2016 OVERVIEW THE AVIATION SECTOR IN DATA AND ANALYSES
ABEAR - Associação Brasileira das Empresas Aéreas Contents Presentation... Introduction... ABEAR: founding airlines... ABEAR: associate companies... 1. The importance of air transportation... Air transportation: its importance and tourism... 2. Results of ABEAR Airlines... Basic statistics... Staff and fleet... Transportation of transplant organs and tissue and medical teams... Market participation... Market concentration in different countries... Consolidated financial statements... 3. Quality of service... On time performance... Baggage handling... Airport service... 4. The market for air passenger transportation in Brazil... Evolution and demand forecasts for air passenger transportation in Brazil... Airports served... Domestic airport connectivity and GDP of corresponding mesoregions... Market penetration of domestic air transport... Domestic passenger origin-destination traffic... 5. The market for air-cargo transportation in Brazil... Evolution and demand predictions for air cargo transport in Brazil... Penetration of air transportation in the domestic freight markets of different countries... 6. Safety, environment and efficiency... Flight safety... Fuel consumption and CO 2 emissions... Effective distances per flight hour... Load factor in passenger domestic flights in Brazil and in the United States... 7. Prices and costs of services rendered... Evolution and composition of service and price costs... Index of graphs and charts... Sources consulted... 5 7 8 10 12 14 20 22 28 30 31 33 34 38 40 44 45 46 48 58 59 62 64 66 68 74 78 80 82 82 85 86 88 95 98 3
ABEAR - Associação Brasileira das Empresas Aéreas Introduction ABEAR has once again met its commitment to the highest standards of innovation in specialized information. The fifth edition of Panorama presents new items and deeper interpretations of data published since the first edition in 2012. Readers of previous editions will notice a new more dynamic and modern visual language, designed to make reading simpler and more pleasant. As far as the topics are concerned, one of the novelties of this edition is the calculation of the impact that a reduction in the price of jet fuel (Jet A1) would have the Brazilian price is one of the highest in the world on production, jobs, salaries and other benefits. We also present in this report the potential for regional market connectivity as part of our constant effort to improve the data that we publish. This has been added to our innumerous statistics and information, which are likewise available in our digital version (www.panorama.abear.com.br). Good reading! Eduardo Sanovicz President of ABEAR DATA RESEARCH AND ANALYSIS Mauricio Emboaba Technical consultant ABEAR ABEAR STAFF Eduardo Sanovicz President Adrian Alexandri Communications director Airton Pereira Director of Institutional Relations Antônio Augusto do Poço Pereira Administrative and Financial Diretor Ronaldo Jenkins Director of Security and Flight Operations Agnes Dantas Advisor Ana Dragonetti Communications assistant Daniela Sarmento Project Coordinator David Maziteli Communications assistant Jurema Monteiro Institutional Relations Advisor Luiz Caversan Communications Consultant Marcos Diegues Technical Consultant Paulo Roberto Alonso Technical Consultant Rogério Benevides Carvalho Technical Consultant William Alencar Technical Consultant Media Relations Máquina Cohn & Wolfe Ana Paula Siqueira da Silva SNEA EDITORIAL BOARD AVIANCA - Tarcisio Gargioni Commercial Vice-President, Marketing and Freight AZUL - Carolina Constantino Manager, Communications, Culture and Social Responsibility GOL - Alberto Fajerman Director of Institution Relations LATAM - Gislaine Rossetti Director of Institutional Relations and Sustainablity CREATIVE DIRECTION AND EDITION PiU Comunica 5
ABEAR - Associação Brasileira das Empresas Aéreas Introduction Overview 2016 is the fifth edition of ABEAR s annual analysis of aviation in Brazil and an improvement on each of the previous publications. The breadth of topics has been enlarged and the statistical studies are more accurate, but the basic assumptions and methods of earlier editions have been maintained. In the first place, all of the information is public and available for audit. This guarantees a high level of credibility that allows any reader who is willing to do the work to retrace our investigative path and arrive at analogous conclusions. The 80 sources consulted offer the reader a solid base of evidence that sustain the analyses undertaken in Overview 2016. In second place, the use of industry benchmarking from other countries as an investigative method has proven increasingly successful. If information and conclusions are not compared to results from other countries they become meaningless. They lose any sense of relative importance and are incapable of communicating the magnitude of the phenomena under consideration. There are important innovations in this edition of Panorama. In its first pages we begin by analyzing air transportation as part of a web of relations with the other seven activities characteristic of the tourism sector. Commercial aviation is not examined as an autonomous activity. As is the case in mature markets, punctuality is examined from two points of view: the passenger s on time arrival and the operator s on time departure. In the section that deals with connectivity between Brazilian airports, the focus is on regional air transportation. Opportunities are analyzed to expand potential markets whose economic capacity is sufficient for such, but which are held back by lack of accessibility. Domestic air transportation of cargo has been examined in a more analytical way, incorporating the information acquired from the elaboration of ABEAR s recently published study, Benefits of Aviation - Impacts of Aviation in the Brazilian States. The analysis of the inefficiencies of passenger air transportation, in the section that addresses useful distance covered per flight hour, is enriched by the conclusion of a new ABEAR study. It quantified inefficiencies on the basis of an analysis of nearly a million domestics takeoffs along 2016. Finally, the question of the price of jet fuelin Brazil (among the most expensive in the world and disproportionate in relation to the developed world) is once again brought into the debate, with new data from a 2016 ABEAR study, which pioneered an innovative approach to the aviation transportation industry in Brazil. Subjects previously analyzed in this report have benefited from the knowledge cumulated by ABEAR. 7
OVERVIEW 2016 ABEAR: Founding companies Created in August of 2012 with the mission of stimulating the habit of flying in Brazil, ABEAR supports programs that promote the growth of civil aviation in the country in a consistent and sustainable fashion, in both the passenger and cargo sectors. More than 99% of the domestic Brazilian aviation market is represented by the founding companies (AVIANCA BRASIL, AZUL, GOL AND LATAM). The association includes among its members BOEING, BOMBARDIER, LATAM Cargo Brasil and TAP. 8 AVIANCA BRASIL has operated regular flights since 2002. In 2017 it serves 23 domestic destinations and three destinations abroad with 240 daily take-offs in 50 Airbus airplanes the youngest fleet in the Americas. Acknowledge for its superior quality, the airlineoffers differentials such as individual entertainment, free onboard cattering, and greater seat pitch (it is the single airline in the country that boasts the A category Selo de Qualidade ANAC in every row of seats in all of its aircraft. Always innovative, AVIANCA was the first airline in South America to offer Internet service on board and one of the pioneers in the use of the modern A320neo in Latin America. Its Amigo Frequent Flyer Program program claims over 4 million registered members. As the Brazilian member of the Star Alliance, the largest global alliance of airline companies, AVIANCA BRASIL connects passengers to more than 1,300 airports throughout the world, by way of 27 international partnerships. In the last six years, the airline has registered above average market growth. This has been made possible by the implementation of a solid execution and investment strategy in fleet renovation, operations expansion, platform technology modernization, service differentiation and training for its staff of 5000 employees. AZUL BRAZILIAN AIRlINES was founded with the purpose of connecting cities without direct service in the country s air transportation network. Its operations began in December 2008. In August 2009, the company set its first global record: one million passengers in less than a year of operation. In 2011, it was the third largest airline in Brazil. In 2012, AZUL joined TRIP in the AZUL TRIP S.A. holding. In 2015, the company reached the mark of 100 million passengers flown, and TudoAzul, its Frequent Flyer Program, accomplished the mark of 5 million members. AZUL and United Airlines celebrated a strategic partnership: the North American airline invested US $100 million to acquire 5% of the Brazilian airline. In the same year, the HNA Group agreed to purchase 23.7% of the economic value of Azul for R$ 1.7 billion. As part of the agreement with the HNA Group, in 2016 AZUL announced an investment of US$100 million in securities convertible into preferential stock shares in TAP Portugal, the equivalent of 40% of its economic value. In 2017, AZUL went public, and began offering stock on the Securities and Exchange Commission (CVM) of São Paulo and the Securities and Exchange Commission (SEC) of New York.
ABEAR - Associação Brasileira das Empresas Aéreas In the 16 years of its history, GOL LINHAS AÉREAS INTELIGENTES has helped to bring people together, build ties and shorten distances with safety and intelligence. The company played an important role in the democratization of air transportation in Brazil, providing 18 million people with their first flight. This made it the largest budget airline with the lowest fares in Latin America. It is still the leader in the number of passengers flown in the domestic market, both in the leisure and corporate sectors, as well as in punctuality according to Infraero and OAG (Official Airline Guide), an independent company specialized in monitoring airline on time performance worldwide. GOL offers the largest number of ANAC A rated seats, providing excellent comfort on its 700 daily flights to 63 domestic and international destinations in South America and Caribbean. The Company maintains strategic alliances with Delta Air Lines, Air France and KLM, and offers its clients 13 codeshare agreements and 70 interline agreements. Its Smiles relationship program, allows members to cumulated miles and acquire tickets to more than 800 destinations in over 160 countries. Besides Gollog delivers cargo and packages in approximately 2500 Brazilian municipalities and 90 international destinations together with its partner companies. LATAM was born of the successful trajectories of TAM and LAN and became the first genuinely Latin American airline, in charge esponsible for 90% of the air traffic on the continent. LATAM airlines Brasil was launched in 2016, bringing together the best of TAM and LAN in order to offer its clients more than just the sum of its parts. With the change to the new brand, the company offers a new travel experience, simplified and better integrated, the best route network and a cutting-edge digital experience. LATAM has the most up-to-date and efficient fleet of aircraft in the region and operates more than 1400 flights per day. It travels to 140 destinations, with daily flights in Latin America, Europe, North America, the Caribbean, Oceania and South Africa. The decision to adopt a single new brand name is a historical feat in the aviation sector. It is the first time two strong brands with similar backgrounds and visions in a single region have come together to create a single, even stronger brand. They have succeeded in incorporating the attributes and advantages of LAN s 87 year and TAM s 40 year trajectories. 9
OVERVIEW 2016 ABEAR: associated companies BOMBARDIER COMMERCIAL AIRCRAFT established its office in Brazil in 2014, at the beginning of a new moment in its relationship with the country and Latin America as a whole. Planning for the future and delivering today, BOMBARDIER continues to provide products that are products that match the market demand. The company fills the need for more efficient, sustainable and comfortable air transportation throughout the world. More than 3,400 regional CRJ series jets, Q series turboprop, and C Series single aisle jets are in service in approximately 250 operators in 90 countries. This achievement was obtained by focusing on our clients needs. The C Series aircraft, completely new and already in service, is focused on the 100 to 150 seat segment, creating new opportunities for the operators of single aisle jets. Boeing established an office in Brazil in 2011, beginning a new relationship cycle with the country. The first delivery of commercial airliners to Brazil dates to 1960. Today, Boeing counts GOL Linhas Aéreas and LATAM among its main commercial clients. Boeing created a center for research and technology in São José dos Campos (SP) aiming to reinforce its relationship with the Brazilian research and design community and contribute to generating new capabilities aligned with goals of economic and technological development of this country. Boeing s Market Perspectives 2017 (CMO) report predicts that Latin American airlines will purchase approximately 3,010 airships, valued at US $350 billion, over the next 20 years. Boeing is the largest aerospace company in the world, leader in the manufacture of commercial aircraft and defense, space and security systems. It employs 170 thousand people in 70 countries. 10
ABEAR - Associação Brasileira das Empresas Aéreas de braços abertos TAP is the airline with the best flights between Brazil and Europe. It offers 70 weekly flights from 10 Brazilian cities Belém, Belo Horizonte, Brasília, Fortaleza, Natal, Porto Alegre, Recife, Rio de Janeiro, Salvador and São Paulo to Lisbon and/or São Paulo. Created in 1945, the airline s privatization was concluded in 2015, the year it celebrated its 70th anniversary, with the Atlantic Gateway consortium as its new stockholder. With a hub in Lisbon, a privileged location with access to Europe, at the crossroads of Africa, North, Central and South America, TAP is the leader in operations between Brazil and Europe and operates a network that covers 84 destinations in 34 countries. TAP operates approximately 2,500 flights per week with a fleet of 80 aircraft 63 Airbus planes and another 17 aircraft (ATR 72 and Embraer 190 models, among them) are used by the TAP Express service, the new commercial brand for the company s regional route network. LATAM Cargo Brazil, a brand adopted in May 2016, merges the cargo units of the LATAM Airlines Brazil Group: LAN Cargo, MasAir, LAN Cargo Columbia and TAM Cargo. The Company offers air transportation services for cargo, express parcels and special orders to 140 destinations in 29 countries throughout the world. In 2013, it integrated its operations with ABSA, a former subsidiary of LAN in the country. The process made cargo transport more robust and multifaceted, compatible with local dimensions and needs. Currently, LATAM Cargo Brazil provides service with direct flights to 50 Brazilian airports, offers pickup in over 400 cities and deliveries in more than four thousand locations in São Paulo (Guarulhos and Congonhas), Rio de Janeiro (Galeão) and Brasília. 11
