Final Report P a G E | I Table of Contents

Socio-economic Impact of an Air Transport Liberalisation Agreement in the Southern African Development Community

Graham Muller Associates

30 August 2010

Final Report P a g e | i Table of Contents

Executive Summary ...... v

Introduction ...... v Literature Review ...... v The nine freedoms of the air ...... v The Yamoussoukro Decision ...... vii Assessing and forecasting the impact of air transportation liberalisation agreements ...... x Economic Impact of an air transport liberalisation agreement in SADC ...... xiii Overview of current status of the SADC Aviation Industry ...... xiii Cost-Benefit Analysis Methodology ...... xvi Cost Benefit Analysis Results ...... xvii Impact of an air transport liberalisation agreement in the Southern African Development Community ...... xx Impact of an air transport liberalisation agreement reflecting the investment and capital expenditure in airport and navigational infrastructure ...... xxi Introduction ...... 1

1 Literature Review ...... 2

1.1 Introduction ...... 2 1.2 The nine freedoms of the air ...... 3 1.3 History of aviation agreements ...... 5 1.3.1 Chicago Convention 1944 ...... 5 1.3.2 Formation of state owned or sponsored airlines...... 6 1.3.3 Liberalisation of aviation agreements...... 7 1.4 Assessing and forecasting the impact of air transportation liberalisation agreements ...... 15 1.4.1 The case study approach ...... 15 1.4.2 The trends model ...... 16 1.4.3 The gravity model ...... 16

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | ii 1.4.4 The stimulation model ...... 17 1.4.5 Air transport cost analysis ...... 17 1.5 Case Studies ...... 18 1.5.1 United States – United Kingdom ...... 18 1.5.2 The European Union ...... 20 1.5.3 India – United Kingdom...... 22 1.5.4 Impact of an international air transportation liberalisation agreement ...... 26 1.6 Forecasted effects of air transportation liberalisation agreements ...... 26 1.6.1 Infrastructure, regulatory body, skills and market size limitations ...... 27 1.6.2 Spread of development from hubs to outlying areas ...... 31 1.7 Concluding Comments ...... 32 2 Impact of air transport liberalisation agreement in Southern African development Community ..... 34

2.1 Introduction ...... 34 2.2 Overview of the Current Status of the SADC Aviation Industry ...... 35 2.2.1 Angola ...... 35 2.2.2 Botswana ...... 36 2.2.3 Democratic Republic of the Congo (DRC) ...... 39 2.2.4 Lesotho ...... 40 2.2.5 Madagascar ...... 41 2.2.6 Malawi ...... 43 2.2.7 Mauritius ...... 45 2.2.8 Mozambique ...... 47 2.2.9 Namibia ...... 49 2.2.10 Seychelles ...... 51 2.2.11 South Africa ...... 52 2.2.12 Tanzania ...... 57 2.2.13 Zambia ...... 60 2.2.14 Airports in SADC ...... 63 2.2.15 Fleet size of all SADC airlines ...... 68 2.3 Analysis of Questionnaire Results ...... 70

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | iii 2.3.1 Airlines ...... 70 2.3.2 Airports ...... 74 2.3.3 Other Stakeholders in the aviation industry ...... 76 2.4 Cost-Benefit Analysis Methodology ...... 82 2.4.1 Model ...... 82 2.4.2 Direct Impacts ...... 92 2.4.3 Indirect Impacts ...... 99 2.4.4 Airport and Navigational Infrastructure ...... 102 2.5 Cost-Benefit Analysis Results ...... 107 2.5.1 Direct Impacts ...... 107 2.5.2 Benefit to airlines ...... 107 2.5.3 Benefits to passengers ...... 111 2.5.4 Indirect Impacts ...... 121 2.5.5 Airport and navigational infrastructure ...... 131 2.6 Impact of an air transport liberalisation agreement in the Southern African Development Community (SADC) ...... 137 2.6.1 Total Computable Benefits ...... 137 2.6.2 Total Costs ...... 139 2.6.3 Impact of an air transport liberalisation agreement in the Southern African Development Community ...... 140 2.7 Impact of an air transport liberalisation agreement reflecting the investment and capital expenditure in airport and navigational infrastructure ...... 142 Conclusion ...... 145

References ...... 146

List of References ...... 146 Conversions are based on the following websites...... 146 List of Tables ...... 148

List of Figures ...... 151

List of Boxes ...... 156

Appendix A – Signing States of the Chicago Convention 1944 ...... 157

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | iv Appendix B – United States Air transportation liberalisation Partners and status of the agreement ..... 158

Appendix C – State ownership for international flag carriers...... 161

Appendix D – Spider Diagram ...... 166

Appendix E – Questionnaires ...... 167

Air transportation liberalisation Questionnaire for Southern African Airlines ...... 167 Air transportation liberalisation Questionnaire for Southern African Airlines ...... 187 Air transportation liberalisation Questionnaire for other Southern Africa Aviation Industry Stakeholders ...... 205 Appendix F – Destinations within SADC ...... 212

Appendix G Total impact per airport over the 50 year period less airport/navigational infrastructure costs (R Millions) ...... 233

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | v Executive Summary

Introduction

This report has been compiled in conjunction with the South African Department of Transport. The project measures the economic impact of implementing an air transportation liberalisation agreement within the Southern African Development Community (SADC) region. The report is divided between a review of literature analysing the impact of air transportation liberalisation agreements around the world, and the forecasted impact of implementing the air transportation liberalisation agreement in the SADC region.

Literature Review

Air transportation liberalisation is the liberalisation of aviation regulations between countries or within geographic regions. Air transportation liberalisation agreements have largely been adopted and pursued by developed countries. The United States has actively been involved in negotiating Air transportation liberalisation agreements between various countries since 1972, while the European Union initiated its internal common market or cabotage area by means of air transportation liberalisation between member states in 1988. The Yamoussoukro Decision (YD) is the inter-African version of air transport liberalisation Agreements and this was signed into operation by member states in 1999, however limited progress has been made on this agreement.

The literature review has been structured in such a way that it looks at:

Analysing the various components that can be utilised when entering air transportation liberalisation agreement; The short comings of Yamoussoukro Decision and the requirement for the establishment of a competition body to monitor airline behaviour in Africa (or SADC); The various methods of measuring the impact of air transportation liberalisation agreements; and The impact of air transportation liberalisation as measured by existing reports and studies. The nine freedoms of the air

Table 1.1-1 displays the various freedoms of the air that make up aviation agreements between countries and regions. Air freedoms 1 to 4 make up traditional aviation agreements between countries with very restrictive aviation laws, whereas air freedoms 5 to 9 would represent a relaxing in aviation agreements between countries. Freedoms 5 to 9 have been allowed by certain countries since 1944, but this has largely been the case in a limited number of aviation agreements.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | vi Table 1.1-1 Definition of air freedom rights

nd 1st Freedom 2 Freedom To overfly one country en-route to another To make a technical stop in another country

rd 3 Freedom 4th Freedom To carry freight and passengers from the home country to another To carry freight and passengers to the home country from another country country

3rd Freedom 5th Freedom

th 5 Freedom 6th Freedom To carry freight and passengers between two countries on route (by To carry freight and passengers between two countries by an an airline of a third (home) country) with origin / destination in its airline of a third country on two routes connecting in its home home country country

th 7th Freedom 8 Freedom or Cabotage To carry freight and passengers between two countries by an airline To carry freight and passengers within a country by an airline of of a third country on a route with no connection with its home another country on a route with origin / destination in its home country country

Traditional bilateral More recent air aviation regulations transportation liberalisation regulations

Source: ICAO Manual of Regulation (2004) and WTO Secretariat 9th Freedom or True Domestic To carry freight and passengers within a foreign country with no connection with the home country

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | vii The Yamoussoukro Decision

Over the last three decades the African aviation market has been dominated by national flag carriers that have benefited from government protection and free market economic logic has played little to no role in this industry. Therefore there has been little improvement and innovation in the quality and quantity of air services around the continent. The African tax payer is predominantly the biggest loser as governments subsidise, recapitalise or protect national flag carriers that typically operate under dismal financial conditions.

Table 1.1-2 below shows the international growth in the aviation market over a 17 year period. It can be seen that while the African aviation market has grown, while this is the fastest growing market after Latin America and Caribbean, the African market is still small when compared with the market size of the Worlds other regions.

Table 1.1-2 Total number of domestic and international airline passengers, by region Passengers (millions) 1800

1600 1529

1400 1367

1200 1104.9 1000 980

1989 743 800 741.8 665.5 1999 600 546.2

2006 318.9

400 272

134.5

114

111 83.5

200 79.1

60.9

47.8 40.8

Africa

North

Europe

America

and

AsiaPacific

Middle East Middle Caribbean Latin America America Latin Source: ICAO, 2007

The YD encourages co-operation between African states through aviation. YD advocates the following:

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | viii Removal of capacity restrictions on passenger seats, freight and flights on certain routes; The removal of expensive and complex tariff regulations; The elimination of all protective policies that protect national flag carriers; The termination of regulations on carriers’ alliance; Doing away with restriction on the conversion of revenues to hard currency and repatriation; Agree on code sharing; and Allow carriers to have own-ground-service abroad

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | ix History and failure to implement

The implementation of the YD was expected to be concluded by 2002, with the complete removal of regulations and all the air freedoms being permitted. Capacity constraints would be removed and a monitoring body would be established to enforce and monitor that countries and airlines do not partake in anti-competitive behaviour.

The YD agreement between African states in 1999 was over flowing with optimism and good intention, but has faced a number of obstacles which have brought implementation to a complete standstill. The reasons for this failure were highlighted by the African Union Report (2005):

confusion in the monitoring body of the Yamoussoukro Decision; conditions for eligibility of airlines in the Yamoussoukro Decision are inadequate. These conditions allow any airline which has “its headquarters, central administration and principal place of business physically located in the state concerned” to be eligible to benefit from the advantages set forth in the Yamoussoukro Decision. Such an airline may be totally or in most part controlled by foreign capital or interests. The European Union has put in place very restrictive conditions in terms of eligibility so as to protect the airlines of its community YD makes no mention of economic control of eligible airlines - there should be a provision in YD requiring airlines to avail to audit boards all accounting and financial documents to ascertain their economic status. These audit boards do not exist. competition rules as contained in the Yamoussoukro Decision are inadequate. Competition rules need to be defined further.

YD has remained mostly stagnant since its inception, except in the Western African region.

African Aviation Competition Authority

Instrumental in the success of the YD is the establishment of a competition authority to oversee the implementation of the agreement, while also monitoring that governments, airlines and airports don’t partake in uncompetitive behaviour. This authority must be comprised of the various member states and not favour any member state.

The completion rules have already been stated, but are worth repeating:

Only African owned airlines should benefit from the implementation of YD The granting of 1st to 5th air freedom rights in each member state (as well as cabotage, the 8th air freedom rights); Encourage the development of new routes; Ensure the removal of capacity restrictions on passenger seats, freight and flights on certain routes;

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | x Ensure the removal of expensive and complex tariff regulations; Ensure the elimination of all protective policies that protect national flag carriers; Ensure the termination of regulations on carriers’ alliance; Remove restriction on the conversion of revenues to hard currency and repatriation; Agree on code sharing; Allow carriers to have own-ground-service abroad; Not allow any direct or indirect state or parastatal subsidies; Not allow private financial aid that is not consistent with generally accepted rules and regulations governing private financing; Allow equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages); Ban on airlines who abuse a dominant positions; Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities. Assessing and forecasting the impact of air transportation liberalisation agreements

The literature reviewed displayed various methods of estimating the impact of air transportation liberalisation regulations. The most common methods used to estimate the impacts are: the trends model; the gravity model; air transport costs analysis; and the case study approach.

The trends approach uses statistical regression analysis to predict future growth in the aviation market; this method is only applicable where air transportation liberalisation agreements have been in place over period and data is available.

The gravity model estimates total unconstrained demand between origins and destinations, by taking into account data such as GDP per capita or population levels, while also considering the distance flown. Equation 1 indicates the mathematical equation utilised in calculating the gravity model for each routes flown. This method calculates weights for each specific route, the higher the weight, the higher demand for those flights.

Equation (1) Demand = (GDP Origin * GDP Destination)/Distance

The simulation method uses historical data and shows how demand in flights changes as air fares increase and decrease, while this is possibly the most thorough way of calculating the impact of an air transportation liberalisation agreement it is mostly inapplicable as reliable data is unavailable, limited or compromised.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xi Lastly the case study approach is the most common method of estimating the impact of air transportation liberalisation agreements; this approach looks at the impact experienced in other countries or regions that have already implemented air transportation liberalisation policies and legislation. Unsurprisingly the case study approach is completely qualitative, speculative, and imprecise; it is also the easiest form of measuring air transportation liberalisation impacts.

Case studies

Case studies showing the impact of implemented air transportation liberalisation agreements have been conducted between the United States and the European Union, the European Union, and India and the United Kingdom. All case studies indicating the impact of air transportation liberalisation agreements involve developed countries, or at least one developed country, as well as countries with established and large aviation markets. This is partly due to the developed countries being among the first states to open their skies and liberalise their aviation legislation. The other observation is that all the case studies are enthusiastically positive with regards to air transportation liberalisation agreements; there is no mention of any negative side effects and impacts.

Liberalisation of the E.U. aviation market between 1988 and 1993 has led to an additional 44 million passengers being carried annually, which equals a 33% increase in passenger seats. This traffic expansion has encouraged development of both the tourism sector and other industries. Some 1.4 million full-time jobs resulted from the liberalisation, and European GDP grew by $US 85 billion. Most importantly noted is the dramatic market growth in low cost carrier airlines and the market share decline of national flag carriers.

Between summer 2004 and summer 2006, the number of direct flights between India and the UK rose from 34 to 112 per week. The increase in capacity and more intense competition has resulted in a reduction in air fares, from £882 to £736 for one-way fare paid by passengers travelling for business class and £251 to £231 for one-way fare paid by passengers travelling economy class.

Forecasted effects of air transportation liberalisation agreements

While the case studies were overwhelmingly positive with regards to air transportation liberalisation agreements, there were two studies that raised legitimate concerns as they forecasted and analysed the effects of air transportation liberalisation agreements. These reports were conducted by Micco and Serebrisky (2006) and Swan (2008).

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xii There are two essential issues that these reports raised as they analysed their data’s results:

Firstly, does the country have adequate infrastructure, a regulatory body, available skills and sufficient market size? And secondly, can a country afford to shift aviation activity away from a central hub airport

Answering these questions has particular relevance for Africa and more specifically for the Southern African Development Community.

Micco et al. (2006) discovered while running a regression on all countries and airports that operate under air transportation liberalisation legislation, that airport with insufficient infrastructure, skills and limited market sizes could not benefit fully from the effects of air transportation liberalisation agreements.

Swan (2008) while analysing aviation data in the Far East discovered that air transportation liberalisation agreements over time will move flights away from major hub airports to smaller airports as flights are added to airline routes.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xiii Economic Impact of an air transport liberalisation agreement in SADC

The purpose of the study is to go further than just assessing the international experience of implementing air transportation liberalisation agreements and determine the impact of implementing the air transportation liberalisation agreement in the SADC region. The impact has been measured on two levels, firstly the impacts experienced within the aviation market (direct impacts); and secondly the impacts felt by supporting industries to the aviation market (indirect impacts).

The study identified the following direct and indirect impacts:

Direct impacts: Indirect impacts: On Airlines On Tourism On Airports On Airport services Passengers Aircraft manufacturers Freight Environment Customs Intermodal services

Government Overview of current status of the SADC Aviation Industry

SADC flight departure and passenger data indicates that certain airlines in SADC service mainly domestic routes and service very few international routes, while other airlines are largely reliant on international business. The general trend for most airlines indicates that there has been a gradual increase in the total number of departures over the years; however a decrease in total departures is noted during the 2007 to 2009 periods for smaller airlines, in all likelihood as a result of the downturn in the global economy over this period. Although the September 11 2001 attacks reduced worldwide air travel significantly, most SADC airlines were unaffected. Other major scares such as the SARS virus and Swine flu also had little impact on most SADC based airlines. SADC airlines more commonly encountered periodic problems due to internal issues such as financial losses, inefficiency and safety of aircraft or due to localised external problems such as political instability in countries where the airlines operate. It is noted that national carriers generally split departures between international and domestic while low cost carriers mainly undertake domestic flights.

A country by country analysis reveals that most national airlines struggle financially whilst some are greatly affected by the political situation in the country such as Air Madagascar and Air Zimbabwe. All airlines from the Democratic Republic of Congo (DRC) and Zambezi Airlines have been banned in European airspace as a result of substandard safety management practices. Airlines within the SADC that have shut down over the years due to the inability to cope with operations include Air Lesotho, Air Tanzania and Zambia airways. Airlines with a greater number of international passengers compared to domestic include Air Mauritius and Air Namibia. The most popular airlines within SADC with total passenger numbers greater than 500,000 annually are Air Mauritius, South African Airways (SAA), SA Airlink and Comair.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xiv International airports with greater than 1,000,000 passengers annually include O R Tambo Airport, Cape Town International, Durban International, Dar-es-Salaam Airport, Harare Airport and Sir Seewoosagur Ramgoolam International in Mauritius. O R Tambo Airport recorded over 10 million passengers annually. International airports with less than 1,000,000 passengers annually include Kinshasa N’Djili, Maputo International, Zanzibar airport, Ivato International, Windhoek International and Lusaka International. International airports that recorded the lowest number of passengers with less than 700,000 annually are Gaborone airport, Maun, Majunga, Lilongwe, Kilimanjaro International, Mwanza and Victoria Falls. South Africa has the largest number of airports within SADC of which 7 are domestic airports. Port Elizabeth airport had the largest number of domestic passengers with over 800,000 annually followed by East London and George airports with over 400,000 domestic passengers annually.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xv Analysis of questionnaire results

Of 106 questionnaires sent, only 16 responses from the following were received.

Category Type of Service Offered Company / Organisation Country

Airline Airline Comair Ltd South Africa

Airline Airline Federal Airlines South Africa

Airline Airline Owenair Pty Ltd South Africa

Airline Airline Air Malawi Malawi

Airport Airport ACSA South Africa

Airport Airport NAC Zambia

Other Stakeholders Aircraft leasing and charter AirQuarius Aviation South Africa

Other Stakeholders Aircraft sales, maintenance, National Airways Corporation South Africa leasing, charter and management

Other Stakeholders Aircraft brakes and landing gear Mistral Aviation Services South Africa overhauls

Other Stakeholders Passenger/cargo Phoebus Apollo Aviation South Africa scheduled/charter flights

Other Stakeholders Non-profit private association Airlines Association of South South Africa representing SADC based airlines. Africa AASA

Other Stakeholders Tourism and incentive charters Namibia Commercial Aviation Namibia

Other Stakeholders Passenger, freight and mail Precision Air Services Tanzania services

Other Stakeholders Ground handling and cargo Swissport Tanzania Tanzania services

Other Stakeholders Charter operations Proflight commuter services Zambia

An overview of the fleet size of airlines in SADC shows that South African Airways has the largest fleet within 50 aircraft, while other national airlines such as TAAG Angla, Hewa Bora Airways, Air Madagascar, Air Mauritius, Air Seychelles, Air Botswana, LAM, Air Malawi and Air Namibia have smaller fleet varying between 4 and 12 aircraft each. Fleet sizes of airlines operating on domestic routes vary between 1 and 32 aircraft.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xvi Feedback from airlines, airports and other stakeholders was generally positive regarding an air transportation liberalisation agreement, however most respondents stated that implementation was poor. Full implementation has been hindered due to lack of government and SADC member commitment to YD, Corruption, poor or substandard airport infrastructure in many countries and airport security concerns among other factors. In order to successfully implement an air transportation liberalisation agreement, governments will have to play an active role and stakeholders should be afforded the opportunity to participate in the decision making. Major changes to infrastructure, improved aircrafts, up to date avionics and transparent policies are some of the compulsory factors necessary to ensure smooth operation of the air transportation liberalisation agreement.

The following changes in status quo are expected by airlines and airports.

Airlines Airports

Frequency of flights Increase Increase on certain routes

Capacity May increase or remain static Increase

Pricing Decrease Decrease

Volume of freight business Increase Likely to increase

Number of competitors on each route Increase on higher traffic route but will n/a decrease on marginal routes

Market share on each route Reduce n/a

Overall, airlines, airports and other stakeholders are positive about the implementation of air transportation liberalisation agreements but are sceptical about the progress made to date on YD and likely to be made into the future. All the stakeholders involved support the idea behind YD and are willing to open their markets to Africa but are not certain that the current infrastructure, legislation and policies support the rapid implementation of such a decision.

Cost-Benefit Analysis Methodology

The economic impacts have been measured using the principles of the gravity model. However, actual economic data between origins and destinations has been used. More specifically we’ve used GDP per capita, urban population levels per country, city population levels and distance between origins and destinations. Equation 2 and 3 show an example of how the various sources of economic data were used to calculate the estimated demand for each potential route in the SADC region.

Equation (2) GDP demand airport A&B = ((GDP per capita index airport A) + (GDP per capita index airport B))/2 Equation (3) Route demand = (GDP demand airport A&B x A)+(City pop demand airport A&B x B)+(Urban pop demand airport A&B x C)+(Airport infra demand airport A&B x

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xvii D)+(Bus, Pol & Dev demand airport A&B x E)+(Tourism infra demand airport A&B x F) where: A + B + C + D + E + F = 100%

With the estimated demand known for each route and the use of South African aviation data (such as: actual pricing; seats numbers available on flights; quantity of flights and distance between airports) potential seat numbers, turnover, costs to airlines, benefits to passengers, indirect costs and tourism impacts can be estimated for each route. The impacts have been estimated over a 50 year period, and this is determined by staggering the potential routes by initially allowing only the routes with a high estimated demand and then every 5 years allowing routes with lower estimated demand. At the 50 year point all routes would be included in the impact analysis.

Cost Benefit Analysis Results

Total Benefits

Total benefits include the following: potential turnover to airlines; time saved by passengers and the direct impact of the tourism industry on GDP. All of these have been reported in 2009 Rands and exclusively look at the aviation industry in the SADC region. Table 1.3-1 and Figure 1.3-1, display the total benefits experienced over a 50 year period post the implementation of air transportation liberalisation agreement in SADC. It can be seen Table 1.3-1 that the most significant benefit brought by an air transportation liberalisation agreement being implemented in SADC is the direct impact on the tourism industry. Tourism is a very labour intensive industry and we can expect that over the 50 year period that approximately 101 million jobs would be created in this industry alone.

