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MasterCard Global Destination Cities Index 2014

By Yuwa Hedrick-Wong and Desmond Choong


A hundred years ago, in January 1914, the first commercial flight flew from Tampa to St. Petersburg in Florida, USA. The distance between these two cities in Florida is about 23 miles, and it took 20 minutes for the flimsy wooden and propeller-driven aircraft to do it flying at a top speed of 60 miles an hour. At US$400, the air fare was very expensive for the two paid passengers (roughly equivalent to US$9,300 today). But this 20 minute flight ushered in the era of commercial air travel.[1] Over the course of the last one hundred years, aircrafts got bigger, faster, safer, and more comfortable; but even more importantly, it also got steadily cheaper to fly. The Tampa to St. Petersburg airfare of US$9,300 could easily pay for a round-the-world plane ticket today with change to spare. Cheaper and faster air travel turned it into a mass phenomenon instead of a pass time for the privileged. The expansion of air travel has been dramatic; in 2013, some three billion air passengers flew on commercial airlines crisscrossing the globe.[2]

Today, air travel is woven into the fabric of our everyday lives. Business travel is a given for many working men and women everywhere. Single-purpose leisure trips such as going somewhere special for a weekend just to shop, or to sample cuisine by a famous chef are routine among the cognoscenti. And as air travel becomes increasingly affordable, it has become a “must do” item in recent years for the mass middle class in emerging markets, many of them going overseas for the first time. As Chart 1 shows, the growth rates of international visitor arrivals and their cross-border spending in the 132 destination cities covered by the MasterCard Global Destination Cities Index exceeded world real GDP growth over the 2009 to 2014 period (2014 based on forecast estimates). And this is a period when the global economy is still struggling with a fragile and uncertain recovery. There is no better illustration of the momentum of growth of air travel today.

The impacts of travel on destination cities[3] that receive visitors are very significant from the business, social, and cultural perspectives. International visitors’ spending constitute an increasingly important source of business revenue in a destination city, encompassing the hospitality, retail, transport, sports, and cultural industries, among many others. In many instances, it is a major economic engine for employment and income generation for the city in question. Along with the flow of visitors comes the flow of new ideas and experiences that benefits both the visitors and the destination cities, which are just as important as the flow of spending. As a result, the more connected a destination city is to other cities, the more vibrant and dynamic it becomes.

MasterCard’s Global Destination Cities Index, now in its fifth year, provides an annual ranking of 132 of the most important destination cities in the world[4]. It generates estimates of the total number of international visitors[5] to each of these cities each year, their cross-border spending in these cities, and breakdown of their numbers by feeder cities. The index is therefore a global map of how these 132 cities are connected and the business potential generated in each of them by the inflows of visitor spending.

The World’s Top 20 Destination Cities in 2014

Mastercard Global Destination Cities Index 2014It has been a tight race between London and Bangkok for the number one position in the last few years. Bangkok overtook London in 2013 to become the top ranked destination city in the world for the first time. But London regained the top rank this year with an 8% growth in visitors, versus a 0.5% decline in Bangkok. Given how close the visitor numbers are between these two destination cities, it is clear that the race is by no means over.

Paris, Singapore, and Dubai followed in third, fourth and fifth ranks respectively. Their respective growth rates, however, diverge significantly. At 1.8%, Paris’ growth is very low, and Singapore’s growth rate is slightly higher at 3.1%. But they are both eclipsed by Dubai’s 7.5%. If their current growth rates are to continue, then Dubai would overtake both Paris and Singapore within five years.

Other major changes in the ranking are: Amsterdam overtook Milan to move up from 13th to 12th rank, and Shanghai overtook Vienna.

Chart 3 and Table 2 below show the rankings for the top 20 global destinations in terms of international visitor spending. London is in the top rank in terms of visitor spending[6], which is estimated to be US$19.27 billion in 2014 (London retained its top ranked position in visitor spending in 2013 despite losing the top ranked position to Bangkok in visitor numbers last year). New York and Paris followed in second and third ranks respectively. Madrid moved up from 17th to 16th rank displacing Sydney, while San Francisco moved up 20th to 19th rank displacing Munich.