OVERVIEW 2016 The importance of air transportation
ABEAR - Associação Brasileira das Empresas Aéreas OVERVIEW Commercial aviation worldwide in 2015 Air transportation and the economic sectors affected by it are responsible for an important part of the worldwide production of wealth. Among the many areas the benefit from the speed and safety of aviation, tourism is the most significant. It is an increasing important part of the world economy. In order to better understand the benefits of aviation throughout the country, the member companies of ABEAR invested in a detailed study aimed at each state in the Brazilian federation. 54% Is responsible for of international tourism s transportation Represents 3.5% of GDP worldwide Tourism, an economic sector that relies on aviation 10.2% of Worldwide GDP Is equivalent to the 21 st largest national economy in the world 1/10 of the jobs in the world US$ 7.6 TRILLION per year in output th PERSPECTIVES Reinforce the role of this economic multiplier interrelated with many other sectors of the economy Publicize the importance of air transportation as a source of jobs and wealth and taxes Develop plans and propose policies fit to the realities of each state in Brazil 13
OVERVIEW 2016 Air transportation: its importance and tourism Air transportation is frequently reviewed as an autonomous economic activity, possibly due to its size and technological sophistication. This approach ends up underestimating its importance. The United Nations World Tourism Organization (UNWTO) analyzes the economic influence of air transportation as part of a broader system divided into eight different activities characteristic of tourism (ACTs). They are: Travel Agencies, Accommodation Services, Air Transportation, Food Services, Ground Transportation, Water Transportation, Transportation Rentals, Culture and Leisure 1. The first three are considered core tourism activities by the Instituto de Pesquisa Econômica Aplicada IPEA) 2. Commercial aviation catalises a significant amount of demand in other activities in the tourism sector. Worldwide, the economic impact of air transportation including direct, indirect, induced and catalised impacts corresponds to US$2.7 trillion annually, or 3.5% of Gross World Product (GWP). If it it was a country, air transportation would be the 21 st largest national economy in the world. Three billion and three hundred million passengers travel by air annually, which corresponds to 54% of international travel worldwide 3. Tourism, including all modes of travel, represents 10.2% of GWP, tallying US$ 7.6 trillion annually. One in ten jobs in the world is generated directly or indirectly by tourism 4. In Brazil, the economic impact of air transportation is similar in its proportions, according to the study, Voar por mais Brasil: os benefícios da aviação nos estados [Benefits of Air Transport Impacts of Aviation in the Brazilian States], out by ABEAR together with the consulting firm, GO Associados, led by the economist Gesner Oliveira. In 2015, the economic impact of aviation accounted for 3.1% of Brazilian overall output, with1.2% resulting specifically from air transportation and 1.9% from tourism (including in both cases direct, indirect and induced impacts). The charts below illustrate the central findings of this study. 1 United Nations World Tourism Organization (UNWTO), Tourism Satellite Account: Recommended Methodological Framework 2008, available at: https://unstats.un.org/unsd/publication/seriesf/seriesf_80rev1e.pdf. 2 Instituto de Pesquisa Econômica Aplicada (IPEA), Sistema de Informações sobre o Mercado de Trabalho do Setor Turismo, available at: www.ipea.gov.br/extrator. 3 Air Transport Action Group (ATAG), Aviation Benefits Beyond Borders: Global Summary, jun. 2016, available at: aviationbenefits.org/media/149654/abbb2016_global-summary_web.pdf. 4 World Travel and Tourism Council (WTTC), Global Economic Impact & Issues 2017, available at: www.wttc.org/-/media/ files/reports/economic-impact-research/2017-documents/global-economic-impact-and-issues-2017.pdf Worldwide, aviation generates US$ 2.7 TRILLION in economic impact per year (direct, indirect, induced and catalised sector results) + 3.5% OF GDP + 3.3 BILLION passengers 14
ABEAR - Associação Brasileira das Empresas Aéreas IMPACT OF AIR TRANSPORTATION ON THE BRAZILIAN ECONOMY OUTPUT AND TAX REVENUE IMPACT OF AIR TRANSPORTATION ON THE BRAZILIAN ECONOMY EMPLOYMENT AND WAGES + Tourism (multiplier) + Tourism (multiplier) + induced + induced + indirect + indirect direct direct 38.8 31.2 48.7 9.5 16.0 556.8 7.4 Taxes (R$ Billion) 4.5 8.2 334.5 920.9 4.638,8 Wages (R$ Billion) 193.4 39.1 Production revenue (R$ Billion) Jobs (Thousands) Source: ABEAR, Benefits of Air Transport Impacts of Aviation in the Brazilian States, available at: www.abear.com.br/uploads/arquivos/dados_e_fatos_arquivos_ptbr/abear_voarpormais Brasil_2016.pdf In 2015, Brazilian aviation was responsible for R$ 193.4 BILLION in national output 3.1% of national output (direct, indirect and induced results) The ABEAR study was replicated in every state in Brazil, measuring individually the different economic impacts direct, indirect, induced (or income impact) and multiplier impacts on production, employment, salaries and tax collection. One methodological difference between this study and others cited herein is that the ABEAR study used collaboration towards output as a metric in each state instead of contribution to Gross Domestic Product (GDP). The reason for this is that it is almost impossible to isolate the value added by air transportation in each state (in a format compatible with GDP metrics). Thanks to this methodological adaptation it was possible to understand with greater precision the results in each individual state. This led to the identification of the importance of demographic density in the creation of demand for air transportation. In states with high demographic density there were more boardings than the level of economic activity alone would suggest. This is explained by the greater access of the local population to air transportation. The following charts present the principal quantitative findings. 15
OVERVIEW 2016 BRAZIL OUTPUT STATE OUPUT (R$MILLIONS) AIR TRANSPORTATION CATALISED SECTOR EFFECTS TOTAL Direct Indirect Induced Tourism (all effects) Acre 63 25 39 285 412 Alagoas 299 226 351 1,372 2,248 Amapá 37 20 32 488 577 Amazonas 925 605 943 2,120 4,593 Bahia 1,612 1,225 1,908 9,361 14,106 Ceará 1,332 974 1,518 6,401 10,225 Distrito Federal 2,777 1,597 2,489 23,981 30,844 Espírito Santo 218 251 390 2,703 3,562 Goiás 244 158 246 2,965 3,613 In São Paulo, R$119.7 BILLION are generated by commercial aviation (including direct, indirect, induced results and catalised sector effects effects in the tourism sector) Maranhão 307 340 531 1,438 2,615 Mato Grosso 385 398 620 2,018 3,421 Mato Grosso do Sul 160 121 189 1,678 2,148 Minas Gerais 1,209 1,012 1,577 11,461 15,259 Pará 763 530 826 3,235 5,354 Paraíba 296 143 223 1,375 2,037 Paraná 771 692 1,079 8,620 11,162 Pernambuco 1,406 1,031 1,606 6,516 10,559 Piauí 165 96 150 871 1,282 Rio de Janeiro 5,448 4,789 7,463 28,057 45,757 Rio Grande do Norte 510 303 472 2,133 3,418 Rio Grande do Sul 1,014 768 1,197 6,575 9,554 Rondônia 153 110 171 677 1,110 Roraima 37 13 20 149 219 Santa Catarina 360 309 482 5,207 6,358 São Paulo 18,074 15,345 23,912 62,408 119,739 Sergipe 150 114 178 833 1,275 Tocantins 53 31 48 515 647 Total Brazil 38,765 31,226 48,660 193,441 312,092 In the Distrito Federal, the R$30.8 BILLION tied to production in the sector correspond to 11% of the total production of of the DF Source: ABEAR, Benefits of Air Transport Impacts of Aviation in the Brazilian States, available at: www.abear.com.br/uploads/arquivos/dados_e_fatos_arquivos_ptbr/abear_voarpormais Brasil_2016.pdf 16
ABEAR - Associação Brasileira das Empresas Aéreas BRAZIL JOBS STATE JOBS AIR TRANSPORTATION Direct Indirect Induced CATALISED SECTOR EFFECTS Tourism (all effects) TOTAL Acre 442 266 731 6,384 7,823 Alagoas 4,022 2,416 6,652 29,665 42,755 Amapá 361 217 597 11,511 12,686 Amazonas 10,794 6,485 17,852 40,215 75,346 Bahia 21,836 13,119 36,115 215,667 286,737 Ceará 17,375 10,439 28,737 160,589 217,140 Distrito Federal 28,482 17,112 47,107 644,183 736,884 Espírito Santo 4,467 2,683 7,387 62,298 76,835 Goiás 2,818 1,693 4,661 72,073 81,245 Maranhão 6,071 3,647 10,040 32,507 52,265 Mato Grosso 7,091 4,260 11,728 38,492 61,571 Mato Grosso do Sul 2,162 1,299 3,575 41,755 48,791 Minas Gerais 18,040 10,838 29,837 270,627 329,342 Pará 9,456 5,681 15,639 66,378 97,154 Paraíba 2,550 1,532 4,217 33,359 41,658 Paraná 12,345 7,417 20,417 193,963 234,142 Pernambuco 18,381 11,043 30,401 156,347 216,172 Piauí 1,714 1,030 2,835 19,410 24,989 In the State of Pernambuco, the aviation sector and the impacted sector employ Rio de Janeiro 85,396 51,305 141,237 710,788 988,726 Rio Grande do Norte 5,405 3,247 8,940 50,173 67,765 Rio Grande do Sul 13,694 8,227 22,648 146,904 191,473 Rondônia 1,954 1,174 3,232 14,548 20,908 Roraima 234 141 388 2,848 3,611 Santa Catarina 5,516 3,314 9,124 122,801 140,755 São Paulo 273,615 164,384 452,532 1,465,329 2,355,860 Sergipe 2,035 1,223 3,366 17,857 24,481 Tocantins 544 327 900 12,153 13,924 Total Brazil 556,800 334,519 920,895 4,638,824 6,451,038 217,140 PEOPLE, close to 5% of the labor force Source: www.abear.com.br/uploads/arquivos/dados_e_fatos_arquivos_ptbr/abear_voarpormais Brasil_2016.pdf 17
OVERVIEW 2016 BRAZIL SALARIES STATE SALARIES (R$ MILLIONS) AIR TRANSPORTATION Direct Indirect Induced CATALISED SECTOR EFFECTS Tourism (all effects) TOTAL Acre 6 4 7 54 71 Alagoas 53 32 59 251 395 Amapá 5 3 5 98 111 Amazonas 143 87 159 339 728 Bahia 290 176 322 1,820 2,608 Ceará 231 140 256 1,354 1,981 Distrito Federal 378 230 420 5,434 6,462 Espírito Santo 59 36 66 525 686 Goiás 37 23 42 608 710 Maranhão 81 49 90 274 494 Mato Grosso 94 57 105 325 581 Mato Grosso do Sul 29 17 32 353 431 Minas Gerais 240 146 266 2,283 2,935 Pará 126 76 140 561 903 Paraíba 34 21 38 282 375 Paraná 164 100 182 1,636 2,082 Pernambuco 244 148 271 1,319 1,982 Piauí 23 14 25 164 226 Rio de Janeiro 1,134 690 1,261 5,997 9,082 Rio Grande do Norte 72 44 80 423 619 Rio Grande do Sul 182 111 202 1,239 1,734 In the State of Pernambuco, aviation transportation and the sector effected payed out R$1.98 BILLION in salaries. Rondônia 26 16 29 123 194 Roraima 3 2 3 24 32 Santa Catarina 73 45 81 1,036 1,235 São Paulo 3,633 2,209 4,039 12,363 22,244 Sergipe 27 16 30 151 224 Tocantins 7 4 8 103 122 Total Brazil 7,394 4,496 8,218 39,139 59,247 It is a higher amount than that payed out by wealthier states with larger populations such as Rio Grande do Sul Source: www.abear.com.br/uploads/arquivos/dados_e_fatos_arquivos_ptbr/abear_voarpormais Brasil_2016.pdf 18
ABEAR - Associação Brasileira das Empresas Aéreas BRAZIL TAXES STATE TAXES (R$MILLIONS) AIR TRANSPORTATION All effects IMPACTED SECTOR Tourism (all effects) TOTAL Acre 8 22 30 Alagoas 68 102 171 Amapá 6 40 46 Amazonas 184 139 322 Bahia 372 743 1,114 Ceará 296 553 849 Distrito Federal 485 2,219 2,704 Espírito Santo 76 215 291 Goiás 48 248 296 Maranhão 103 112 215 Mato Grosso 121 133 253 Mato Grosso do Sul 37 144 181 Minas Gerais 307 932 1,239 Pará 161 229 390 Paraíba 43 115 158 Paraná 210 668 878 Pernambuco 313 539 851 Piauí 29 67 96 Rio de Janeiro 1,453 2,448 3,901 Rio Grande do Norte 92 173 265 Rio Grande do Sul 233 506 739 Rondônia 33 50 83 Roraima 4 10 14 Santa Catarina 94 423 517 São Paulo 4,655 5,047 9,703 Sergipe 35 62 96 Tocantins 9 42 51 Total Brazil 9,473 15,979 25,452 Source: www.abear.com.br/uploads/arquivos/dados_e_fatos_arquivos_ptbr/abear_voarpormais Brasil_2016.pdf 19
OVERVIEW 2016 ABEAR airlines results 20
ABEAR - Associação Brasileira das Empresas Aéreas OVERVIEW ABEAR airlines in 2016 Air transportation is highly relevant and sensitive to fluctuations in the economy. The difficulties confronted by the Brazilian economy over the last years have resulted in a drop in aviation sector demand. This has led to adjustments in the number of seats offered and in employment in order to remain viable and relevant to the needs of both passengers and airlines. ABEAR associates have proven their capacity to adjust to the vicissitudes of the moment, mitigating the negative effects of the economic crisis. 95 million paid passengers flown 25% of international flights in Brazil 99% of domestic flights 834.5 thousand take offs PERSPECTIVES Continue to adjust the supply and availability of fleet and employees to demand, which should increase with the return of economic growth. Guarantee the most efficient use of aircraft in order to offer even more competitive prices. Make the adjustments necessary to guarantee the economic sustainability of the airlines. 21
OVERVIEW 2016 Basic statistics The air transportation of passengers demand has kept in line with the country s recent economic difficulties, which resulted in a drop in GDP of 3.6% in 2016, according to the Instituto Brasileiro de Geografia e Estatística IBGE. Demand for domestic flights fell 5.5% in this period. In the international segment, the number of passengers flown was 3.4% lower. ABEAR affiliated airlines increased their capacity share on international flights in the last quarter, however, from 24% at the end of 2015 to 28% in the same period in 2016. Among the measures taken to diminish the impact of the drop in demand, Brazilian airlines reduced the number of domestic flights in 5.7%. Utilization of aircraft capacity remained practically unaltered in this manner. The levels of domestic flight capacity efficiency reached levels comparable to those of mature markets such as the United States and Europe. The chart below illustrates the recent evolution of domestic passenger load factor in Brazilian flights. EVOLUTION OF THE LOAD FACTOR IN PASSENGER DOMESTIC FLIGHTS 90% 80% 70% 60% 50% 40% 30% 65% 59% 58% 60% 57% 80% 80% 80% 76% 73% 71% 69% 70% 68% 66% 66% 68% In spite of a 2016 decline in passenger demand of 5.5% 20% 10% 0% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 the average load factor remained steady at Source: Agência Nacional de Aviação Civil (ANAC), Demanda e Oferta do Transporte Aéreo, available at: www.anac.gov.br/assuntos/dados-e-estatísticas/demanda-e-oferta-do-transporte-aéreo (accessed 26 January 2017). The domestic air cargo market showed similar behavior to the passenger market, with a decline of 5.8% in 2016. Brazilian airlines managed their capacity supply in accordance with domestic demand. In the international sector, they increased their market share, as was the case with passenger flights. In spite of the drop in demand, airlines affiliated with ABEAR maintained near unchanged their market share. The following charts summarize the basic statistics of 2016 and 2015 and present the variations from one year to the next. 22 80%
