia estimates that as at June 2023, there were around 30,800 tourism businesses in Western Australia. Visit Tourism Research Australia's website to view the Tourism Businesses in Australia, June 2018 to June 2023 report .

State of the Industry - Australia

Tourism Research Australia publishes an annual State of the Industry Report . This report provides an overview of the visitor economy in Australia, reporting key metrics for both demand (e.g. visitation) and supply (e.g. aviation access). 

Latest tourism statistics

• Visitor statistics
• Useful links

Last Reviewed: 2024-05-13

Acknowledgement of Country Tourism Western Australia acknowledges Aboriginal peoples as the traditional custodians of Western Australia and pay our respects to Elders past and present. We celebrate the diversity of Aboriginal West Australians and honour their continuing connection to Country, culture and community. We recognise and appreciate the invaluable contributions made by First Nations peoples across many generations in shaping Western Australia as a premier destination.

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All contents copyright © Government of Western Australia. All rights reserved.

WTTC: Australia's travel & tourism industry to generate USD176bn in 2024

World Travel & Tourism Council ( WTTC ) forecast (21-Jun-2024) the following for Australia 's travel & tourism sector from its 2024 Economic Impact Research:

• Travel & tourism will contribute more to Australia 's economy in 2024 than any previous year on record. The sector is poised to surpass its previous peak with a projected economic contribution of AUD265.5 billion (USD176.16 billion), representing 10% of the Australian economy;
• The sector is expected to maintain "robust" growth over the next decade, aligning with the global economy's growth rate, and is projected to exceed AUD345 billion (USD228.91 billion) by 2034;
• In 2023, jobs in Australia 's travel & tourism sector increased by approximately 10% year-on-year, reaching 1.42 million and representing a tenth of the national workforce;
• Latest research predicts a full recovery of jobs lost during the pandemic in 2024, with job levels surpassing the 2018 peak by 2026. Over the next decade, the sector is expected to support over two million jobs, representing 12% of all Australian employment;
• Spending reached AUD31.6 billion (USD20.97 billion) in 2023, with forecasts suggesting it will near AUD35 billion (USD23.22 billion) in 2024 and set a new record in 2025;
• By 2034, WTTC predicts international visitor spending will reach almost AUD52.5 billion (USD34.83 billion);
• The sector is forecast to contribute AUD337.4 billion (USD223.87 billion) in 2024, 10.7% of Oceania's total. Jobs are expected to grow by 10% and reach 2.33 million across the region, equivalent to nearly one in nine jobs;
• Domestic visitor spending is anticipated to reach almost AUD180 billion (USD119.43 billion), an uplift of almost 31% since 2019, whilst international visitor spending is projected to recover to AUD65.7 billion (USD43.59 billion) and be within "touching distance" of the 2019 peak.

WTTC president and CEO Julia Simpson stated: " Australia is set to break tourism records", noting WTTC will "throw a spotlight" on the value of travel & tourism to the Australian economy during the WTTC Global Summit in Perth in Oct-2024. Ms Simpson said the summit will "highlight Australia 's dynamic growth, reflecting travel & tourism's broader economic recovery and rising employment trends". [ more - original PR ]

Want More News Like This?

Queensland government pumps $10m into regional tourism as outback operators report 'very quiet' season

Outback Queensland tourism operators have raised concerns over a lacklustre tourism season that has them asking visitors: "Where the bloody hell are you?" 

Businesses are "cautiously concerned to pessimistic" about whether the usual midyear influx of caravanners and grey nomads is coming at all.

"If we compare it to pre-COVID visitation, it's way down," cafe owner Yvonne Tunney said.

Ms Tunney runs a cafe and accommodation in Karumba in the Gulf of Carpentaria, a small coastal town that relies heavily on tourism.

"It's been perfect weather and fishing's been great … but like everywhere else is reporting, it's very quiet as far as tourism numbers and activity goes," she said.

"For those who come out here regularly, they just can't believe it."

Alan Smith, owner of Outback Aussie Tours, was concerned about the financial impact on small, tourism-dependent towns.

"When you get a stinger like this when it's slow to start, it's really going to put them under a lot of pressure," he said.

"You can only make so much money out of two or three months."

"I think we're going to lose people out of the communities and out of the business if this stuff continues much longer."