Table 1.1-3 Total Benefits incurred by the implementation of an air transport liberalisation aagreement in SADC BENEFITS Direct Impact Of Tourism Years* Passenger Time Saving Potential Turnover Industry On GDP (2009 TOTAL BENEFITS (Rand per KM) Rands) 5 R 395,592,569.17 R 8,070,414.24 R 7,552,340,410.36 R 7,956,003,393.77 10 R 615,030,014.60 R 14,835,378.82 R 13,205,292,139.30 R 13,835,157,532.72 15 R 631,437,961.30 R 15,242,987.56 R 13,673,144,858.21 R 14,319,825,807.06 20 R 1,055,829,325.19 R 26,510,838.22 R 28,251,360,598.84 R 29,333,700,762.24 25 R 3,194,221,298.65 R 76,673,240.19 R 50,738,372,511.99 R 54,009,267,050.82 30 R 8,886,816,358.07 R 296,141,084.61 R 105,672,816,915.10 R 114,855,774,357.77 35 R 15,354,301,000.26 R 720,722,026.57 R 165,457,639,030.49 R 181,532,662,057.32 40 R 20,306,047,606.09 R 1,242,964,240.75 R 217,448,285,885.45 R 238,997,297,732.29 45 R 21,592,032,312.26 R 1,370,343,414.87 R 228,121,055,753.45 R 251,083,431,480.59 50 R 21,804,364,460.93 R 1,395,717,456.70 R 229,837,249,446.98 R 253,037,331,364.61

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xviii Figure 1.1-1 below graphs the total benefits over the 50 year period. The s-curve graph is to be expected as it indicates that initially benefits are limited as the market adjusts to the new aviation regulations, and once this adjustment is made large benefits start accruing. Finally after 35 years benefits begin to drop off as all major routes are saturated and lower demanded flights are added to flight schedules. It can also be seen on this figure the sheer size of the benefit experience by the tourism industry and the slight benefit experienced by time savings to passengers.

Figure 1.1-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC Total Benefits R 300,000,000,000.00

R 250,000,000,000.00

R 200,000,000,000.00 Direct Impact On GDP (2009 Rands) R 150,000,000,000.00 Time Saving (Rand per KM) R 100,000,000,000.00 Potential Turnover

R 50,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xix

Total Costs

The total costs included: cost of flight cancellation; cost of flight diversions; cost of accident resulting in fatality; cost of minor injury during flight; cost of major injury during flight; cost of pollution; cost of noise pollution; and cost of security. These costs have been shown in Table 1.3-2 and Figure 1.1-2. These results are shown over a 50 year period in 2009 Rands.

Table 1.1-4 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC Years Cost of flight Cost of flight Cost of accident Cost of minor Cost of major Cost of Cost of noise Cost of Security Navigation TOTAL COSTS cancellation diversions resulting in injury during injury during Pollution pollution Route Costs (FL fatality flight flight 145) 5 R 16,598,813 R 315,380 R 81,715 R 1,258 R 17,046 R 8,913,137 R 8,843,296 R 44,638,920 R 20,021,154 R 99,430,719 10 R 30,904,372 R 694,787 R 180,018 R 2,771 R 37,553 R 13,051,508 R 15,498,560 R 77,498,801 R 30,307,051 R 168,175,421 15 R 32,305,925 R 768,933 R 199,230 R 3,066 R 41,561 R 13,398,790 R 16,227,904 R 80,718,169 R 31,258,269 R 174,921,847 20 R 52,098,054 R 1,204,203 R 312,008 R 4,802 R 65,088 R 23,030,384 R 27,259,232 R 132,556,756 R 53,547,308 R 290,077,835 25 R 101,208,861 R 2,207,197 R 571,882 R 8,802 R 119,300 R 75,339,598 R 56,797,664 R 306,044,393 R 162,721,282 R 705,018,979 30 R 223,961,750 R 4,561,179 R 1,181,796 R 18,189 R 246,533 R 225,875,003 R 136,752,000 R 753,253,360 R 473,688,910 R 1,819,538,721 35 R 356,211,205 R 7,081,210 R 1,834,733 R 28,239 R 382,741 R 413,023,162 R 231,019,712 R 1,247,466,816 R 858,029,359 R 3,115,077,177 40 R 465,155,210 R 9,153,407 R 2,371,637 R 36,503 R 494,744 R 570,231,582 R 316,170,624 R 1,656,004,414 R 1,184,967,692 R 4,204,585,812 45 R 491,444,508 R 9,652,908 R 2,501,057 R 38,495 R 521,742 R 615,124,875 R 338,780,288 R 1,754,588,698 R 1,277,056,026 R 4,489,708,596 50 R 497,433,107 R 9,766,692 R 2,530,538 R 38,948 R 527,892 R 624,335,802 R 345,253,216 R 1,777,045,809 R 1,296,504,038 R 4,553,436,042 *post implementation of an air transportation liberalisation agreement in SADC

Once again the S-curve bend can be observed in Figure 1.1-1. It can also be seen that the cost of security is by far the highest cost over the 50 year period. The cancellation costs and diversion costs could increase depending on occurrence disasters like the recent volcanic eruption in Iceland, grounding all the aircrafts and costing airlines billions of Euros.

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates P a g e | xx

Figure 1.1-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC

R 5,000,000,000 R 4,500,000,000 Navigation Route Costs (FL 145) R 4,000,000,000 Cost of Security R 3,500,000,000

R 3,000,000,000 Cost of noise pollution R 2,500,000,000 R 2,000,000,000 Cost of Pollution R 1,500,000,000 Cost of major injury during R 1,000,000,000 flight R 500,000,000 Cost of minor injury during R - flight 5 10 15 20 25 30 35 40 45 50 Cost of accident resulting in fatality Year

Impact of an air transport liberalisation agreement in the Southern African Development Community

Figure 1.1-3 shows the total impact of an air transport liberalisation agreement in SADC being implemented in the Southern African Development community. This Figure graphs both the total benefits and the total costs. It can be seen how marginal the total costs are in relation to the overall economic benefit in the case of an air transport liberalisation agreement being implemented in the SADC region.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | xxi Figure 1.1-3 The total impact of an air transport liberalisation agreement being implemented in the Southern African Development community

R 300,000,000,000.00

R 250,000,000,000.00

R 200,000,000,000.00

R 150,000,000,000.00 TOTAL BENEFITS TOTAL COSTS R 100,000,000,000.00

R 50,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

Impact of an air transport liberalisation agreement reflecting the investment and capital expenditure in airport and navigational infrastructure

An air transport liberalisation is unable reach the full potential of the demand indicated in the previous section unless there is a significant upgrade and investment to both the airport and navigational infrastructure and equipment in the SADC region. Annual airport capacities would need to be increased to meet the anticipated passengers expected through the various airports in the region. The information that has contributed to infrastructural costs has been provided by Airports Company South Africa (ACSA) and Air Traffic Navigational Systems (ATNS.)

ATNS provided a list of infrastructure required per airport based on expected demand for flights and ACSA provided the airport capacities for each of the South African airports and indicated that for an additional 1 million passenger capacity that the infrastructure would cost R 600 million. Table 1.1-5 below lists the various infrastructural investments in the navigational equipment and cost of creating additional passenger capacity per airport. The column ‘benefit’s less costs’ indicates the total weekly costs and benefits per week highlighted in previous sections over the 50 year period. Once taken into account the infrastructural costs the column ‘Total impact after infrastructure costs’ highlights the

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | xxii impact per airport. It can be seen that only 5 airports cannot meet the infrastructural costs incurred over the 50 year period, but in total the benefits of air transport liberalisation are overwhelming and cross subsidisation of these airport that incur negative impacts could easily make them feasiable.

Table 1.1-5 impact over 50 years after infrastructure costs are taken into account per airport Location Benefits less costs Airport Airport Total impact after infrastructure navigational infrastructure costs systems Cabinda R 13,135,594,876 R 30,762,646,164 R 105,500,000 R -17,732,551,288 Catumbela R 15,135,950,379 R 21,704,608,871 R 105,500,000 R -6,674,158,492 Dundo R - R - R - R - Huambo R 18,968,271,072 R 32,799,705,108 R 21,666,667 R -13,853,100,703 Kuito R 18,689,215,470 R 31,326,914,031 R 21,666,667 R -12,659,365,227 Luanda R 35,312,114,184 R 14,454,353,583 R 521,500,000 R 20,336,260,601 Lubango R 32,307,418,877 R 31,374,951,739 R 21,666,667 R 910,800,471 Luena R 37,396,632,803 R 27,386,961,412 R 21,666,667 R 9,988,004,724 Malanje R 33,419,030,001 R 31,857,532,089 R 21,666,667 R 1,539,831,245 Menongue R 42,194,390,670 R 30,677,820,412 R 21,666,667 R 11,494,903,591 Namibe R 52,565,917,229 R 31,967,122,412 R 21,666,667 R 20,577,128,150 Ondjiva R 55,206,012,572 R 29,117,281,210 R 21,666,667 R 26,067,064,695 Saurimo R 66,112,557,006 R 30,955,943,213 R 21,666,667 R 35,134,947,126 Soyo R 73,599,566,822 R 29,976,647,084 R 21,666,667 R 43,601,253,072 Uíge R 60,701,876,855 R 30,352,589,998 R 17,333,333 R 30,331,953,524 Francistown R 112,435,059,703 R 35,135,585,164 R 105,500,000 R 77,193,974,539 Gaborone R 126,747,019,578 R 11,489,436,347 R 521,500,000 R 114,736,083,231 Kasane R 87,449,683,593 R 27,894,701,088 R 21,666,667 R 59,533,315,838 Maun R 104,737,840,516 R 26,245,742,034 R 105,500,000 R 78,386,598,482 Bukavu R 91,974,793,085 R 20,836,679,463 R 13,000,000 R 71,125,113,622 Buta-Zega R 90,872,827,828 R 18,670,970,711 R 13,000,000 R 72,188,857,118 Gbadolite R 97,660,364,082 R 19,005,255,956 R 21,666,667 R 78,633,441,459 Gemena R 102,803,308,089 R 21,174,304,236 R 13,000,000 R 81,616,003,852 Goma R 108,712,929,432 R 21,571,107,575 R 13,000,000 R 87,128,821,857 Isiro-Matari R 120,400,614,619 R 21,672,433,831 R 13,000,000 R 98,715,180,789 Kananga R 97,178,167,198 R 23,874,821,943 R 13,000,000 R 73,290,345,255 Kindu R 102,167,901,405 R 21,663,633,278 R 13,000,000 R 80,491,268,127 Kinshasa R 146,328,475,939 R 8,183,067,357 R 521,500,000 R 137,623,908,582 Kisangani R 131,214,272,888 R 17,332,241,664 R 105,500,000 R 113,776,531,224 Lubumbashi R 155,406,013,907 R 19,548,909,955 R 105,500,000 R 135,751,603,952 Mbandaka R 127,269,799,143 R 22,957,803,412 R 13,000,000 R 104,298,995,731 Mbuji-Mayi R 125,232,224,584 R 24,753,794,341 R 21,666,667 R 100,456,763,576 Maseru R 167,101,320,224 R 15,845,658,240 R 105,500,000 R 151,150,161,984

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | xxiii Antanànarìvo R 309,736,207,278 R 8,121,960,886 R 521,500,000 R 301,092,746,392 Mahajanga R 231,990,742,240 R 16,996,112,279 R 105,500,000 R 214,889,129,962 Nosy Be R 225,102,887,915 R 21,804,839,914 R 13,000,000 R 203,285,048,001 Toamasina R 295,708,091,889 R 19,094,988,396 R 105,500,000 R 276,507,603,493 Toliara R 239,258,253,432 R 22,937,552,850 R 21,666,667 R 216,299,033,915 Blantyre R 190,228,104,292 R 17,641,591,388 R 105,500,000 R 172,481,012,904 Lilongwe R 181,331,634,287 R 6,055,562,817 R 521,500,000 R 174,754,571,469 Port Louis R 606,131,604,552 R 12,345,883,086 R 521,500,000 R 593,264,221,466 Beira R 217,136,053,533 R 20,113,697,085 R 105,500,000 R 196,916,856,448 Chimoio R 170,895,781,172 R 23,705,642,728 R 15,166,667 R 147,174,971,776 Cuamba R 159,194,864,421 R 21,423,216,316 R 13,000,000 R 137,758,648,105 Lichinga R 177,744,106,905 R 23,590,797,889 R 105,500,000 R 154,047,809,016 Maputo R 285,106,971,134 R 7,783,416,063 R 521,500,000 R 276,802,055,071 Moçimboa da R 202,459,822,345 R 19,933,260,259 R 105,500,000 R 182,421,062,085 Praia Mueda R 187,439,099,382 R 19,705,744,750 R 13,000,000 R 167,720,354,631 Nampula R 269,697,762,029 R 20,528,698,094 R 105,500,000 R 249,063,563,935 Tete R 195,888,132,266 R 23,765,714,787 R 21,666,667 R 172,100,750,812 Grootfontein R 248,492,530,242 R 21,432,237,428 R 84,400,000 R 226,975,892,814 Karabib R 221,958,472,576 R 24,282,126,981 R 15,166,667 R 197,661,178,929 Katima Mulilo R 229,639,103,367 R 28,014,954,576 R 17,333,333 R 201,606,815,458 Keetmanshoop R 309,841,858,605 R 28,306,690,157 R 17,333,333 R 281,517,835,115 Mariental R 269,882,924,036 R 27,107,878,848 R 15,166,667 R 242,759,878,521 Ondangwa R 258,900,704,039 R 27,454,733,326 R 17,333,333 R 231,428,637,379 Rundu R 257,454,998,068 R 29,184,572,233 R 17,333,333 R 228,253,092,501 Windhoek R 396,517,070,883 R 9,559,680,305 R 521,500,000 R 386,435,890,578 Seychelles R 703,501,657,625 R 8,749,277,162 R 521,500,000 R 694,230,880,462 Bisho R 554,445,228,667 R 38,724,314,820 R 105,500,000 R 515,615,413,847 Bloemfontein R 518,236,753,001 R 42,568,700,235 R 105,500,000 R 475,562,552,766 Cape Town R 850,893,805,391 R 19,395,099,853 R 521,500,000 R 830,977,205,539 Durban R 680,019,685,523 R 38,705,155,564 R 521,500,000 R 640,793,029,959 George R - R - R - R - Lanseria R 623,425,486,875 R 50,916,414,646 R 105,500,000 R 572,403,572,229 Johannesburg R 599,808,390,969 R - R 521,500,000 R 599,286,890,969 Kimberley R 520,597,571,517 R 44,083,043,709 R 105,500,000 R 476,409,027,808 Mafikeng R 456,878,656,267 R 40,811,869,973 R 21,666,667 R 416,045,119,627 Nelspruit R 511,508,260,400 R 42,677,327,211 R 105,500,000 R 468,725,433,189 Polokwane R 459,727,696,484 R 42,265,713,353 R 21,666,667 R 417,440,316,465 Port Elizabeth R 757,947,901,871 R 41,889,245,560 R 105,500,000 R 715,953,156,311 Pilanesberg R 458,020,497,838 R 40,046,339,331 R 19,500,000 R 417,954,658,507 Umtata R 589,451,162,905 R 40,306,034,452 R 21,666,667 R 549,123,461,786

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | xxiv Upington R 564,438,760,296 R 42,797,693,603 R 105,500,000 R 521,535,566,693 Welkom R 539,261,292,507 R 42,529,814,313 R 19,500,000 R 496,711,978,194 Manzini R 337,187,877,496 R 17,821,283,568 R 105,500,000 R 319,261,093,927 Dar-Es-Salaam R 640,241,051,391 R 8,424,782,414 R 521,500,000 R 631,294,768,976 Dodoma R 460,907,809,563 R 24,775,748,996 R 105,500,000 R 436,026,560,566 Kilimanjaro R 601,328,818,794 R 21,088,863,923 R 105,500,000 R 580,134,454,871 Mtwara R 463,076,216,765 R 24,211,283,510 R 21,666,667 R 438,843,266,588 Mwanza R 599,323,031,470 R 27,957,419,377 R 21,666,667 R 571,343,945,426 Zanzibar R 575,823,890,548 R 27,027,185,021 R 521,500,000 R 548,275,205,528 Kitwe R -770,778,388 R - R - R -770,778,388 Livingstone R 370,996,780,292 R 18,800,111,355 R 105,500,000 R 352,091,168,937 Lusaka R 456,850,384,931 R 8,921,260,504 R 521,500,000 R 447,407,624,427 Mfuwe R 95,333,266,016 R 8,502,307,049 R 8,666,667 R 86,822,292,300 Ndola R 430,933,005,132 R 27,766,951,019 R 21,666,667 R 403,144,387,446 Bulawayo R 307,810,325,118 R 23,414,456,928 R 105,500,000 R 284,290,368,191 Harare R 382,745,641,210 R 6,518,897,873 R 521,500,000 R 375,705,243,338 Hwange R 238,906,513,453 R 17,155,638,949 R 21,666,667 R 221,729,207,837 Victoria Falls R 228,987,817,785 R 10,761,251,323 R 105,500,000 R 218,121,066,462 TOTAL R 24,566,019,405,225 R 2,133,076,262,959 R 12,076,400,000 R 22,420,866,742,266

Conclusion

The literature review and impact analysis have both overwhelmingly demonstrated the positive effects of implementing an air transportation liberalisation in the SADC region. However, there are a few issues that need to be considered before implementing an air transportation liberalisation agreement:

The establishment of a competition authority, with the power to penalise countries and airlines acting in ways that are un-competitive. The inevitable market share decline of national flag carriers and in some cases the closing of unprofitable nation flag carriers. This will, in all likelihood save taxes. The emergences of privately owned low cost carriers as the dominant airlines within the region. The shifting of connector flights away from historical hub airports. Substantial new investment in airports within SADC and in additional infrastructure, skills and capacity (including aircraft) to take advantage of an air transportation liberalisation.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 1 Introduction

This report has been prepared for the South African Department of Transport.

The report summarises the methodology and findings of an investigation into the impacts of implementing air transportation liberalisation legislation in the form of implementation of an air transport liberalisation agreement throughout the Southern African Development Community (SADC) region.

The report has been divided into two parts:

1) The first part (Section 1) investigates the current literature regarding air transportation liberalisation and the effects and impacts experienced in other countries and regions around the world; 2) The second part (Section 2) of the report takes some of the lessons learnt from the first section and applies these in an analytical and modelling study to forecast the impact of air transportation liberalisation legislation being introduced in the SADC region in the form of implementation of an air transport liberalisation agreement throughout the Southern African Development Community (SADC) region.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 2 1 Literature Review

1.1 Introduction

Air transportation liberalisation agreements are concerned with the liberalisation of aviation regulations and agreements between countries. This report comprises a review of the current literature regarding the economic impacts of air transportation liberalisation agreements and of the consequences and potential risks of adopting air transportation liberalisation agreements. This report is primarily concerned with setting the back drop to assessing the impact of an air transportation liberalisation agreement on Africa in the Southern African Development Community (SADC).

Key to this study is the African air transportation liberalisation initiative known as the Yamoussoukro Decision (YD) launched in 1999. Although this initiative is now more than a decade old, little of it has been implemented and the aviation market within Africa remains largely closed, regulated and dominated by national flag carriers. There has been limited political will in implementing YD in the various African regions and the wider continent. YD relates to the liberalisation of access to the aviation market in Africa and seeks to achieve:

Unrestricted access to all air routes; Elimination of restriction on capacity, frequency on any route and in operation in any international markets; Elimination of restriction on charters; Liberalization of air cargo rules; Doing away with restrictions on the conversion of revenues to hard currency and repatriation of revenues; Agreement on code sharing; Permitting carriers to have their own ground service abroad; and Termination of regulations on carriers’ alliance.

At the time of writing this report literature available on air transportation liberalisation agreements and the Yamoussoukro decision was limited and lacking in economic quality. Furthermore, most of the air transportation liberalisation literature is focussed on developed countries (the United States, the European Union and the United Kingdom) and thus the analysis is more applicable to highly developed countries and regions. The emphasis on developed country studies is somewhat to be expected, however aviation markets of these regions are double the size of those in the rest of the world. More specifically, the African aviation market is only 7.45% of the size of the North American aviation market and 8.34% of the size of the European aviation market, as seen in Figure 1.3-3. Therefore, the anticipated impact of an air transport liberalisation agreement in SADC would be a fraction of that experienced in developed regions where air transportation liberalisation has been adopted.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 3 The report is structured as follows:

Section 1.2 examines the nine ‘freedoms of the air’ that make up a typical air transportation liberalisation agreement. Section 1.3 looks briefly at the history of aviation and the history of aviation agreements, starting with the Chicago Convention of 1944 and concluding with an in depth analysis of the Yamoussoukro Decision of 1999 (Africa’s air transportation liberalisation initiative). Section 1.4 reviews five methods that can be used to assess or forecast the impacts of aviation agreements. Section 1.5 reviews three case studies that detail the impacts of implementing air transportation liberalisation agreements. These case studies review the United States and the United Kingdom; the European Union; and India and the United Kingdom. Included is research conducted by InterVISTA-ga2 in 2006, which attempts to determine the global impact of every country liberalising their aviation regulations. Section 1.6 discusses two significant research reports which highlight some important considerations regarding the economic impact of air transportation liberalisation agreements. Finally section 1.7 concludes the analysis by highlighting the implications of the report for Southern Africa.

1.2 The nine freedoms of the air

As a point of departure it is important that the nine freedoms of the air are clearly defined, as they will be referred to throughout the remainder of this study. Aviation agreements between countries and within regions can consist of up to nine freedoms of the air. Table 1.2-1 overleaf explains each of the nine air freedom rights in a typical aviation agreement between two nations or a region.

Freedom Rights 1 - 4 are known as traditional bilateral aviation regulations that have been in place since the Chicago Convention of 1944 (discussed overleaf), whereas Freedom Rights 5 - 9 are the more recent air transportation liberalisation regulations being pursued by a number of countries and regions. Freedoms 5 – 9 are far more liberal and give airlines and airports far more flexibility and possibilities.

For a complete list of countries with air transportation liberalisation agreements with the United States in place please refer to Appendix B.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 4 Table 1.2-1 Definition of air freedom rights

nd 1st Freedom 2 Freedom To overfly one country en-route to another To make a technical stop in another country

rd 3 Freedom 4th Freedom To carry freight and passengers from the home country to another To carry freight and passengers to the home country from another country country

3rd Freedom 5th Freedom

Traditional bilateral More recent air aviation regulations transportation liberalisation regulations

Source: ICAO Manual of Regulation (2004) and WTO Secretariat 9th Freedom or True Domestic To carry freight and passengers within a foreign country with no connection with the home country

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 5 1.3 History of aviation agreements

Aviation as a mode of transport has grown increasingly in importance over the last century, ever since the Wright brothers took their first controlled flight on 17 December 1903. Less than a decade later aircraft were being used in World War I for reconnaissance and attacks against both ground positions and enemy aircraft. The first aircraft to start transporting people and cargo over long distances were known as Zeppelin blimps or airships. This short lived technology came to an end in 1937, when the Hindenburg Zeppelin blimp crashed killing 36 people (Bryan, L.A, Taylor, M.S, 2006).

The 1920’s and 1930’s saw great advances within the aviation industry, such as the first transatlantic flight in 1927 and the first transpacific flight a year later. By the start of the World War II many towns and cities had built airports, and there were many qualified pilots. World War II brought about a number of advances in the aviation industry, such as the first jet aircraft and the first liquid fuelled aircraft. During World War II the importance of modern aviation was recognised and a conference was convened to agree on aviation regulations. This conference, known as the Chicago Convention of 1944, resulted in regulations that have governed international aviation law and bilateral agreements between countries for the second half of last century (Bryan, et al, 2006).

1.3.1 Chicago Convention 1944

The Chicago Convention of 1944 was attended by 54 states (see Appendix A for a list of countries that attended the Chicago Convention) but ended in 52 states signing the Convention on International Civil Aviation. The signed convention was a list of international aviation regulations, standards and procedures decided on by participating nations.