ABEAR - Associação Brasileira das Empresas Aéreas BASIC OPERATIONAL STATISTICS 2016 AVIANCA BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 12,161 10,204 83.9 9,203 49,236 75,543 143,123 1,053 International 55 33 60.3 8 12,734 567 2,976 3,842 Total 12,216 10,237 83.8 9,211 61,970 76,110 146,098 1,074 AZUL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 19,376 15,192 78.4 19,414 32,139 255,178 381,097 693 International 3,493 3,043 87.1 484 9,312 2,732 18,605 5,083 Total 22,869 18,235 79.7 19,899 41,450 257,910 399,702 740 GOL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 41,104 32,031 77.9 30,250 90,575 246,737 428,788 985 International 5,226 3,897 74.6 1,875 2,641 14,590 45,468 2,031 Total 46,330 35,928 77.5 32,124 93,217 261,327 474,255 1,043 LATAM AIRLINES BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 37,612 30,931 82.2 28,672 112,419 207,113 357,239 980 International 30,702 26,076 84.9 5,118 98,329 27,868 158,769 4,241 Total 68,314 57,007 83.4 33,790 210,748 234,981 516,008 1,367 LATAM CARGO BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic - - - - 37,391 1,864 5,002 1,749 International - - - - 59,191 2,309 9,756 2,974 Total - - - - 96,582 4,173 14,758 2,427 23
OVERVIEW 2016 TOTAL ABEAR Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 110,252 88,358 80.1 87,539 321,760 786,435 1,315,248 897 International 39,476 33,049 83.7 7,485 182,207 48,066 235,573 3,553 Total 149,728 121,407 81.1 95,024 503,967 834,501 1,550,821 1,050 OTHER BRAZILIAN AIRLINES Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 1,004 669 66.6 1,138 3,289 42,500 64,583 619 International - - - - - - - - Total 1,004 669 66.6 1,138 3,289 42,500 64,583 619 TOTAL BRAZIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 111,256 89,027 80.0 88,678 325,049 828,935 1,379,831 883 International 39,476 33,049 83.7 7,485 182,207 48,066 235,573 3,553 Total 150,732 122,076 81.0 96,163 507,256 877,001 1,615,404 1,029 Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos do Transporte aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações/base-de-dados-estatísticos-do-transporte-aereo (accessed 15 May 2017). BASIC OPERATIONAL STATISTICS 2015 AVIANCA BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 10,654 8,911 83.6 8,041 41,613 71,510 133,221 1,029 International 55 19 34.7 5 4,728 341 1,849 3,895 Total 10,709 8,930 83.4 8,046 46,341 71,851 135,070 1,042 AZUL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 20,320 16,030 78.9 20,178 33,061 274,882 415,846 694 International 3,092 2,598 84.0 397 4,513 1,890 15,414 6,180 Total 23,412 18,628 79.6 20,575 37,575 276,772 431,260 731 24
ABEAR - Associação Brasileira das Empresas Aéreas GOL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 43,450 33,903 78.0 35,050 90,769 298,745 474,033 865 International 6,294 4,508 71.6 1,990 2,131 16,893 53,901 2,122 Total 49,744 38,411 77.2 37,040 92,900 315,638 527,934 932 LATAM AIRLINES BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 42,543 34,626 81.4 31,417 131,039 235,832 410,450 995 International 31,307 26,029 83.1 4,903 111,932 26,953 163,678 4,566 Total 73,850 60,655 82.1 36,321 242,971 262,785 574,128 1,361 LATAM CARGO BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic - - - - 45,131 2,745 7,420 1,759 International - - - - 57,130 2,164 9,268 3,003 Total - - - - 102,262 4,909 16,688 2,307 TOTAL ABEAR Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 116,968 93,471 79.9 94,686 341,614 883,714 1,440,969 862 International 40,748 33,154 81.4 7,295 180,434 48,241 244,111 3,698 Total 157,716 126,624 80.3 101,981 522,048 931,955 1,685,080 1,009 OTHER BRAZILIAN AIRLINES Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 1,251 902 72.1 1,495 2,077 51,990 76,935 575 International - - - - - - - - Total 1,251 902 72.1 1,495 2,077 51,990 76,935 575 TOTAL BRAZIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 118,220 94,372 79.8 96,181 343,690 935,704 1,517,904 846 International 40,748 33,154 81.4 7,295 180,434 48,241 244,111 3,698 Total 158,967 127,526 80.2 103,476 524,125 983,945 1,762,015 986 Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos do Transporte aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações/base-de-dados-estatísticos-do-transporte-aereo (accessed 15 May 2017). 25
OVERVIEW 2016 VARIATION AVIANCA BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic 14.1% 14.5% 0.3% 14.5% 18.3% 5.6% 7.4% 2.4% International 1.0% 75.8% 25.6% 75.6% 169.3% 66.3% 60.9% -1.4% Total 14.1% 14.6% 0.4% 14.5% 33.7% 5.9% 8.2% 3.0% AZUL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic -4.6% -5.2% -0.5% -3.8% -2.8% -7.2% -8.4% -0.0% International 13.0% 17.2% 3.1% 22.0% 106.3% 44.6% 20.7% -17.7% Total -2.3% -2.1% 0.2% -3.3% 10.3% -6.8% -7.3% 1.2% GOL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic -5.4% -5.5% -0.1% -13.7% -0.2% -17.4% -9.5% 13.8% International -17.0% -13.6% 2.9% -5.8% 24.0% -13.6% -15.6% -4.3% Total -6.9% -6.5% 0.3% -13.3% 0.3% -17.2% -10.2% 11.9% LATAM AIRLINES BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic -11.6% -10.7% 0.8% -8.7% -14.2% -12.2% -13.0% -1.5% International -1.9% 0.2% 1.8% 4.4% -12.2% 3.4% -3.0% -7.1% Total -7.5% -6.0% 1.3% -7.0% -13.3% -10.6% -10.1% 0.4% LATAM CARGO BRASIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic - - - - -17.2% -32.1% -32.6% -0.6% International - - - - 3.6% 6.7% 5.3% -1.0% Total - - - - -5.6% -15.0% -11.6% 5.2% 26
ABEAR - Associação Brasileira das Empresas Aéreas TOTAL ABEAR Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic -5.7% -5.5% 0.2% -7.5% -5.8% -11.0% -8.7% 4.0% International -3.1% -0.3% 2.4% 2.6% 1.0% -0.4% -3.5% -3.9% Total -5.1% -4.1% 0.8% -6.8% -3.5% -10.5% -8.0% 4.1% OTHER BRAZILIAN AIRLINES Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic -19.8% -25.9% -5.5% -23.8% 58.4% -18.3% -16.1% 7.6% International - - - - - - - - Total -19.8% -25.9% -5.5% -23.8% 58.4% -18.3% -16.1% 7.6% TOTAL BRAZIL Flights Seatkilometers passengerkilometers Load factor passengers Tons of cargo Take-offs Total block hours Average stage lenght (km) Domestic -5.9% -5.7% 0.2% -7.8% -5.4% -11.4% -9.1% 4.3% International -3.1% -0.3% 2.4% 2.6% 1.0% -0.4% -3.5% -3.9% Total -5.2% -4.3% 0.8% -7.1% -3.2% -10.9% -8.3% 4.4% Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos do Transporte aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações/base-de-dados-estatísticos-do-transporte-aereo (accessed 15 May 2017). 27
OVERVIEW 2016 Employees and fleet Areduction of nearly 6.8% in the number of employees in 2016, in relation to 2015, from 57,420 to 53,494, is consistent with the drop in demand in the same period. ABEAR carriers have 1,820 PASSENGERS PER EMPLOYEE a number similar to that of the sector in the United States NUMBER OF EMPLOYEES ON DECEMBER 31 ST, 2016 LATAM Cargo Brasil AVIANCA Brasil AZUL GOL LATAM Airlines Brasil Total ABEAR Outras companhias Total Brasil Pilots and copilots 74 457 1,525 1,563 1,842 5,461 ND ND Cabin crew 0 922 2,150 2,970 4,628 10,670 ND ND Maintenance personnel 6 590 1,724 2,106 2,734 7,160 ND ND Airport personnel 98 1,294 2,752 4,650 9,514 18,308 ND ND Other employees 89 1,290 2,160 3,840 4,516 11,895 ND ND Total 267 4,553 10,311 15,129 23,234 53,494 ND ND Source: ABEAR associates; Airfleets.net, disponível em: www.airfleets.net. The size of the fleet was reduced by 11.6% in 2016 in comparison with the 498 units of the previous year. FLEET ON DECEMBER 31 ST, 2016 Aircraft type LATAM Cargo Brasil AVIANCA Brasil AZUL GOL LATAM Airlines Brasil Total ABEAR Other companies Total Brasil Airbus A318 10 10 10 Airbus A319 4 21 25 25 Airbus A320 31 5 65 101 101 Airbus A321 31 31 31 122 EMPLOYEES PER AIRSHIP Airbus A330-200 Airbus A330-200F Airbus A350 XWB 1 5 6 6 1 1 1 6 6 6 ATR 72-600 39 39 3 42 many more than the 96 of North-American airlines Boeing 737-700 Boeing 737-800 Boeing 767-300 Boeing 767-300F Boeing 777-300 Embraer E190 Embraer E195 28 28 28 92 92 92 14 14 14 3 3 3 10 10 10 10 10 10 64 64 64 Others 0 16 16 Total 3 47 123 120 147 440 19 459 Sources: FlightGlobal, available at: www.flightglobal.com (accessed 23 May 2017). Agência Nacional de Aviação Civil (ANAC), Frota Brasileira - Estatística, available at: www.anac.gov.br/assuntos/setorregulado/ aeronaves/frota-brasileira-estatística-1 (accessed 23 May 2017). 28
ABEAR - Associação Brasileira das Empresas Aéreas The Brazilian fleet is among the newest in the world, as can be seen in the chart below which uses air carriers from other countries for comparison. SIZE AND AVERAGE AGE OF FLEETS OF BRAZILIAN AND FOREIGN CARRIERS Air carrier Company Average age (years) Quantity AVIANCA Brasil Brasil 4.4 47 AZUL Brasil 4.8 123 GOL Brasil 9.0 120 LATAM Airlines Brasil Brasil 7.0 147 LATAM Cargo Brasil Brasil 13.3 3 Average ABEAR 6.7 Source: ABEAR associates; Other air carriers AMERICAN AIRLINES USA 10.7 950 AVIANCA Colombia 5.7 86 DELTA Air Lines USA 17.6 857 VOLARIS Mexico 4.6 65 SOUTHWEST Airlines USA 12.1 728 AIR FRANCE France 12.6 224 BRITISH Airways United Kingdom 13.1 267 EASYJET United Kingdom 7.4 273 LUFTHANSA Germany 11.4 264 RYANAIR Ireland 7.1 400 ALL NIPPON AIRWAYS (ANA) Japan 9.0 205 CHINA EASTERN Airlines China 5.7 339 CHINA SOUTHERN Airlines China 7.4 525 EMIRATES Airline United Arab Emirates 5.6 257 QATAR Airways Qatar 6.2 199 SINGAPORE Airlines Singapore 8.2 109 Average airship age of these foreign carriers 10.5 Source: FlightGlobal, available at: www.flightglobal.com (accessed 23 May 2017). The average age of ABEAR affiliates fleets is 6.7 YEARS 3.8 years less than a significant sample of important international airlines 29
OVERVIEW 2016 Transportation of organs, tissues and medical teams The cost-free transportation of human organs, tissues and medical teams out by ABEAR affiliated airlines is unique in the world. This is a collaborative effort undertaken by ABEAR, the Brazilian Air Force, Infraero, The Brazilian Ministry of Health, The Brazilian Secretary of Civil Aviation and airports. This work is performed regularly by representatives of the National Transplant Central (CNT) and the Center for Air Space Management (CGNA), together with the airlines. The following charts show the overall results of this service, which was formally structured in 2013. TRANSPORTATION OF ORGANS, TISSUES AND MEDICAL TEAMS IN AIRCRAFT (UNITS) 9,000 8,000 7,957 7,000 6,938 6,557 6,919 6,000 5,000 4,806 4,691 4,000 3,737 3,850 3,000 2,429 2,000 1,752 2,005 1,934 1,135 1,000 837 815 380 0 2013 2014 2015 2016 Teams Organs and tissues Others Total Source: Coordenação do Sistema Nacional de Transplantes (CNT), available at: www.portalsaude.saude.gov.br. Compiled by ABEAR. 30
ABEAR - Associação Brasileira das Empresas Aéreas Market participation The participation of ABEAR affiliated aviation companies in the supply and demand of the international and domestic markets can be visualized in the following charts. We do not see major alterations in market share between 2015 or 2016. The participation in supply and demand is balanced, moreover, revealing proximity in the load factor among all of the carriers. SHARE OF SUPPLY DOMESTIC FLIGHTS 2015 - (ASK %) 1% 1% 9% SHARE OF SUPPLY DOMESTIC FLIGHTS 2016 (ASK %) 11% 36% 17% 34% 17% 37% 37% SHARE OF DEMAND DOMESTIC FLIGHTS 2015 - (RPK %) 1% 9% SHARE OF DEMAND DOMESTIC FLIGHTS 2016 (RPK %) 1% 11% 37% 17% 35% 17% 36% 36% Avianca Azul / Trip GOL LATAM Others Source: Agência Nacional de Aviação Civil (ANAC), Demanda e Oferta do Transporte Aéreo, available at: www.anac.gov.br/assuntos/dados-e-eestatísticas/demanda-e-oferta-do-transporte-aereo 31
OVERVIEW 2016 SHARE OF SUPPLY INTERNATIONAL FLIGHTS 2015 (ASK %) SHARE OF SUPPLY INTERNATIONAL FLIGHTS 2016 (ASK %) 0% 2% 0% 2% 4% 3% 19% 20% 76% 75% SHARE OF DEMAND INTERNATIONAL FLIGHTS 2015 (RPK %) SHARE OF DEMAND INTERNATIONAL FLIGHTS 2016 (RPK %) 0% 2% 0% 2% 3% 3% 20% 21% 75% 74% Avianca Azul / Trip GOL LATAM Others Source: Agência Nacional de Aviação Civil (ANAC), Demanda e Oferta do Transporte Aéreo, available at: www.anac.gov.br/assuntos/dados-e-eestatísticas/demanda-e-oferta-do-transporte-aereo 32
ABEAR - Associação Brasileira das Empresas Aéreas Market concentration in different countries T he air transportation sector shows a high level of concentration compared to other sectors of the economy. The principal reasons for this are the need for operational scale and capital due to the high cost of its equipment requirements. In order to evaluate the level of market concentration of air transportation in Brazil it is necessary to compare it to other countries markets. The method used worldwide to ascertain the level of sectorial concentration is the Herfindahl-Hirschman Index. It is calculated using the formula: n HHI = Σ (MSi x 100) 2, 1 Where MSi is the competitor s I market share, expressed in decimal units, and n is the total number of competitors in the market. The graph below shows the HHI values of the 20 largest domestic passenger aviation markets. As is apparent, the level of market concentration in Brazil is just about at the median. The market concentration of the domestic air transport in Brazil is just below the average: the HHI is 3,015 This scenario is similar of those existing in more mature markets, such as Japan, Spain and France. MARKET CONCENTRATION OF DOMESTIC PASSENGER AIR TRANSPORTATION HERINDAHL-HIRSCHMAN INDEX (HHI) 6,000 5,000 5,138 4,466 4,000 3,908 3,724 3,664 3,647 3,000 3,399 3,292 3,173 3,109 3,106 3,015 2,864 2,824 Median = 3,108 2,000 2,560 2,463 2,234 2,017 1,636 1,188 1,000 Canada South Korea Colombia Philipines Spain Malaysia Turkey Japan Australia France Italy Brazil United Kingdom Germany Mexico India China Russia Indonesia United States Sources: Directorate of Civil Aviation (http://dgca.nic.in/); Civil Aeronautical Board - Phillipines, www.cab.gov.ph; http://www.anna.aero/; China Civil Aviation Authority, www.caac.gov.cn; Aeronautica Civil - Colombia, www.aerocivil.gov.co; Ministry of Transport, Telecommunication and Maritime Affairs - Turkey, www.udhb.gov.tr; Dirección General de Aeronáutica Civil - Mexico, www.sct.gob.mx; Ministry of Transport - Thailand, www.news.mot.go.th; Agência Nacional de Aviação Civil, www.anac.gov.br; Korean Statistical Information Service, http://kosis.kr; Eurostat - http://ec.europa.eu; Ministry of Land, Infrastructure and Transport, Civil Aviation Bureau - Japan, www.mlit.go.jp; Civil Aviation Board - United Kingdom, https://www.caa.co.uk; Statistics Canada, www5.statcan.gc.ca; US Department of Transportation, www.transtats.bts.gov; Bureau of Infrastructure, Transport and Regional Economics - Australia, http://bitre.gov.au; Federal Air Transport Agency - Russia, http://www.favt.ru; International Civil Aviation Organization - ICAO, ICAO Data Plus; International Monetary Fund, www.imf.org. Observations: 1. The HHI is defined as the sum of the square of companies market participations in a specific domestic market, expressed in decimal points. It varies from 1 to 10,000. The higher the HHI, the greater the market concentration. 2. The HHI was calculated on the basis of the number of passengers flown in 2015 in twenty of the largest domestic markets worldwide, corresponding to 91% of domestic demand worldwide. 33