The numbers of international visitors can also be represented on a per resident basis for each of the destination cities to illustrate the magnitude of their impacts. Chart 4 summarizes the ratios between international visitors and residents in the top 20 destination cities in both 2009 and 2014. While the ratio increased for top 20 destination cities between 2009 and 2014, Dubai is in a league of its own, with the highest ratio of 4.8 visitors per resident, up from 4.2 in 2009. Amsterdam’s ratio is the second highest at 2.6, up from 1.9 in 2009. While Singapore and London have the same ratio of 2.3 in 2014, the former has grown much faster from 1.4 in 2009 compared to London’s 1.8. Kuala Lumpur follows at 1.8, Bangkok at 1.6, and Barcelona at 1.5. Overall, eleven of the top 20 destination cities have a ratio that is bigger than one in 2014. This means that the number of international visitors that each of these cities received in 2014 was equal to or more than the total number residents in the city.

Chart 5 presents the ratios of international visitors’ spending in the destination cities on a per resident basis. Again, Dubai has the highest ratio at US$3,863 per resident. Singapore is at second place with US$2,600 per resident. London follows with US$2,378 per resident. Among the top 20, Shanghai has the lowest visitor spending per resident at US$238.

Top 10 Destination Cities in Asia/Pacific

The top 10 destination cities in Asia/Pacific are shown in Chart 6 and Table 3. Bangkok, ranked second in the world, is in the top rank in the region with 18.37 million international visitors. The top five ranks of Bangkok, Singapore, Kuala Lumpur, Hong Kong, and Seoul remain unchanged from 2013. Tokyo, Mumbai and Beijing round-off the list at 8th, 9th and 10th rank respectively.

The top 10 destination cities in Asia/Pacific by international visitor spending are presented in Chart 7 and Table 4. Bangkok leads with US$14.6 billion followed closely by Singapore at US$14.3 billion. The placements of the top ten Asia Pacific destinations are unchanged from last year.

The dynamism of a destination city is closely affected by its feeder cities – the cities where its international visitors come from or via which they are transiting through.[7] If a destination city is connected with a network of fast growing feeder cities where outbound travel is taking off, then it is well positioned to benefit from such growth. On the other hand, if certain feeder cities are slowing down in economic growth with household income stagnating, then the associated destination cities will likely suffer unless they are able to tap into other growing feeder cities. Mapping a destination city’s key feeder cities therefore generates valuable insights on a destination city’s growth potential as well as challenges ahead. The top 5 feeder cities for each of the three top ranked destination cities in each region are provided here to illustrate the interconnected of these cities.

The top 5 feeder cities for Bangkok are shown in Chart 8. Singapore is the biggest feeder city for Bangkok. While also serving as an origin city for visitors to Bangkok, Singapore is also a major gateway hub for other countries to reach Bangkok. This is followed by Tokyo, Hong Kong, Kuala Lumpur, and Shanghai. Despite all five feeder cities being from Asia/Pacific, 42% of visitors to Bangkok are from outside of the region. In fact, Bangkok has a very diversified network of feeder cities and origin countries, which explains Bangkok’s well known resilience as a tourism hotspot. However, in 2014 four of the top five feeder cities show a drop in visitor numbers to Bangkok due to its ongoing political turmoil, a key reason why Bangkok lost the world’s top rank position to London in 2014.

The top five feeder cities for Singapore, ranked second as a destination city in Asia/Pacific and fourth in the world, are shown in Chart 9. They are Jakarta, Tokyo, Shanghai, Hong Kong, and Manila, and all are in Asia/Pacific. This is consistent with the fact that 82% of visitors to Singapore are from the region.

The top 5 feeder cities for Kuala Lumpur, the third ranked destination city in Asia/Pacific, are shown in Chart 10. They are Singapore, Jakarta, Bangkok, Manila and Melbourne. With the exception of Singapore, they show very strong growth in visitor numbers to Kuala Lumpur, with Melbourne being the highest with an impressive growth rate of 34.7%. About 60% of visitors to Kuala Lumpur are from the Asia/Pacific region.