The regulations, standards and procedures dealt with included: communications systems and air navigation; airport characteristics; rules of the air and airport traffic control; air worthiness of aircrafts; licensing and operation and mechanical personnel; aeronautical maps and charts; log books; and measures to facilitate air navigation (Bryan, L.A., et al; 2006).

Most importantly, the convention affirmed that every nation has sovereignty over the airspace above its territory and that “every civil aircraft must be registered, carry the nationality of the country of registration, and bear appropriate identification markings” (Bryan, L.A., et al; 2006). However, the convention also granted transit rights and permitted non-scheduled, charter, and private flights. Transit rights refer to the right to fly over another nation’s territory and to the right to land for non-traffic purposes, such as refuelling (1st to 4th freedoms of the air, see Section 2, above.)

The Chicago Conference agreed that a regulatory body should be established to ensure that the contracting states implement and abide by the regulations, standards and procedures decided upon at the convention. This was the initial formation of the ‘International Civil Aviation Organisation’ (ICAO). The ICAO was formally established in 1947 as an agency of the United Nations linked to the Economic and Social Council (ECOSOC). The Chicago Conference set forth the purpose of ICAO as:

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 6 "The future development of international civil aviation can greatly help to create and preserve friendship and understanding among the nations and peoples of the world, yet its abuse can become a threat to the general security; and it is desirable to avoid friction and to promote that co-operation between nations and peoples upon which the peace of the world depends; therefore, the undersigned governments having agreed on certain principles and arrangements in order that international civil aviation may be developed in a safe and orderly manner and that international air transport services may be established on the basis of equality of opportunity and operated soundly and economically.”

(Preamble to the Convention on International Civil Aviation - Chicago, 7th December 1944)

The ICAO’s primary mandate was to foster development and promote co-operation in international civil aviation. The major success of the convention was that it greatly advanced aviation safety and standards as well as helping to foster bilateral aviation agreements between participating states.

1.3.2 Formation of state owned or sponsored airlines

The formation of state owned or sponsored flag carrier airlines (such as South African Airways) operating out of a hub airport (such as O.R. Tambo Airport), is a result of the regulations set out by the Chicago Convention. Traditional aviation agreements between countries help protect flag carrier airlines by defining the landing rights allowed, restricting the number of flights on a particular route, restricting the amount of freight or passenger seats available and restricting foreign airlines to specific airports. Therefore, flights are directed through a specific airport, as illustrated in figure 1.3-1, below. As can be seen in this figure an overwhelming majority of South African Airways flights are directed through O.R. Tambo International Airport in Johannesburg.

Figure 1.3-1 South African Airways International Route Map

Source: http://www.airlineroutemaps.com/Africa/South_African_Airways.shtml, accessed October 2009

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 7 Illustrated in Figure 1.3-1, airlines have traditionally operated out of a central hub airport to various destinations around the world. Therefore, if a person wants to travel from Windhoek (Namibia) to Lusaka (Zambia) on South African Airways, they would need to fly first to Johannesburg before transferring to a flight to Lusaka. The trip to Johannesburg not only adds unnecessary time to the journey, but adds significant cost in airport taxes and flight costs.

State sponsorship or ownership of international flag carrier airlines is still very prevalent in Africa and a list of flag carriers and level of state ownership can be found in Appendix C. More than 50% of national flag carriers listed in Appendix C are still owned or funded by the state.

1.3.3 Liberalisation of aviation agreements

Since the Chicago Convention of 1944, aviation technology has accelerated rapidly. Today modern aircraft are far more efficient in terms of speed, service and safety than in the past. However, due to aviation regulations between countries not modernizing in tandem with technology and increased levels of globalisation, these improvements in the aviation industry have had a somewhat limited impact on the commercial aviation market. The InterVISTA-ga2 report highlights this in the following passage:

“Commercial aviation still faces a challenge common to many of the newer and technically advanced areas of our society. Our social and political institutions have not kept pace with the evolution of technology or the needs of the public. Commercial aviation remains encumbered by well-meaning but outmoded and arcane rules, principles and institutions. They often prevent fit, willing and able airlines from fully serving passengers and shippers who are completely willing and able to pay. They also impose protective machinery that frustrates innovation and directs the evolution of the industry into a contrived and artificial structure. By sheltering airlines from market forces, they reduce the incentives to pass on to passengers, shippers and investors the benefits of improved technologies.”

When aviation regulations were created in the first half of last century, aircraft technology, speed and safety were limited and expensive. This encouraged formation of national flag carrier airlines that were either state-owned or state-subsidised. Airlines were treated and run as pure monopolies (within nation states) and cartels internationally, requiring state assistance and regulation to survive. However, as technologies and efficiencies in the aviation industry have improved and become accessible, the overall costs of operating airlines have decreased.

The airline market can best be explained by Figure 1.3-2 overleaf, which shows the demand curve for a pure monopoly and a monopoly.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 8 Figure 1.3-2 Demand Curve for both a Pure and Normal Monopoly

When aircraft technology was expensive and airline efficiency was severely limited compared with today, airlines were treated as pure monopolies or members of cartels that needed to be protected and subsidised or owned by government. Thus Part A of Figure 1.3-2 shows that the average cost of an airline, characterised as a pure monopoly, is higher than the price, resulting in economic losses. This is due to inefficient technologies which were too costly for commercial viability. To ensure the survival of an industry or company operating under conditions of pure monopoly, it is essential that it is subsidised by the difference of P2 and P1. Therefore, in order for countries to access the global market, it was essential for governments to meet this short fall in the operating costs of national flag carrier airlines.

In today’s world where aviation technology is more advanced and accessible, average costs have decreased and the market can better be described as a monopoly. It can be argued that the average costs of the airline industry have decreased to levels where average costs are now lower than price. National flag carrier airlines operating as monopolies seek to maximise profit through offering a sub- optimal quantity of seats. This profit can be seen in Part B of 1.3-2, namely the difference of P1 and P2. In an open and competitive market, national flag carrier airlines would be forced to operate at competitive equilibrium (where the marginal cost line, average cost line and average revenue/demand line intersect). As can be seen in the figure, competitive market forces would determine equilibrium at price PE (lower than that of the price set by a monopoly) and quantity of seats QE (higher than the quantity set by a monopoly), directly benefiting consumers of air transport and freight.

Airlines have not only functioned as monopolies in the last 15 years, but also as oligopolies on routes that are shared with competing airlines. Airlines collaborate with each other to reduce competition and keep prices high on certain routes, thus increasing the profit made. In an open competitive market, both

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 9 airlines would undercut each other prices and improve their services and capacity on those routes, thereby making air travel more accessible.

Thus, the focus of the international aviation community over the last 15 years has been on liberalising aviation agreements between countries and opening up the airways, to eliminate this market inefficiency that is ultimately being paid for by the consumer.

1.3.3.1 Air Transportation Liberalisation Agreements

The United States started pursuing the first air transportation liberalisation agreement in 1972. By 1983 the country had signed 23 bilateral air service agreements. European states followed suite in the 1990s by opening up their airspaces to other European nations (discussed in Section 1.5.2 further on). In 1992 a massive step was taken towards liberalising air regulations when the US signed an air transportation liberalisation agreement with the Netherlands. This agreement gave each country unrestricted landing rights.

Air transportation liberalisation has been more vigorously pursued by the international community over the past 15 years, particularly at a regional level. Prior to 1994 there were just two regional air transportation liberalisation agreements, namely the European Union that included 15 member states, and the Andean Pact that comprised of five South American states (ICAO, 2005). Since 1995, eight more regional arrangements have emerged:

The Caribbean Community (CARICOM) Air Service Agreement amongst 15 States in the Caribbean (1996, entry into force in 1998 for nine States); The Fortaleza Agreement amongst six states in South America (1997); The Banjul Accord amongst six states in Western Africa (1997, a separate more liberal multilateral agreement was signed among seven States in 2004); The CLMV Agreement by Cambodia, Lao People’s Democratic Republic, Myanmar and Viet Nam (1998, a formal multilateral agreement was signed in 2003); The Intra-Arab Freedoms of the Air Programme amongst 16 States of the Arab Civil Aviation Commission (ACAC) in the Middle East and Northern Africa (1999); MALIAT – Multilateral Agreement on the Liberalisation of International Air Transportation (MALIAT) between Brunei, Chile, New Zealand, Singapore and the United States An agreement amongst the six States of the Economic and Monetary Community of Central Africa (CEMAC) (1999); An agreement amongst the 20 States of the Common Market for Eastern and Southern Africa (COMESA) (1999); and The Yamoussoukro II Ministerial Decision amongst 53 African Union States (1999, entry into force in 2000).

Of the eleven agreements listed above, eight have been fully implemented or are in the process of a gradual implementation. The last three in the above list require further discussion or decisions made by

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 10 the various governments, one of these being the air transportation liberalisation initiative for Africa the Yamoussoukro Decision. An attempt has been made to find more information on these regional air transportation liberalisation agreements; however the literature available is either in a foreign language or does not give the detail required for analysis. There is no literature available for the Africa air transportation liberalisation agreements.

1.3.3.2 The Yamoussoukro Decision

The structure of the aviation market in Africa over the last three decades has been shaped by protective bilateral agreements between states, where free market economic logic has played an limited role. The majority of African states have moved towards bilateral aviation agreements and regulations that ensure the protection of national flag airline carriers (Economic Commission for Africa, 2001). There has been a limitation on the agreement of 3rd and 4th air freedoms (air freedoms are explained in Section 1.2) and reluctance to authorise technical landing for flights continuing to other destinations. The majority of African countries designated flag carriers enjoy exclusive monopolistic rights in these markets. The consequence of this has been a limited improvement in the quality and quantity of air services throughout the continent. In addition, the vast majority of African airlines either have government as a majority or full shareholder. This has been demonstrated in the table provided in Appendix C, listing every airline in the world and whether these airlines are owned, partly owned or subsidised by their governments.

Figure 1.3-3 overleaf shows the total number of domestic and international airline passengers, by region. As can be seen from the figure, Africa has significantly smaller volumes of passenger seats being purchased, at 114 million seats in 2006, than the developed regions of North America, Europe and Asia - at 1529 million, 1367 million and 980 million passenger seats respectively. Latin America and the Caribbean is almost double the size of Africa, at 272 million passenger seats, with only the Middle East showing similar market size at 111 million seats in the year 2006.

African ministers took significant steps forward in liberalisation of the African airspace when they signed the Yamoussoukro Decision (YD) in 1999. The intention was that YD would be achieved by gradual liberalization of scheduled and non-scheduled intra African air transport services, thus leading to the emergence of a viable and quality African air transport that meets the imperatives of the consumers of air services (African Union, 2005).

The general aim of YD is to encourage co-operation among African states through air transportation policies that encourage deregulation of the aviation industry, promoting competition on routes and reduced airfares between African destinations. YD promotes fundamental changes in the nature and operation of airlines, in national economies, in tourism and in relationships between African states (SSamula B. & Venter C., 2005). YD gave the Economic Commission for Africa (ECA) and the ICAO the responsibility of implementing the agreement between the various African states.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 11 Figure 1.3-3 Total number of domestic and international airline passengers, by region Passengers (millions) 1800

1600 1529

1400 1367

1200 1104.9 1000 980

1989 743 800 741.8 665.5 1999 600 546.2

2006 318.9

400 272

134.5

114

111 83.5

200 79.1

60.9

47.8 40.8

Africa

North

Europe

America

and

AsiaPacific

Middle East Middle Caribbean Latin America America Latin Source: ICAO, 2007

YD advocates the following:

That only African owned airlines would benefit from the implementation of YD The granting of 1st to 5th air freedom rights (as well as cabotage, the 8th air freedom rights); Encouraging the development of new routes; Removal of capacity restrictions on passenger seats, freight and flights on certain routes; The removal of expensive and complex tariff regulations; The elimination of all protective policies that protect national flag carriers; The termination of regulations on carriers’ alliance; Doing away with restriction on the conversion of revenues to hard currency and repatriation; Agree on code sharing; and Allow carriers to have own-ground-service abroad

The ECA and ICAO are not the only institutions that are interested in the liberalisation of the African skies. Figure 1.3-4 overleaf highlights the relationship of the various organisations and structures that are responsible for the implementation of YD

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates Department of Transport P a g e | 12

Figure 1.3-4 Break down of the Yamoussoukro Decision implementation organs

Source: SSamula B. & Venter C., 2005

Impact of the Yamoussoukro Decision: 6th April 2010 - report prepared by Graham Muller Associates Department of Transport P a g e | 13

Full aviation liberalisation proposed by YD was expected to be completed by 2002 with a total removal of restrictions on traffic rights (including 5th air freedoms), as well as removal of capacity constraints between origins and destinations, non-regulation of tariffs by government, multiple designations, and complete liberalisation of cargo and non-scheduled air services (Economic Commission for Africa, 2001). Also by 2002 a monitoring body would have been formed to oversee and enforce the various YD agreements.

All in all YD had a number of very good intentions for the African continent; however it has faced significant obstacles in realising the potential gains and implementation has largely failed. The reasons for this failure are highlighted in an African Union Report (2005):

Confusion in the monitoring body of the Yamoussoukro Decision o The African Union (AU) is named as chair of the monitoring body, but has been given equal status to the other specialised African institutions such as the African Airlines Association (AFRAA), the African Civil Aviation Commission (AFCAC) and Regional Trade Organisations (RTOs). o The roles of these specialised African institutions are unclear and they are cited only as members, resulting in confusion as to responsibilities. o Furthermore the RTOs are mentioned as back-up to the AU, which is not practical as these bodies would primarily be responsible for ensuring the implementation of YD at a regional level. Conditions for eligibility of airlines in the Yamoussoukro Decision are inadequate. These conditions allow any airline which has “its headquarters, central administration and principal place of business physically located in the state concerned” to be eligible to benefit from the advantages set forth in the Yamoussoukro Decision. Such an airline may be totally or in most part controlled by foreign capital or interests. The European Union has put in place very restrictive conditions in terms of eligibility so as to protect the airlines of its community. YD makes no mention of economic control of eligible airlines - there should be a provision in YD requiring airlines to avail to audit boards all accounting and financial documents to ascertain their economic status. These audit boards do not exist. Competition rules as contained in the Yamoussoukro Decision are inadequate. Competition rules need to be defined further and the following prohibitions need to be made: o No direct or indirect state or parastatal subsidies. o No private financial aid that is not consistent with generally accepted rules and regulations governing private financing. o Equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages) o Ban on abuse of dominant positions. o Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities.

Impact of the Yamoussoukro Decision: 6th April 2010 - report prepared by Graham Muller Associates P a g e | 14 o Establishment of an African Union level body to ensure implementation and compliance. o Authorities responsible for the implementation of the Yamoussoukro Decision lack resources and co-ordination for the attainment of the objectives set in the short term - The monitoring body requires adequate financial resources and political support to enable it to fully play its role.

For the most part of the last decade the implementation of YD has moved at slower pace than expected and is still far from being implemented in most regions of Africa and the continent itself. Progress has been made amongst many of the West African countries and domestically within South Africa. Furthermore, a number of countries have opened their skies to the United States; among these are Morocco, Nigeria, Ghana, Senegal, Tanzania, Namibia, Burkina Faso, Gambia and Benin (see Appendix B) Both Ethiopia and Kenya have entered into air transportation liberalisation negotiations with the United States.

1.3.3.3 African Aviation Competition Authority

For a successful implementation of an air transport liberalisation agreement, a proper competition authority is required to monitor that no airline acts in an uncompetitive, monopolistic or oligopolistic manor. Without a monitoring body national flag carriers who have dominated the aviation market in Africa could uncompetitive restrict the access of new low cost carriers. Dominant airlines in the region (such as South African Airways) could also exert unnecessary pressure on smaller airlines.

It is necessary that a competition authority be setup by the regional political body such as the South African Development Community. The competition authority should comprise of employees/members from the various members states of the agreement, if this is not possible each state must be in full agreement with the staff/member complement of the competition authority. It is absolutely essential that the competition authority be given full political support of each member state and the power to prosecute airlines that act in an uncompetitive manor. Without any of these commitments establishing an aviation competition authority is pointless.

The completion rules have already been stated, but are worth repeating:

o Only airlines operating in SADC should benefit from the implementation of air transport liberalisation agreement in SADC o The granting of 1st to 5th air freedom rights in each member state (as well as cabotage, the 8th air freedom rights); o Encourage the development of new routes; o Ensure the removal of capacity restrictions on passenger seats, freight and flights on certain routes; o Ensure the removal of expensive and complex tariff regulations; o Ensure the elimination of all protective policies that protect national flag carriers;

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 15 o Ensure the termination of regulations on carriers’ alliance; o Remove restriction on the conversion of revenues to hard currency and repatriation; o Agree on code sharing; o Allow carriers to have own-ground-service abroad; o Not allow any direct or indirect state or parastatal subsidies; o Not allow private financial aid that is not consistent with generally accepted rules and regulations governing private financing; o Allow equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages); o Ban on airlines who abuse a dominant positions; o Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities.

1.4 Assessing and forecasting the impact of air transportation liberalisation agreements

There are various methods that have been used to evaluate and forecast the impact of air transportation liberalisation agreements on aviation markets. Methods include: the case study approach; the trends model; gravity models; stimulation models and air transportation cost analysis (Swan, 2008). These methods predict or analyse the growth in aviation markets if regulations were liberalised, thereby making it possible to understand how growth is being restricted in regulated airline markets. Each method has its limitations and takes into account different aspects predicting the effects of air transportation liberalisation agreements. The various approaches that can be used are discussed in detail in this section. Graham Muller Associates incorporated various aspects of these methods when predicting the impact of air transportation liberalisation agreements in SADC region.

1.4.1 The case study approach

The case study approach is relatively simple and looks at actual data. Of all the existing methods, it is the only method that does not forecast or predict future growth. The case study approach analyses passenger seats, freight by tonnage and air fares before and after air transportation liberalisation agreements have been implemented. This is a crude analysis of air transportation liberalisation agreements as it does not fully take into account the market size, distances between countries, level of airport infrastructure and the proportion of the urban population with access to airports. This analysis has a limited applicability to nations considering air transportation liberalisation agreements, as country conditions often differ drastically. This method tends to be the most common analysis used in the literature reviewed. Various case studies are discussed in Section 1.5 further on.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 16 1.4.2 The trends model

The trends model uses statistical regression analysis to isolate the effects of travel against an economic activity such as GDP. This model uses historic travel, flight and GDP data to forecast future aviation industry growth. Therefore the model does not recognize changing conditions like air transportation liberalisation agreements that increase the amount of passenger seats and freight tonnage as shown in the case studies reviewed below. GDP is used to explain growth in air travel, there is no dependence on other causal activities, such as price, service, trade, distance, regulations or airport infrastructure. Thus results using this method are often unreliable and if a country is still operating under regulated aviation agreements the method will not account automatically for the growth brought about by deregulation. (Swan, 2008). This can always be catered for in a more complex model.

1.4.3 The gravity model

While the trends model constrains the forecast by not being able to account for regulation changes, the gravity model is an unconstrained forecast that determines total demand in a deregulated air market. The gravity model uses the size of the origin (city or country) times the size of the destination as an indication of the demand for flights between them. This model assumes that the bigger the population size of the origin and the population size of the destination, the bigger the attraction and demand for flights. Sizes of the origin and destination are measured in population, GDP or number of passengers/freight traveling by air.

The model does not account for distance and therefore ignores the impact expected when the origin and destination are further apart and the flights demanded diminish. Therefore in some instances the distance between the origin and destination can be used to further calculate the estimated demand of flights on a particular route (number of flights or airline operating on routes is not taken into account.) Equation (1) shows the most classical form of the gravity model calculation.

Equation (1) Demand = (Pop Origin * Pop Destination)/Distance

The problem with this model is that it tends to overstate or understate demand on certain routes. This model also assumes that bigger populations consume more air travel, which is only a valid assumption provided that the majority of the population is earning a salary that permits them to consume air travel.

Figure 1.4-1 overleaf shows the ratio between the gravity model’s forecasted amount of air travel consumed and the actual amount of air travel consumed in the European region. For this to be an accurate method of forecasting the majority of the points should be located around the horizontal line at 1.0. Instead, for the majority of these routes there was far more air travel consumed than forecasted (Swan, 2008).

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 17 Figure 1.4-1 Gravity forecast fails to fit actual data, European Region

Source: Swan, W. 2008

1.4.4 The stimulation model

The stimulation model estimates the increase in air traffic arising from changes in fares and service levels. This model requires good data on how the volume of air tickets purchased changes as the price of these tickets changes. The model could have problems in forecasting air traffic levels where the base data is taken from an airport or airline running at full capacity. Generally the type of data required for this analysis is not available or there is inadequate historical data on how price changes have affected air traffic (Swan, 2008).

1.4.5 Air transport cost analysis

There has only been one study to date that uses various sources of historic data to run regressions analysing the main contributors to air transportation costs. This is not a reflection of the merit of the approach, but is likely to be a result of the extensive data requirements of a fully comprehensive cost analysis. This approach is discussed in detail in Section 1.6.1 further on. Cost analysis is able to take into account distance, total volume, value per unit weight of cargo, foreign airport infrastructure, regulatory quality, as well as whether or not an air transportation liberalisation agreements existed between the countries involved and to what extent air freedoms were allowed in this agreement.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 18 1.5 Case Studies

This section examines three case studies with respect to the impact that air transportation liberalisation agreements have had on each country. These case studies look at the United States and the United Kingdom, the European Union, and finally India and the United Kingdom. It is important to note from the outset of this section that all the case studies discussed below instituted 1st to 5th air freedoms, as well as allowing cabotage the 8th air freedom, when liberalising their aviation markets.

1.5.1 United States – United Kingdom

The United States (U.S.) and United Kingdom (U.K.) aviation agreement is complex and somewhat contentious. While this agreement is liberal in some aspects it is still restrictive by limiting access to Heathrow and Gatwick airport. In the years leading up to the 1990’s U.K. – U.S. air traffic represented one third of all U.S. – E.U. traffic. During the 1990’s, the U.S. and the U.K. liberalized the traditional agreement that had been in place since 1978. As part of that agreement, the U.S. - U.K. market was deregulated, with the exception of Heathrow and Gatwick airports. Otherwise, carriers could operate any city pairs, and at pricing that was commercially determined. Both the U.S. and the U.K. have globally dominant aviation markets and large economies, which tends to make aviation agreements involving these two counties fairly problematical. Both states attempted to sway the agreement in their favour and maintain or grow their market share.

The liberalisation of the air market between the U.K. and the U.S. led to capacity growth on then trans- Atlantic route at a compound annual rate of 7.8%. The market share in passenger seats over the Atlantic shifted over a ten year period from 48% U.S. flag carriers in 1990 to 58% U.S. flag carrier in 2000. At the end of 2005, the U.S. had lost a slight portion of this gain with market share over the transatlantic falling back to 56%. Figure 1.5-1, overleaf, demonstrates graphically the number of passenger seats for both U.S. and U.K. carriers between the periods 1990-2005. A decrease in passenger seats between 2001 and 2002 can be attributed to the 11 September 2001 attacks in the U.S. and the outbreak of the Severe Acute Respiratory Syndrome (SARS) virus in 2002.