OVERVIEW 2016 Consolidated Financial Statements T he year of 2016 was a tough year for Brazilian air carriers due primarily to a drop in yield (passenger revenue per passenger kilometer flown) in the domestic market. The behavior of this indicator is sensitive to the performance of the Brazilian economy. By reducing its overall operating costs in approximately 10% (measured in constant currency values for 2016), the aviation sector was able to mitigate some of the negative effects of low fares. Significant positive results were obtained in the most part by way of careful demand management. This reduced operating losses to practically half the levels of 2015. In 2016 ABEAR affiliated airlines reduced their operating costs by 10% FINANCIAL STATEMENTS (R$ 000) 2016 2015 2014 Net 32,700,268 100.0% 32,197,806 100.0% 32,292,187 100.0% Cost of services rendered -27,531,300-84.2% -28,882,002-89.7% -26,374,228-81.7% Gross profit (loss) 5,168,968 15.8% 3,315,804 10.3% 5,917,959 18.3% OPERATING EXPENSES Sales -2,779,957-8.5% -2,806,644-8.7% -3,101,717-9.6% Administrative -3,093,206-9.5% -1,949,040-6.1% -2,546,769-7.9% Equity result 1,250 0.0% 1,991 0.0% 1,302 0.0% Operating profit (loss) -702,945-2.1% -1,437,889-4.5% 270,775 0.8% Financial Income 729,353 2.2% 817,236 2.5% 716,153 2.2% Financial Expenses -1,373,417-4.2% -5,395,302-16.8% -2,962,144-9.2% Income before taxes on profits -1,347,009-4.1% -6,015,955-18.7% -1,975,216-6.1% Income taxes and social contribution taxes -229,603-0.7% -20,610-0.1% 311,310 1.0% Profit/Loss for the period -1,576,612-4.8% -6,036,565-18.7% -1,663,906-5.2% Source: Agência Nacional de Aviação Civil (ANAC), Demonstrações Contábeis de Empresas Aéreas Brasileiras, available at: www.anac.gov.br/assuntos/dados-e-estatísticas/demonstrações-contábeis/demonstrações-de-empresas-aereas-brasileiras. Compiled by ABEAR. There are no major differences between 2015 and 2016 in the overall results shown in industry balance sheets. However, when we look closely at long term assets, there is a substantial drawdown under the headings related parties (goods and royalties among companies in the same group) and fixed assets (aircraft and their components, primarily). When they are added together these cost reductions correspond to practically the totality of the retraction in current assets in relation to the previous year. 34
ABEAR - Associação Brasileira das Empresas Aéreas CONSOLIDATED FINANCIAL STATEMENTS Balance Sheet December 31 st Assets (R$ 000) 2016 2015 2014 CURRENT ASSETS Cash and equivalents 1,171,900 1,642,183 1,929,859 Financial applications 805,132 607,520 966,679 Accounts due 4,136,366 3,586,190 3,417,747 Inventory 692,595 752,185 706,749 Recoverable taxes 325,360 608,857 477,542 Financial instruments and derivatives 21,455 42,805 51,077 Prepaid expenditures 111,214 199,335 211,751 Other current assets 1,220,123 826,032 353,306 8,484,145 8,265,107 8,114,710 NON-CURRENT Financial applications 148,559 13,521 52,828 Related parties 2,932,966 3,976,325 3,505,155 Prepaid expenditures 1,121,799 1,529,391 1,033,390 Deferred and recovered taxes 1,233,021 1,369,823 1,114,391 Legal deposits 2,252,174 1,881,768 1,413,306 Other non-current assests 147,216 203,064 300,896 Fixed 8,438,447 10,060,179 8,487,896 Intangible 2,266,707 2,205,868 2,154,916 18,540,889 21,239,939 18,062,778 Total Assets 27,025,034 29,505,046 26,177,488 Liabilities (R$ 000) 2016 2015 2014 CURRENT Loans 3,398,440 2,948,557 1,863,837 Suppliers 5,669,674 5,763,415 3,101,789 Transportation to carry out 2,342,353 2,223,666 2,074,438 Salaries, provisions and payroll taxes 1,121,503 909,872 943,500 Fiscal obligations 596,394 653,108 611,986 Deferred income 2,193,954 2,241,375 2,060,025 Financial instruments and derivatives 145,382 369,263 92,565 Other obligations 1,841,101 2,397,858 1,788,087 17,308,801 17,507,114 12,536,227 NON-CURRENT Loans 8,128,065 11,648,901 9,730,537 Contingency reserves 2,308,803 2,549,734 1,947,378 Deferred income 391,674 126,186 834,791 Fiscal obligations 581,053 476,092 105,597 Financial instruments and derivatives 19,530 51,635 32,617 Debentures 15,225 0 0 Related parties 2,181,264 1,103,135 187,750 Other obligations 570,355 542,230 322,386 14,195,969 16,497,913 13,161,056 The same can be said of current liabilities, where there are important variations in the items loans (reductions) and related parties (increases). As is the case in non -current assets, these two movements in non-current liabilities, when combined, show a total reduction in value in comparison to the previous year. These financial movements result in a discreet favorable variation in the consolidated liquid patrimony in spite of expressive losses. In terms of cash flow, the expressive operational losses of 2016 (equivalent to those of 2015) were aggravated by the acquisition of fixed assets and intangibles (half of those seen in 2015) for a total of R$ 2,96 billion. In contrast, the related parties and capital increases totaled R $ 2,33 billions. These movements which total R$ 635 million explain in large part the total loss of aggregate income, of R$ 470 million. In sum, the income losses consolidated by ABEAR affiliated airlines which resulted of the adverse economic environment were managed primarily by a cautious drawdown in supply (capacity reduction), a decrease in payments related to sectoral expansion (reduction of the expansion pace and capital contributions and an increase in capital. Overall, the decrease in aggregate income corresponded to approximately 30% of the losses in the period. 35
OVERVIEW 2016 NET EQUITY Share capital 12,555,481 10,411,446 9,843,744 Capital reserves 1,166,228 1,794,542 1,195,460 Profits/accumulated losses -18,096,334-16,524,768-10,493,558 Others -33,011-90,491-27,979 Valuation adjustment -72,100-90,710-37,462-4,479,736-4,499,981 480,205 Total equity and liabilities 27,025,034 29,505,046 26,177,488 Source: Agência Nacional de Aviação Civil (ANAC), Demonstrações Contábeis de Empresas Aéreas Brasileiras, available at: www.anac.gov.br/assuntos/dados-e-estatísticas/demonstrações-contábeis/demonstrações-de-empresas-aereas-brasileiras. Compiled by ABEAR. CONSOLIDATED FINANCIAL REPORTS Cash flow December 31 st 2016 2015 Net earnings/loss for the period -1,576,612-6,036,565 ADJUSTMENTS TO RECONCILE NET PROFITS TO CASH GENERATING FROM OPERATING ACTIVITIES Income tax and deferred social contribution taxes 135,717 15,807 Depreciation and amortization 1,198,529 1,188,559 Result of the sales of fixed and intangible assets 632,942 291,531 Loss from asset retirements 214,664 28,682 Interest and currency variations on assets and debts -70,423 2,414,423 Equity equivalence -1,250-1,991 Results from derivative financial instruments -30,409 185,812 Payment based on stock shares 21,810 9,829 Allowance for doubtful receivables 23,355 79,200 Other provisions 446,313 129,241 Maintenance provisions -517,243 326,538 Contingency provisions 56,109 105,750 Financial/Tax gain for adhesion to Refis Federal Tax Recovery Program 0 0 Labor benefits 0-50,485 Extinction of finance lease obligation -357,673-135,626 Discounts conceded on advanced bookings 141,380 0 VARIATIONS IN ASSETS AND LIABILITIES Accounts receivable -573,660-247,643 Financial applications 51,211-28,420 Stocks -13,798-69,495 Recoverable taxes 227,947-121,415 Deposit guarantees and maintenance reserves -362,464-414,999 Prepaid expenditure 32,061-25,596 Suppliers -98,431 2,640,794 Salaries and social contributions 166,609-35,797 Taxes payable 12,570 63,908 36
ABEAR - Associação Brasileira das Empresas Aéreas Payments of contingencies and judicial deposits -47,241-96,769 Tax installments 12,485 148,413 Payment of Refis Federal Tax Recovery Plan 0 0 Derivatives operations obligations -13,384-6,267 Interest paid -881,783-923,585 Fiscal recovery program -6,505-7,572 Air traffic liability 92,804-371,685 Technical reserves and insurance -248,570-56,359 Other liquid assets and liabilities 214,191-295,942 generated by operational activities -1,166,170-1,116,374 CASH FLOW FROM FINANCIAL INVESTMENTS Financial applications -371,036 428,878 Restricted cash investments 496,017-401,396 Capital increase 0 0 Related party loans 7,898 1,233,544 Acquisitions of fixed and intangible assets -1,252,178-2,425,751 Sales of fixed assets 459,726 305,784 Cash from back to back operations 0 38,232 Pre-payment of airships 0 0 Guarantee deposits 0 19,547 generated by or used in investment activities -659,573-801,162 CASH FLOWS FROM FINANCING ACTIVITIES Capture and payment of debentures -27,581 1,518,347 Advance on future capital increase 284,998 589,000 Loans and financing, capture and payments -543,682-1,007,770 Payments and financial leasing -626,716-378,079 Repayment of senior level bonuses 0-928,386 Related parts 1,233,298 1,050,185 Capital increase 1,093,247 567,702 Cash utilized in financing activities 1,413,564 1,410,999 Currency variation in cash from foreign subsidiaries -24,023 180,669 Decrease/increase in cash and cash equivalents -436,202-325,868 Currency variation effect on cash or cash equivalents -34,081 38,192 Cash and cash equivalents at the beginning of the period 1,642,183 1,929,859 Cash and cash equivalents at the end of the period 1,171,900 1,642,183 Source: Agência Nacional de Aviação Civil (ANAC), Demonstrações Contábeis de Empresas Aéreas Brasileiras, available at: www.anac.gov.br/assuntos/dados-e-estatísticas/demonstrações-contábeis/demonstrações-de-empresas-aereas-brasileiras. Compiled by ABEAR. 37
OVERVIEW 2016 Quality of service 38
ABEAR - Associação Brasileira das Empresas Aéreas OVERVIEW Quality indicators On-time performance in departures and arrivals, proper baggage handling and solid airport customer service: brazilian carriers are a reference in this field. It each of these items Brazilian airlines score as well as or better than their counterparts in more mature markets. Research out by the Secretaria da Aviação Civil - SAC, which is part of the Ministério dos Transportes, Portos e Aviação Civil, confirm a high level of customer satisfaction with aviation in general and carriers in particular. The approval of measures such as those allowing for charges for baggage checking will result in lower prices for those who don t want to check baggage and better service for those who do. 88% on-time departure with minimum tolerance margin (15 minutes) 2.1 bags were mishandled for every 1000 pieces checked in 2016 98% punctuality with the maximum tolerance margin (98%) Versus 3.1 in 2014 4.28 on a scale of 0 to 5 is the grade given airlines by Brazilian passengers. PERSPECTIVES Improve services and support infrastructure enhancements that contribute to better punctuality. Improve baggage handling, with the help of new rules in this sector. Offer services increasingly tailored to the wishes and needs of clients, in accordance with new airline directives. 39
OVERVIEW 2016 On-time performance One of the most important indicators of quality air services throughout the world is the on-time performance of flights. There are different margins of tolerance within which a flight can be considered on-time: 15, 30 and 60 minutes late. On-time performance can also be measured on departure or arrival. The first corresponds to the airline s perspective, since it does not control possible obstacles that might occur after takeoff. The second measure corresponds to the passenger s point of view, for whom arriving on-time is what matters. The evaluation of on-time performance should be out in relation to carriers in countries of reference, since each form of transportation has its own standards. Railroads, to take one example, have much high standards for punctuality since they are less effected by the weather. The following charts compare ABEAR affiliated airlinesbetween 2015 and 2016, in accordance with different margins of tolerance. The results are similar to those of air carriers in the United States. ON-TIME DEPARTURE ON DEPATURE IN BRAZIL DOMESTIC FLIGHTS 2015/2016 January and December register the highest number of delays. But even in this period average punctuality is above 80% 100% 95% 90% 85% 80% 75% 70% Jan Fev Mar Abr Mai Jun Jul Ago Set Out Nov Dez On-time departure 2015 15 minutes Average: 88% On-time departure 2016 15 minutes Average: 88% On-time departure 2015 30 minutes Average 94% On-time departure 2016 30 minutes Average 94% On-time departure 2015 60 minutes Average 98% On-time departure 2016 60 minutes Average 98% Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/historico-de-voos. Compiled by ABEAR. 40
ABEAR - Associação Brasileira das Empresas Aéreas PERCENT OF DELAYS ON DEPARTURES IN BRAZIL AND THE UNITED STATES DOMESTIC FLIGHTS 2016 100% 95% 90% 85% 80% 75% 70% Jan Fev Mar Abr Mai Jun Jul Ago Set Out Nov Dez On-time Brazil 15 minutes Average: 88% On-time USA 15 minutes Average: 83% Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/historico-de-voos. Bureau of Transportation Statistics (BTS), Airlines and Airports, available at: www.bts.dot.gov. Compiled by ABEAR PERCENT OF DELAYS ON ARRIVAL IN BRAZIL AND THE UNITED STATES DOMESTIC FLIGHTS 2016 100% Air carriers are responsible for only 95% 90% 85% 80% 75% 70% Jan Fev Mar Abr Mai Jun Jul Ago Set Out Nov Dez On-time Brasil 15 minutes Average: 87% As can be seen in the charts, the carriers on-time remained stable if compared to 2015 land levels superior to those of the United States. On-time USA 15 minutes Average: 83% Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/historico-de-voos. Bureau of Transportation Statistics (BTS), Airlines and Airports, available at: www.bts.dot.gov. Compiled by ABEAR. 33% of delays in domestic flights 21% of delays above 15 minutes in Brazil are caused by weather conditions 41
OVERVIEW 2016 It is likewise relevant to verify the reasons for delays, which can be classified by weather and the cause for their occurrence. In the following charts the justifications for delays registered in the National Civil Aviation Association data based were used and organized in accordance with the criteria used by the US Department of Transportation: RESPONSIBILITY OF THE AIR CAR- RIER: the cause for canceling or delay results of circumstances controlled by the aviation company (maintenance or crew difficulties, cleaning of aircraft, freight baggage, fueling, etc.). RESPONSIBILITY OF THE AERO- NAUTICAL SYSTEM: A wide range of possibilities unrelated to climatic extremes, such as airport operations, heavy air traffic and air traffic control. SAFETY: Delays or flight cancelations caused by the evacuation of a terminal, the deplaning of an aircraft due to safety violations, defective tracking equipment or long lines (more than 29 minutes) in screening areas. NON-SPECIFIC CAUSES: Are those which have not been clearly identified or do not fit in aforementioned groups. The codes of justification for delays or cancelation used by ANAC were established in accordance with Department of Transportation criteria: AIR CARRIER RESPONSIBILITY: DF, DG, FP, GF, HB IR, MA, RA, TC, TD, WI; RESPONSIBILITY OF THE AERO- NAUTICAL SYSTEM: AA, AF, AI, AJ, AM, AR AT, HD, OA, RI, WA, WO, WR, WS, WT; SAFETY: AG, AS; NON-SPECIFIC CAUSES: MX. PARTICIPATION OF WEATHER RELATED CAUSES IN DELAYS OF OVER 15 MINS 2016 40% 35% 30% 25% 20% 15% Brazil Average: 21% USA Average: 31% 10% 5% 0% 42 Jan Fev Mar Abr Mai Jun Jul Ago Set Out Nov Dez Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/ dados-e-estatisticas/historico-de-voos. Bureau of Transportation Statistics (BTS), Airlines and Airports, available at: www.bts.dot.gov. Compiled by ABEAR.