Top 10 Destination Cities in Europe

Europe’s top 10 destination cities by international visitors are presented in Chart 11 and Table 5. London, being top ranked in the world, is naturally also top ranked in Europe. Paris, Istanbul and Barcelona are in second, third and fourth ranks respectively, unchanged from last year. Amsterdam moves to 5th rank displacing Milan.

Chart 12 and Table 6 show the top 10 destination cities by international visitor spending in Europe. The top four ranks held by London, Paris, Barcelona and Istanbul are unchanged from last year. Vienna moves up two places to 8th rank displacing Milan and Berlin which both move down to 9th and 10th rank respectively.

Details of London’s top 5 feeder cities, New York, Amsterdam, Frankfurt, Stockholm, and Dublin, are summarized in Chart 13. Visitor numbers from New York are growing strongly, contrasting the dropping numbers from Stockholm and Dublin. The majority of international visitors to London are from Europe accounting for 67% of the total. The strong growth of London international visitor arrivals allowed it to quickly reclaim the number one position from Bangkok which suffers from a drop in visitor numbers due to unstable political conditions.

Paris, in the 2nd rank in Europe and 3rd in the world, also has New York as its biggest feeder city, followed by London, Amsterdam, Rome, and Tokyo. Unlike London, however, a majority of its visitors, 53%, are from outside of Europe.

Istanbul, one of the most dynamic and fast growing destination cities, is ranked 3rd in Europe and 7th in the world. Its top 5 feeder cities are all in Europe, as shown in Chart 15, and they are all showing double digit growth in visitor numbers to Istanbul. Overall, 55% of visitors to Istanbul come from outside of the European region.

Top 10 Destination Cities in Latin America

Latin America’s top 10 destination cities are shown in Chart 16 and Table 7. Lima is the top ranked destination city in Latin America with 5.11 million international visitors in 2014. Mexico City is ranked 2nd while Sao Paulo is ranked 3rd. Punta Cana, which replaces Santiago in this edition, is in 4th rank followed by Buenos Aires in 5th place. Caracas falls out of the top ten to 11th place with the entry of Punta Cana.

As shown in Chart 17 and Table 8 below, Punta Cana is the regional top rank in international visitor spending at US$2.4 billion, followed by Sao Paulo and Buenos Aires. Bogota moves ahead of Rio de Janeiro to claim 6th rank. With the addition of Punta Cana, Caracas is displaced out of the top ten and holds the 11th rank.

Details of the top 5 feeder cities for Lima are summarized in Chart 18. Four of the five feeder cities are within the Latin American region: Santiago, Buenos Aires, Bogota, and Mexico City. Miami in the US is Lima’s second biggest feeder city. Overall, 56% of Lima’s visitors come from outside of the region.

The top 5 feeder cities for Mexico City are all in the US: New York, Los Angeles, Miami, Houston, and Chicago. Visitors from New York and Chicago are growing strongly, in sharp contrast with declining numbers from Los Angeles, Miami, and Houston. Overall, 54% of visitors come from outside of the region.

Sao Paulo’s top 5 feeder cities represent four countries: Argentina, USA, Chile, and Germany. These feeder cities are Buenos Aires, Miami, New York, Santiago, and Frankfurt. This diversity is reflected in the fact that two-thirds of international visitors to Sao Paulo come from outside the Latin American region.

Top 10 Destination Cities in Middle East and Africa

Middle East and Africa’s top 10 destination cities are shown in Chart 21 and Table 9. Dubai is in the top rank in the region with 11.95 million international overnight visitors, followed by Riyadh and Johannesburg. In 4th place is Abu Dhabi, another city from the United Arab Emirates followed by Cape Town in 5th place.

The regional top 10 ranking by international visitor spending are presented in Chart 22 and Table 10. While Dubai and Riyadh are in the first and second ranks respectively, Dubai is in a league of its own with US$10.9 billion of visitor spending, more than double Riyadh’s US$4.1 billion. Due to the political unrest, Cairo is the only city with negative growth in the top 10 (of both international visitors and spending) in 2014

Details of Dubai’s top 5 feeder cities are summarized in Chart 23, and they are London, Riyadh, Kuwait, Jeddah, and Paris. While growth rates of visitors from Saudi Arabia and Kuwait are either dropping or barely growing, growth rates of visitors from London and Paris are growing strongly in double digits. This is consistent with the trend that international visitors from outside of the region is becoming more important for Dubai, currently accounting for 62% of the total.