It is estimated that the air transportation liberalisation agreement between the U.S. and U.K. is responsible for stimulating 9,197 full-time equivalent jobs in the United States and over 16,700 full-time equivalent positions in the United Kingdom. It is also estimated that the gross domestic product of the United States also expanded by $747 million due to the agreement and the United Kingdom by roughly $970 million. InterVISTA-ga2, 2006, estimated that a full air transportation liberalisation agreement between the U.S. and the E.U. would result in a 29% increase in traffic, due to increased passenger volumes between the U.S. and Heathrow and Gatwick airports. The economic benefits of a complete air transportation liberalisation agreement would also mean that “117,000 full-time equivalent positions would be created and the GDP of the two countries would grow by roughly $7.8 billion” in 2006 (InterVISTA-ga2, 2006.) Subsequent to the InterVISTA-ga2, 2006 report, the U.S. negotiated an air transportation liberalisation agreement with the E.U. that has paved the way for the U.S. to enter into a complete air transportation liberalisation agreement with the U.K.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 19 Figure 1.5-1 Air market share between U.S. carriers and U.K. carriers

12000

10000

8000

6000

4000

2000 Number of Seats (000s) Seats of Number

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004 2005 US Flag Capacity Total US-UK Capacity

Source: adapted, InterVISTA-ga2, 2006

1.5.1.1 A limited air transportation liberalisation agreement with the U.S.

The E.U. air transportation liberalisation agreement with the U.S. has been criticised due to E.U. companies being restricted such that they cannot obtain more than 25% of voting rights in US aviation companies. On the other hand U.S. companies can acquire more than 50% of any E.U. aviation company or airline (www.wharton.universia.net, 2009).

E.U. airlines are allowed to fly from any European Airport to any U.S. Airport, but cabotage within the U.S. is completely restricted. On the other hand U.S. airlines are not only allowed to fly from any U.S. Airport to any E.U. Airport, but cabotage within the E.U. is permitted.

British Airways has indicated that under an air transportation liberalisation agreement with the US it has the most to lose, as 40% of transatlantic flights from Europe depart from Heathrow Airport which has been deregulated. E.U. leaders (in particular the U.K. leaders) believe they can push the U.S. to review the limitations of the agreement in 2010 when the air transportation liberalisation agreement is revisited.

These restrictions are destroying competition and already DHL (a European based freight company) cannot compete against U.S. freight companies. In this regard, DHL has closed down its U.S. branch,

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 20 which means that some 8000 U.S. jobs have been lost. Furthermore it has now outsourced its aviation services to ABX Air & ASTAR (both of these are US based freight companies) (Brown, 2008).

1.5.2 The European Union

The European Union signed an internal air transportation liberalisation agreement in 1992, called the ‘Single Aviation Market’; this was signed by the 12 member states at the time. The InterVISTA-ga2, 2006 report looked at the impact of this deregulation on the European Community market as a whole and the impact of this deregulation on a number of selected air routes from Germany.

The process of liberalising aviation regulations was spread between 1987 and 1992, as it was resisted by various member states and the entire aviation industry. The 1992 legislation was the third of three packages. The first two (1987 and 1990) retained the bilateral system. Table 1.5-2 shows a summary of the Intra-EU transport packages, the three air legislation agreements (1987, 1990 and 1992) and the various aspects of this agreement.

The three stages of liberalisation in the E.U. aviation market and the dates that these agreements came into force have been displayed in the three columns on Table 1.5-2, overleaf. The columns display how over a 4 year period:

The regulations of airfares (fares) were relaxed, More route designations could be added regardless of smaller demand, Capacity share between states was eventually abolished, and Air freedoms were increased

Table 1.5-3, overleaf, is a good indication of how a phased implementation of an air transportation liberalisation agreement could be structured, thereby giving states, airports and airlines time to adjust and improve aviation efficiencies.

Table 1.5-1, overleaf, shows the capacity and traffic growth for all of Europe, between the periods of 1990 – 2002. The results shown only take into account the change between the first and the last year in the four year period. This removes some of the explainable short term fluctuations such as the 11 September 2001 attacks in the U.S. As can be seen, the growth in passengers carried by all European airlines between 1998 - 2002 more than doubles that between 1990 - 1994.

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Muller Associates P a g e | 21 Table 1.5-1 Capacity and Traffic Growth for All Europe, 1990-2002

Increase in passengers carried

Market 1990- 1994- 1998- 1994 1998 2002

Total 20.40% 37.80% 40.90% Europe Source: InterVISTA-ga2, 2006

One of the significant findings of the liberalisation process in the E.U. has been the gain in market share by low cost carriers. Before liberalisation low cost carriers were restricted to certain

Table 1.5-2 Summary of Intra-EU transport packages

Source: InterVISTA-ga2, 2006

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 22 routes and booking slots. They also competed against subsidised national flag carriers. Table 1.5-3 below shows how the low cost carrier airlines have grown their market share in the aviation industry, from 1996 to 2003. These low cost carriers have moved from a 1.4% market share to more than a fifth of the share in the aviation market.

Table 1.5-3 : Capacity Shares of Low Cost Carriers

Year Low-Cost Operators’ Share of Capacity 1996 1.40% 1997 2.80% 1998 3.70% 1999 4.20% 2000 6.00% 2001 6.40% 2002 11.10% 2003 20.20% Source: InterVISTA-ga2, 2006

1.5.3 India – United Kingdom

The aviation regulations between India and the United Kingdom (UK) were liberalised in late 2004 to mid 2005. The United Kingdom Civil Aviation Authority put together a case study of pre- and post- lair transportation liberalisation agreements between India and the UK. The Civil Aviation Authority focuses primarily on the effects that this agreement has had to date on aviation in the UK. They laid out the report in four sections: impact on consumers; impact on the airlines; impact on the airports; and impact on the wider economy.

1.5.3.1 Impact on consumers

Consumers were the biggest beneficiaries of the air transportation liberalisation agreement between India and the UK, due to the increased number and choice of services, destinations and airlines operating between these two countries. Between summer 2004 and summer 2006, the number of direct flights between India and the UK rose from 34 to 112 per week. This can be seen in Figure 1.5-2 overleaf, which shows growth in U.K. – India direct services between 2000 and 2006.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 23 Figure 1.5-2 Growth in UK-India direct services 2000-2006

Source: United Kingdom Civil Aviation Authority, 2006

The majority of the new flights are operating between the main airports of India and the UK– London Heathrow (an increase of 77 services per week), Delhi (an increase of 23 services per week) and Mumbai (an increase of 38 services per week). However, new flight origins and destinations have been added in both the UK and in India– Birmingham, Amritsar and Bangalore. This increase in services has been provided by a combination of airlines which were already serving the market (British Airways, Virgin and Air India) and new entrant airlines (JetAirways, bmi and Air Sahara.) Figure 1.5-3, overleaf, shows the added airports and airlines serving the market.

Furthermore, the increase in capacity and more intense competition has resulted in a reduction in air fares, from £882 to £736 for one-way fare paid by passengers travelling for business class and £251 to £231 for one-way fare paid by passengers travelling economy class. Airlines have had to discount fares to compete for customers.

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 24 Figure 1.5-3 Breakdown of direct services to India in summer 2004 and 2006

Source: United Kingdom Civil Aviation Authority, 2006

1.5.3.2 Impact on Airlines

The impact of air transportation liberalisation agreements on airlines is both positive and negative. The increased competition reduces profits, whilst the new commercial freedoms enabled previously excluded carriers to enter the market, offering services for the first time. The frequency market shares for the carriers before and after liberalisation can be seen in Table 1.5-4 below. This shows that the liberalisation of the aviation market led to more competition and reduced the oligopolistic and uncompetitive nature of this previously regulated market.

Civil Aviation Authorities modelling shows that while UK airlines benefited from an increase in revenue of £30 million between 2004 and 2005, reductions in fares reduced profits by £46 million.

Table 1.5-4 Frequency market shares at the beginning of IATA Summer 2004 and 2006 seasons

Summer Summer Airline 2004 2006 British Airways 56% 37% Virgin Atlantic 9% 12% bmi 0% 6%

Air India 35% 22% Jet Airways 0% 20% Air Sahara 0% 3% Total 100% 100% Source: United Kingdom Civil Aviation Authority, 2006

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 25 1.5.3.3 Impact on Airports

The benefit to airports from air transportation liberalisation agreements is the added revenue brought about by the increase in services from the added number of flights. Civil Aviation Authorities modelling suggests a net benefit to UK airports of around £12 million of additional profits from increased revenues of £65 million. The paper did not quantify the impact on Indian Airports. Airports such as Amritsar and Bangalore, which were previously not served, now accommodate international flights to and from the UK. Figure 1.5-4 below shows the growth of point-to-point markets from the UK to India. As can be seen, the air transportation liberalisation agreement benefited the existing airports as well as new airports accepting international flights.

Figure 1.5-4 Growth of direct point-to-point markets from the UK to India

Source: United Kingdom Civil Aviation Authority, 2006

1.5.3.4 Impact on the wider economy

The impact on the wider economy is mostly made up of circumstantial evidence in the report. Trade levels between the UK and India increased by approximately 25% from 2005 to 2006. Foreign direct investment by Indian companies into the UK grew by 110 % in the same period. While it is difficult to demonstrate that the air transportation liberalisation agreement was responsible for this, the results suggest that the agreement was certainly a contributor. The Civil Aviation Authority stated that “this point is supported by survey data for the latest available years (2004 to 2005) which shows that direct

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates P a g e | 26 business traffic has grown at a similar rate to leisure traffic in the year 2004 to 2005 (37 per cent compared to 48 per cent), suggesting that aviation liberalisation is facilitating greater business activity between the two countries.” Added to this circumstantial evidence is the fact that India’s strong economic growth is being partly driven by a move into higher-value, more export-orientated sectors such as IT and pharmaceuticals, which have a requirement for air transportation. The growth in the frequency and capacity of direct UK-India flights is likely to have a further effect on the development of these businesses. It is also important not to forget that there has been substantial growth in tourism between these two countries.

1.5.4 Impact of an international air transportation liberalisation agreement

The InterVISTA-ga2 report attempts to measure the impact of a global liberalisation of aviation agreements. The impacts were measured in

Passenger seats, Air freight traffic, Employment, Gross domestic product, Tourism and Catalytic investment impacts for any country-pair. Most of the base data used in the models came from various case studies that analysed the various changes in the measurements when aviation regulations were liberalised. Time series and cross sectional models were then used to assess the impact of air transportation liberalisation.

The findings of the United Kingdom Civil Aviation Authority, 2006, report estimated that if 320 pair country markets, currently not in an air transportation liberalisation mode, liberalise their air service agreements air traffic would grow by 63%, significantly higher than recent world traffic growth of around 6 - 8% per annum. This growth could potentially create 24.1 million full-time jobs and generate an additional $490 billion in GDP, which is the equivalent of an economy the size of Brazil.

1.6 Forecasted effects of air transportation liberalisation agreements

The case study approach in Section 1.5 paints air transportation liberalisation agreements in a very positive light and suggests that only benefits accrue to countries that open up their airspaces and airports. However, air transportation liberalisation agreements do not always have the impact hoped by countries entering negotiations, as shown in studies conducted by Micco and Serebrisky (2006) and Swan (2008).

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Muller Associates P a g e | 27 There are two essential issues discussed by Micco, et al, (2006) and Swan (2008) that should be considered before a country enters into an air transportation liberalisation agreement:

These two questions have particular relevance for Africa and more specifically for the Southern African Development Community. In this section we will discuss and highlight the outcomes and recommendations of Micco, et al, (2006) and Swan (2008).

1.6.1 Infrastructure, regulatory body, skills and market size limitations

The first study undertaken by Micco, et al, (2006), made use of regression analysis to estimate the effect that air transportation liberalisation agreements had on transport costs. They primarily used data on air transport costs from the US Imports of Merchandise Database. The data covered the period 1990 to 2003, where the US entered into a number of air transportation liberalisation agreements with various countries. This period provides ample time to analyse these agreements and assess their effects in totality.

Further data used in the regression included:

The distance between the freights origin and its destination in the US. This is an important consideration as distances between origins and destinations do not change when air transportation liberalisation agreements are concluded, and the price of jet fuel price is unaffected by these agreements. GDP and GDP per capita in US dollars for both the origin of the freight and its destination in the US. The percentage of the population which resides in urban areas, as it was assumed that the vast majority of air freight is generated from urban and peri-urban areas. Certain data on airports and cities; these geographic coordinates, population of major urban cities, number of paved runways, as well as runway lengths and widths. An infrastructure skills index.

The econometric model used in Micco, et al, (2006), is shown in equation (2) overleaf. The coefficients are shown in Table 1.6-1 overleaf. The results display the cross sectional analysis of regression on transport costs. It can be seen in Table 1.6-1 that the product unit value (which is the value per unit weight of cargo at 4-digit SITC) and distance per port of entry (which is the distance between the origin of the air freight and the destination in the US) have the highest positive coefficients, meaning that total transport cost increases most significantly for each additional km travelled or value per unit weight of freight transported. Improved foreign airport infrastructure reduces transport costs by the greatest

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Muller Associates P a g e | 28 amount, whilst the benefit of an air transportation liberalisation agreement has a much smaller impact on transport costs than expected.

The figures in brackets in Table 1.6-1 show the standard error, and it can be seen that the standard error for certain coefficients is so slight that we can assume these to be close to correct. However, the standard error for Total Volume, Imbalance and Open Sky Agreement vary quite significantly. It is also reported on Table 1.6-1 that Distance per port of entry, Product unit value, Foreign airport infrastructure index and the implied effect infrastructure index are all significant at 1%, this tells us that we are 99% confident that these variables have an effect on transportation costs. These results tell us that the distance of an airport, the value of the product being shipped and the infrastructure of the foreign airport have the largest significant effect on transportation costs.

Table 1.6-1 Section analysis of regression on transport costs

Distance per port of entry (ln) 0.244 S.E. (0.04) significant at 1% Total volume (ln) 0.001 S.E. (0.02) Product unit value (ln) 0.476 S.E. (0.011) significant at 1% Imbalance -0.079 S.E. (0.072) Air transportation liberalisation agreement -0.04 S.E. (0.046) Foreign airport infrastructure index II (FAII1) -0.39 S.E. (0.119) significant at 1% Regulatory quality -0.15 S.E. (0.04) Implied effect infrastructure index -0.183 significant at 1% Sample All countries R-squared 0.335 Source: Micco, et al, (2006)

Equation (2): Transport cost origin-destination = dummy variable + distance origin-destination + total volume origin-destination + product unit value origin-destination + trade imbalance origin-destination + foreign airport infrastructure origin + regulatory quality origin + air transportation liberalisation agreements + error term

Further analysis was conducted on the air transportation liberalisation agreement coefficient in this study but more noteworthy are the results shown in Figure 1.6-1 overleaf. As seen in Figure 1.6-1, the coefficient on air transportation liberalisation agreements increases in size with each year, indicating that air transportation liberalisation agreements have more of an impact on reducing transport costs the longer the time period elapsed since implementation. This is to be expected as air markets need time to adjust to the new regulations when significant changes take place. Micco, et al, (2006) primarily focused

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Muller Associates P a g e | 29 on air freight transport. They eventually estimated that over a period of five or more years, an air transportation liberalisation agreement could potentially reduce air freight transport costs by roughly 9% and increase foreign trade by 12%.

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Muller Associates P a g e | 30 Figure 1.6-1 The effect of air transportation liberalisation agreements on air transport costs over time

Source: Micco, A. et al 2006

The most important finding in this paper is that air transportation liberalisation agreements do not have the same effects in all countries. For instance air transportation liberalisation agreements in developed and upper-middle- income developing countries reduce air transport costs, but for low-income developing countries air transportation liberalisation agreements are not associated with a fall in freight rates. This is understood as an indication that low-income developing countries cannot take full advantage of air transportation liberalisation agreements because of other barriers to competition or because of their limited market size. Micco, et al, (2006) also find that countries with better access to airports, well trained airport staff, adequate airport infrastructure and better regulatory quality, have lower air transport costs.

Therefore, if air transportation liberalisation agreements are to be maximised to their full potential these issues need to be dealt with first:

Sufficient airport infrastructure needs to be in place .i.e. Appropriate runway lengths and widths, modern air traffic control systems etc. Staff needs to be skilled in the various areas required to run an efficient air service. Regulatory structures need to be in place to monitor the air market. The market size of the country needs to be assessed and increased. Cargos and manufactured products (such as certain agricultural products, as well as electronic and highly technological goods) that are transported by air freight need to be assisted and initiated. Other barriers to competition could range from political unrest and corruption to restrictive government policies. All of these need to be addressed in order for air transportation liberalisation to be successful in a country.

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Muller Associates P a g e | 31 1.6.2 Spread of development from hubs to outlying areas

The second study by Swan (2008) investigates how regulated markets have constrained travel within the region. Swan (2008) lists techniques for forecasting air transportation levels in deregulated air markets, highlighted in Section 1.5 above (the ‘Aviation forecasting models’). The paper moves on to review forecasts by Boeing and Airbus for regional growth in air travel and air freight, by comparing these to recent trends in growth and forecasts conducted by the author.

Table 1.6-2 below shows the forecasted growth in air travel between North-East Asia and North America predicted by Airbus, Boeing and Swan. As can be seen these growth levels fluctuate between 5% - 6.5% over 10 and 20 year periods.

Table 1.6-2 Forecasts in North-East Asian travel to North America

Swan Boeing Airbus Boeing 10yr 20yr 20yr China 5.1% 6.4% 6.4% Japan 5.3% 5.1% 5.0% 4.2% Korea 5.9% 5.1% 5.6% 5.9% Source: adapted Swan, W. 2008

Figure 1.6-2 Actual air travel between North-East Asia and North America

Source: Swan, W. 2008

The report reveals how accurate these growth levels are by comparing them to the actual trends in air travel growth to North America for the periods of 2007 and 2008. The actual air travel between these two regions can be seen in Figure 1.6-2 above

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Muller Associates P a g e | 32 . Air travel between Japan and North America decreased during this period, while air travel grew at a much higher rate than expected in China and Korea. Swan (2006) explains such differences between the actual figures and the forecasts by stating: “the lesson here is that useful regional forecasts need to start with good regional data, and they need to recognize changes in routes, fares, and political constraints specific to the markets.”

The models used to forecast air travel growth are unable to account for changes in routes and route development, and this tended to be the main reason the forecasts differed so much from the actual data in air travel. Swan (2008) found that actual growth levels in air travel were similar to GDP growth levels for each of the countries concerned.

One of Swan’s (2008) major findings in this report was that air services dramatically increased travel to cities outside the existing list of major gateways, allowing them to participate to a much greater degree in international trade. This is an important point for the Southern African Development Community to take into account, as air travel and services may shift away from O.R. Tambo Airport in South Africa, to outer lying airports in the region. Hence it is these smaller airports which may stand to benefit the most from an air transportation liberalisation agreement and this may be at the expense of larger airports. Over time an air transportation liberalisation agreement could help small regional and airports develop by attracting more air traffic and economic activity into these regions, but at the same time O.R. Tambo may lose air traffic and potential revenue.

1.7 Concluding Comments

From the literature reviewed we can conclude that air transportation liberalisation initiatives that have been pursued are mostly successful in regions where implemented, provided that there is adequate airport and tourism infrastructure. The literature would seem to suggest strongly that the deregulation of the air space over Africa and the Southern African Development Community would bring about significant changes to the structure and makeup of the current air market in Africa, and add value to the economies of Africa. The level of change would depend on the how many freedoms of the air would be permitted.

A number of African national flag carrier airlines would be the most vulnerable to these changes, as it was reported in European region that low cost carrier airlines were the most likely to benefit from air transportation liberalisation legislation. National flag carrier airlines would need to cut costs and move towards efficient practices (similar to those of low cost carriers); they would also lose out on potential revenue and market share as low cost airlines compete for passengers around Africa and the Southern African Development Community. African tourism and business relationships would stand to gain the most from an air transportation liberalisation agreement.

Crucial to the success of an air transport liberalisation agreement being implemented in the SADC region and ultimately the African continent as a whole is the establishment of a competition authority. The primary role of this authority would to discourage anti-competitive behaviour, allow easy access for new

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Muller Associates P a g e | 33 African airlines wishing to enter the market and ensure that no airline abuses a position of market dominance. Furthermore this regulator could ensure that African governments remove aviation regulations in the time frames agreed upon. It is therefore necessary that African member states to this agreement give this body ultimate authority and the power to enforce the terms of the agreement among reluctant states, airlines and airports.

The literature reviewed also shows that air freedoms 1 – 5, along with air freedom 8 encompasses the standard package for an air transportation liberalisation agreement. Furthermore the literature forecasts that if there were a global liberalisation of aviation markets, then air traffic would grow significantly. This growth in air traffic would be create large amounts of additional full time employment, as well as contributing hundreds of billions of additional dollars to global GDP (this extra GDP was estimated to be equivalent to that of total Brazilian GDP.) The impact of air transport liberalisation agreement being implemented in SADC is discussed and forecasted in the sections to follow.

An important consideration raised by the literature is that in order to take advantage of air transportation liberalisation agreements, appropriate aviation infrastructure and skills are required, namely– airport infrastructure, airline and airport efficiencies, regulatory controls, market size, the population’s ease of access to airports and aviation markets, and political and business stability. Without these conditions, countries will not be able to take advantage of these liberalised regulations. Furthermore, the literature recognised that air transportation liberalisation would divert flights away from hub airports, as passengers would demand more direct flights. It is necessary to assess whether the current hub airports in SADC could sustain themselves in the future as further use is made of alternative airports within the region.

Whilst the following sections will only estimate the impact of an air transportation liberalisation agreement on the SADC region, it would be advisable for the Department of Transport to further investigate the functions and make up of a regulatory body that would be necessary to assist in implementing the air transportation liberalisation agreement for the entire region.

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Muller Associates P a g e | 34 2 Impact of air transport liberalisation agreement in Southern African development Community

2.1 Introduction

This study sets out to determine the impact of implementing an air transport liberalisation agreement in SADC. The following measures of liberalisation have been taken into account throughout the remained of this section:

Only airlines operating in SADC should benefit from the implementation of air transport liberalisation agreement in SADC; The granting of up to 5th air freedom rights plus cabotage, the 8th air freedom right; Encouraging the development of new routes; Removal of capacity restrictions on passenger seats, freight and flights on certain routes; The removal of expensive and complex tariff regulations; The elimination of all protective policies in favour of national flag carriers; The termination of regulations on carriers’ alliance; Doing away with restriction on the conversion of revenues to hard currency and repatriation; Agree on code sharing; and Allow carriers to have own-ground-service abroad

After considering the above agenda and the general experience with air transportation liberalisation initiatives elsewhere in the world, the research team determined that if an air transport liberalisation agreement were to be implemented within the SADC region, two results can be expected:

a) That there will be impacts within the aviation market; and b) There will be impacts felt within supporting industries to the aviation market. The impacts that will be felt within the aviation market are termed as direct impacts and the impacts experienced within the supporting industries are termed as indirect impacts.

An assessment of both the direct and indirect impacts will be used to determine the costs and benefits of implementing the an air transport liberalisation agreement within the SADC region. This method is known as cost-benefit analysis (CBA).