ABEAR - Associação Brasileira das Empresas Aéreas RESPONSIBILITY FOR DELAYS IN DOMESTIC FLIGHTS 2016 7% 5% Responsibility of aeronautical system Responsibility of air carrier 33% 55% Non-specific delays (MX) Security (prevention against illicit acts, AS) Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/historico-de-voos. Bureau of Transportation Statistics (BTS), Airlines and Airports, available at: www.bts.dot.gov. Compiled by ABEAR. In the charts that follow, the causes for delays attributed to air carriers and the aeronautical system are detailed in accordance with their principal justifications. CAUSES FOR DELAYS IN DOMESTIC FLIGHTS ATTRIBUTED TO CARRIERS 2016 14% Aircraftconnection 15% 38% Aircraft Failure Ground equipment failure Others Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/historico-de-voos. Compiled by ABEAR. 32% CAUSES FOR DELAYS ATTRIBUTED TO AERONAUTICAL SYSTEM FAILURE 2016 20% 28% Airport with operational restrictions (AR) Non-penalized aircraft return (RM, RI) 7% Unfavorable meteorological conditions (WO) Others Source: Agência Nacional de Aviação Civil (ANAC), Histórico de Voos, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/historico-de-voos. Compiled by ABEAR. 45% 43
OVERVIEW 2016 Baggage handling Another item of great importance in the evaluation of air carrier service is baggage handling. The second chart on this page presents a comparison among the different ABEAR affiliated airlines and others in different regions of the world in terms of baggage handling mistakes per thousand passengers boarded. As is apparent, ABEAR associates show excellent performance in this area. In the following chart, worldwide statistics relative to the motives for failures in baggage handling are presented: REASONS FOR DELAYS IN CHECKED BAGGAGE DELIVERY WORLDWIDE TOTAL 2016 4% For every thousand passengers, ABEAR airlines record 2.1 baggage mishandlings This is less than half the world average of 5.7. 15% 10% 4% 47% Missed connection Boarding missed Incorrect boarding 4% 16% Incorrect aircraft arrival Airport/Customs/Weather conditions/weight or space restrictions Ticketing error/switched baggage/security/ Others Source: SITA, Air Transport Industry insights 2016: The Baggage Report, available at: www.sita.aero (accessed 04 May 2017). Compiled by ABEAR. Labeling error LOST AND DAMAGED BAGAGE PER THOUSAND PASSENGERS BOARDED 2016 10.00 8.00 8.1 Asia 6.00 5.7 North America Europe 4.00 2.7 Worldwide average ABEAR affiliates 2.00 1.8 2.1 Source: SITA, Air Transport Industry insights 2016: The Baggage Report, available at: www.sita.aero (accessed 04 May 2017). Compiled by ABEAR. Observation: Mishandled baggage is understood to mean passenger complaints regarding loss, theft, robbery or damage occurring during the air trip. 44
ABEAR - Associação Brasileira das Empresas Aéreas MISHANDLED BAGGAGE PER THOUSAND PASSENGERS BOARDED 2014-2016 8.00 7.3 6.5 6.00 5.7 4.00 3.6 3.1 2.8 3.1 2.7 2.00 2.1 1.8 ABEAR - 2014 ABEAR - 2015 ABEAR - 2016 United States - 2014 (domestic) United States - 2015 (domestic) United States - 2016 (domestic) Worldwide average - 2014 Worldwide average - 2015 Worldwide average - 2016 Sources: ABEAR associates; Bureau of Tansportation Statistics (BTS), Airlines and Airports, available at: www.bts.gov. SITA, Air Transport Industry insights 2016: The Baggage Report, available at: www.sita.aero (accessed 04 May 2017). Compiled by ABEAR. Observation: Mishandled baggage are understood as processes opened concerning passenger complaints referent to losses, thefts, robberies or damages of baggage during flights. Airport service Since the beginning of 2013, a Secretaria Nacional de Aviação Civil (SAC) has out quarterly research to assess the quality of service at Brazil s 15 principal airports. Answers are given on a scale of 0 to 5. The research has shown very positive results and includes the ground services of carriers. The chart below shows the results from the fourth quarter of 2016. On a scale of 0 to 5, the carriers service received a EVALUATION OF BRAZILIAN AIRPORTS FOURTH QUARTER OF 2016 GENERAL RESULTS 4.22 3.50 4.28 4.49 4.09 4.28 4.28 Airport infrastructure Passenger facilities Air carriers Official Public Organs Public transportation Average grade Source: Secretaria nacional de Aviação Civil (SAC), Pesquisa Permanente de Satisfação do Passageiro, available at: www.aviacao.gov.br/assuntos/pesquisa-satisfação (accessed 04 May 2017). Compiled by ABEAR. 45
OVERVIEW 2016 The passenger air transport market in Brazil 46
ABEAR - Associação Brasileira das Empresas Aéreas OVERVIEW Due to its dimensions, the Brazilian market has different dynamic than that observed in European countries, to take an example. In parallel, demographic distribution has concentrated a significant segment of activity in a few airports. The modest average income of the population and the low levels of integration in worldwide supply chains makethe Brazilian case even more peculiar. The use of statistical models of high explanatory value together with alternative scenarios has helped air carriers to better understand future perspective. Currently an increase in the number of domestic flights hinges on economic recovery. On the other hand a revision of aviation fuel tariffs would make lower passenger ticket prices viable. The domestic market in 2016 106 airports served by regular flights Aviation fuel: the principal obstacle 40% more expensive than the international average PERSPECTIVES 96 million passengers transported Continue planning for alternate scenarios, paying attention to different factors that influence the sector. Take advantage of renewed economic optimism to encourage improved access to Brazilian airports. 0.47 passengers transported per inhabitant slight above the average of the 20 largest domestic markets, which average is 0,42 26% of the airlines expenses rd 3 largest domestic market in absolute numbers Support the reduction of taxation and a revision of the pricing of aviation fuel for domestic flights, since this is the most important cap to the competitiveness of air transportation. 47
OVERVIEW 2016 Evolution and demand forecasts for air passenger transportation in Brazil As is the case throughout the world, the demand for air transportation in Brazil is closely related to GDP and the prices charged for the services offered. The quantification of these relations is important to better understand market dynamics and carry out demand forecasts. The productive capacity of air carriers cannot be altered quickly since it depends on expensive assets. Employees with specialized skills, moreover, require medium and long-term training. When these factors are added to the volatile behavior of GDP in Brazil, accurate shortrange predications are difficult to make. This makes business planning, understood as anticipated decision making, all the more important. In order to deal with imprecisions that result of changes in the overall business environment, high-tech companies adopt planning with alternate scenarios, applying it to short planning cycles and subject to more frequent revision. Alternative hypotheses are constructed from the drivers of the business dynamics of air transportation, including fares and GDP. Air transportation offers two distinct types of flights: domestic and international. Different than in Europe, the behavior of these two markets is distinct in Brazil due to limited integration in the worldwide production chains and the large size of its domestic market in relation to its economy. For these reasons, domestic and international markets receive distinct statistical treatments. Passenger demand for domestic flights in Brazil In the last ten years, the passenger demand of domestic flights in Brazil has more than doubled. The usual metric for domestic passenger air transportation (dependent variable) is the revenue passenger-kilometer (RPK) and the independent variables are GDP and the prices paid by the passenger per kilometer flown (or yield). The functional specification used in statistical modelling is dual logarithmic because, once calibrated, the elasticities (or percentual variations of the dependent variable on the independent variables) are calculated automatically. The level of adherence between the model estimates and data collected is measured by the coefficient of determination (R 2 ). By algebraic construction the values of R 2 vary between 0 and 1. When the value approximates 1, the statistical model explains the data observed efficiently; the opposite is the case when it approximates 0. Besides that, the greater the quantity of observations, the greater the explanatory capacity of the statistical model, at least theoretically. 48
ABEAR - Associação Brasileira das Empresas Aéreas THE EVOLUTION OF PASSENGER DEMAND IN DOMESTIC FLIGHTS IN BRAZIL 120,000,000 100,000,000 Estimate: In (RPK =-10.435 + 1.777In(GDP) 0.528In(yield) + 0.249 Dummy1 + 0.164 Dummy2 80,000,000 Trend Line Y = 2794.7x 3-126780x 2 + 2E + )6x 2E + 06 60,000,000 40,000,000 20,000,000 1970 1971 1972 1973 1974 1975 1976 Domestic Demand (RPK) Estimate (RPK) Tendency 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Sources: Agência Nacional de Aviação Civil (ANAC), Anuários do Transporte Aéreo (In English, Air Transport Yearbooks). Developed by ABEAR. 2009 2010 2011 2012 2013 2014 2015 2016 Thirty observations is generally considered the minimum adequate for the development of a robust statistically study. The statistical model summarized here, involving observations from 1970 to 2016, found a value for R 2 equal to 0.989. In other words, the statistical model developed here would be capable of explaining 98.9% of the values observed and only 1.1% of them would depended on unconsidered variables, at a level of confidence of 95%. In sum: the model explains the demand behavior very well in the 47 observations made (between 1970 and 2016). In parallel, the demand elasticities encountered equaled 1.777 in relation to GDP and -0.528 in relation to GDP and yield. These findings are in consistent with worldwide averages. At the same time, a trend line line was generated to determine to what extent the domestic passenger air travel have had a consistent behavior over time. The high level of adherence between the trend line line and actual data (R 2 equal to 0.974) reveals that growth in demand occurred in a natural fashion, although has accelerated since the beginning of the 21 st century. 49
OVERVIEW 2016 The recent acceleration in the growth of domestic demand is a result, fundamentally, of an accentuated drop in the average prices paid by passenger per kilometer flown. This is a result of the tariff liberalization in the Brazilian domestic market between 2000 and 2003, as shown by the chart below. PASSENGER YIELD ON DOMESTIC FLIGHTS IN BRAZIL (2016 R$/KM) 1.0000 0.9000 0.9415 0.8000 0.7000 0.6000 0.5000 0.4000 0.3000 0.2000 0.1000 0.0000 0.7126 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 SOURCE: Agência Nacional de Aviação Civil (ANAC), Anuário do Transporte Aéreo, available at: www.anac/assuntos/dados-e-estatísticas/anuario-do-transporte-aereo. Compiled by ABEAR. 0.2572 2006 2008 2010 2012 2014 2016 The forecast of domestic demand behavior (dependent variable) were calculated from the forecasted values of the GDP and the yield (independent variables). The rates of annual GDP variation were extracted from the Market Expectation System of the Brazilian Central Bank, in accordance with the table below. ANNUAL BRAZILIAN GDP VARIATION FORECASTS Year Average Optimistic Pessimistic 2017 0.7% 1.7% -0.3% 2018 2.3% 3.7% 1.0% 2019 2.4% 3.6% 1.3% 2020 2.4% 3.6% 1.3% 2021 2.4% 3.6% 1.3% Source: Banco Central do Brasil, Sistema Expectativas de Mercado, available at: www3.bcb.gov.br/expectativas/public/consulta/serieestatisticas (accessed 09 December 2016). The following chart shows a parallelism between demand and Brazilian GDP up to the period prior to tariff liberalization. From that point on the growth in domestic demand is significantly higher than the growth in GDP. 50
ABEAR - Associação Brasileira das Empresas Aéreas GDP, YIELD AND PASSENGER DEMAND IN DOMESTIC FLIGHTS IN BRAZIL 100,000,000 PRE-LIBERALIZATION TRANSITION POST-LIBERALIZATION 1.0000 90,000,000 0.9000 80,000,000 0.8000 70,000,000 0.7000 60,000,000 0.6000 50,000,000 0.5000 40,000,000 0.4000 30,000,000 0.3000 20,000,000 10,000,000 1970 1971 1972 1973 1974 1975 RPK Demand 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 GDP (2016 R$ x 100.000.000) Sources: Agência Nacional de Aviação Civil (ANAC), Anuário de Transporte Aéreo, available at: www.anac.gov.br/assuntos/dados-e-estatísticas/anuário-do-transporte-aereo; Instituto de Pesquisa Econômica Aplicada (IPEA), available at: www.ipeadata.gov.br. Compiled by ABEAR. 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Yield (2016 R$) IPCA 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 0.2000 0.1000 The forecasting of yield values at constant prices were developed from the geometric average of annual variations verified in the actual data of approximately -2.8% a year. This figure is close to variations in worldwide averages, of approximately -3% a year. It is interesting to observe that this figure corresponds to the worldwide average of productivity gains in the sector, which corroborates the thesis that, in the long term, airlines do not retain these gains. The chart below illustrates the forecasts for yield values over the upcoming years. DOMESTIC YIELD HISTORICAL FIGURES AND FORECASTS 1.0000 0.9000 0.8000 0.7000 0.6000 0.5000 0.4000 0.3000 0.2000 0.1000 0.0000 ACTUAL 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 PREDICTED 0.3059 0.3008 0.2958 2014 2016 2018 2020 2022 0.2908 0.2859 0.2811 Domestic Yield (2016 R$/km) SOURCE: Agência Nacional de Aviação Civil (ANAC), Anuário do Transporte Aéreo, available at: www.anac/assuntos/dados-e-estatísticas/ anuario-do-transporte-aereo. Compiled by ABEAR. 51
OVERVIEW 2016 By combining the values of GDP and yield with the statistical model above one arrives at the forecasts of domestic air traffic that follow. FORECASTS OF PASSENGER DEMAND (RPK 000) 150,000,000 140,000,000 137,653,459 130,000,000 127,335,719 120,000,000 117,791,340 122,017,838 110,000,000 100,000,000 90,000,000 93,108,940 91,471,461 89,846,697 100,777,493 96,753,132 92,844,817 108,962,354 96,385,087 102,517,524 108,644,192 100,113,395 115,137,003 103,985,919 108,008,238 80,000,000 70,000,000 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Elaborated by ABEAR. FORECASTS OF PASSENGER DEMAND (PASSENGERS CARRIED) 140,000,000 132,826,521 130,000,000 120,000,000 114,973,000 123,577,763 117,739,177 110,000,000 100,000,000 99,501,788 106,967,390 100,640,557 106,044,712 111,739,058 100,917,067 104,220,836 90,000,000 92,459,414 90,833,358 89,219,928 95,528,370 91,669,530 94,620,396 97,718,028 80,000,000 70,000,000 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Elaborated by ABEAR. 52