Riyadh’s top 5 feeder cities are Cairo, Dubai, Doha, Amman, and Mumbai; and 64% of its visitors came from within the region.

Johannesburg’s top 5 feeder cities are London, Frankfurt, Harare, Maputo, and Paris, as shown in Chart 25. While visitor numbers from London and Frankfurt are growing, the others are dropping. An overwhelming majority (77%) of international visitors to Johannesburg came from inside of the region.

North America’s Top 10 Destination Cities

The top 10 destination cities in North America are presented in Chart 26 and Table 11. New York is the top ranked in the region and ranked sixth in the world, with 11.81 million international visitors. It is followed by Los Angeles, Miami, Toronto and San Francisco, which are unchanged from their last year’s ranking.

As shown by Chart 27 and Table 12 below, New York is also top ranked in the region in international visitor spending at US$18.6 billion (and ranked second in the world). This is followed by Los Angeles, Miami, Toronto and San Francisco.

The top 5 feeder cities of New York are shown in Chart 28. They are London, Sao Paulo, Toronto, Paris, and Beijing, a very diverse mix. Visitors from Beijing are growing especially strongly at 17.3%. The fact that 90% of visitors to New York came from outside of North America underscores its prowess as a global city.

Los Angeles’ top 5 feeder cities are Vancouver, London, Seoul, Paris and Taipei, also a very diverse mix, as seen in Chart 29. Similar to New York, 83% of visitors to Los Angeles came from outside of the region.

Chart 30 shows the top 5 feeder cities of Miami. Four out of the five are in Latin America, illustrating the strong connection between Miami and cities in Latin America. In fact, 94% of visitors to Miami came from outside of North America, and most are from Latin America.

The Air Hub Index: Power of Connectivity

The flows of visitors and their spending from feeder cities to destination cities are in essence a form of service trade. Unlike trade in goods, however, the buyers (visitors) physically move from where they live to where the sellers live, the destination cities. Thus, in cross-border air travel, the connection between demand (buyers) and supply (sellers) is mediated by the logistics of air connectivity. Very often when a new airport is opened or an old one upgraded and when new flight connections are inaugurated; the volume of air travel increases correspondingly. So expanding or shrinking air connectivity will have very material impacts on the growth and decline of destination cities, and can be construed as a key leading indicator.

The “air hub index” is designed to measure the breath of a destination city’s connectivity by air with the rest of world, as well as the strength of each of the connections. The index then assigns a value to each destination city on the basis of the number of international flight connections that it has (weighed differently between inter-region versus intra-region flights) and the frequencies of these flights.[8] Chart 31 presents the ranking and index scores of the top 50 destination cities. It is obvious that there is a lot of overlap between the ranking in destination cities by international visitors and by air hub scores; but there are also significant differences suggesting a dynamic and changing future.  Of the global top 10 destination cities, only seven are in the top 10 by the air hub index scores. Indeed, the world’s second ranked destination city, Bangkok, is ranked 11th in the air hub index; whereas Moscow which ranks 48th globally as a destination city is ranked tenth in the air hub index.

The air hub index offers yet another perspective on change when the growth rates in index scores are compared between the destination cities. Chart 32 summarizes details of the top 10 fastest growing destination cities by air hub index scores. Some of them, like Bangkok, Dubai, Singapore, Istanbul, and Hong Kong, are already among the top ranked destination cities, but others like Moscow, Shanghai, and Abu Dhabi, are not yet there, but they could be on their way as they are actively growing their flight connectivity as suggested by the rapid increase in their air hub scores.


The continuing and robust growth of air travel and cross-border spending as reported by MasterCard’s Global Destination Cities Index, which consistently exceeded world GDP growth over the 2009 and 2014 period, suggest a very powerful trend in the making.  It appears to be a multidimensional phenomenon driven by a combination of rapid growth of mass tourism due to the expanding middle class in many emerging markets, rising needs for business travel in spite of the internet and the digital world, and proliferating innovations in luxury travel.  It is a trend that is likely to persist in the foreseeable future.