Mr Smith said after "two of the best years of tourism" during the pandemic, the pendulum was now swinging the other way.

"The economy's been tightened and it's time to pay back that COVID debt," he said.

To the west, the Birdsville Big Red Bash is one of the outback's biggest, most iconic music events, and draws thousands to the desert dunes every year.

It kicks off in less than two weeks, but it too has been hit by reduced patronage.

Organiser Greg Donovan said ticket sales were down compared to previous years " like all other festivals at the moment."

"A lot of people are now moving back to overseas travel … particularly the demographic that comes out to the bash," he said.

So where are the tourists?

It's the Macquarie Dictionary 2023 Word of the Year: "Cozzie livs".

The cost of living — fuel, groceries, and travel have all skyrocketed, meaning for many it is cheaper to travel overseas than it is to travel within their own state.

The state government is stepping in and investing $10 million to fund 57 regional tourism projects.

The hope is these projects, which range from installing accessible footpaths to building an equine healing therapy centre in Chinchilla, will entice tourists to travel in Queensland, rather than go abroad.

Minister for Tourism Michael Healy said the money will bring nearly 300,000 additional visitors to the regions.

"We want to encourage as many people as possible to experience the wonders of Outback Queensland," he said.

Can Queenslanders afford to travel right now?

On an ABC North West Queensland Facebook post describing the slow tourism season out west, hundreds of people weighed in.

"Airports and planes are packed … cheaper to head overseas than holiday at home unfortunately," Leanne Seaton said. 

"Maybe the cost of caravan parks on top of increased fuel costs and grocery costs are making it out of reach for tourists," another commented.

"This will be a trend over the next 20+ years as the level of retirees fall due to the need to work longer just to live. The 2010-COVID days probably saw the peak in retirees and grey nomads for our era," commented Davis Walshe.

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Fewer grey nomads in outback queensland as holiday-makers head overseas.

Where are all the tourists? Outback suffers worst start to peak season in four years

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THE ECONOMIC IMPACTS AND BENEFITS OF TOURISM IN AUSTRALIA A GENERAL EQUILIBRIUM APPROACH

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Larry Dwyer

Tourism Management

Procedia - Social and Behavioral Sciences

Dr Jeetesh Kumar

Christine T Ennew

Tourism Economics

Diana Maris

There are substantial differences between models of the economic impacts of tourism. Not only do the nature and precision of results vary, but data demands, complexity and underlying assumptions also differ. Often, it is not clear whether the models chosen are appropriate for the specific situation to which they are applied. The goal of this article is to provide an overview and evaluation of criteria for the selection of economic impact models. A literature review produced 52 potential criteria, subdivided into 10 groups. Based on an analysis of experts&#39; opinions, the perceived importance of each criterion was determined and a set of essential criteria created. To illustrate the usage of these essential criteria, five models (export base, Keynesian, ad hoc, input–output and computable general equilibrium) were evaluated and compared based on their performance on these criteria. This paper builds on the existing literature by showing that it is possible to make a more informed c...

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Joseph Khelashvili

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Theoretical structure of a tourism focused CGE model for measuring economic impact of an economy

Sriyantha Fernando

Measuring the contribution of tourism to a national economy has always been a frustrating exercise. Tourism does not have specific products. It represents the sum of expenditure by travellers for wide range of products. It is not possible to identify tourism as a single "industry" in the national accounts, its value to the economy is not readily revealed. As a result of the absence of tourism in official economic statistics, there is often an on-going battle to establish tourism credibility as an economic activity and generator of income in the economy. As a result, a significant volume of tourism research over the past few decades have focussed on the development and use of a variety of economic techniques aimed at quantifying the effects of tourism on an economy. In conventional literature has proven that Computable General Equilibrium (CGE) modelling is the best applied tool addressing and analysing tourism related issues in an economy. The paper provided a complete description of the theoretical structure of the CGE-Tourism including all equations and variables by using relevant Excerpts for different blocks of equations in the TABLO file associated with the GEMPACK software used to operationalise the model. The incorporation of tourism using the dummy sector approach into an ORANI type CGE model as an extension and can be considered as the main contribution of this study to the CGE modelling literature for an economy. This is a clear departure from the traditional methods used for tourism modelling in an economy. This model can be used to simulate the economic impact of the tourism boom in an economy

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