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Muller Associates P a g e | 35 The study identified the following direct and indirect impacts:

Direct impacts: Indirect impacts: On Airlines On Tourism On Airports On Airport services Passengers Aircraft manufacturers Freight Environment Customs Intermodal services Government

Based on available data, direct and indirect impacts are calculated and utilised in the cost benefit analysis. Data used includes feedback from stakeholders via the questionnaire and other sources..

A diagram that illustrates the various components of the cost benefit analysis can be viewed in the Appendix D.

It is observed that the quantifiable benefits of implementing an air transport liberalisation agreement in SADC far outweighs the quantifiable costs of such an implementation over the 50 year period.

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2.2 Overview of the Current Status of the SADC Aviation Industry

SADC flight departure data indicates that certain airlines in SADC service mainly domestic routes and service very few international routes, while other airlines are largely reliant on international business. The following analysis focuses on the number of domestic and international departures for major airlines in the SADC region. The general trend for most airlines indicates that there has been a gradual increase in the total number of departures over the years; however a decrease in total departures is noted during the 2007 to 2009 periods for smaller airlines, in all likelihood as a result of the downturn in the global economy over this period. Although the September 11 attacks reduced worldwide air travel significantly, most SADC airlines were unaffected. Other major scares such as the SARS virus and Swine flu also had little impact on most SADC based airlines. SADC airlines more commonly encountered periodic problems due to internal issues such as financial losses, inefficiency and safety of aircraft or due to localised external problems such as political instability in countries where the airlines operate. It is noted that national carriers generally split departures between international and domestic while low cost carriers mainly undertake domestic flights.

A country by country analysis follows.

2.2.1 Angola

There are currently 9 airlines operating in Angola. Non-availability of data for these airlines prevents analysis of the current and past trend in departures and passenger numbers. Fleet sizes for the airlines were available and are illustrated in Figure 2.2-1 overleaf.

The largest fleet belongs to SonAir with 32 aircraft. SonAir is a privately owned airline that specialises in transporting passengers to and from offshore and onshore oil industry facilities. The airline also provides services to other businesses, single entities, charter services within Africa, and private and government businesses. It operates from 7 regional airports within Angola and internationally to Houston with the aid of World Airways. SonAir also provides helicopter services to businesses.

The national operator TAAG Angola Airlines has 12 aircraft and flies to Cameroon, Cape Verde, Central African Republic, DRC, Congo, Mozambique, Namibia, Sao Tome and Principe, South Africa, Zambia, Zimbabwe, Cuba, Brazil, China, United Arab Emirates and Portugal internationally. It operates from 16 airports within Angola. TAAG has code share agreements with Air France, Brussels Airlines, British Airways and Lufthansa.

Diexim Expresso operates regional flights, VIP flights and charter flights between Angola and Namibia. It operates from 5 destinations within Angola. Air 26 also provides domestic services within Angola and operates from 7 airports within Angola. Alada provides passenger and cargo charter services throughout Angola and to other parts of Africa. Air Gemini is a cargo airline mainly servicing the diamond mines and undertaking humanitarian missions. Aeronautica provides charter freight and passenger services.

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Angola Air Charter is a charter airline specialising in charters within Africa and to Europe, particularly to Belgium and the Netherlands. Transafrik is a cargo airline.

Figure 2.2-1 Fleet size – Airlines in Angola

12 7 8 8 5 3 2 1

2.2.2 Botswana

Air Botswana is the national airline of Botswana. The airline was faced with numerous financial problems since 1988 as can be seen on Figure 2.2-2 overleaf. In 1994, the government had to write off losses of over 50 million Pula as the airline was unable to cope with the financial demands being made upon it. The airline began to pick up after the losses were written off and both domestic and international departures began to increase. The airline recorded a net profit for the years 1998 and 1999, but expenses exceeded revenues in 2000 resulting in a drop in net profit for that year. The airline was hard hit when a pilot on a suicide mission crashed into two other planes at the airport. The airline had to lease an aircraft after the incident in order to resume operations.

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Figure 2.2-2 Air Botswana Financial data

30 25 20 15 10 5

US $ $ (Million) US 0 -5 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 -10 -15

Operating Revenues Operating Expenses Net Profit

Departures increased over the years as the government attempted to privatise the airline due to recurring losses. Negotiations to privatise failed and the airline resumed operating at a loss. Although the airline is faced with many challenges, international and domestic departures continued to increase over the years indicating that there is demand for travel into and out of Botswana regardless of the financial turmoil of the airline. Departures data can be seen on Figure 2.2-3 overleaf. Air Botswana has a greater number of international departures than domestic departures; this would indicate that Gabarone Airport is the primary destination for businessman and tourist entering Botswana. It must also be considered that Botswana is considered one of the stronger economies of southern Africa with lucrative diamond exports due to the presence of the world’s largest and richest diamond mine attracting thereby attracting flights and passengers.

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Figure 2.2-3 Air Botswana Domestic and International departures

8000 7000 6000 5000 4000 3000 2000 1000 0 1992 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Domestic International

While the airline has struggled financially over the years, statistics show that passenger numbers have not suffered. Air Botswana experienced an increase in both domestic and international passengers over the years. Air Botswana flies to 4 airports within Botswana and internationally to South Africa and Zimbabwe. Air Botswana has a greater number of international passengers than domestic passengers indicating that travel within Botswana is not as popular as international travel. Both International and domestic passenger volumes have been increasing over the years as can be seen on Figure 2.2-4 below.

Figure 2.2-4 Air Botswana Domestic and International passengers

180000 160000 140000 120000 100000 80000 60000 40000 20000

1991 1994 1990 1992 1993 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

AirBotswana Domestic AirBotswana International

Air Botswana has 6 aircraft in its fleet. The airline has three ATR 42-500s, two ATR 72-500s and one Boeing 737-200 aircraft. The fleet size is illustrated in Figure 2.2-5 overleaf.

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Figure 2.2-5 Air Botswana Fleet

ATR 42-500 ATR 72-500 Boeing 737-200

2.2.3 Democratic Republic of the Congo (DRC)

There are 7 airlines currently operating in the DRC. Hewa Bora Airways is the largest airline in DRC and operates regional and domestic routes. It operates from 8 airports within DRC and also flies to the Republic of the Congo and to South Africa. Filair operates within DRC and flies to 5 airports within the DRC. Air Tropiques provides domestic, regional and charter flight services. Air Kasai operates charter services within Africa. Business Aviation provides domestic and international air services. It flies within the DRC and internationally to Brazzaville and Pointe-Noire. Comapgnie Africaine d’Aviation operates domestic routes within the DRC to 8 airports. Wimbi Dira is a charter, passenger and cargo airline flying to the main cities in the DRC. All the airlines based in the DRC are prohibited from entering European airspace due to sub-standard safety management practices. Fleet sizes of the above airlines can be seen on Figure 2.2-6 overleaf.

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Figure 2.2-6 Fleet size – DRC Airlines

6 5 5

3 2 2

Air Kasai Air Business Compagnie Filair Hewa Bora Wimbi Dira Tropiques Aviation Africaine D Airways Airways Aviation

2.2.4 Lesotho

Air Lesotho was a government owned national airline and operated on both domestic and international routes. The airline ceased international operations in 1996 due to the inability to satisfy the minimum requirements specified by the Department of Civil Aviation. As can be seen on Figure 2.2-7 below, domestic and international departures decreased drastically over the years until it stopped operations in 1996. At the end of 1996, the airline was financially insolvent and ceased to operate.

Figure 2.2-7 Air Lesotho Domestic and International Departures

5000

4000

3000

2000

1000

0 1990 1991 1992 1995 1996

Domestic International

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2.2.5 Madagascar

In Madagascar an average of 15,000 departures were recorded between 1990 and 1998. Most of these were domestic departures with a small portion of international departures. In the late 1990s the country was recovering from years of political instability. In the 1998 elections, President Ratsiraka was re-elected, restoring some confidence in the country. Both domestic and international departures increased. Domestic departures rose from 14,472 to 19,771 in 1999 while international departures increased from 1,885 to 2,260. The country enjoyed a few years of growth and stability but confidence was quickly lost when the country held new elections in December 2001 which led to sporadic violence due to ethnic clashes and the political crisis ensued until July 2002.

Departures recovered from the sharp drop in 2002 and returned to average departures by 2003. Madagascar recorded its highest ever tourist numbers in 2007. This can be seen on Figure 2.2-8 below where both domestic and international departures more than doubled from 2006. Domestic departures increased by 145% from 11,115 to 27,238 departures, while international departures increased by 220% from 3,168 to 10,168 departures in 2007.

In 2008, departures dropped drastically from the previous record high of 2007 due to the onset of a global economic recession and renewed political instability in the country. The majority of tourists flying to Madagascar are from France and, as a result, the global recession had a significant impact on tourism to Madagascar. In 2009, a coup to overthrow the government led to political riots indicating that the country was politically unstable. The swine flu pandemic further fuelled fears for international travellers as many countries around the world proved vulnerable, mainly in South America and Africa, due to perceived limited resources for curbing a potential epidemic.

Figure 2.2-8 Air Madagascar Domestic and International departures

40000 35000 30000 25000 20000 15000 10000 5000

2007 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2008 2009

Domestic International

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Passenger numbers for Air Madagascar are reflected in the figure below. As is seen in the departures Figure 2.2-8 on the previous page, Air Madagascar experienced a sharp decline in the number of domestic and international passengers in 2002 and again in 2009 due to political instability and a global recession visible on Figure 2.2-9 below. The national government owned airline is directly affected by instability in the country. The political situation in Madagascar has damaged the economy.

Figure 2.2-9 Air Madagascar Domestic and International passenger numbers

500000

400000

300000

200000

100000

2009 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

AirMadagascar Domestic AirMadagascar International

Air Madagascar recorded the largest number of domestic and international passengers in 2001 and 2007 while the lowest number of passengers was experienced in 2002 and 2009.

Although Madagascar has been plagued with years of political unrest, the airline has managed to break even over the years barely covering expenses with revenues as seen on Figure 2.2-10 overleaf. The decline in the economy in 2001 and 2002 affected the airline’s revenues resulting in losses in the years 2001 and 2002. The airline recovered in 2003 and managed to record a profit. By 2008 the airline once again recorded a loss as the country was once again impacted with fresh political turmoil.

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Figure 2.2-10 Air Madagascar Financial Data

160 140 120 100 80 60 40 US $ $ (Million) US 20 0 -20 -40

Operating Revenue Operating Expenses Net Profit

There are two Madagascar based airlines operating in Madagascar, Air Madagascar and Tiko Air. Tiko Air provides charter services within Madagascar. Figure 2.2-11 below shows the fleet size of both airlines.

Figure 2.2-11 Fleet size – Madagascar airlines

Air Madagascar Tiko Air

2.2.6 Malawi

Air Malawi is the national airline of Malawi. The airline mainly services domestic routes and has a few flights on international routes. It operates from 2 airports in Malawi and flies to South Africa, Tanzania, Zambia and Zimbabwe, internationally. Data is only available for the years 1990 to 1993 seen on Figure 2.2-12 overleaf. Domestic departures make up a larger portion of total departures while international departures have remained constant at about 1,100 annually. The government has since attempted to

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Muller Associates Department of Transport P a g e | 44 privatise the airline however all negotiations have been unsuccessful. The airline has generally operated at a loss over the years; however, the airline posted a profit for the year 2007.

Figure 2.2-12 Air Malawi domestic and international departures

4500 4000 3500 3000 2500 2000 1500 1000 500 0 1990 1991 1992 1993

Air Malawi Domestic Air Malawi International

As can be seen on Figure 2.2-13 below, both domestic and international passengers patronising Air Malawi remained fairly constant for the years 1990 and 1991 but an increase of 11% and 8% for domestic and international passengers respectively was recorded in 1993.

Figure 2.2-13 Air Malawi Domestic and International Passengers

70000 68000 66000 64000 62000 60000 58000 56000 54000 52000 1990 1991 1992 1993

Domestic International

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Air Malawi has 4 aircraft in its fleet. The airline has 1 ATR 42-320 and 3 Boeing 737-200s illustrated in Figure 2.2-14 below.

Figure 2.2-14 Air Malawi Fleet

ATR 42-320 Boeing 737-200

2.2.7 Mauritius

Air Mauritius mainly services the international market as Mauritius is regarded as one of the world’s best holiday destinations. Over the years, Mauritius has become very popular for its sandy beaches and friendly hospitality as well as its 5 star resorts. Mauritius is also a very stable country, politically. It boasts a rich cultural heritage, superior diving and fishing spots, great food and tropical weather conditions. Departures to the only domestic destination, Rodrigues (Sir Gaetan Duval Airport) are very few in number as can be seen in the figure overleaf.

Air Mauritius flies to over 30 destinations around the world. In Africa, Air Mauritius operates to South Africa, Kenya, Madagascar and Reunion. Departures for Air Mauritius were highest in 2004 and 2005 but have since dropped to lower levels. A drop in departures in 2008 and 2009 in Figure 2.2-15 overleaf can be attributed to the global recession as many foreign travellers opted not to travel. The country depends heavily on tourism. A drop in departures is also attributed to a change and upgrade in the airline’s fleet.

Air Mauritius reduced the operation of two older aircraft in 2007 while awaiting delivery of new aircraft to permit an increase in operations to major destinations such as India, Malaysia, Singapore and Perth.

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Figure 2.2-15 Air Mauritius Domestic and International departures

16000 14000 12000 10000 8000 6000 4000 2000

2000 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2001 2002 2003 2004 2005 2006 2007 2008 2009

Air Mauritius Domestic Air Mauritius International

The main focus of the airline is its international clientele. Over the years the number of international passengers has grown steadily reaching a peak in 2007. Although the global recession has resulted in a decrease in international travel, the number of international passengers serviced in 2009 was still quite high at over 100,000 as illustrated in Figure 2.2-16 below.

Figure 2.2-16 Air Mauritius Domestic and International passengers

1400000

1200000

1000000

800000

600000

400000

200000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Air Mauritius Domestic Air Mauritius International

Air Mauritius has 12 aircraft in its fleet. The fleet comprises of 2 Airbus A319-100s, 2 Airbus A330-200s, 6 Airbus A340-300 and 2 ATR 72-500s as seen in Figure 2.2-17 overleaf.

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Figure 2.2-17 Air Mauritius Fleet

2 2 2

Airbus A319-100 Airbus A330-200 Airbus A340-300 ATR 72-500

2.2.8 Mozambique

Linhas Aereas de Moçambique (LAM) is the national airline of Mozambique. Between 1977 and 1992, Mozambique suffered an intense civil war. President Chissano worked hard to reform the country and the civil war ended in October 1992. Over 1.5 million Mozambicans fled the country to neighbouring states but began to return by mid 1995. The country suffered severely and this is visible in Figure 2.2-18 overleaf where both international and domestic departures dropped significantly up to the 1992 to 1994 period.

By 1996, the country began to recover stability, leading to an improvement in the local economy. Elections held in December 1999 were peaceful and thus had little impact on tourism. Both domestic and international departures began to increase gradually over the years and have peaked for the moment in 2009. Mozambique is popular for its beaches and diving resorts, attracting mostly tourists from neighbouring states. The global recession in 2008 has therefore had little impact on departures as tourists opt to choose destinations closer to their home countries to contain costs.

Since Mozambique’s main tourist market is within southern Africa, an increase in total departures indicates that the Mozambique tourism industry has not been impacted as adversely as many international holiday destinations.

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Figure 2.2-18 LAM Domestic and International Departures

12000

10000

8000

6000

4000

2000

0 1990 1991 1992 1993 1994 1996 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

LAM Domestic LAM International

Figure 2.2-19 below shows that both domestic and international passengers on LAM have increased over the years indicating that the country has recovered from its previously adverse political situation. Domestic passengers are much higher as LAM flies to 10 domestic destinations within Mozambique while international routes operated include Angola, Kenya, Portugal, South Africa and Tanzania.

Figure 2.2-19 LAM Domestic and International Passengers

400000 350000 300000 250000 200000 150000 100000 50000 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

LAM Domestic LAM International

LAM has 6 aircraft in its fleet as seen on Figure 2.2-20 overleaf. Its fleet consists of one Antonov An-26, three Boeing 737-200s and two Embraer E-190 LR/ARs.

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Figure 2.2-20 LAM Fleet

Antonov An-26 Boeing 737-200 Embraer E-190 LR/AR

2.2.9 Namibia

Air Namibia is the national airline of Namibia. In 1994, majority of Air Namibia’s operations were domestic; however domestic departures have decreased over the years and had halved between 1994 and 2000. International departures have increased over the years to almost double the 1994 level in 2000. Departures figures for the years 1994, 1996 and 200 are illustrated in Figure 2.2-21 below. Air Namibia has been upgrading aircraft over the years and has 2 Airbus A340-312s which has enabled the airline to cut costs and increase efficiency. Air Namibia currently flies to Angola, Zimbabwe, Botswana, South Africa and Germany on its international routes and operates from 7 airports within Namibia.

Figure 2.2-21 Air Namibia Domestic and International Departures

8000

6000

4000

2000

0 1994 1996 2000

Air Namibia Domestic Air Namibia International

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Air Namibia has a relatively large number of international passengers compared to domestic passengers as can be seen in Figure 2.2-22 below. Both international and domestic passenger numbers have increased over the years 1994 to 2000. The airline suspended flights to Switzerland and UK in 2009 but still flies to Germany in Europe.

Figure 2.2-22 Air Namibia Domestic and International Passengers

250000

200000

150000

100000

50000

0 1994 1995 1996 1997 1998 1999 2000

Domestic International

The Air Namibia fleet comprises of two Airbus A340-300s, one Boeing 737-200, two Boeing 737-500s, one Boeing 737-800 and two Raytheon Aircraft Beechcraft 1900D Airliners seen in Figure 2.2-23 below.

Figure 2.2-23 Air Namibia Fleet

2 2 2

1 1

Airbus A340-300 Boeing 737-200 Boeing 737-500 Boeing 737-800 Raytheon Aircraft

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2.2.10 Seychelles

Air Seychelles is the national airline of Seychelles and is wholly owned by the Seychelles Government. Seychelles is a popular holiday destination offering a spectacular beach holiday. The airline has been operating successfully over the years with both domestic and international departures increasing over the years as seen in Figure 2.2-24 below. The airline offers domestic flights as well as international flights. It operates from 3 airports within the Seychelles and also flies to Mauritius, South Africa, Singapore, France, Italy and the United Kingdom, internationally.

Figure 2.2-24 Air Seychelles Domestic and International Departures

20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0 1990 1993 1996 1997 1998 1999

Domestic International

Many passengers fly into the main airport in Mahe and take flights internally to the Praslin and Bird Island airports. As can be seen on Figure 2.2-25 overleaf, domestic and international passengers have been increasing over the years. International passengers decreased in 1998 and 1999 as many routes previously serviced were discontinued. The airline stopped flying to Kenya, Israel, Spain and Manchester in 1998 and discontinued operations to India, the Maldives, Thailand, United Arab Emirates, Frankfurt and Munich in Germany, Russia and Switzerland between 2000 and 2010.

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Figure 2.2-25 Air Seychelles Domestic and International passengers

300000

250000

200000

150000

100000

50000

0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

Air Seychelles Domestic Air Seychelles International

Air Seychelles has 9 aircraft in its fleet as seen in Figure 2.2-26 below. Its fleet comprises of 1 Boeing 767-200, 1 Boeing 767-200ER, 3 Boeing 767-300ERs, 3 DHC-6 Twin Otter Series 300s and 1 Shorts 360- 300.

Figure 2.2-26 Air Seychelles Fleet

3 3

1 1 1

Boeing 767-200 Boeing 767- Boeing 767- DHC-6 Twin Shorts 360-300 200ER 300ER Otter Series 300

2.2.11 South Africa

South Africa is served by 18 locally based airlines providing services to both the domestic and the international markets. Some of the larger airlines are South African Airways (SAA), SA Airlink, Comair,

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Mango Airlines and 1time Airlines. Smaller airlines provide charter and air cargo services and specialise in providing services to private businesses and VIP customers.

South African Airways (SAA) is the national carrier for South Africa. It has been operating for more than seventy years and is a member of the Star Alliance global network. It has code share agreements with United Airlines, Air New Zealand, Lufthansa and other Star Alliance partners. SAA flies to 5 domestic destinations and 32 international destinations worldwide.

SAA recorded very low international and domestic departures in 1990 and 1991 as the country was emerging from apartheid rule and the country faced international sanctions that prohibited travel into and out of South Africa. By 1993, the government began to prepare for democratic elections and sanctions against South Africa were dropped allowing for freer travel to and from South Africa. A surge in domestic and international departures followed in 1993 and 1994 as confidence in South Africa was slowly restored as seen in Figure 2.2-27 below. Lack of data between 1995 and 2001 does not allow for analysis of air travel into and out of South Africa, however from 2002 to 2009, there has been a consistent increase in international departures while SAA domestic departures have decreased over these years due to the introduction of many low cost airlines into South Africa. SAA began to lose its majority share in the domestic market as more airlines began offering seats on competing routes at lower prices. The global recession appears to have had a very small impact, resulting in a small decrease in total departures in 2009.

Figure 2.2-27 South African Airways Domestic and International departures

80000 70000 60000 50000 40000 30000 20000 10000 0 1990 1991 1993 1994 2002 2003 2004 2005 2006 2007 2008 2009

Domestic International

Passengers travelling on both domestic and international routes on SAA have consistently increased over the past 7 years as illustrated on Figure 2.2-28 overleaf. Domestic passengers have shown a slight decline since 2007 because many passengers opted to travel on other airlines within South Africa due to affordability and flexibility.

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Figure 2.2-28 South African Airways Domestic and International passengers

5000000

4000000

3000000

2000000

1000000

0 2002 2003 2004 2005 2006 2007 2008 2009

SAA Domestic SAA International

SA Airlink has been an alliance partner with South African Airways and South African Express since 1997. SA Airlink operates on domestic routes within South Africa and flies to Bulawayo, Harare, Tete, Beira, Antananarivo, Pemba, Livingstone, Lusaka, Maseru, Manzini and Ndola. Domestic departures for SA Airlink varied between 20,000 and 30,000 over the 6 year period as seen in Figure 2.2-29 below. International departures have increased in 2007 and 2008 as SA Airlink changed its name and corporate identity and began to offer flights to smaller and regional centres throughout Southern Africa.

Figure 2.2-29 SA Airlink Domestic and International departures

40000 35000 30000 25000 20000 15000 10000 5000 0 2002 2003 2004 2005 2006 2007 2008

Domestic International

A change in brand image led to an increase in both domestic and international passengers on SA Airlink in 2007. International passengers remained constant from 2002 to 2006 but an increase in the number of routes offered within southern Africa increased the number of international passengers departing on SA Airlink. Domestic routes are very popular and about 65,000 passengers fly on SA Airlink monthly. A

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Muller Associates Department of Transport P a g e | 55 decrease in 2005 in domestic passengers due to increased competition within the South African domestic airline industry caused SA Airlink to modify its strategy which was implemented in early 2006. The airline has since, once again, achieved an increase in both domestic and international passengers as demonstrated in Figure 2.2-30 below.