The picture is an equally dynamic one when it comes to the comparative performance of the destination cities as reflected by the ranking in the Index.  At the very top is the close race between London and Bangkok, with London reclaiming the top rank this year after losing it to Bangkok last year.  The fact of the matter is that many destination cities moved up in the ranks in the last five years, overtaking others, regardless whether they rank high or low in the Global Destination Cities Index. Not surprisingly many of the “upwardly mobile” destination cities are in emerging markets because of their growing air connectivity and fast improving infrastructure. In fact, using the growth rates in the Air Hub Index as the leading indicator, it would appear that seven out of the ten fastest growing “air hubs” are in emerging markets.

While destination cities in emerging markets may be growing faster in relative terms, the absolute size of the pie of air travel is also expanding fast. So it is not a zero sum game where destination cities in emerging markets are gaining at the expanse of those in the developed markets. A more accurate characterization is that they seem to grow synergistically, which explains why this is such a robust and resilient trend.

Appendix: Methodology

  1. The 132 Destination Cities of the Index
Region Destination Cities
Asia/Pacific      (42 cities) Ahmedabad , Almaty , Bangkok , Beijing , Bengaluru , Chengdu , Chennai , Coimbatore , Colombo , Dalian , Delhi , Dhaka , Guangzhou , Hangzhou , Hanoi , Harbin , Ho Chi Minh City , Hong Kong , Hyderabad , Islamabad , Jakarta , Karachi , Kolkata , Kuala Lumpur , Lahore , Manila , Melbourne , Mumbai , Nanjing , Osaka , Pune , Qingdao , Seoul , Shanghai , Shenzhen , Singapore , Sydney , Taipei , Tianjin , Tokyo , Xi an , Xiamen
Europe(36 cities) Amsterdam , Ankara , Athens , Barcelona , Berlin , Brussels , Bucharest , Budapest , Copenhagen , Dublin , Dusseldorf , Edinburgh , Frankfurt , Geneva , Hamburg , Istanbul , Kiev , Lisbon , London , Madrid , Milan , Minsk , Moscow , Munich , Novosibirsk , Paris , Prague , Rome , Sofia , St Petersburg , Stockholm , Vienna , Vladivostok , Warsaw , Yekaterinburg , Zurich
Latin America(19 cities) Belo Horizonte , Bogota , Brasilia , Buenos Aires , Caracas , Cordoba , Curitiba , Lima , Medellin , Mexico City , Monterrey , Montevideo , Quito , Recife , Rio de Janeiro , San Jose , Punta Cana/ , Santo Domingo , Sao Paulo
Middle East & Africa (21 cities) Abu Dhabi , Accra , Amman , Beira , Beirut , Cairo , Cape Town , Casablanca , Dakar , Damascus , Dubai , Durban , Kampala , Johannesburg , Lagos , Maputo , Nairobi , Riyadh , Tehran , Tel Aviv , Tunis
North America(14 cities) Atlanta , Boston , Chicago , Dallas , Houston , Los Angeles , Miami , Montreal , New York , Philadelphia , San Francisco , Toronto , Vancouver , Washington

/ Punta Cana replaces Santiago

  1. Global Air Hub Index

It is an index that seeks to measure the breadth of a city’s international connectivity as well as the strength of each connection. Using Amsterdam as an example, for each city pair with Amsterdam as the departure node, we calculate the connectivity score for the city pair as: 100 x {Weekly Flight Frequency} X {Intra/Inter Regional Multiplier} / {City Pair with Max Weekly Flight Frequencies


Weekly Flight Frequency: is the number of flights per week departing from Amsterdam to a particular city. This is the main driver of the connectivity score and it is sourced from OAG Flight Schedules Data. Airlines will also provide their flight schedules for one year ahead, which is how we obtained the weekly flight frequencies for 2014. While the number of cities that Amsterdam is connected to determines Amsterdam’s raw connectivity, the strength of each connection is measured by the weekly flight frequency and weighted by whether or not the connection is Inter-regional or Intra-regional.