ABEAR - Associação Brasileira das Empresas Aéreas FORECASTS OF ANNUAL DOMESTIC PASSENGER DEMAND VARIATIONS (RPK%) 9.0% 8.0% 8.2% 8.1% 8.1% 8.1% 8.1% 7.0% 6.0% 5.8% 6.0% 6.0% 6.0% 6.0% 5.0% 4.6% 4.0% 3.0% 3.3% 3.8% 3.9% 3.9% 3.9% 2.8% 2.0% 1.0% 0.9% 0.0% 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Elaborated by ABEAR. FORECASTS OF VARIATION IN ANNUAL PASSENGER DEMAND RATES (PASSENGERS CARRIED %) 8.0% 7.6% 7.5% 7.5% 7.5% 7.5% 7.0% 6.0% 5.0% 5.2% 5.4% 5.4% 5.4% 5.4% 4.0% 4.0% 3.2% 3.3% 3.3% 3.3% 3.0% 2.7% 2.0% 2.2% 1.0% 0.0% 0.4% 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Compiled by ABEAR 53
OVERVIEW 2016 Passenger demand on international flights to and from Brazil The statistical treatment of the international air travel market is similar to that of the domestic market. It is difficult, however, to ascertain the distances travelled by international passengers because a relevant portion of them proceed or originate from places beyond the central connection points. Because Brazilian statistics don t cover these itineraries, the variable dependent used in the dimensioning of the international market is the number of enplaned passengers. Consequently, the average price paid by passengers per kilometer cannot be calculated and the only independent variable used in the statistic modelling is Brazilian GDP. The results of the statistical study are presented in the graph below. PASSENGERS BOARDED IN BRAZIL ON INTERNATIONAL FLIGHTS 25,000,000 Estimate In(PAX) = -18.629 + 0.294 Dummy2 20,000,000 Trend Line Y = 311.98x 3 8855.3x 2 + 226176x + 481737 R 2 = 0.98451 15,000,000 10,000,000 5,000,000 1971 1972 1973 1974 1975 1976 Real 1977 1978 1979 1980 1981 1982 1983 Estimated 1984 1985 1986 1987 1988 1989 1990 1991 1992 Trend Line SOURCE: Agência Nacional de Aviação Civil (ANAC), Anuário do Transporte Aéreo, available at: www.anac/assuntos/dados-e-estatísticas/anuario-do-transporte-aereo. Compiled by ABEAR. 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 The predictions of passengers boarded on international flights were made using the same criteria and GDP value scenarios utilized in the domestic market predictions, represented in the following charts. 54
ABEAR - Associação Brasileira das Empresas Aéreas DEMAND PREDICITONS FOR INTERNATIONAL FLIGHTS (BOARDED PASSENGERS) 33,000,000 32,166,326 31,000,000 29,696,289 29,000,000 27,000,000 27,415,926 27,584,999 25,000,000 25,310,671 24,732,351 26,119,760 23,000,000 21,534,068 23,361,863 22,179,606 23,418,637 22,284,794 22,939,956 23,614,379 21,648,343 21,000,000 21,052,634 21,044,278 20,577,269 19,000,000 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Elaborated by ABEAR. PREDICITIONS OF ANNUAL VARIATIONS IN DEMAND FOR INTERNATIONAL FLIGHTS (BOARDED PASENGERS %) 10.0% 8.5% 8.3% 8.3% 8.3% 8.3% 8.0% 6.0% 5.4% 5.6% 5.6% 5.6% 5.6% 4.0% 3.9% 2.9% 2.9% 2.9% 2.9% 2.3% 2.0% 1.5% 0.0% -0.7% -2.0% 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Elaborated by ABEAR. 55
OVERVIEW 2016 Cumulative demand predictions for the sum of domestic and international flights Adding up the predictions of passengers boarded on domestic and international the following results are obtained, which correspond to the totality of the market of air transportation in Brazil: Between 2017 and 2022, demand for international flights should grow more than 40% FORECASTS FOR DEMAND IN PASSENGERS CARRIED IN DOMESTIC AND INTERNATIONAL FLIGHTS (BOARDED PASSENGERS) 170,000,000 164,992,846 160,000,000 153,274,053 150,000,000 145,324,176 142,388,926 140,000,000 137,858,819 130,000,000 132,278,060 130,777,063 127,835,215 120,000,000 110,000,000 113,993,482 111,885,992 109,797,97 122,863,652 117,707,976 112,713,807 124,059,194 116,268,740 120,002,821 123,857,023 100,000,000 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Compiled by ABEAR. 56
ABEAR - Associação Brasileira das Empresas Aéreas FORECASTS OF VARIATION IN ANNUAL RATES OF DEMAND VARIATION IN DOMESTIC AND INTERNATIONAL FLIGHTS (BOARDED PASSENGERS %) 9.0% 8.0% 7.8% 7.7% 7.6% 7.6% 7.6% 7.0% 6.0% 5.0% 5.2% 5.4% 5.4% 5.4% 5.4% 4.0% 4.0% 3.2% 3.2% 3.2% 3.2% 3.0% 2.7% 2.0% 2.1% 1.0% 0.0% 0.2% 2017 2018 2019 2020 2021 2022 Optimistic scenario Most likely scenario Pessimistic scenario Source: Compiled by ABEAR. 57
OVERVIEW 2016 Airports Serviced T he number of cities served by regular flights has fallen year by year, from 127 in 2011 to 106 in 2016. The adverse economic scenario in Brazil since 2014 has had a negative impact on demand, making regular flights to small markets unsustainable. This situation is worsened by a near constant raise in operating costs in the sector. Among these costs two are particularly troublesome, exchange rates and the price of jet fuel (Jet A1) in domestic flights. Jet A1 in Brazil is approximately 40% more expensive than the average international price. There are several reasons for this. In the first place, the pricing system is based on the assumption that all of the fuel is imported when, in fact, 80% 1 of it is produced in Brazil. In second place, there is the Petrobrás 2 monopoly on the exploration and refining of petroleum and distribution of fuel in the country. Finally, the ICMS tax (Value Added Tax - VAT in Brazil on the jet fuel used in domestic flight operations has no parallel anywhere in the world. The charts below illustrate the drop in the number of airports with regular commercial aviation service in Brazil and its relation to the evolution of operational costs in the sector. Between 2010 and 2016, the total cost per hour off light increased 38% NUMBER OF AIRPORTS SERVED BY SCHEDULED DOMESTIC AIR CARRIERS MONTHLY TOTALS 135 130 125 120 115 110 105 100 Jan/10 Mai/10 Ago/10 Dez/10 Abr/11 Ago/11 Dez/11 Abr/12 Ago/12 Dez/12 Abr/13 Ago/13 Dez/13 Abr/14 Ago/14 Dez/14 Abr/15 Ago/15 Dez/15 Abr/16 Ago/16 Dez/16 Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos de Transporte Aéreo, available at: www.anac.gov.br/dados-e-estatísticas/dados-estatisticos/dados-estatisticos. 19 airports lost regular flight service in the same period NUMBER OF AIRPORTS SERVICED BY REGULAR DOMESTIC AVIATION AND TOTAL COSTS PER HOUR OF FLIGHT 140 120 100 139 138 138 127 131 125 123 122 117 109 100 109 110 106 2010 2011 2012 2013 2014 2015 2016 Number of airports served (annual average) Total costs per hour of flight (2010 = 100) Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos de Transporte Aéreo, available at: www.anac.gov.br/dados-e-estatísticas/dados-estatisticos/dados-estatisticos. 1 Agência Nacional de Petróleo, Gás Natural e Biocombustíveis, Anuário Estatístico Brasileiro de Petróleo, Gás Natural e Biocombustíveis 2016, available at: www.anp.gov.br/wwwanp/images/publicações/anuário_estatístico_anp_2016.pdf 58
ABEAR - Associação Brasileira das Empresas Aéreas Domestic flight connectivity of airports and GDP of corresponding mesoregions Domestic connectivity is the level at which an airport is connected to domestic flights and a network of airports, measured by the following formula: CONNECTIVITY = {E} TAKEOFF FREQUENCY X NUMBER OF SEATS OFFERED PER TAKEOFF X WEIGHT OF DESTINATION AIRPORT. IN WHICH WEIGHT OF DESTINATION AIRPORT = TOTAL NUMBER OF PASSENGERS BOARDED ANNUALLY AT THIS AIRPORT CONNECTIVETY INDEX = (CONNECTIVITY OF AN AIRPORT IN NETWORK / HIGHEST CONNECTIVITY VALUE IN THE NETWORK) x 100 All airports in the Agência Nacional de Aviação Civil (ANAC) data base that operated at least one commercial flight in 2016 were included in these calculations. In these charts, the connectivity of Brazilian airports was associated to the mesoregions defined by the Instituto Brasileiro de Geografia e Estatística (IBGE). Data dispersion in relation to the trend line were satisfactory for this type of study and correspond to a determination coefficient of 61%. In principal, airports with coordinates situated below the trend line present opportunities for an increase in connectivity. CONNECTIVITY INDEX VERSUS GDP OF CORRESPONDING MESOREGIONS ALL MESOREGIONS (R$ BILLIONS 2014) 90 80 (CONIND) = 0.00013 X (MRGDP)ˆ2 + 0.0707 X (MRGDP) 70 60 50 40 30 20 10 50 100 150 200 250 Index of connectivity versus GDP Interpolar line Observation: Except SBGR, SBSP, SBGI, SBRJ Sources: Agência Nacional de Aviação Civil (ANAC), Estatística Básica de Transporte Aéreo, available at: www.anac.gov. br/assuntos/setor-regulado/empresas/envio-de-informações /base-de-dados-estatisticos-do-transporte-aero; Instituto Brasileiro de Geografia e Estatística (IBGE), Produto Interno Bruto de Municípios 2010-2014, available at: www.ibge.gov.br/home/estística/economia/pibmunicípios/2014/dfault.sbtm. Compiled by ABEAR. 59
OVERVIEW 2016 In the following chart airports in mesoregions with GDP equal to or below R$30 billion (in 2014) were singled out. This reveals there is a not insignificant number of airports that could accommodate an increase in connectivity if they had been served with aircraft adequate to the size of these markets. CONNECTIVITY INDEX VERSUS GDP OF CORRESPONDING MESOREGIONS WITH GDP BELOW R$ 30 BILLIONS IN 2014 6 5 4 3 2 SBQV SNBR SBJA 1 SBAU SBHT SBML SBKG SBRD SBDO SWBC SBTT SBBW SBSM SBCR SBUF SBLJ SBDBSBUG SBJI SBTG SBCM SBIP SBGV SBPK SNJD SBTC SSKW SBLE SBTF SBCZ SBTL 5 10 15 20 25 30 SBUA SWLB SBPB SBIH SBTB SWGN SBVH SNDV SSZW SBGP SNVB Sources: Agência Nacional de Aviação Civil (ANAC), Estatística Básica de Transporte Aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações /base-de-dados-estatisticos-do-transporte-aero; Instituto Brasileiro de Geografia e Estatística (IBGE), Produto Interno Bruto de Municípios 2010-2014, available at: www.ibge.gov.br/home/estística/economia/pibmunicípios/2014/dfault.sbtm. Compiled by ABEAR. The following table presents the domestic connectivity indexes of the top 50 airports in Brazil. DOMESTIC CONNECTIVITY INDEX OF MAIN BRAZILIAN AIRPORTS Airport ICAO code Connectivity Index GDP Mesoregion 2014 (in current R$ million) RIO DE JANEIRO - SANTOS DUMONT SBRJ 100.0 461 SÃO PAULO - CONGONHAS SBSP 96.7 1,072 BRASÍLIA SBBR 85.1 197 SÃO PAULO - GUARULHOS SBGR 79.9 1,072 BELO HORIZONTE - CONFINS SBCF 69.9 228 RIO DE JANEIRO - GALEÃO SBGL 69.3 461 PORTO ALEGRE SBPA 67.0 169 CURITIBA SBCT 61.7 147 SALVADOR SBSV 59.5 105 RECIFE SBRF 48.7 97 FORTALEZA SBFZ 40.8 78 FLORIANÓPOLIS SBFL 35.7 37 CAMPINAS SBKP 30.4 186 60
ABEAR - Associação Brasileira das Empresas Aéreas Airport ICAO code Connectivity Index GDP Mesoregion 2014 (in current R$ million) GOIÂNIA SBGO 30.3 89 VITÓRIA SBVT 29.1 74 CUIABÁ SBCY 20.9 30 NATAL SBSG 20.3 31 MACEIÓ SBMO 18.7 32 BELÉM SBBE 17.9 45 FOZ DO IGUAÇU SBFI 17.1 41 MANAUS SBEG 16.9 81 NAVEGANTES SBNF 15.7 75 CAMPO GRANDE SBCG 15.4 6 JOÃO PESSOA SBJP 13.8 28 PORTO SEGURO SBPS 13.4 29 ARACAJU SBAR 11.8 29 SÃO LUÍS SBSL 11.8 37 UBERLÂNDIA SBUL 11.0 78 RIBEIRÃO PRETO SBRP 10.5 79 LONDRINA SBLO 10.2 62 TERESINA SBTE 9.5 22 MARINGÁ SBMG 6.8 62 JOINVILLE SBJV 6.6 52 SÃO JOSÉ DO RIO PRETO SBSR 6.4 46 PALMAS SBPJ 5.3 12 PORTO VELHO SBPV 5.1 15 ILHÉUS SBIL 5.0 29 JUAZEIRO DO NORTE SBJU 4.6 10 PETROLINA SBPL 2.8 8 PRESIDENTE PRUDENTE SBDN 2.7 22 MACAPÁ SBMQ 2.5 13 MONTES CLAROS SBMK 2.4 21 MARABÁ SBMA 2.4 43 IMPERATRIZ SBIZ 2.3 16 CHAPECÓ SBCH 2.3 40 RIO BRANCO SBRB 2.2 11 CAXIAS DO SUL SBCX 2.1 47 VITÓRIA DA CONQUISTA SBQV 1.9 24 BOA VISTA SBBV 1.7 8 CALDAS NOVAS SBCN 1.7 49 Sources: Agência Nacional de Aviação Civil (ANAC), Estatística Básica de Transporte Aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações /base-de-dados-estatisticos-do-transporte-aero; Instituto Brasileiro de Geografia e Estatística (IBGE), Produto Interno Bruto de Municípios 2010-2014, available at: www.ibge.gov.br/home/estística/economia/pibmunicípios/2014/dfault.sbtm. Compiled by ABEAR. 61
OVERVIEW 2016 The penetration of domestic passenger air transportation In 2015 Brazil was the third largest domestic market in terms of number of air transported passengers (96 million), behind only the United States (696 million) and China (394 million) and slightly ahead of Japan (95 million). However, the market penetration (ratio between passengers transported annually on domestic flights and the country s population) remained well below ideal: a mere 0.47 passenger transported per inhabitant. This number is only slightly higher than the average of the 20 largest domestic markets, of 0.42. The Brazilian GDP per capita, lower than the average of the countries in the comparison sample (US 8.7 thousand versus US 12.9 thousand) is a factor that limits the aviation sector performance. A balanced comparison should take into account the market penetration in each country in relation to the respective GDP, as is illustrated in the chart on the following page. Evidently, other variables likewise contribute to the greater or lesser market penetration in each country, such as size of territory, level of competition from other modes of transportation and disposable income. Anyway, the interpolation line used has a determination coefficient [R 2 ] of above 75%, which means that all other variables, aside from GDP per capita, represent less than 25 % of the total variations. As it may seen, the market penetration of domestic air transportation is greater than the GDP per capita of Brazil would lead one to expect, which demonstrates a commercial efficiency above the average of the other countries studied. GDP explains more than 75% of the market penetration of the air transportation 62 By 2022 the market penetration in Brazil is expected to reach 0.55
ABEAR - Associação Brasileira das Empresas Aéreas DOMESTIC PASSENGER ENPLANEMENTS AND GDP PER CAPITA (2015 US$) 2.50 Austrália 2.00 Estados Unidos 1.50 1.00 0.50 Malásia Turquia Colômbia Brasil Rússia Indonésia Filipinas China México Índia Mediana mundial Espanha Itália Coreia do Sul Japão y = 1E - 09x 2-3E - 05x + 0.5339 R² = 0.7537 10,000 20,000 30,000 40,000 50,000 60,000 França Canadá Alemanha Reino Unido Sources: International Civil Aviation Organization (ICAO), www.icao.int; Directorate of Civil Aviation (India), dgca.nic.in; Civil Aeronautical Board (Philipines); Airline Network News and Analysis, www.anna.aero; China Civil Aviation Authority, www.caac.gov.en; Aeronáutica Civil (Colombia), www.aerocivil.gov.co; Ministry of Transport, Telecommunication and Maritime Affairs, www.udhh.gov.tr; Dirección General de Aeronáutica (Mexico), www.set.gob.mx; Directorate General of Civil Aviation (Indonesia), hubad.depluh.go.id; Agência Nacional de Aviação Civil (Brazi), www.anac.gov.br; Korean Statistical Information Service (South korea), kosis.kr; Eurostat, cc.europa.eu; Ministry of Land, Infrastructure and Transport, Civil Aviation Bureau (Japan), www.milt.go.jp; Civil Aviation Board (United kingdom, www.caa.co.uk; Statistics Canada, www5.statcan.ge.ca; US Department of Transportation (USA), www.transtats.bts.gov; Bureau of Infrastructure, Transport and Regional Economic (Australia),bitre.gov.au; Federal Air Transport Agency (Russia), www.favtru; International Monetary Fund, www.imf.org. In spite of the recent economic retraction, the perspectives for the evolution of domestic air transport of passengers market penetration in Brazil are highly favorable, as the follow chart shows. It is worth noting that, in this case, The trend line presents a goodness-of-fit statistic coefficient superior to 94% [R2], demonstrating the reliability of these forecasts. EVOLUTION OF MARKET PENETRATION DOMESTIC AIR PASSENGER CARRIED IN BRAZIL (PASSENGERS PER CAPITA) 0.70 FORECAST 0.60 0.50 0.40 0.30 0.20 0.10-1970 1972 1974 1976 1978 Actual and market penetration estimates Trend line 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 0.55 0.52 0.50 0.48 0.46 0.44 2014 2016 2018 2020 2022 Trend line Y= 0.0003x 2 0.0064x + 0.0858 R 2 = 0.94379 Source: Agência Nacional de Aviação Civil (ANAC). Anuário de Transporte Aéreo, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/anuário-do-transporte-aereo. Compiled by ABEAR. 63