Figure 2.2-30 SA Airlink Domestic and International passengers

600000

500000

400000

300000

200000

100000

0 2002 2003 2004 2005 2006 2007 2008

SA Airlink Domestic SA Airlink International

Comair Ltd started operating its low cost airline Kulula.com in 2002. Since then, South Africa has seen the growth of low cost airlines with the introduction of Mango, 1Time and Nationwide Airlines. Comair successfully launched its low cost airline in 2002 allowing many travellers the option to fly economically. Comair also operates British Airways domestic flights within South Africa and regionally within SADC. The airline market in South Africa was previously dominated by South African Airways which was costly, thus deterring many travellers from flying and causing potential customers to seek alternative cheaper options for travel. Comair introduced its low cost airline with flexibility and cheaper prices and became instantly popular.

Departures have constantly increased over the 7 years Kulula.com has been in operation. Comair mainly services the domestic market but offers flights to the African cities of Windhoek, Harare, Lusaka, Ndola and Mauritius. Domestic departures have almost doubled since Comair started operation in 2002 and serviced about 31,000 domestic and 3,100 international departures in 2009 as seen in Figure 2.2-31 overleaf. The global recession hit South Africa in early 2009; however it did not affect low cost airlines as adversely because, in unfavourable economic times, more customers choose to travel on low cost airlines.

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Figure 2.2-31 Comair Domestic and International departures

40000 35000 30000 25000 20000 15000 10000 5000 0 2002 2003 2004 2005 2006 2007 2008 2009

Domestic International

Passenger numbers for Comair have increased consistently over the 7 years from 100,000 passengers to 330,000 passengers as seen in Figure 2.2-31 below. International passenger numbers have remained constant over the same period of time. Comair currently flies to Harare, Windhoek, Lusaka daily, flies to Ndola five times a week and once a week to Mauritius. As the international flights are not as frequent as domestic flights, the number of passengers carried on international flights is much lower.

Figure 2.2-32 Comair Domestic and International passenger numbers

3500000

3000000

2500000

2000000

1500000

1000000

500000

0 2002 2003 2004 2005 2006 2007 2008 2009

Comair Domestic Comair International

The fleet size of the various airlines within South Africa is illustrated in Figure 2.2-33 overleaf. SAA has the largest fleet in South Africa with 50 aircraft. SA Airlink and SA express both have over 20 aircraft

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Muller Associates Department of Transport P a g e | 57 while low cost carriers Comair, Kulula.com and 1time Airlines have more than 10 aircraft each. National Airways Corporation (NAC) is a private charter company with a large fleet of 18 aircraft. While Mango Airlines is a large player in the low cost airline market, it only has 4 aircraft. Other South African airline companies have less than 10 aircraft each and mainly service domestic charter and cargo markets.

Figure 2.2-33 Fleet size – South African Airlines

26 22 18 13 15 12 10 11 4 6 4 4 4 3 2 3 1

2.2.12 Tanzania

Air Tanzania temporarily suspended operations in December 2008 and has not resumed operations as yet. Air Tanzania was government owned until 2002 when it sold 49% stake to South African Airways. This partnership lasted till September 2006 when the government of Tanzania bought back SAA’s stake in the business. The partnership between SAA and Air Tanzania was regarded as unsuccessful and the government stated that the airline was more successful before undertaking the abortive partnership. Air Tanzania was revamped in 2007 and began using electronic ticketing, a new trademark and cleared outstanding debt in order to start afresh. As can be seen on Figure 2.2-34 overleaf, international and domestic departures were high in 1991 but began to fall in 1993. The airline maintained a fairly constant level of departures until 1998 but the airline began to experience a decline in business by 1999 and the number of departures fell. During the privatisation process, the airline experienced poor trading conditions with the lowest level of departures noted in 2001 and 2002. The airline failed to operate successfully after the revamp and suspended operations in 2008.

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Figure 2.2-34 Air Tanzania Domestic and International departures

10000

8000

6000

4000

2000

Domestic International

While domestic passengers on Air Tanzania have been falling since 1990, international passengers have remained constant over the years. The lowest number of passengers was recorded in 2002 and this can be attributed to change in ownership and privatization. After SAA took over operations, domestic passengers increased between 2002 and 2005 as more flights were introduced. However, by 2006, the airline was struggling again and both domestic and international passengers numbers began to decrease as can be seen on Figure 2.2-35 below.

Figure 2.2-35 Air Tanzania Domestic and International Passengers

250000

200000

150000

100000

50000

1996 1990 1991 1992 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Air Tanzania Domestic Air Tanzania International

Air Tanzania has not operated successfully over the years and maintained a net loss for the 3 years to 1993. The airline managed to operate profitably between 1993 and 1996; however by 1998 the airline was again suffering financially and began to make losses as seen on Figure 2.2-36 overleaf. Expenses exceeded revenues and the airline struggled to break even. Due to its unfavourable financial position, the government decided to privatise the airline so as to cut its losses however this was also unsuccessful, finally leading to liquidation.

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Figure 2.2-36 Air Tanzania Financial data

70 60 50 40 30 20 10

US $ (Million) $ US 0 -10 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 -20 -30

Operating Revenues Operating Expenses Net Profit

Besides Air Tanzania, there are 3 other airlines operating in Tanzania. Eagle Air and Regional Air Services are domestic airlines operating flights within Tanzania and charter flights in eastern and southern Africa. Regional Air Services is a subsidiary of Air Kenya. Precision Air is a low cost airline operating from 10 airports within Tanzania and also operated flights to Kenya and Uganda.

The fleet size of the above airlines is illustrated in Figure 2.2-37 overleaf. Precision Air has the largest fleet and is currently the largest airline in Tanzania since Air Tanzania ceased operations. Regional Air Services has 5 aircraft while Eagle Air only has 2 aircraft.

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Figure 2.2-37 Fleet size – Tanzania airlines

Eagle Air Precisionair Regional Air Services

2.2.13 Zambia

Zambia Airways was the national airline of Zambia. The airline was liquidated in 1995 as it was unable to cope with operations domestically and internationally. The government of Zambia could not assist the airline and indicated that it had to cover its own debts and expenses from revenues. The airline was not able to cover costs in a worsening economic climate and shut down operations in early 1995. Departures data for Zambia Airways’ last few years in operation are illustrated in Figure 2.2-38 below.

Figure 2.2-38 Zambia Airways Domestic and International departures

4000 3500 3000 2500 2000 1500 1000 500 0 1990 1991 1992 1993 1994

Domestic International

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Zambezi Airlines is a privately owned airline operating in Zambia. It operates at 2 airports within Zambia and flies to South Africa and Tanzania internationally. It has 3 aircraft in its fleet, 2 Boeing 737-500s which were acquired in mid 2009 seen in Figure 2.2-39 below. The airline is currently banned from entering European Airspace due to substandard safety standards.

Figure 2.2-39 Zambezi Airlines Fleet

Boeing 737-500 Embraer EMB-120 Brasilia

2.2.13.1 Zimbabwe

Air Zimbabwe is the national airline of Zimbabwe. Negative publicity, politics and the economic situation in Zimbabwe has had an adverse effect on the national airline. The volatile political situation in Zimbabwe has led to the general decline of the tourism industry as well as an economic crisis. As seen in Figure 2.2-40 overleaf, the highest number of departures was recorded in 1992 but the airline experienced a large decrease in both domestic and international departures in 1993 and 1994 attributed to clashes between the government and trade unions, resulting in general unrest in the country. The airline recovered in 1995 but land redistribution and the eviction of white farmers in 1999 led to a general decline of economic conditions in the country. Zimbabwe began to attract negative publicity and widespread international condemnation of the situation in the country followed. Departures began to fall in 1999 and the airline began to suffer financially due to the economic and political situation. In 2003 the airline announced that it was struggling financially and ceased operations temporarily and departures fell to less than 1,000 that year. Operations have since resumed.

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Figure 2.2-40 Air Zimbabwe Domestic and International Departures

14000

12000

10000

8000 6000

4000

2000

0 1990 1992 1993 1994 1995 1996 1997 1998 1999 2000 2002 2003

Domestic International

Air Zimbabwe has had a somewhat tumultuous history as the number of domestic passengers began to drop between the years 1996 and 2003. International passengers also decreased over the same period. The drop in domestic passenger numbers was, however, far greater than that of international passenger numbers as seen in Figure 2.2-41 below.

Figure 2.2-41 Air Zimbabwe Domestic and International passengers

450000 400000 350000 300000 250000 200000 150000 100000 50000 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Air Zimbabwe Domestic Air Zimbabwe International

Air Zimbabwe has been operating at a loss for most of the past two decades. In 1992, the airline was able to realise a profit however, by 1993 the airline was once again making losses. The decline in the political situation and the economy of Zimbabwe has had an adverse impact on the viability of the airline. The airline was losing customers and was unable to cover its operating costs with the revenue

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Muller Associates Department of Transport P a g e | 63 received from sales, excess baggage and freight. The financial situation of Air Zimbabwe is illustrated in Figure 2.2-42 below.

Figure 2.2-42 Air Zimbabwe Financial Data

140 120 100 80 60 40

US $ $ (Million) US 20 0 -20 1990 1991 1992 1993 1994 1995 1996 1997 1998 -40 Operating Revenues Operating Expenses Net Profit

2.2.14 Airports in SADC

The table overleaf reflects the total number of passengers recorded arriving or departing at airports in the SADC region. Airports that served more than 1,000,000 passengers in 2009 are defined as airports with high frequency, airports with mid to high frequency serve between 200,000 to 1,000,000 passengers and airports with low frequency serve less than 200,000 passengers in 2009.

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Table 2.2-1 Airports in SADC – Total Passengers

Airport Country 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Gaborone - Sir Seretse Khama Botswana 188,925 224,488 240,526 225,392 473,794 285,708 355,727 518,284 346,411 386,313 International Maun Botswana 137,056 139,571 163,307 142,737 154,092 193,067 205,078 239,368 272,010 Kinshasa N'Djili DRC 267,175 273,563 298,019 358,833 437,882 516,345 599,845 586,870 677,865 663,354 Antananarivo - Ivato International Madagascar 581,965 611,423 678,366 707,304 713,566 336,711 552,138 611,973 709,034 714,488 812,151 828,162 611,175

Majunga Madagascar 89,054 87,897 82,437 84,244 77,505 28,206 43,820 59,849 57,037 52,405 58,443 62,400 46,746 Lilongwe Malawi 208,356 207,157 198,924 202,618 193,446 173,521 176,703 196,140 186,363 173,829 282,529 303,210 296,190 Mauritius - Sir Seewoosagur Mauritius 1,484,263 1,524,738 1,600,155 1,763,143 1,819,136 1,896,307 1,982,855 2,058,944 2,167,468 2,217,167 2,562,830 2,606,813 2,381,810 Ramgoolam International Maputo International Mozambique 308,500 330,969 390,882 436,849 419,327 437,832 445,383 478,115 558,979 624,540 693,618 669,372 668,706 Windhoek International Namibia 429,811 470,534 490,325 481,419 379,327 404,759 506,077 527,085 530,675 637,247 693,671 712,242 681,324 Bloemfontein South Africa 233,121 221,205 219,607 211,490 210,359 215,643 225,636 242,315 305,578 424,223 411,726 399,826 Cape Town International South Africa 3,998,316 4,306,716 4,614,931 4,654,107 4,210,792 5,019,283 5,329,534 6,018,044 6,738,020 7,224,587 8,400,569 8,150,611 7,725,223 Durban Louis Botha International South Africa 2,386,247 2,488,370 2,523,899 2,501,999 2,405,726 2,580,323 2,773,133 3,105,269 3,592,501 4,029,074 4,799,702 4,458,223 4,310,095 East London South Africa 369,445 363,262 352,012 318,793 365,069 380,771 422,672 560,419 664,292 744,455 714,427 674,680 George South Africa 111,892 132,401 227,591 245,052 285,464 335,813 438,747 579,017 589,854 651,563 630,385 527,026 Johannesburg O.R. Tambo South Africa 9,722,758 10,870,104 11,339,920 11,680,598 11,789,814 12,743,545 13,506,495 15,340,670 15,769,094 17,344,669 19,439,083 18,636,251 17,607,255 International Kimberley South Africa 84,444 83,903 82,703 91,100 93,193 89,676 97,442 102,841 129,136 147,277 155,507 130,644 Port Elizabeth South Africa 812,601 822,343 869,523 860,691 836,324 866,955 950,622 1,050,552 1,163,218 1,409,609 1,491,800 1,468,176 1,357,696 Upington South Africa 28,225 29,242 25,730 29,553 32,842 33,681 30,546 32,856 37,009 47,666 50,378 42,519 Kruger Mpumalanga 177,498 215,353 241,533 247,573 208,751 Dar-es-Salaam Tanzania 572,447 582,166 621,513 652,008 703,483 816,263 1,011,392 1,124,235 1,249,419 1,450,138 1,542,778 1,422,846 Kilimanjaro International Tanzania 310,469 134,407 207,256 221,108 192,204 184,652 294,750 363,512 480,053 566,579 521,915 426,600 Mwanza Tanzania 93,311 204,915 111,282 137,767 161,213 186,590 203,087 234,301 229,496 224,207 Zanzibar Tanzania 196,816 236,148 248,554 203,586 307,765 317,308 418,980 549,408 534,466 593,482 571,416 575,504 Lusaka International Zambia 328,132 339,944 341,361 466,533 433,521 392,285 390,505 432,712 447,141 603,107 734,442 837,901 663,223 Victoria Falls Zambia 178,376 168,849 194,938 181,167 210,464 185,859 137,552 Harare International Zimbabwe 629,549 554,370 592,437 629,979 610,221 731,340 674,281 612,208

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Airports in SADC – Total Passengers

Figure 2.2-43 Airports with highest frequency:

25,000,000

20,000,000

15,000,000

10,000,000

5,000,000

0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Johannesburg O.R. Tambo International Cape Town International Durban International Mauritius - Sir Seewoosagur Ramgoolam International Dar-es-Salaam Harare International

Airports with highest frequency are O R Tambo Airport Johannesburg, Cape Town International, Durban International, Dar-es-Salaam Airport, Harare Airport and Sir Seewoosagur Ramgoolam International in Mauritius. O.R Tambo Airport in South Africa has had a total of over 10 million passengers a year. Total passengers at these airports have been increasing over the years and peaked in 2007 after which passenger numbers began to decline. The global recession has had some effect on air travel and total passengers declined in 2008 and 2009. All the above airports are international airports and serve both domestic and international flights and passengers. Dar es Salaam, Harare and Mauritius airports have recorded over 1.5 million passengers annually. These 6 airports illustrated in Figure 2.2-43 above are the most frequented airports in the SADC region.

2.2.14.1 Airports with mid- to high frequency:

Airports with mid- to high frequency include airports in Madagascar, the DRC, Mozambique, Zanzibar, Zambia and Namibia illustrated in Figure 2.2-44 overleaf. These airports recorded between 200,000 and 900,000 passengers annually. Most of the airports noted show an upward trend in the total number of passengers embarking over the years. A dip in total passengers in 2002 and 2009 for Madagascar occurred due to the political unrest experienced in the country during those years. All the airports that recorded mid to high number of passengers are international airports except for East London airport

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Muller Associates Department of Transport P a g e | 66 which only serves domestic flights. Air travel numbers were generally low in 2002 due to the aftermath of the September 11 attacks, fuelling fears of terrorist attacks amongst passengers and deterring air travel. The attacks did not have a large impact on African destinations; however there was global decline in air travel during the period following the attacks in the US.

Figure 2.2-44 Airports with mid to high frequency:

900000

800000

700000

600000

500000

400000

300000

200000

100000

0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Kinshasa N'Djili Antananarivo - Ivato International Maputo International Windhoek International Zanzibar Lusaka International

2.2.14.2 Airports with low frequency:

Airports with low frequency are the airports serving the lowest number of total passengers annually – defined as airports with fewer than 700,000 passengers annually. In general, passenger numbers at low frequency airports gradually increase and peak in 2007. A decline is experienced in 2002 due to the September 11 attacks and again in 2008 and 2009, which can be attributed to the global downturn in the economy. International airports illustrated in Figure 2.2-45 overleaf that recorded low numbers of passengers include Gaborone airport, Maun, Majunga, Lilongwe, Kilimanjaro International, Mwanza and Victoria Falls. Kilimanjaro International and Gaborone recorded the largest increase in total passengers, while Majunga, Lilongwe, Victoria Falls, Mwanza and Maun had constant number of passengers over the years. Kilimanjaro international recorded the largest increase in total passengers over the years.

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Figure 2.2-45 International Airports with low frequency:

600,000

500,000

400,000

300,000

200,000

100,000

0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Gaborone - Sir Seretse Khama International Maun Majunga Lilongwe Kilimanjaro International Mwanza Victoria Falls

Domestic airports illustrated in Figure 2.2-46 below with low numbers of passengers include Port Elizabeth, East London, Bloemfontein, George, Kimberley, Upington and Kruger Mpumalanga. Upington and Kimberley airports reflect a fairly constant level of total passengers over the years, while the rest of the domestic airports demonstrated an increase in total passengers.

Figure 2.2-46 Domestic Airports with low frequency:

1600000 1400000 1200000 1000000 800000 600000 400000 200000 0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Bloemfontein East London George Kimberley Port Elizabeth Upington Kruger Mpumalanga

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2.2.15 Fleet size of all SADC airlines

An overview of the fleet size of all airlines within SADC in 2007 is provided in Figure 2.2-47 overleaf. Fleet size between airlines fluctuates enormously. The fleet size between airlines operating internationally and domestically varies greatly compared to low cost airlines that only operate to domestic destinations. National carrier South African Airways has the largest fleet within SADC, while other national airlines such as TAAG Angla, Hewa Bora Airways, Air Madagascar, Air Mauritius, Air Seychelles, Air Botswana, LAM, Air Malawi and Air Namibia have smaller fleet varying between 4 and 12 aircraft each..

Privately owned airlines in Angola, DRC, South Africa, Tanzania and Zambia own smaller fleets mainly serving the domestic market. SonAir has the largest fleet of 32 aircraft while popular operators such as Diexim Expresso, Transafrik, 1time, Mango, Comair and Precision Air have less than 10 aircraft each.

Specialized charter companies in South Africa, Angola and DRC have a variety of small aircraft. National Airways Corporation of South Africa has a large fleet of 18 small aircraft.

The figure overleaf shows the fleet size of the larger SADC based airlines. Each country has been differentiated by means of a colour coded system and the key appears below the figure.

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Figure 2.2-47 Fleet Size (2007)

32 26 22 18 13 15 12 11 12 12 10 11 7 8 8 9 8 9 8 5 6 5 5 6 4 6 4 6 4 4 4 5 5

2 3 1 2 3 2 1 3 2 3 1 2 3

Filair Filair

Air 26 Air

Alada

Safair Safair

Airlink Airlink

Mango

SonAir

Comair Comair

Interair

Tiko Air Air Tiko

Air Kasai Air

Eagle Air Air Eagle

Norse Air Air Norse

Transafrik Transafrik

Air Gemini Air

Air Malawi Air

SAA Cargo Cargo SAA

SA Express Express SA

Federal Air Air Federal

kulula.com

Tramon Air Air Tramon

Aeronautica

Precisionair Precisionair

Air Namibia Air

Air Botswana Air

Air Mauritius Air

Air Tropiques Tropiques Air

1Time Airlines 1Time

Air Seychelles Seychelles Air

Star Air Cargo Air Star

Air Zimbabwe Zimbabwe Air

Air Madagascar Air

Diexim Expresso Diexim

Zambezi Airlines Zambezi Airlines

Business Aviation

Imperial Air Cargo Cargo Air Imperial

Angola Air Charter Air Angola

Hewa BoraHewa Airways

AirQuariusAviation

Naturelink Charters

WimbiDira Airways

Regional Air Services Regional Services Air

TAAG Angola Airlines TAAG

South AfricanAirways

Compagnie Africaine CompagnieAfricaine Aviation D

Linhas Aereas Aereas Linhas Moçambique de LAM National Airways Airways NationalCorporation (NAC)

Angola Malawi South Africa Botswana Mauritius Tanzania DRC Mozambique Zambia Madagascar Namibia Zimbabwe Seychelles

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2.3 Analysis of Questionnaire Results

Between August 2009 and January 2010, 106 airlines, 3 airport authorities and 14 SADC transport ministries were contacted and sent questionnaires regarding progress with the implementation of an air transport liberalisation agreement in SADC related to the adoption of air transportation liberalisation policies in Africa (the questionnaires can be found in Appendix E.) Of the 68 questionnaires sent out, only 16 were returned completed. Analysis of the answers to the returned and completed questionnaires follows.

2.3.1 Airlines

Feedback was received from five airlines within the SADC namely Federal Airlines, Owenair Pty Ltd, South African Airways and Comair Limited of South Africa and Air Malawi of Malawi. Each airline is unique servicing a different market or market segment. However the five airlines share similar views on the impact of implementing an air transportation liberalisation agreement in the SADC region. The profiles of the responding airlines are summarised in Table 2.3-1 below:

Table 2.3-1 Airlines Data

Company / Country of Type of Airline Annual Ownership Owners Organisation Operation Turnover Federal Airlines South Africa High end domestic and Did not Private 100% domestic private international disclose company ownership Air Malawi Malawi National flag carrier Did not Government 100% domestic disclose owned government ownership Comair limited South Africa Domestic low cost carrier, high R 3 billion Privately 88% domestic private end domestic and owned ownership, international, charter carrier, company British Airways franchise, code 12% foreign private sharing and alliance ownership Owenair (Pty) South Africa Chartered carrier R 6 million Private 100% domestic private Ltd company ownership South African South Africa National flag carrier Did not Government 100% domestic Airways disclose owned government ownership

The responding airlines stated in general, that the air transportation liberalisation aviation agreement reached between African states, namely the Yamoussoukro Decision (YD,) was a poor and a weak agreement as there has been no evidence of any multilateral implementation. This is due to lack of arbitration procedures being agreed to progress deadlocked negotiations and lack of regulation by means of competition laws. A phased in approach whereby each airline could have been engaged with individually taking into account the differing passenger route densities on the routes that each airline operates was recommended. There was no deadline set and the agreement was reached without prior consultation with airlines. African states have not implemented YD due to lack of political commitment, anti-transformation, resistance from weak state owned airlines, based on fear of the consequences of more open commercial competition, lack of infrastructure development, limited fleet size in less

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Muller Associates Department o f Transport P a g e | 71 developed countries and lack of consensus on a clear way forward. YD does not consider the strengths and weaknesses of countries airlines, nor of the state of airport and aviation infrastructure in the various regions of the African continent. The likely impact of implementing such an agreement on specific countries has also not been determined.

Airlines cited the following as reasons why full implementation of the YD has been hindered:

Lack of individual government commitment to YD; Lack of SADC member commitment to YD; National flag carriers disapproval of YD due to perceived threats to existing privileged positions of aviation industry dominance; Lack of effective competition law in individual countries and regionally; Corruption; Poor or non-existent legislation; Political instability in certain African countries; Poor / substandard airport infrastructure in many countries; Airport security concerns; Risks regarding the handling of higher flight frequencies at some airports; and Resistance from stakeholders trying to protect monopoly or privileged positions of market dominance.

Airlines recommend that in order to successfully implement YD, governments will be required to play an active role in ensuring that airlines are informed about intended progress (to a declared timetable) towards implementation of YD in Africa. Bottlenecks need to be addressed; national airlines need to be supplied with avionics so as to compete effectively; regulations need to be standardised and amended to cover aspects such as competition law and arbitration procedures to speedily resolve disputes; and stakeholders should be afforded the opportunity to buy into the implementation plan and be party to discussions and planning of implementation. Lastly, African governments should focus on African carriers which must be developed to compete globally rather than focusing on non-African airlines.