Inter/Intra Regional Multiplier: International Destinations from Amsterdam that are Inter-regional (i.e. outside of Western Europe in the case of Amsterdam ) are weighted at twice (i.e. x 2) that of International Destinations within the same region as Amsterdam (i.e. intra-regional, within Western Europe).

City Pair with Max Weekly Flight Frequencies: This number is used to normalize the raw connectivity scores. It has absolutely no effect on the relative scores between cities and is used only for ease of presentation when viewing the data.

Every Amsterdam – XXX city pair is thus given its own connectivity value. We add them up to get a connectivity value for Amsterdam itself.  We now do this for every one of the 132 cities. Once we have the connectivity scores for all 132 cities, we perform a final normalization so that the scores can be presented out of a maximum of 100 (Index format). The divisor for this is the highest raw 2009 score (in this case London’s raw connectivity score in 2009).

  1. Estimation of Overnight Visitors

City level international overnight arrivals are those who actually stay in the destination city, at least for one night. In order words we only count cases where the disembarkation city is also an overnight destination city. This is opposed to cases where the disembarkation city is merely a transit point while the destination city which maybe some other city in the same country.

The sources for city level overnight arrivals by foreign visitors are typically the National Statistics Boards of the relevant countries or their Tourism Boards. The indicators for 122 out of the 132 cities were directly sourced for or estimated from official data. The other 10 cities were estimated using the Airflow Model (see below).

Total overnight foreign visitor official data was available directly for estimation for 70 cities. Where this was not available, we sourced for

  • Foreign overnight arrivals by air at the city level (12 cities)
  • Foreign overnight arrivals at paid accommodations at the city level (40 cities)

In previous editions of this report Dubai international overnight visitors were at the paid accommodation level only; in this edition however, Dubai Tourism and Commerce Marketing has kindly provided us with estimates of international overnight visitors who stay with friends and family and as such we have revised our data to include this.

In cases where official data or estimates derived from official data do not cover the most recent year but do cover earlier years, we have projected from the years where data was available using the growth rates from the Airflow model. For all cases forecasts for 2014 are projected using growth rates from the Airflow model.

  1. The Airflow Model

Every month the OAG collects the airline flight schedules for the next 12 months on a global basis. Using only non-stop flights we extract for each city to city pair the number of

  • Weekly flight frequencies
  • Passenger Capacity

On any airline flight route, the average % of seats filled (i.e. called the “load factor”) varies. This information is extremely sensitive for competitive reasons and airlines will only release this data with a 1 year lag. Nevertheless, by using the historical load factor on most city to city flight routes, we can estimate a proxy for the current and forecasted load factor.  We used a weighted average of the historical load factors with heavier emphasis on the most recent years which ranges from 30% to 100%, but airlines will try to maintain a load factor of between 70 to 80% by changing the number of weekly flights or by changing the aircraft type to increase or decrease passenger capacity. As such, for determining the years for which we do not have load factor numbers we apply an increasing improvement of 5% per year on the historical average, starting at 70% and improving to 85% over time.

Using the data above a first estimate of the number of passengers departing from one city to another can be made using: Estimated Travelers = Load Factor / Passenger Capacity

Now on any flight there will also be passengers who are returning home after having visited the departure city. For example, in the case of a Caracas to Miami flight there will be US passengers returning back to Miami (after having visited Caracas). We want to net out those passengers. As airlines do not reveal the residency of their passengers there is no way to know at a city to city level what portion of passengers on each flight is returning home. We need to go to the country-country level for this and for that we use UNWTO (United Nations World Tourism Organization) data. They collect the number of annual residents traveling between country pairs and we use these numbers to create a ratio of:

Departure Country A to Arrival Country B Ratio =

Annual Number of Residents from Country A going to Country B /

{Annual Number of Residents from Country A going to Country B + Annual Number of Residents from Country B going to Country A}

For example, in the case of the Caracas – Miami route, in 2009 there were 340,403  Venezuelans in total traveling to the US, and 43,752 US residents in total traveling to Venezuela via the Miami – Caracas route implying a ratio of 88.6% which is the estimated ratio of Venezuelans on any given flight from Venezuela to the US. We use this ratio to net out returning US residents and to obtain the number of Venezuelans traveling from Caracas to Miami as follows:

Estimated Venezuelan Resident Travelers from Caracas to Miami =

Estimated Travelers / Ratio of Venezuelan Resident Travelers to Total Travelers {US & Venezuela}

Where UNWTO data was not available for a country pair (data available for 76% of the country pairs), data was sourced at the National level where available (2% of city pairs) or we used the ratio of the IMF Balance of Payments travel debit accounts to construct a secondary proxy ratio. In this release we have focused on key border regions around the world where the UNWTO cross-country visitor data may give less accurate ratios. In all cases, the general idea was to use overnight visitors (where data was available) instead of overall visitors to construct more accurate departure-arrival ratios of air travelers. This has resulted in some shifts to the flow of travel between these areas (and therefore overall expenditure as well). The border regions include the Mexican-US border, EU countries which share a border, the Singapore-Malaysia border, and the Ukraine-Russia-Belarus-Moldova border areas.

In this release, out of the 132 cities, 10 were estimated using the airflow model as we were unable source for official statistics. They are:

Eastern Europe Asia Africa
Novosibirsk, Yekaterinburg, Kiev, Minsk, Almaty Dhaka, Tehran Dakar, Lagos, Accra


To estimate the number of visitors to each of the destination cities, the following steps are followed.

(i)                  As explained previously, on any given flight there are departing residents from the departure country, returning visitors, and a third group of residuals. The residuals group can be a low proportion of the passengers for typically non-hub cities, and very high for hub cities. To estimate the proportion of this group, we use: Residuals = Total Estimated Passengers – Number of Departing Residents – Number of Returning Visitors

(ii)                Residuals constitute 2 main groups: (A) non-residents (of either the origin or destination country) who from the origin city are visiting the destination city, and residents of the origin country, and (B) non-residents (of either the origin or destination country) who will be transiting through the destination city without visiting it. We are interested in (a) but in order to separate the residuals into its 2 components we use a relative connectivity ratio “RCR” that is based on the International Air Connectivity Index (IACI) scores previously created.

RCRo-d= ( IACIo / (IACIo +IACId) )2


RCRo-a : Is the Relative Connectivity Ratio of the Origin City relative to the Destination City

IACIo    : Is the International Air Connectivity Index of the Origin City

IACId    : Is the International Air Connectivity Index of the Destination City

We then separate out (A) using

A = Residual x  RCR   &   B = Residual – A

We then add A {Non-residents (of either the departing or arrival country) who from the departure city are visiting the arrival city} to the number of residents visiting the arrival country {calculated earlier} to obtain the estimated number of travelers who will visit the destination city, which is equal to:

Visitors =  Origin Country Residents + Non-Residents from other Countries

  1. Estimates of Visitors’ Cross-Border Expenditure

In most cases the estimated visitor spend at the city level was directly sourced from official statistics, or estimated using data from national international visitor surveys (49 cities). Where survey level data at the city level was unavailable but available at the national level, we used the later in terms of the national average expenditure per overnight tourist which we multiplied with city level overnight visitors to obtain total expenditure (44 cities). Where survey data was not available at either the city or country level, we calculated and used the average expenditure in destination countries using IMF Balance of Payments Travel Credit data (adjusted down to include only overnight visitors as the Balance of Payments data includes both excursionist and overnight visitors) and the total number of overnight visitors to the country (36 cities). For Kiev, Singapore and Paris we looked at country to country data to estimate the average expenditure of outbound travelers. City to city expenditure data is difficult to obtain (partial figures do exist but these are not publicly available). For this we use the United Nations’ Trade in Services database (travel component) which does not include transport, i.e. Airfares at the paired country level. For country pairs where this data is not available we default to using.