OVERVIEW 2016 Origin-destination traffic of domestic passengers In spite of its significant dimensions and positive expectations for domestic air travel in Brazil, passenger flow is highly concentrated in a few airports and markets (pairs of airports). The 15 main domestic airports in number of passengers boarded (Guarulhos, Congonhas, Brasília, Galeão, Santos Dumont, Confins, Campinas, Salvador, Porto Alegre, Recife, Curitiba, Fortaleza, Florianópolis, Belém e Vitória) concentrate approximately 80% of the domestic passengers transported in the country. A total of 106 Brazilian airports registered schedule flights in 2016. ORIGIN-DESTINATION PASSENGER TRAFFIC IN LINE (ODL) 2016 SBGR SBSP SBBR SBGL SBCF SBRJ SBKP SBSV SBPA SÃO PAULO - GUARULHOS SBGR - 0 521 653 585 370 0 919 903 SÃO PAULO - CONGONHAS SBSP 1-1,041 478 866 1,957 0 353 868 BRASÍLIA SBBR 544 1,037-342 419 564 303 405 222 RIO DE JANEIRO - GALEÃO SBGL 655 473 352-200 0 215 571 442 BELO HORIZONTE - CONFINS SBCF 580 872 410 208-414 306 219 38 RIO DE JANEIRO - SANTOS DUMONT SBRJ 379 1,949 553 0 420-329 10 168 CAMPINAS SBKP 0 0 300 216 299 336-157 261 SALVADOR SBSV 937 341 406 570 231 12 161-3 PORTO ALEGRE SBPA 908 859 228 433 41 183 255 4 - RECIFE SBRF 880 185 350 397 133 0 124 260 9 CURITIBA SBCT 752 719 248 270 45 154 229 3 292 FORTALEZA SBFZ 742 74 372 415 34 0 55 171 9 FLORIANÓPOLIS SBFL 513 405 136 187 1 17 119 0 135 BELÉM SBBE 237 32 261 126 69 0 13 2 0 VITÓRIA SBVT 313 268 108 222 186 265 93 47 1 GOIÂNIA SBGO 347 374 235 27 97 49 134 2 3 CUIABÁ SBCY 285 141 304 24 29 7 154 0 5 MANAUS SBEG 278 0 249 102 12 1 57 1 0 NATAL SBSG 344 35 237 227 25 0 50 24 1 MACEIÓ SBMO 361 44 213 124 25 0 67 71 4 OTHERS 2,284 2,224 1,951 789 793 105 1,544 358 158 TOTAL 11,339 10,034 8,475 5,809 4,510 4,435 4,209 3,579 3,522 64
ABEAR - Associação Brasileira das Empresas Aéreas Besides, 60% percent of domestic traffic is concentrated in 105 airport pairs out of a total of 8.001 different airport connections in the country. The strong concentration of domestic passengers between the major poles greatly limits the development of interregional commercial aviation. 15 airports concentrate 80% of the domestic passengers transported in Brazil SBRF SBCT SBFZ SBFL SBBE SBVT SBGO SBCY SBEG SBSG SBMO OTHERS TOTAL 872 738 738 501 231 300 357 275 269 350 364 2,277 11,225 187 728 77 414 32 264 376 136 0 36 46 2,215 10,075 339 237 389 142 258 107 211 301 257 236 205 1,928 8,448 438 265 380 186 121 225 28 22 98 219 128 782 5,800 133 47 35 1 66 179 94 37 11 26 25 804 4,504 0 151 0 18 0 267 52 6 0 0 0 106 4,408 125 231 55 119 14 91 138 154 57 49 68 1,527 4,196 257 3 176 0 3 46 1 0 1 23 69 356 3,596 9 294 8 137 0 2 3 6 0 1 4 160 3,535-6 312 0 28 3 9 1 2 65 49 408 3,221 4-0 0 0 0 2 25 0 0 0 347 3,091 287 0-0 116 0 0 1 62 64 1 267 2,673 0 0 0-0 0 0 0 0 0 0 87 1,600 30 0 119 0-0 0 0 128 1 0 498 1,517 4 0 1 0 0-0 0 0 0 0 1 1,510 11 2 1 0 0 1-50 0 2 2 93 1,430 1 23 2 0 0 0 56-5 0 0 355 1,390 1 0 62 0 126 0 0 1-0 0 340 1,231 66 0 63 0 1 0 2 0 0-1 15 1,091 47 0 1 0 0 0 2 0 0 1-13 971 398 349 260 84 502 1 92 368 333 15 14 541 13,167 3,209 3,076 2,677 1,601 1,500 1,487 1,425 1,385 1,222 1,089 975 13,122 88,678 Source: Agência Nacional de Aviação Civil (ANAC), Estatística Básica de Transporte Aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações /base-de-dados-estatisticos-do-transporte-aero. Compiled by ABEAR. 65
OVERVIEW 2016 The market of air cargo transportation in Brazil 66
ABEAR - Associação Brasileira das Empresas Aéreas OVERVIEW Air freight transportation in 2016 The market of air cargo transportation has many specificities. It suffers stiff competition from other modes of transport, but is, on the other hand, the preferred means of transportation for certain types of goods, such as those of high value and perishables. It is influenced by the performance of the economy in general, but it reacts differently to negative variable. In Brazil, the cargo flows are highly concentrated in a few airports due to the concentration of industrial activity and connecting hubs in the country. 12% 0.1% of freight in all modes of transportation Manufacturing concentration is the primary obstacle 80% 20% of traffic is concentrated in nine airports of weight shipped in all modes of transportation Performance in accordance with the size of the economy of traffic is concentrated all the São Paulo-Guarulhos-Manaus axis PERSPECTIVES Continue to formulate plans for alternate scenarios, while paying attention to the different factors that influence the dynamics of this sector. Take advantage of renewed optimism to promote connectivity of Brazilian airports. Defend tax cuts and a reformulation of the pricing of aviation fuel, which is the biggest obstacle to making aviation transportation more competitive. 67
OVERVIEW 2016 Evolution and demand predictions for air cargo transport in Brazil The behavior of demand for air cargo is closely related GDP, as in the case for air passenger travel. Although the data for air cargo correlates less directly to statistically models. There are a number of reasons for this. In the first place, there is less competition in air freight than in passenger travel. Thus, relative price variations among modals might not be captured by modeling that considers GDP as an explanatory variable of demand. In the second place, air freight statistics tend to be less accurate than air passenger statistics. The statistics for air cargo transported by foreign companies before 2000 are not open to the public, moreover. In order to avoid get around these limitations, in this edition of Panorama we have considered statistical models only as far back as 2000, when ANAC started its data base. The demand for air freight on domestic flights in Brazil We chose to identify the weight of cargo shipped as the dependent variable in order to measure demand for this service. The independent variable was GDP. Two dummy variables were created in order to match the statistical model to the data used. The first was introduced to adjust the model to the data for the year 2009, in which a troubled economic scenario had a direct impact on demand. The other dummy attempts to adjust the model s estimates to the real demand from 2016, in order to make better calibrates predictions for the future. The following chart presents real annual demand and estimated air freight in the domestic market. As is apparent, the level of adjustment obtained (measured by the coefficient of R 2 determination) was 0.848, which means that a little less than 85% of the 68 variations in demand are explained by variations in GDP. Although inferior to the number obtained for air passenger travel this can be considered satisfactory for our purposes. Variations in GDP explain nearly 85% of the variations in air freight demand Growth of 173 thousand tons in air freight is predicted for the period between 2017 and 2022
ABEAR - Associação Brasileira das Empresas Aéreas EVOLUTION IN DEMAND FOR DOMESTIC AIR FREIGHT IN BRAZIL (1000S OF TONS) 600 500 400 300 200 100 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 Estimated Real Trend Line Source: Agência Nacional de Aviação Civil (ANAC). Anuário de Transporte Aéreo, available at: www.anac.gov.br/assuntos/dados-e-estatisticas/anuário-do-transporte-aereo. Compiled by ABEAR. 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Regression In (ton 000)= -16.3265 + 1.4463 In (GDP bil) 0.3638 Dummy R 2 = 0.8081 y = 23.714x 0.7484 R 2 = 0.92107 The elasticity of domestic demand for air freight in relation GDP is 0,815, which means that demand increases 0.815 percent for every percent increase in GDP demand. Projections for demand in domestic air freight elaborated in the following charts were made by applying the GDP predictions in the table below to the statistical model, the same procedure used for air passenger transportation. DEMAND PREDICTIONS FOR DOMESTIC AIR FREIGHT IN BRAZIL (TON 000) 750 700 650 600 582 615 583 649 605 685 628 724 652 FORECASTS FOR ANNUAL VARIATIONS IN GDP IN BRAZIL 550 500 551 562 542 514 522 532 543 554 565 Year Median Optimistic Pessimistic 2017 0.7% 1.7% -0.3% 2018 2.3% 3.7% 1.0% 2019 2.4% 3.6% 1.3% 2020 2.4% 3.6% 1.3% 2021 2.4% 3.6% 1.3% 450 400 2017 2018 2019 2020 2021 2022 Source: Banco Central do Brasil, Sistema Expectativas de Mercado, available at: www3.bcb.gov.br/expectativas/public/ consulta/serieestatisticas (accessed 09 December 2016). Optimistic prediction Pessimistic prediction Most likely prediction Source: Elaborated by ABEAR. 69
OVERVIEW 2016 FORECASTS OF ANNUAL VARIATIONS IN AIR FREIGHT DEMAND IN BRAZIL (TON %) 4 3 3.0% 2.9% 2.9% 2.9% 2.9% 2 1.9% 2.0% 2.0% 2.0% 2.0% 1 0 1.4% 0.6% 1.0% 1.0% 1.0% 1.0% 0.8% 2017 2018 2019 2020 2021 2022-1 -2-3 -2.2% Optimistic scenario Pessimistic scenario Most likely scenario Source: Elaborated by ABEAR. Demand for air cargo transportation on international flights in Brazil As is the case with the statistical treatment of domestic air freight demand, international demand has GDP as an independent variable and two dummy variables with the same purposes. But in this case, the dummy variable number 1 was applied to the years 2008 and 2009, when the international crisis was at its worst. The results obtained, which are presented in the following chart, show a better fit between the data and the model than in the former case. The coefficient value obtained is 0.916, or in other words, the statistical model is capable of explaining 92% of international air freight demand. 70 The transportation of international air freight demand was most sensitive to the effects of the international economic crisis of 2008 and 2009, While domestic airfreight mas most greatly affected by the domestic crisis of 2015 and 2016. International air freight transported in Brazil is expected to expand by 191,000 tons between 2017 and 2022
ABEAR - Associação Brasileira das Empresas Aéreas EVOLUTION OF DEMAND FOR INTERNATIONAL AIR CARGO IN BRAZIL (TON 000) 900 800 700 600 500 400 300 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Estimate Real Trend Regression In (ton 000) = -6.8596 + 1.3080 In(GDP bil) 0.2281 Dummy1 + 0.0156 Dummy2 R 2 = 0.9159 Y = 22.403x + 411.98 R 2 = 0.79487 Sources: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos do Transporte Aéreo, available at: www.anaca.gov.br/assuntos/setor-regulado/empresas-envio-de-informaçoes-do-transporte-aereo; Instituto de Pesquisa Econômica Aplicada (IPEA), available at: www.ipeadata.gov.br. Compiled by ABEAR. The projections for the future behavior of demand for international air freight are elaborated by way of the combination of GDP estimates from the previous chart with the expression of a statistical regression function. The following chart shows the results of this part of the study. FORECASTS OF DEMAND IN INTERNATIONAL AIR FREIGHT IN BRAZIL (TON 000) 950 900 850 800 768 804 842 793 882 819 923 845 750 700 732 723 691 745 700 769 711 723 736 748 650 600 2017 2018 2019 2020 2021 2022 Optimistic prediction Pessimistic prediction Most likely prediction Source: Elaborated by ABEAR 71
OVERVIEW 2016 FORECASTS OF VARIATION IN ANNUAL DEMAND RATES FOR INTERNATIONAL AIR CARGO (TON %) 6% 5% 4.8% 4.7% 4.7% 4.7% 4.7% 4% 3% 3.1% 3.2% 3.2% 3.2% 3.2% 2% 2.2% 1% 0.9% 1.3% 1.6% 1.7% 1.7% 1.7% 0% -1% -2% -3% -4% - 3.6% 2017 2018 2019 2020 2021 2022 Optimistic scenario Pessimistic scenario Most likely scenario Source: Elaborated by ABEAR Sum totals of demand for domestic and international air freight The sum total of demand estimates for domestic and international air freights results in the prediction for total air freight demand, as shown by the following charts: FORECASTS OF INTERNATIONA AND DOMESTIC AIR FREIGHT DEMAND IN BRAZIL (TON 000) 1,400 1,300 1,252 1,304 Optimistic prediction 1,200 1,100 1,000 1,062 1,050 1,009 1,153 1,107 1,108 1,078 1,020 1,035 1,201 1,140 1,050 1,172 1,066 1,205 1,082 Pessimistic prediction Most likely prediction 900 Source: Elaborated by ABEAR. 800 2017 2018 2019 2020 2021 2022 72
ABEAR - Associação Brasileira das Empresas Aéreas FORECASTS OF ANNUAL RATES OF VARIATION IN DOMESTIC AND INTERNATIONAL AIR FREIGHT DEMAND IN BRAZIL (TON %) 5 4 4.2% 4.2% 4.2% 4.2% 4.2% 3 2 2.0% 2.7% 2.8% 2.8% 2.8% 2.8% 1 1.1% 1.5% 1.5% 1.5% 1.5% 0 0.8% -1-2 -3-4 -3.1% 2017 2018 2019 2020 2021 2022 Optimistic scenario Pessimistic scenario Most likely scenario Source: Elaborated by ABEAR. 73
OVERVIEW 2016 Penetration of air transportation in the domestic freight markets of different countries T he following chart shows that, although it is not a statistically high value, there is positive correlation between GDP and the volume of freight transported on domestic flights. The interpolation curve constructed between different points shows that the penetration of this service in the Brazilian market is close to what one would expect. FREIGHT SHIPPED ON DOMESTIC FLIGHTS (TON) VERSUS GDP (US$ PPP) IN 2015 1,100,000 Line Fits Y = -0.0035x 2 + 90.231x + 98623 R 2 = 0.19923 Japan 900,000 700,000 Indonesia 500,000 Turkey India 300,000 Philipines Canada South Korea Brazil Russia 100,000 Malaysia Colombia Australia Spain Mexico Italy France United Kingdom Germany 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Sources: Directorate of Civil Aviation (India) dgea.nic.in; Civil.Aeronautical Board (Philipines), www.cab.gov.ph; Airline Network News and Analysis, www.auna. Aero; China Civil Aviation Authority, www. Caac.gov.cn; Aeronáutica Civil (Colômbia), www.aerocivil.gov.co; Ministry of Transport, Telecommunications and Maritime Affairs (Turkey), www.udhb.gov.tr; Dirección General de Aeronautica Civil (México), www.set.gov.mx; Directorate General of Civil Aviation (Indonésia), hubud.dephub.go.id; National Civil Aviation Agency (ANAC) (Brazil), www.anac.gov.br; Korean Statistical Information Service (South Korea),kosis.kr; Eurostal, ec.europa.eu; Ministry of Land, Infrastructure and Transport, Civil Aviation Bureau (Japan), www.mlit.go.jp; Civil Aviation Board (United Kingdom), www.caa.co.uk; Statistics Canada, www5.statcan.ge.ca; US Department of Transportation (United States), www.transstats.hts.gov; Bureau of Infrastructure, Transport and Regional Economics (Australia), bitre.gov.au; Federal Air Transport Agency (Russia), www.favt.ru; International Civil Aviation Organization (ICAO), ICAO Data Plus: International Monetary Fund (IMF), www.imf.org. Observation: The United States and China were not included due to the far superior level of air freight shipped in comparison with other countries. 74