The airlines have differing views on the likely impact on countries that would implement YD. While some airlines are sceptical and feel that most African airlines will not survive, others feel that a number of small airlines will be sacrificed initially but the long term overall consequences will be positive. Implementation will see an increase in tourism and business travel leading to increased traffic on dense and lucrative routes resulting in lower fares, more competition and therefore more participants in the airline industry. Airlines will benefit from offering reliable and efficient services at pricing levels that will stimulate demand and therefore profitability - which will have widespread benefits for SADC economies. Many national flag carriers and smaller, less efficient airlines will be unable to compete if they are not recapitalised with competitive equipment and many may not survive.

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Impact of the YD on airlines will result in the following changes in the current status quo:

Frequency of flights – increase Capacity (number of seats on offer) – may increase or remain static Pricing – decrease due to increased competition Volume of freight business – increase Number of competitors on each route – increase on higher traffic routes but will decrease on more marginal routes Market share of airline on each route – will reduce but as part of a rapidly growing industry

With the implementation of YD, airlines will be able to fly to destinations previously inaccessible. Airlines will tend to increase the frequency of flights on the more lucrative routes so as to reap maximum benefits. Depending on the demand for seats of the more popular routes, airlines will have to either reduce flights on less popular routes and divert flights to the more popular routes or increase their fleet to accommodate the demand. This will result in either an increase in overall capacity if more aircraft are introduced or the overall capacity will remain static with airlines diverting aircraft to more popular routes.

An increase in competition in the form of an increase in number of flights on routes within the SADC will lead to a decrease in the average price of air tickets as airlines compete to maximise their market share. This decrease in price will likely benefit passengers directly and may boost the number of passengers travelling within the region, thereby greatly extending access by the general public to air travel. Not only will this boost tourism and business travel around SADC and Africa, but will also benefit airlines, airports, hotels, car hire companies, restaurants and other direct and indirect stakeholders in the aviation industry. Similarly, freight business will be stimulated through cheaper tariffs leading to an increase in the volumes of freight being imported and exported throughout SADC and the African continent.

As airlines strive to maximize market share, an increase in the number of competitors will lead to a decrease in the market share of individual airlines. Airlines will need to emphasise aspects of service such as reliability, safety and the level of service provided in order to mitigate against market share losses. Although airlines will experience a fall in market share due to an increase in the number of players in the market, the overall size of the market is expected to grow rapidly, which will result in individual airlines, in the main continuing to grow despite falling market share.

Airlines that will benefit the most from implementing the YD are typically strong network and alliance carriers, while small charters and weak state owned carriers may not survive. Strong network alliance carriers will survive the intense competition which may result in a decrease in fares as these carriers have financial muscle and easy access to capital for rapid expansion. Large airlines will feel intimidated as new airline start serving the same routes and will feel threatened by the increase of operators, but airlines with a large market share will be better off than small airlines which may not be able to compete

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Muller Associates Department o f Transport P a g e | 73 as efficiently. Weak state owned airlines are characterised by old out-dated aircraft fleets that, together with reluctance to embrace change, will limit expansion possibilities.

The state of airport infrastructure will have a significant influence in determining the effect of implementing an air transportation liberalisation agreement. If YD is implemented, infrastructure constraints will restrict transformation of the aviation industry as current infrastructure will not be sufficient to cope with the resulting growth of air traffic volumes. Implementation of YD will result in an increase in flight frequencies around Africa and infrastructure investment will need to be facilitated to ensure that capacity is enhanced to cater for these demands. Currently, air traffic control, airport runway capacity, airport runway length, baggage handling, security and even freight logistics capacity is in the hands of government departments that will be incapable of responding to the increased demand. There is insufficient capacity to accommodate increased number of flights in terms of limited airport runway slots, restricted manpower and expertise in air traffic control, airport runway lengths at some airports, not enough capacity to handle large numbers of passengers and baggage and a strained and inadequate security at most airports. These constraints will have to be addressed before YD is implemented and failure to do so will result in dire consequences such as flight delays, loss of baggage, security threats and safety concerns. Airports will have to ensure that facilities comply with minimum standard requirements. Customs facilities, information technology infrastructure and effective airport security are some of the issues that will need to be revised and addressed in order to successfully benefit from the YD agreement. Privatisation of many of these services is probably a necessary reform for successful implementation of YD.

If SADC undertakes a comprehensive implementation of an air transportation liberalisation agreement, airlines feel that it would open up the opportunity to review the mix of aircraft types, assessing the need for both bigger and smaller types of aircraft on certain routes, existing and new. Implementing YD will create additional job opportunities on both existing and new routes, creating the opportunity to expand network reach and frequency leading to additional and increasing competition , lowering of prices for air tickets and ultimately to an increase in market size, revenue and profits. Airlines will be willing to operate on new routes as well change some of the current routes so as to avoid stopovers and hub transfers by introducing direct flights to more destinations. In relative terms YD will disadvantage small local airlines because they are less likely to have access to investment funding for expansion which larger, mainly international airlines will be able to access more readily. All airlines will, nevertheless, have the potential to benefit from YD if management embraces the business opportunities that will be on offer.

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2.3.2 Airports

If YD is implemented in the SADC region, then an increase in the number of flights to both current and new airport destinations can be expected. Therefore, airports that are currently being utilised (as hubs or as international gateways) will experience an increase in inbound and outbound flights, while some airports (with adequate infrastructure, not receiving international flights) that are underutilised will also experience an increase in inbound and outbound flights.

Receiving only two responses from major airport companies may not clearly indicate the impact on airports of implementing the YD but feedback does provide a basic idea about the implications that the YD will have on airports. Feedback was received from two airport companies profiled in Table 2.3-2 below:

Table 2.3-2 Airports Data

Company / Country of Annual Main sources of income Ownership Owners Organisation Operation Turnover Airports South Africa R 3.17 Aeronautical revenue, landing fees, Partly 74.6% domestic Company of billion passenger service charges, aircraft owned by government South Africa parking, commercial revenue, government ownership, advertising, retail, parking, car hire, (ACSA) property rental, premiums received 25.4% domestic private ownership

National Zambia US $ 26.7 Aviation - landing, passenger service Fully owned 100% domestic Airports Million charge, parking, ground handling, air by government Corporation navigation charges and Non-aviation - government ownership Limited rentals, car parks, concessions, advertisements

The main sources of income reported by airports include aviation business - landing, passenger service charge, parking, ground handling, air navigation charges and non-aviation business - rentals, car parks, concessions and advertisements. Major airports within the SADC are either fully or partly owned by the government thus any commercial benefit to the airport will have an impact on the country’s economic conditions, directly and indirectly.

While airports authorities agree with airline operators that the YD agreement is good in principle, they also feel that implementation has been poor. The YD agreement will improve revenue generation as more airlines will operate from various airports, in turn, positively impacting the profitability of airports. Thus, an introduction of the fifth freedom will lead to a removal of restrictions, allowing more airlines to operate freely on numerous routes previously forbidden. YD will also stimulate traffic growth and make travel more affordable by introducing more intense market competition. Lack of progress with implementation has resulted in constrained aviation industry conditions prevailing in the past and while much consideration needs to be given as to how to pave the way forward, airports authorities state that

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Muller Associates Department o f Transport P a g e | 75 a huge transformation in airport operation will need to occur and this will have to be done with many parties involved, including private sector investment and management.

Bottlenecks identified by airport authorities are identical to those mentioned above and include:

Lack of government commitment to YD Lack of SADC commitment to YD National flag carriers resistance to YD

In order to successfully implement YD, governments will need to remove bottlenecks that hinder the free flow of private sector investment and participation in the air transport industry. This can be done by granting the fifth freedom and at the same time helping local air transport businesses to partner with international or local large participants in the industry to form alliances to ensure that they will survive under the intense competition that is characteristic of a successful implementation of an air transportation liberalisation agreement. This will result not only in rapid growth as lower prices stimulate economic activity, but will also encourage quality in the aviation industry through providing consumers with choice and providing local airlines the opportunity to participate in this growth through the introduction of innovative approaches to service provision.

The impact of YD on airports will be: Frequency of flights – increase on certain routes Capacity – increase Pricing – decrease Volume of freight business – likely to increase, dependent on demand and pricing structure (affordability)

Airports expect an increase in frequency of flights on certain more popular routes which would lead to an overall increase in frequency of flights at many airports. Increase in flight frequencies will lead to an increase in capacity as more flights to more varied destinations will become available. Ticket prices will decrease due to increased competition. Although no indication of the trend of airport charges has been mentioned, increased choice and economies of scale should drive airport charges down as well. Volume of freight business will be dependent on demand and pricing and if pricing decreases, there will be an increase in the volume of freight into and out of airports thus relieving other modes of transport especially road .

Increased aviation activities will certainly have a positive effect on the commercial standing of all airports within SADC, however airports enjoying the highest demand will benefit at a larger scale than those enjoying less demand. Implementation of YD will create a climate characterised by an increase in demand for aviation services in general, however the decision itself will not convert into automatic demand for more flights at any individual airport. Airports will be afforded the opportunity to grow their business if there is a pro-active move on the part of individual airport management teams to

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Muller Associates Department o f Transport P a g e | 76 attract business in the more open and flexible environment that will accompany implementation of YD. As more flights are introduced, revenues will rise, encouraging airports to further expand capacity in order to facilitate continually increasing levels of aviation activities.

Potential infrastructure constraints such as airport runway capacity, airport runway length and baggage handling facilities will need to be addressed as these will cause bottlenecks and may lead to delays and inefficiencies in service support, which will discourage rather than encourage new business. Infrastructure constraints are likely to significantly restrict the potential benefits associated with implementation of YD if airspace and airport capacity is limited by inadequate infrastructure investment. Not all airports have the facilities and infrastructure to accommodate all sizes of aircraft and large increases in air traffic volumes. Airport planners will need to ensure that facilities are of adequate capacity to meet increased levels of demand and are compliant with minimum standards in order to fully benefit from the implementation of YD.

Airlines will be free to develop routes more easily and open up new markets for travellers, the overall the impact of air transportation liberalisation on airports will be to increase potential revenues which will, in turn, justify investments in upgraded airport infrastructure and facilities.

2.3.3 Other Stakeholders in the aviation industry

Other stakeholders in the aviation industry include small charter operators, aircraft leasing companies, aircraft sales and maintenance businesses, cargo and freight service operators and mail services. Currently these are typically small operations that service a niche market and offer specialised services such as package tours, domestic charter or scheduled flights. Stakeholders in this category that provided feedback are listed in the schedule overleaf.

Most of the above named stakeholders are small charter operators with the exception of Mistral Aviation, which specialises in landing gear overhauls and aircraft brake maintenance, Airline Association of South Africa (AASA), which is a non-profit organisation providing guidance to SADC airlines and Swissport Tanzania, which is a ground handling and cargo services company.

More than half the stakeholders stated that the agreement reached at YD was positive for the industry because it provided greater opportunity for start up airlines to compete with established airlines and level the playing field by allowing competitive operators freer access to potentially lucrative markets. Implementation of YD will also allow established airlines to serve a broader market without encountering rigid barriers that have previously restricted their operations. Some stakeholders feel that the YD agreement has been poorly received because it was adopted out of the recognition that the restrictive and protectionist intra-African regulatory regime based primarily on bilateral air services agreements (BASAs) has historically hampered expansion and improvement of air transportation on the African continent. As such, existing vested interests, which often rely on old, poorly maintained aircraft operating out of poorly managed airports, feel threatened and have consequently successfully resisted multi-lateral implementation of YD.

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Other Stakeholders that responded are profiled in Table 2.3-3 below:

Table 2.3-3 Stakeholders Data

Company / Country of Annual Main sources of income Ownership Owners Organisation Operation Turnover AirQuarius South Africa R 101 Aircraft leasing and charter Private Private ownership Aviation million company NAC South Africa R1,9 billion Aircraft sales, aircraft maintenance, Privately owned 100% domestic aircraft leasing, aircraft (rotor and company private ownership fixed wing) charter, aircraft management Airline South Africa n/a Membership subscriptions and Non-profit Private ownership Association of management fees privately owned Southern Africa company (AASA) Mistral Aviation South Africa R10 - R12 Aircraft brakes and landing gear Private Private ownership Services million overhauls company Namibia Namibia $ 7 million Tourism and incentive charters Private Private ownership Commercial Namibian Aviation company Phoebus Apollo South Africa Passenger/ cargo scheduled/ charter Sole Private ownership Aviation flights and wet-leasing of aircraft proprietorship Precision Air Tanzania $65 million Provision of scheduled passenger, Private 51% domestic services Ltd US freight and mail services private, 49% foreign Partnership private Proflight Zambia $ 8 million Charter operations Private 75% domestic commuter US private, 25% foreign services Partnership private Swissport Tanzania T Shs Ground handling, cargo services Private 49% domestic Tanzania 18.528 private, 51% foreign million Partnership private

One of the vital principles of YD is market liberalisation, which is viewed as a means to stimulate the development of air services in Africa and attract the flow of private capital into the industry. In essence the agreement reached is solid and the theory makes sense for Africa and for airline industry stakeholders. In practice, however, YD made assumptions regarding compliance by individual countries that have not been realised. The heads of state came to an agreement, but at “grassroots level” many of the stakeholders (and individual managers in stakeholder entities) have not been committed to YD and may have actively resisted implementation of the agreement. Implementation of YD has thus been very limited and stakeholders believe that national governments have resisted implementation with the result that no meaningful progress has been made since the agreement was reached.

The Yamoussoukro Decision, which came into force in 2000, evolved from the Yamoussoukro Declaration of 1988. However, throughout the intervening years, the full potential of YD to unlock commercial opportunities for African airlines has not been realised and implementation has been virtually non-existent. A sub-committee on air transport established by this decision and monitored by a

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Muller Associates Department o f Transport P a g e | 78 body comprised of representatives from Economic Commission for Africa (ECA), African Union (AU), African Civil Aviation Commission (AFCAC) and African Airlines Association (AFRAA) then overseen by an executing agency has not carried out the duties set out in the declaration even though a large fund was set aside for implementation. The explicit roles of these organisations were unclear thus no action was taken due to the confusion. Only a few countries practise true “air transportation liberalisation”. These are mainly countries which have implemented bilateral agreements instead of letting airline companies get on with freely operating the routes and frequencies that they want to as envisaged by YD.

The following factors have been identified by stakeholders as hindering the full implementation of YD:

Lack of individual national government commitment to YD Lack of SADC commitment to YD National flag carriers resistance to implementation of YD A lack of laws promoting free competition regionally A lack of laws promoting free competition within individual countries Corruption Poor legislation Political instability in some African countries Poor/substandard airport infrastructure in Africa Airport security concerns Lack of start up capital for would be operators European Union blacklisting of African airlines Lack of clarity regarding the roles of the various sub-committees and monitoring bodies Lack of commitment and action by ministry officials Lack of incorporation of the principles of YD, as appropriate and necessary, into national legislation Lack of infrastructure (no effective executing agency and other monitoring structures) Government protection of airlines from competition (preserving of state monopolies)

The above have been identified as factors which hinder the successful implementation of the YD and will need to be addressed before any progress can be made. Governments need to amend aviation policies and legislation accordingly. Before implementation, a plan needs to be formulated to include all stakeholders in a participative process to evaluate options and develop a well rounded policy that will benefit all stakeholders including the governments involved. It is important that the appropriate officials are mandated to implement the YD within a specified time frame. Existing bilateral government agreements should be amended to remove limits on frequency and capacity.

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A possible approach would be to involve a larger authority in decision making. The African Union (AU) is Africa’s premier institution and is the principal organization for the promotion of socio-economic integration on the continent. The AU is also the monitoring body established to oversee implementation of the Yamoussoukro Decision. Given the AU’s objective to promote sustainable development and to integrate African economies, the African Union (AU) is best positioned to provide the necessary oversight platform for steering implementation of the Yamoussoukro Decision and liberalization of the air transport industry in Africa. Its recent moves to actively support the African Civil Aviation Commission (AFCAC) and the various regional economic communities (RECs) demonstrated the willingness of the organization to accept leadership. Individual national governments need therefore to support the AU and provide the necessary funds and resources to assist the AU in this regard.

If implemented successfully, the impact of the YD would be immensely positive for countries partaking in the decision. It would create an environment for the development of intra-African and international air services, liberalized intra-African aviation markets and highly stimulatory developments concerning, traffic rights, capacity, frequency and pricing. YD will lead to the rapid development of inter-African air transport activities and improved quality of service to consumers. Sub-regional services will be encouraged to merge and grow as well as permit air transport services to privatise. With the implementation of YD, countries will establish safe, reliable and affordable air transport services that are attractive to customers and that will stimulate a freer and much higher level of movement of persons, goods and services in Africa. Implementation of YD may also protect African airlines from European and other non-African competitors and eliminate barriers that hamper the sustainable development of air transport services. African airlines will be able to create a strong regional base from which they can expand and compete with international airlines by forming international alliances and strong business partnerships that will assist in future growth and development. Although the impact is largely expected to be positive, stakeholders do recognise that some countries may struggle to adapt mainly due to a misguided commitment to outdated aviation practices and equipment. Countries that are reluctant to embrace transformation and face competition will eventually suffer dire consequences in respect of their own national airlines and other aviation industry stakeholders as continent-wide competition overtakes those who refuse to adapt.

Stake holders agree that companies throughout Africa that embrace the changes implied by full implementation of YD will be able to build strong partnerships with other operators around Africa and further afield and will enjoy the chance to exploit the many opportunities available to them. Airlines will benefit as it will be easier to obtain quicker flight clearances and all fees surrounding flights which include landing and parking fees should be more competitive as opposed to companies not based in Africa. Increased scheduled flight services will act as a catalyst for economic growth within the continent. The financial benefit gained from implementing the YD will be significant for almost all participants as there will be greater freedom, more capacity to accommodate new routes, increased revenue for all stakeholders. Implementation of YD will create the opportunities to increase aircraft fleets for both new and established operators as they build their capacity to serve the higher levels of demand created from the implementation. Thus, not only will airlines benefit, but also companies that service, lease and maintain aircraft will reap benefits.

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The view of stakeholders is that the companies most likely to benefit from the YD will be start up and low cost operators, regional airlines, established airlines and airlines that can sustain the more intense levels of competition. With the freedom to operate on any routes airlines will prioritise the most lucrative ones. Small carriers will have the opportunity to expand and diversify their current flight operations. Companies involved in maintenance and aircraft leasing will benefit from the opening of new potential markets enabling stakeholders to widen their business horizons. Some stakeholders feel that emerging airlines will be faced with limited growth while established airlines that already have a strong base in the market will find it easier to attract new business. Companies least likely to benefit from the YD are underperforming domestic carriers, inefficient national carriers and companies that are unable to compete effectively.

Infrastructure constraints that stakeholders indentified as possibly restricting implementation of YD are:

Air traffic control Airport runway capacity (no. of slots) Airport runway length Baggage handling Security Freight logistics capacity

The above constraints are the same as those mentioned by both the airlines and airports groups of stakeholders. Stakeholders are mainly concerned that those factors that will affect the smooth operation of companies due to the increased demand that will result once the YD has been implemented. In some countries, where services have not been upgraded to meet international standards, infrastructure may not be able to cope with the increased air traffic. In many cases airports are not geared to accommodate large aircraft and thus they do not have sufficient capacity or the appropriate runway length for modern aircraft. In terms of freight logistics, airports and freight companies would have to ensure that they can handle an increase in freight and cargo volumes by creating efficient cargo hubs. Air freight usually consists of perishable goods that have a short life span and must be handled with speed and without delay. One of the biggest passenger concerns when travelling around Africa is baggage handling and security. This would have to be addressed effectively and measures need to be taken to ensure that no compromises are made.

A comprehensive air transportation liberalisation agreement would be a great benefit to all stakeholders in the aviation industry as it gives companies the opportunity to investigate new markets and routes and source new and modern equipment in partnership with other operators. This will inevitably lead to structural changes to some of the companies to allow for ongoing expansion. Expansion will benefit not only the company but the economy as whole through creating employment and generating higher levels of revenue. The implications for ground handling companies are also positive as the increased demand will require larger operations allowing these companies to expand; however, these trends may also attract an increase in competition. Stakeholders are generally realistic in recognising that before any of

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Muller Associates Department o f Transport P a g e | 81 the benefits are enjoyed, infrastructure investment will be required to accommodate the increase in flights, passenger numbers and cargo volumes. Some stakeholders are concerned that they may not be able to survive as they will get swallowed by the competition of an open market and thus are not entirely enthusiastic about the implementation of YD.

Overall, however, airlines, airports and other stakeholders are positive about the implementation of YD but are sceptical about the progress made to date and likely to be made into the future. Stakeholders support the idea behind YD and are willing to open their markets to Africa but are not certain that the current infrastructure, legislation and policies support the rapid implementation of such a decision.

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2.4 Cost-Benefit Analysis Methodology

2.4.1 Model 2.4.1.1 Introduction

The demand forecast model predicts the potential routes that airlines could operate in the South African Development Community (SADC) under an air transportation liberalisation regime. It is principally based on the gravity method described in the literature review. The gravity model traditionally uses the size of the origin (city or country) times the size of the destination as an indication of the demand for flights between them. This model assumes that the bigger the population size or GDP of the origin and the population size or GDP of the destination, the bigger the attraction and demand for flights. Equation (1) shows the typical mathematical equation that would be used to determine the potential demand between an origin and destination.

Equation (1) Demand = (GDP Origin * GDP Destination)/Distance

For the purpose of this study the demand forecast model has been based on the principles of the gravity model, by using data from origin and destination location in a similar fashion as Equation 1 above (this will be explained in the sections that follow.) In the sections to follow it will be shown how a demand forecast has been predicted for each potential route in the SADC region and this forecast has been weighted between 0 and 1 (0 being very low demand and 1 being extremely high demand). The model excludes all airports with a runway length shorter than 6500 feet (1.98 km), as airlines and aircraft manufacturers cited this length as a minimum for commercial aircrafts and aircrafts designed to carry freight, and runways that are unpaved. Routes that are less than 200 km were excluded, due to ineffectiveness of flying distances this short.

2.4.1.2 Data Utilised To Calculate Demand Forecast Indicator

The demand forecast indicator takes into account various indices for each airport that fit the description discussed above. The indices accounted for include:

Country’s gross domestic product per capita; Population of origin and destination cities; Country’s urban population for 2005; The business, politics and development index indicators; Tourism infrastructure index; Whether the origins and destinations fall internally within one country; Airport infrastructure; and Distance between the various origins and destinations.

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A brief description of these various data sets and indices follows in the remainder of this section.

2.4.1.2.1 Gross domestic product per capita

The gross domestic product per capita has been sourced from the International Monetary Fund website. The GDP per capita figures used are stated in US$ 2007 at current prices and are displayed in Table 2.4-1 below. GDP per capita was used as countries with a higher GDP per capita are more likely to demand more flights as flying is still largely a luxury form of transport in Africa.