The formula is as follows:

Average Expenditure of Visitors =

Total Amount Spent on Travel in the destination country by residents of the origin country (ex Air Tickets) / Total Number of origin country residents traveling to the destination country

Based on the latest year available for average expenditure per traveler we then project the average expenditure per traveler using the nominal growth rate of GDP per Capita provided by the IMF WEO forecast database. Using the estimated number of residents flying from each departure city to each destination city, we can then calculate the estimated expenditure by multiplying in the average expenditure to obtain city to city expenditure estimates. That is for each city pair:

Estimated Visitor Spend = Number of Visitors x  Average Expenditure in the Destination country


  1. Data Sources


Indicators Source
Dynamic 1 Year Forward Flight Schedules OAG
Traffic by Flight Stage & Load Factor IATA
Country-Based Tourism Statistics UNWTO
Country-Based Tourism Statistics National Tourism Boards
Trade in Services UN
WEO Data Base IMF
Global Data Base CEIC
World Tourism Indicators WTTC


  1. Glossary


Visitor: Person who is travelling on a non-stop direct flight to her destination and is not a resident of the destination country. A visitor may make more than one trip, and each trip counts as a new visit. That is, a person who makes 2 trips to a destination as described above counts as 2 visitors to that destination. A person on the return leg home does not count as a visitor.

Visitor Spend: The estimated total amount that visitors spend in the destination city/country. It excludes air ticket expenditure required to get the visitor to the destination city.

Origin City: The city from which visitors embark on their flight to the destination city. Passengers who count as visitors may be residents of the origin city/country or may be non-residents from other countries (but not the destination city/country).

Destination City: The city where passengers disembark (leave the airport) and are counted as visitors (which only includes non-residents of the destination city/country).

Feeder City/Country: Sometimes visitors & visitor spend is described at the country or city level interchangeably.  For example, visitors from Frankfurt to London are described as non-residents & residents of the origin country visiting the destination country via London. By residents of the feeder country we mean German residents inclusive of residents of Frankfurt. This is because residents from other parts of Germany may have domestically flown or driven to Frankfurt to take their flight to London together with residents of the Frankfurt urban area. Non-residents of the feeder country include for example Singaporeans who are on their way to London who have either visited Frankfurt before going to London or who are simply transiting through Frankfurt on their way to London. The point is that the feeder city is the most recent place from which travelers embarked before arriving at their destination which is a constraint of using only non-stop flights. Finally, visiting the destination country via London, implies that visitors may disembark in London to visit the city but they could also go from London to visit other parts of the country via a domestic flight.

About the Authors

Yuwa Hedrick-Wong

Yuwa is currently Chief Economist, MasterCard Center for Inclusive Growth, and Global Economic Advisor, MasterCard. He is also HSBC Professor of International Business at the University of British Columbia, Canada.

He is an economist with 25 years of experience gained in over thirty countries.  He is a Canadian who grew up in Vancouver and has spent the last 20 years working in Europe, Sub-Sahara Africa, and Asia Pacific.  He has served as advisor to over fifty leading multinational companies.

He is a published author on consumer markets, economic development, trade and international relations. Yuwa studied philosophy, political science, and economics at Trent University, and pursued post-graduate training at the University of British Columbia and Simon Fraser University in Canada, where he received his Ph.D.

He lives on Salt Spring Island, off the west coast of Canada, with his wife and their cat; and is an enthusiastic apprentice in the fine art of gardening.

Desmond Choong

Desmond Choong is a Research Economist with the MasterCard Center for Inclusive Growth. In this capacity, he sources, reviews and develops research aimed at advancing the Center’s goals. Based in Singapore, he is an economist and business analyst with extensive experience in the Asia/Pacific region and a focus on index modeling, market sizing and macroeconomic analysis. He has spent thirteen years consulting for multinational companies across a wide range of industries, including finance, resources, and travel and hospitality. Desmond has taught International Trade at Boston University and holds a B.A. in English/Economics from Boston College and a M.A. in Political Economics from Boston University.

[1] Dowling, S. January 30, 2014. “100 Years of Air Travel: How Planes Shrunk the Globe”. BBC Future.

[2] IATA data.

[3] See Glossary Section in the Appendix for the definition of “Destination City”.

[4] See Appendix for the list of the 132 destination cities.

[5] See Glossary Section in the Appendix for the definition of “Visitor” and the methodology for estimation. .

[6] See Appendix for definition of “Visitor Spending” and the methodology for estimation.

[7] See the Glossary Section of the Appendix for the definition of “feeder city”.

[8] See Appendix for the methodology of computing the Air Hub Index scores.

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