ABEAR - Associação Brasileira das Empresas Aéreas Domestic freight origin and destination traffic The geographic concentration of domestic air freight is higher than that of air passengers. The nine principal airports in the country (7% of a total of 127) concentrate 80% of the weight shipped. They are (in order of volume shipped): Guarulhos, Manaus, Brasília, Congonhas, Fortaleza, Galeão, Recife, Campinas and Porto Alegre. On the other hand, of the 8,001 pairs of airports in Brazil, 36 or less than a mere 0.5% -- were responsible for half of the domestic freight traffic. 9 airports shipped 80% of the air cargo by weight in Brazil The aviation sector carries 0.1% of weight of Brazilian commerce but 12% of the value In spite of the expressive participation of Brasília in the shipping and receiving of air freight, local industrial production is modest. In truth, this airport is an import hub for domestic flights and the movement of freight is explained by the transfer of cargo between airships. It is interesting to point out, moreover, that the Guarulhos-Manaus axis is responsible for approximately 20% of the domestic freight shipped by air. The elevated regional concentration of industrial production in Brazil means than air freight is shipped in only a few airports because the highest demand for this type of service is for valuable products. In 2015, the participation of the aviation sector in commerce accounts (the sum total of imports and exports) reached 12 % of economic value and 0.1% of total weight. The following chart shows the flow of domestic air freight in the country in 2016 as measured in tons. 75
OVERVIEW 2016 ORIGIN-DESTINATION OF AIR FREIGHT TRAFFIC IN LINE (ODL) 2016 (TON) SBGR SBEG SBBR SBSP SBFZ SBGL SBRF SBKP SBPA SÃO PAULO - GUARULHOS SBGR - 32,817 3,612 0 5,665 2,048 7,622 522 4,038 MANAUS SBEG 32,398-3,114 0 140 1,027 4 1,389 0 BRASÍLIA SBBR 1,517 3,300-2,514 1,200 848 1,587 493 626 SÃO PAULO - CONGONHAS SBSP 6 0 6,115-424 958 938 1 2,913 FORTALEZA SBFZ 6,060 1,911 2,264 353-2,570 1,030 126 0 RIO DE JANEIRO - GALEÃO SBGL 2,030 859 1,417 995 1,541-2,335 308 1,249 RECIFE SBRF 6,572 415 1,706 741 1,589 1,775-624 11 CAMPINAS SBKP 65 630 787 19 264 476 1,558-686 PORTO ALEGRE SBPA 4,950 0 643 1,616 51 955 69 693 - BELÉM SBBE 891 2,965 462 32 468 115 32 2 0 VITÓRIA SBVT 1,997 0 1,252 2,291 1 1,320 3 353 1 BELO HORIZONTE - CONFINS SBCF 887 48 1,003 1,358 55 439 649 628 43 CURITIBA SBCT 1,913 0 1,578 1,620 0 460 7 423 404 SALVADOR SBSV 3,096 0 477 772 425 533 604 112 3 NATAL SBSG 2,227 0 768 9 353 415 71 140 0 GOIÂNIA SBGO 429 0 885 1,067 0 16 0 238 0 RIO DE JANEIRO - SANTOS DUMONT SBRJ 132 0 702 694 0 0 0 124 66 FLORIANÓPOLIS SBFL 742 0 188 818 0 172 0 107 35 CUIABÁ SBCY 453 0 315 165 0 7 0 227 1 NAVEGANTES SBNF 156 0 35 677 0 57 0 350 24 OTHERS 2,732 477 2,886 2,772 222 322 252 1,175 30 TOTAL 69,254 43,422 30,210 18,511 12,399 14,511 16,763 8,032 10,129 76
ABEAR - Associação Brasileira das Empresas Aéreas SBBE SBVT SBCF SBCT SBSV SBSG SBGO SBRJ SBFL SBCY SBNF OTHERS TOTAL 3,411 1,263 1,550 1,048 7,073 1,829 1,028 176 671 1,544 77 8,504 84,498 860 0 78 0 0 0 0 0 0 0 0 1,085 40,096 2,099 260 766 492 1,190 588 624 764 194 1,220 5 10,792 31,080 130 1,357 2,452 1,358 1,403 100 1,811 1,304 947 1,020 355 5,220 28,811 1,506 0 21 0 1,048 460 0 0 0 1 0 893 18,245 811 549 526 582 1,713 356 72 0 201 52 27 1,827 17,449 89 0 498 1 969 119 1 0 0 0 0 1,324 16,432 3 269 1,174 343 635 82 353 308 208 574 156 1,812 10,403 0 0 212 165 13 0 0 112 24 2 11 30 9,547-0 219 0 0 0 0 0 0 0 0 3,681 8,866 0-473 0 201 0 0 404 0 0 0 0 8,297 366 115-66 983 4 88 165 0 92 0 1,104 8,092 0 0 254-2 0 2 260 1 2 0 344 7,269 0 36 276 2-35 0 1 0 0 0 380 6,752 0 0 19 0 30-0 0 0 0 0 199 4,231 0 0 129 0 1 0-23 0 85 0 96 2,970 0 265 99 51 7 0 13-3 0 3 15 2,174 0 0 1 4 0 0 0 2-0 0 35 2,104 0 0 27 0 0 0 28 0 0-0 765 1,987 0 0 0 1 0 0 0 12 0 0-0 1,311 1,045 0 432 197 297 2 33 9 13 586 0 955 14,436 10,321 4,115 9,205 4,309 15,567 3,574 4,053 3,539 2,261 5,179 634 39,062 325,049 Source: National Civil Aviation (ANAC), Base de Dados Estatísticos do Transporte Aéreo, available at; www.anac.gov.br/assuntos/sector-regulado/empresas/envio-de-informações/base-de-dados-estatisticos-do-transporte-aereo (acessed on 05/15/2017). 77
OVERVIEW 2016 Safety, environment and efficiency 78
ABEAR - Associação Brasileira das Empresas Aéreas OVERVIEW Safety and efficiency numbers A complex and important sector such as aviation is obliged to concern itself not only with its workforce and passengers, but likewise with everything around it. Brazilian aviation has improved its safety procedures and is among the best in the world in this area. A fleet of young airships guarantees low levels of pollution, although there is still a margin for improvement in the time spent on trips a comparison with the United States shows that Brazil can greatly improve the relationship between flight time/fuel spent. More efficiency will benefit all. accidents per million takeoffs in the period 2 from 2007 2016. Em 2007-2009 this number was 3.63. The worldwide average in 2015 was 2.8 accidents per million takeoffs. 0.079 kg of CO 2 emitted per seat-kilometer offered Is a better result than north-american air carriers, which registered 0.087, a difference of 8.9%. 8% is the difference between the real distances flown per hours and those recommend by the manufacturers. This means that it takes more time than necessary to fly from one point to another, generating fuel inefficiencies. PERSPECTIVES Preserve and perfect safety procedures. Increase air carriers responsibilities to reduce inefficiencies during flight. Defend improvements in the air transport infrastructure system, to improve efficiency, reduce fuel consumption and, consequently, pollution emission. 79
OVERVIEW 2016 Flight security O ne of the central objectives of ICAO, the UN agency specialized in civil aviation, is the reduction of the number of aviation accidents. ICAO organizes this subject into regional offices the Regional Aviation Safety Group (RASG). There are six RASGs throughout the world, as shown in the map below. They consolidate the aviation accident statistics in their respective regions. REGIONAL ICAO OFFICIES FOR MATTER OF FLIGHT SAFETY (REGIONAL AVIATION SAFETY GROUP RASG) RASC-PA RASG-MID RASG-EUR RASG-APAC RASG-AFI Source: International Civil Aviation Organization (ICAO), Safety Report 2016, appendix 2. 80
ABEAR - Associação Brasileira das Empresas Aéreas Brazil does well in terms of aviation safety worldwide. The following charts offer a comparison between aviation accidents in Brazil and the world. This also allows for an appreciation of favorable historical evolution in flight safety in the country. AVIATION ACCIDENTS IN SCHEDULED FLIGHTS IN MILLIONS OF TAKEOFFS 2015 8 7 6 5 4 3 2 1 0 Americas 7.3 3 2.6 2.5 2.5 Africa (excludes Middle East) Middle East Europe India, China, Pakistan, Oceania and others 2.8 World Brazil registered, 2.26 aviation acidentes per million take-offs between 2007 and 2015 less than the worldwide average (2.8) and that of the Americas (2.6). Source: International Civil Aviation Organization (ICAO), Safety Report 2016. ANNUAL ACCIDENTS IN SCHEDULED FLIGHTS IN BRAZIL PER MILLION TAKEOFFS SINCE 2007 In 2016 the accumulated rate fell to 2 accidents per million take-offs. 5.00 4.50 4.00 3.50 3.00 2.50 2.00 3.34 3.63 3.24 2.95 2.76 2.48 2.58 2.26 2.00 1.50 1.00 0.50 2008 2009 2010 2011 2012 2013 2014 2015 2016 Source: Centro de Investigação e Prevenção de Acidentes Aeronáuticos (CENIPA), available at: www.cenipa. Era.mil.br/cenipa/Anexos/panorama_2016.pd. 81
OVERVIEW 2016 Fuel consumption and CO 2 emissions Due to the relative youth of the Brazilian fleet, when compared to aviation in developed markets, fuel consumption and pollution emission are proportionately lower than in the United States, in spite of inefficiencies in the national transportation system. The following chart sums up the indicators related to this topic. FUEL CONSUMPTION, CO 2 EMISSIONS AND DOMESTIC PASSENGER FLIGHT INDICATORS 2016 UNITED STATES AVIATION COMPANIES Consumption (millions of liters) ASK (billions) RPK (billions) Use (%) Consumption/ ASK Consumption/ RPK CO 2 Emissions (kg/ask) CO 2 emissions (kg/rpk) 42,273 1,255.3 1,062.1 84.6 0.034 0.040 0.087 0.103 AVIATION COMPANIES ABEAR Consumption (millions of liters) ASK (billions) RPK (billions) Use (%) Consumption/ ASK Consumption/ RPK CO 2 Emissions (kg/ask) CO 2 emissions (kg/rpk) 3,381 110.3 88.4 80.1 0.031 0.038 0.079 0.099 Difference -8.9% -3.9% -8.9% -3.9% Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos do Transporte Aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações /base-de-dados-estatisticos-do-transporte-aero; Air Transport Action Group (ATAG), www.atag.org; Bureau of Transportation Statistics (BTS), Airlines and Airports, available at: www.bts.dot.gov. Compiled by ABEAR. Effective distance per flight hour T he efficiency indicator of effective distance per flight hour corresponds to the quotient between the distance in a straight line between two airports, adjusted by the curvature of the Earth, and the airborne time. Calculation of fuel consumption for each airship and every specific operation, as developed by the manufacturers, are also taken into consideration in this efficiency assessment. The average value of each indicator calculated by the aircraft manufacturers for the completion of an ideal average domestic leg was taken as a reference value. Comparing the actual average values with the reference values one obtains the average deviation for each the corresponding years. When the effective average distancesper flight hour is lower than the reference values, the aircraft are taking more time to complete the flight stages, on average, than what the manufacturers calculated would be necessary for minimum fuel consumption. This situation typical results from air traffic congestion and other infrastructure inefficiencies of air transportation on land or in the air. 82
ABEAR - Associação Brasileira das Empresas Aéreas On the other hand, when the actual distances per flight hours are greater than the reference values, the aircraft are flying faster, on average, than is recommended for minimum fuel consumption. In both cases, more fuel is burned than the necessary minimum, which generates environmental and energy inefficiency. In this analysis, the differences between actual and reference values, calculated in percentage points, are called gaps. The following charts illustrated the results obtained in Brazil and the United States between 2000 and 2016. As can be observed, the inefficiencies have diminished but are still at a high level. A similar calculation out with data from domestic flights in United States revealed much lower values than in Brazil. EFFECTIVE DISTANCE PER HOUR OF FLIGHT, REFERENCE VALUES AND DIFFERENCES (GAP) 700 40% 35% 600 30% 500 25% 400 20% 300 7% 11% 11% 11% 11% 10% 10% 9% 9% 8% 15% 10% 200 0% -1% -1% 100-4% -4% -5% -1% 0% -1% -1% 3% 3% 0% 1% 1% 1% 1% 0% 0% 0% 0% 0% 0% 0% 5% 0% -5% -10% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Effective distance per hour of flight (km/h) in Brasil Real Effective distance per hour of flight (km/h) in Brasil Reference Gap United States Gap Brazil Sources: ICAO, Airbus, Boeing, Embraer, Fokker. Observations: 1. The reference valueof the average effective distance per flight hours corresponds to the weighted average of the economic speeds of the aircraft that compose the Brazilian domestic fleet (as indicated by the aircraft manufacturers manuals), in each year.. 2. Takes into consideration scheduled freight and domestic operation in twin engine jets. There is no evidence, however, that the inefficiencies are seasonal, as might be expected. In spite of the longer effective distance values per hour in high demand months, there is not a large variation in gap. 83
OVERVIEW 2016 MONTHLY EVOLUTION OF EFFECTIVE DISTANCE PER FLIGHT HOUR, REFERENCE AND DIFERENCE VALUES (GAP) 590 50% 580 45% 570 40% 560 35% 30% 550 25% 540 20% 530 520 510 9% 9% 9% 8% 8% 8% 8% 8% 8% 8% 7% 7% 15% 10% 5% Effective distance per flight hour (km/h) in Brazil Reference Effective difference per flight hour in Brazil Actual 500 0% Gap Brazil Jan Fev Mar Abr Mai Jun Jul Ago Set Out Nov Dez Observation: The reference value of the average effective distance per flight hours corresponds to the weighted average of the economic speeds of the aircraft that compose the Brazilian domestic fleet (as indicated by the aircraft manufacturers manuals), in each year. The estimates of lack of efficiency can be classified in accordance with the point where they occur. This was the objective of a study elaborated by ABEAR regarding the all take-offs in 2015, with a total of nearly one million observations. For each take-off the flight time and reference time were calculated and shown in block time and flight time. Operations with a flight time smaller than the reference time were accounted as inefficiencies attributable to the carriers. Those in which the flight time was greater than the reference were considered as problems of the system or air transport infrastructure. The on ground performance was not calculated.was not taken into account. The results of this large scale study are presented in the following chart. The difference between the effective distance of the actual flight and reference value in Brazil dropped 3% in 3 years a significant improvement. TOTAL INEFFICIENCY OF FLIGHTS (MINUTES) 2015 Inflight On ground O / D Block-time Reference (min) Block-time Real (min) Flight time Reference (min) Actual flight time (min) Inefficiency Company Inefficiency System Inefficiency Company + System Inefficiency (Efficiency) Total Geral 113,986 113,561 93,436 97,947-741 5,252 4,511-4,936 Source: Elaborated by ABEAR. 100% 100% 82% 86% -1% 5% 4% -4% As expected, the bottlenecks were predominately attributed to the air transport system, although the quantity of inefficiencies attributable to carriers was not negligible. 84
ABEAR - Associação Brasileira das Empresas Aéreas Load factors of domestic passenger flights in Brazil and the United States Another measure of operational efficiency is a comparison between the seats offered by the airlines and the effective utilization of these seats. A comparison of historical series of domestic flight load-factors in Brazil and in the United States shows that the Brazilian levels closely approximate American levels. In other words, this statistical indicator shows an evolution very favorable to Brazilian carriers, as one may can see in the following chart: Since 2013, the airlines members of ABEAR have maintained a load-factor of 80% EVOLUTION OF THE LOAD-FACTORS OF DOMESTIC FLIGHTS IN BRAZIL AND THE UNITED STATES 90% 85% 80% 84,7% 4.7 percentage point difference 80,0% 75% 71.2% 70% 65% 60% 12.6 percentage point difference 58,6% 55% 50% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Domestic LF Brazil Domestic LF United States Source: Agência Nacional de Aviação Civil (ANAC), Base de Dados Estatísticos do Transporte Aéreo, available at: www.anac.gov.br/assuntos/setor-regulado/empresas/envio-de-informações /base-de-dados-estatisticos-do-transporte-aero; Bureau of Transportation Statistics (BTS), Airlines and Airports, available at: www.bts.dot.gov. Compiled by ABEAR. 85
OVERVIEW 2016 Prices and costs of services provided 86