Table 2.4-1 Gross Domestic Product Per Capita, Current 2007 Prices

Country GDP per capita US$ Angola 5,276.83 Botswana 8,032.88 Democratic Republic of Congo 174.068 Lesotho 706.021 Madagascar 430.419 Malawi 268.594 Mauritius 5,891.24 Mozambique 420.611 Namibia 3,502.10 Seychelles 8,482.88 South Africa 6,185.43 Swaziland 2,380.52 Tanzania 392.434 Zambia 957.335 Zimbabwe 139.754

2.4.1.2.2 Population by city

Where a city has an airport with the appropriate runway length and surface, the rough population of that city has been taken into account. It has been assumed that the larger the city, the higher the demand for flights to and from that city. A full list of cities in the SADC region and the population levels for each of these cities was obtained from http://www.tageo.com/index.htm. This data was used to create relative proportions for each of the cities, thereby determining the ranking of cities expected to have a higher demand for flights under an air transportation liberalisation regime. A table listing the populations used by city can be found in Appendix F.

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2.4.1.2.3 Urban population

In addition to the city population data, each country’s urban population levels were gathered from a United Nations database (http://data.un.org/Default.aspx). Urban population data for 2005 for the SADC countries in question was utilised. This data is shown in Table 2.4-2, below. These figures have been taken into account to determine a ranking of origin and destination cities that could be expected to have a higher demand for flights under an air transportation liberalisation regime based on the overall urban population of the countries where these sites are located.

Table 2.4-2 Urban Population by Country

Country Urban population Angola 5,930,052 Botswana 926,625 Democratic Republic of Congo 18,818,523 Lesotho 326,690 Madagascar 5,023,620 Malawi 2,216,048 Mauritius 545,310 Mozambique 7,520,960 Namibia 680,385 Seychelles 46,980 South Africa 27,463,128 Swaziland 246,648 Tanzania 14,373,375 Zambia 4,258,820 Zimbabwe 4,670,590

2.4.1.2.4 Business, politics and development index indicators

The business, politics and development indicators have been drawn from various sources and have been combined to create one weight in the demand forecast model. The business information which included the ‘Country Risk Rating (September 2008)’ and ‘Global Competitiveness Index (2007-2008)’, is sourced from the World Economic Forum (gcr.weforum.org). The political information is sourced from the ‘Press Freedom Index (2008)’ and can be found in the Reporters Without Borders website (http://www.rsf.org/). The development information utilised is the ‘Human Development Index (2006)’ from the United Nations Development Program (http://hdr.undp.org/en/statistics/). These indicators are summarised in Table 2.4-3, overleaf. Each of these indicators has been modified to be rated between 100 and 0 (with 100 being an excellent rating and 0 being an extremely poor rating). The various indicators have been averaged in the last column of the table and these averages have been used in determining the demand weighting for each qualifying airport.

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Table 2.4-3 Business, Political and Development Indicators for SADC Country

Country Country Risk Rating Global Competitiveness HDI Press Freedom Average (Sept 2008) Index (2007-2008) 2006 Index (2008)

Angola 36 45 48.4 70.5 50.1 Botswana 65 60.71428571 66.4 86 69.6 Democratic Republic of Congo 30 41.14285714 36.1 48.75 39.0 Lesotho 41 48.57142857 49.6 70.5 52.3 Madagascar 35 48.28571429 53.3 79 54.0 Malawi 35 48.85714286 45.7 85 53.6 Mauritius 56 60.71428571 80.2 91 72.0 Mozambique 41 45 36.6 79.5 50.5 Namibia 40 57 63.4 94.5 63.7 Seychelles 40 60.71428571 83.6 84.5 67.2 South Africa 60 63 67 92 70.6 Swaziland 38 48.57142857 54.2 49.5 47.6 Tanzania 39 49.85714286 50.3 85 56.1 Zambia 36 49.85714286 45.3 84.5 53.9 Zimbabwe 30 41.14285714 32.1 46 37.3 Source: World Economic Forum (gcr.weforum.org), Reporters Without Borders website (http://www.rsf.org/) and United Nations Development Program (http://hdr.undp.org/en/statistics/)

2.4.1.2.5 Tourism infrastructure index

The level of tourism infrastructure is likely to influence the number of flights demanded in each country under an air transportation liberalisation regime. Countries with modern and developing tourism infrastructure tend to attract far more tourists; therefore the ‘Tourism Infrastructure index’ was sourced from the World Economic Forum website (http://www.weforum.org/documents/TTCR09/index.html). This index takes into account the following:

Air transport infrastructure in each country, Ground transport infrastructure, Tourism infrastructure, Information and Communication Technologies (ICT) infrastructure and, Price competitiveness in the transport and tourism industry. The tourism infrastructure index is measured between 7 and 0 (with 7 representing excellent tourism infrastructure and 0 representing extremely poor tourism infrastructure.) The tourism infrastructure index for each SADC country is summarised in Table 2.4-4.

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Table 2.4-4 Tourism Infrastructure Index by Country

Country Tourism Infrastructure Index Angola 3.05 Botswana 4.125 Democratic Republic of Congo 3.1 Lesotho 3.05 Madagascar 3.425 Malawi 3.025 Mauritius 5.05 Mozambique 3.05 Namibia 4.075 Seychelles 5.05 South Africa 4.775 Swaziland 3.05 Tanzania 3.2 Zambia 3.325 Zimbabwe 3.1

2.4.1.2.6 Airport infrastructure

Airport infrastructure influences the demand forecast for routes. Where infrastructure is lacking, so is the supply of flights. A detailed list of airport infrastructure has been obtained from the International Civil Aviation Organisation. This data indicates the airports with an instrument procedure list (a landing procedure manual for pilots), airports with runways, airports with customs facilities, and whether the airports run privately, publicly or by the military. An example of the information utilised can be seen in Table 2.4-5 below, where an airport which has a given infrastructure is given a value of 1.

Table 2.4-5 Airport Infrastructure

Airport Country Usage Customs Runway Instrument Previously Paved Approach Served Procedure Airport Luanda Angola Civil 1 1 1 1 Gaborone Botswana Civil 1 1 1 1 Maseru Lesotho Civil 1 1 1 1 Antanànarìvo Madagascar Civil 1 1 1 1 Lilongwe Malawi Civil 1 1 1 1 Port Louis Mauritius Civil 1 1 1 1 Maputo Mozambique Civil 1 1 1 1 Windhoek Namibia Civil 1 1 1 1 Johannesburg South Africa Private 0 1 1 0 Johannesburg South Africa Civil 1 1 1 1 Dar-Es-Salaam Tanzania Civil 1 1 1 1 Lusaka Zambia Civil 1 1 1 1 Source: International Civil Aviation Organisation

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2.4.1.2.7 Domestic flights

Domestic routes within one country exhibit higher flight supply than international routes. Therefore where air routes are entirely domestic a positive weighting of one has been assigned.

2.4.1.3 Determining the Demand for Each Potential Route in SADC

2.4.1.3.1 Method of calculating the indices for each factor

As already mentioned, each of the aforementioned data sets for each of the potential pairs of airports in the SADC region has been converted into an index between 0 and 1. The calculation of these indices varies according to the data available; the 1 and 0 index only considers two airports. The varied data results in a varied effect on the ultimate anticipated demand for flights to and from various destinations. The indices have been calculated by one of two methods, the dimension index method or as a proportion.

2.4.1.3.1.1 The dimension index method

For each indicator a minimum and maximum goalpost must be defined and then the indicator must be normalized between 0 and 1, based on the country or the airports relative position. This concept is displayed in Box 2.4-1 below.

Box 2.4-1

Actual value of indicator Minimum of indicator|------x------|Maximum of indicator

Index =(Actual value of indicator) – (Minimum of indicator) (Maximum of indicator) – (Minimum of indicator)

Where this method was utilised in determining the various indices it was observed that those indices would tend to supply more flights if they started from a low level of operation. This was evident when considering GDP per capita (discussed in detail below). Therefore each indicator was logged, as seen in Box 2.4-2.

Box 2.4-2

Index = log (Actual value of indicator) – log (Minimum of indicator) log (Maximum of indicator) – log (Minimum of indicator)

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In the case of GDP per capita this effectively means that increases in income at a lower level has a greater impact on the GDP per capita index, as shown in Figure 2.4-1 below.

Figure 2.4-1 GDP per Capita Index

1 0.9 0.8 0.7 0.6 0.5 0.4

0.3 GDP per GDP capita Index 0.2 0.1 0 GDP per capita, US$ (2007)

2.4.1.3.1.2 Proportion method

The proportion method was used where data had already been taken from an existing index. This was effectively converted into an index between 0 and 1, where proportions were maintained.

2.4.1.3.2 Gross domestic product per capita index

The GDP per capita index used the dimension index method to determine the weight of the index. The calculation of the GDP per capita index assumes that an air transport liberalisation agreement in SADC will make flying more affordable and that those individuals with lower income levels. These individual will switch to air transportation when cost and amount of time travelling between various cities within the SADC region decreases. Therefore the higher an individual’s income and countries GDP per capita the higher the amount of people utilising air transport as method of transportation. Thereby as incomes increase within a country the transition from road and rail transport to air transport will increase at an increasing rate due to new low cost carriers entering the market.

2.4.1.3.3 Urban population of countries

Urbanization has increased significantly around Africa; we would expect this over the next 50 years. Governments increasingly will be required to respond to this phenomenon with appropriate social,

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Muller Associates Department o f Transport P a g e | 89 political and economic interventions that would lead to increased job creation and economic activity around urban centres. As shown in the literature review one of the basic assumptions of the gravity model is that increased urban populations will lead to an increase in demand for flights.

Once again the dimension index method is utilised, since countries moving off a low base of urbanization would, under an air transportation liberalisation regime, demand flights from low income carriers more rapidly as the population urbanises. The bias towards countries with lower urban populations follows the argument presented by Swan (2008) in the literature review where under an air transportation liberalisation agreement between countries flights and aviation development shift away from the traditional airport hubs to the more decentralised airports and cities. This has been observed in South Africa over the last decade where low income carrier airlines have increasingly expanded their destinations to urban centres with lower populations such as the Durban to George, Durban to Port Elizabeth and Johannesburg to Windhoek or Gaborone flights (www.1time.aero & www.kulula.com). This is a trend that has also been displayed in the European Union and India where routes have began to expand to traditionally less well serviced airports and cities with lower populations.

2.4.1.3.4 Population by city

Similar to the argument above it is anticipated that cities with higher populations tend to demand more flights, and with the implementation of air transport liberalisation agreement in SADC it is expected that there will be a gradual shift away from the traditional airport hubs and major urban centres. Once again the dimension index method was employed to determine an index level for each airport.

2.4.1.3.5 Business, politics and development index indicators

The countries business, politics and development index indicators were already in index form. They were converted into proportions between 0 and 100 as shown in Table 2.4-3 above. These were then averaged and then converted to an index between 0 and 1, maintaining the established proportions.

2.4.1.3.6 Tourism infrastructure index

Likewise the tourism infrastructure index has already been established by the World Economic Forum as shown in Table 2.4-4. These indices fall between 0 and 7 for each country, thus we divided each of these indices by 7 to establish proportion between 0 and 1.

2.4.1.3.7 Airport infrastructure

As seen in Table 2.4-5, above, airport infrastructure for the various airports in SADC has been rated between 0 – 1, depending on whether an airport has the infrastructure in place for the four factors listed. To calculate this into an index we added the factors together and divided by 4 to yield an airport infrastructure index.

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2.4.1.3.8 Example of calculated Indices

Table 2.4-6, below, gives an example of the various indices discussed for the main airports of each SADC country.

Table 2.4-6 Example of Calculated Indices by Airport

Airport Country Airport GDP per City Urban Business, Politics & Tourism Infra. capita Pop. Pop. Development Infra. Luanda Angola 1 0.8991 0.9169 0.6740 0.5006 0.4357 Gaborone Botswana 1 0.9802 0.6707 0.4189 0.6958 0.5893 Kinshasa DRC 0.95 0.2407 0.9747 0.8328 0.3900 0.4429 Maseru Lesotho 1 0.5109 0.6379 0.2756 0.5232 0.4357 Antanànarìvo Madagascar 1 0.4154 0.8308 0.6512 0.5397 0.4893 Lilongwe Malawi 1 0.3244 0.7513 0.5387 0.5364 0.4321 Port Louis Mauritius 1 0.9203 0.6432 0.3460 0.7204 0.7214 Maputo Mozambique 1 0.4110 0.8562 0.7067 0.5048 0.4357 Windhoek Namibia 1 0.8200 0.6928 0.3764 0.6373 0.5821 Seychelles Seychelles 1 0.9907 0.4969 0.0025 0.6719 0.7214 Johannesburg South Africa 1 0.9297 0.9604 0.8847 0.7062 0.6821 Manzini Swaziland 0.9375 0.7455 0.6013 0.2369 0.4757 0.4357 Dar-Es-Salaam Tanzania 1 0.3976 0.8960 0.7980 0.5605 0.4571 Lusaka Zambia 1 0.5697 0.8346 0.6285 0.5392 0.4750 Harare Zimbabwe 0.875 0.1983 0.8902 0.6412 0.3731 0.4429

2.4.1.4 Utilising the Gravity Model to Establish the Route Demand

Determining the demand for each factor above between airports in SADC requires use of the gravity model, where similar factors are averaged to determine a combined index per route. The methods employed in the model are shown in Box 2.4-3 overleaf.

Box 2.4-3 Equation (2) Factor Demand = (Factor Index airpory A) + (Factor Index airport B)

Example: GDP demand airport A&B = (GDP per capita index airport A) + (GDP per capita index airport B)

To determine the estimate route demand, each of the factor demands needs to be combined. The model in question has done this by assigning weights to each factor depending on the importance that this factor has on overall demand. See equation (3) in Box 2.4-4 below. The model allows these weights

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Muller Associates Department o f Transport P a g e | 91 to be changed for the various demand factors on the tab ‘Weights & Proportions’. Table 2.4-7 below gives an example of how the demand estimates for each potential route in SADC has been calculated using the weights. The higher the demand estimate the higher the number of flights will be demanded.

Box 2.4-4 Equation (3) Route demand = (GDP demand airport A&B x A)+(City pop demand airport A&B x B)+(Urban pop demand airport A&B x C)+(Airport infra demand airport A&B x D)+(Bus, Pol & Dev demand airport A&B x E)+(Tourism infra demand airport A&B x F)

where: A + B + C + D + E + F = 100%

Table 2.4-7 Determining the Demand Estimate for Routes

Airports Same Airport GDP City Urban Business, Tourism DEMAND Country Infra- per Populatn Populatn Politics & Infra- ESTIMATE structure capita Development structure Weight 15% 5% 20% 25% 5% 20% 10% 100% Windhoek Johannesburg 0 1 0.8748 0.8266 0.6306 0.6717 0.6321 0.6607 Cape Town Johannesburg 1 1 0.9297 0.9363 0.8847 0.7062 0.6821 0.8737 Durban Johannesburg 1 1 0.9297 0.9302 0.8847 0.7062 0.6821 0.8722 Johannesburg Lusaka 0 1 0.7497 0.8975 0.7566 0.6227 0.5786 0.6445

2.4.1.5 Time Frames

There are 3916 potential routes in the SADC region. These routes are comprised of 89 airports with paved runways that are longer than 6400 feet. Not all of these routes will be feasible or cost effective in the short run, particularly if the current aviation market in SADC is taken into account. However, in the long term there is no reason for these routes not to become feasible, provided infrastructure, business and income levels continue to improve in each country. Therefore the model is structured such that it determines demand, potential turnover and seat numbers over a 50 year period.

In the first 5 years post implementation of an air transport liberalisation agreement in SADC, it can be expected that all the routes that are currently being operated by national flag carriers and low cost carriers would expand and attract new airlines and lower prices. New routes are unlikely as airlines and airports adjust to the new market regulations and demands. The first five years post the air transport liberalisation agreement in SADC only takes into account current routes being used. After 10 years the model predicts that routes with a demand estimate of greater than 0.75 would see new flights being operated. After a 15 year period the model predicts that routes with a demand estimate of greater than 0.70 would see new flights being operated. The model continues in this fashion of decreasing the demand estimate by 0.05 over 5 year intervals all the way to a 50 year time period where all routes have been included in the model.

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2.4.2 Direct Impacts

2.4.2.1 Determining Potential Turnover and Seat Numbers per Route

This section deals only with the direct impact experienced by airlines if an air transport liberalisation agreement was implemented in the SADC region. The red blocks highlighted in Figure 2.4-2 below display the primary focus of this model, namely; introduction and expansion of new flights to both new and existing destinations. Sections that follow will detail methodology used to estimate the direct and indirect impacts.

Figure 2.4-2 Flow chart showing methodology for the section

New destinations Benefits New Flights Current Airlines Destinations Costs Airports

Direct Open Skies Impacts Passengers

Freight

Customs

The demand estimate for each route has been used to determine the potential turnover as well as the seats demanded per week. The following section explains the methodology on how the figures for each individual route have been determined.

The questionnaire sent to airlines revealed both current seat capacities and pricing per flight. We received information on these from South African Airways (SAA), Comair (British Airways & Kulula.com) and Airports Company South Africa (ACSA). This information combined with the now calculated demand estimates between 0 and 1 reveals potential turnover and seat requirements on each route per week.

The model only takes into account data from South African domestic flights on very competitive routes (namely: Durban to Johannesburg, Cape Town to Johannesburg and Cape Town to Durban.) This is because of the vigorous competition of the established low cost carriers that operate on these routes. An air transportation liberalisation agreement in the SADC region will encourage aviation competition along all routes, which favours mostly low cost carriers.

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Table 2.4-8 shows how the supply of seats and potential turnover per route were determined. The average seats per route, along with the minimum price per seat were obtained from Kulula, British Airways and SAA questionnaires and online information. Multiplying these columns gives us the estimated turnover per flight; this has then been adjusted for a 75% take up of capacity. (SAA stated in their questionnaire that roughly 75% of capacity is taken up on flights). The distance in kilometres was then used to determine the turnover per kilometre on the three routes, which as can be seen in Table 2.4-8 ranged from R 34.68 to R 40.64. The turnover per kilometre was then divided by the demand estimate (these ranged between R 40.18 to R 46.60.) From these figures we determined if the demand estimate was 1 then an average of R 43.71 per kilometre would be the potential turnover per kilometre. The R43.71 per kilometre was then multiplied by:

Each routes distance in kilometres; Each routes demand estimate; and 131.56 (the average number of flights per week to and from Johannesburg to each South African domestic destination, as obtained from ACSA), and this was used to estimate the potential turnover per week for each particular route.

To estimate seat numbers per week, the ‘average seats per flight’ (130) was multiplied by the 131.56 (average number of flights to and from Johannesburg to each South African domestic destination) and then multiplied by each routes demand estimate. This calculated the estimated number of seats that would be demanded on each particular route. From the estimated turnover and seat numbers per week, an average ticket price per seat per flight was estimated.

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Table 2.4-8 Potential Turnover and Seat Numbers

Airport Demand Average Minimum Estimated Capacity Distance Turnover Turnover Potential Seat Average Estimate Seats / Price Turnover / take up of (km) per km per Km / Turnover per Numbers Ticket flight flight 75% Demand week per Price per estimate week flight Cape Durban 0.8630 123 R 480.00 R 59,040.00 R 44,280.00 1,277.00 R 34.68 R 40.18 R 6,336,564.47 7,361 R 430.42 Town Cape Johannesburg 0.8706 136 R 480.00 R 65,440.00 R 49,080.00 1,271.43 R 38.60 R 44.34 R 6,364,160.74 7,425 R 428.55 Town Durban Johannesburg 0.8722 130 R 200.00 R 25,933.33 R 19,450.00 478.59 R 40.64 R 46.60 R 2,400,018.47 7,439 R 161.31 Average: 130 R 43.71 8,529

2.4.2.2 Passenger Time Saving

This section focuses on the benefit to passenger if an air transport liberalisation agreement is implemented in SADC. Passengers firstly benefit from the decrease in airfares (due to increased competition among airlines), secondly from time saving now that airlines can bypass hub airports and land in destinations of their choice. Due to the lack of the current aviation information collected from the survey questionnaires provided by airlines it is impossible to determine the benefit that would accrue to passengers from a decrease in aviation prices. This price decrease would also happen over a period of time and only as competition increases; competition currently is marginal in SADC and therefore it would be guess work or complete speculation to predict how the competition would increase over time. Figure 2.4-3 displays how the passengers’ benefits fit into the overall impact.

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Figure 2.4-3 Showing how passengers’ benefits fit into the overall methodology

Airlines

Airports

Open Skies Direct Impacts Passengers Benefit Time Saving

Freight

Customs

The time benefit to passengers has been calculated by assuming that in order for a person to currently travel between various locations in SADC they are required to travel through the major airports in each country. This therefore means that a person wanting to travel from Durban, South Africa to Beira, Mozambique would need firstly to travel OR Tambo, Johannesburg and then to Maputo, Mozambique before connecting to Beira. This assumption has been followed for each potential origin and destination in SADC. Due to the sheer volume of potential routes that are available under the regulation allowed by an air transport liberalisation agreement, and the complexities of air travel in SADC this simplified assumption has been adopted. Under an air transport liberalisation agreement in SADC flying from origin to destination would be shortened because airline are allowed to fly directly from Durban, South Africa to Beira, Mozambique, thus there is massive time saving due to the direct flight offered.

Figure 2.4-4 overleaf illustrates the assumption of current air travel around SADC. It can be seen that all air traffic filters through a central hub within each country (yellow/gold lines to and from red points) and then through the central airport hub in SADC, namely OR Tambo in Johannesburg (red lines to the largest red point.) From this figure it can be seen that travelling around SADC can be costly in terms of tickets, airport taxes and time. An air transport liberalisation agreement in SADC would eventually do away with the large number of connecting flights and passengers could connect directly to their ultimate destination.

With the distances travelled by passengers prior to an air transport liberalisation agreement in SADC and the distances travelled post an air transport liberalisation agreement in SADC, there is saving in the distance travelled by passenger (this distance saved can be translated into the amount of kilometres saved in travel.) This distance can be converted into time when we take into account the average cruising speed of a commercial aircraft. The current average cruising speed of a commercial Airbus, Boeing or McDonald Douglas Aircraft is 900 kilometres per hour. With the amount of time saved in

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Muller Associates Department o f Transport P a g e | 96 terms of air travel known and now converted into time savings per hour it is easy to calculate the time saving benefit if you know the value of a passengers time in hours. Assuming the value of an hour for a passenger is a tricky undertaking due to the cross section of passengers that make use of air travel (these is an infinite number of reasons passenger fly and each of these would vary the value of time.) For the purposes of this study it has assumed that a person utilising air transportation would values an hour at R 200 (this is a completely arbitrary amount and a further study is required to understand a passengers value time saved.)

Figure 2.4-4 Assumed flight patterns between origins and destinations pre air transport liberalisation in SADC

Source: adapted, Google Earth 2010

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2.4.2.3 Direct Costs to Airlines

The direct impacts likely to be experienced by airlines are divided into costs and benefits. For this study, these costs have been broken down into five categories – cancellation costs, diversion costs, cost of fuel, aircraft operation costs and increased accidents and incidents.

All data has been derived from the EUROCONTROL 2007 document1 and the Standard Economic Values Guidelines report2. Where applicable, values sourced from these two documents have been converted into 2009 Rands3.

The table below summarises the monetary value of the abovementioned costs. The cost of fuel and the effect of an increase in the rate of fuel burn have been excluded from the table, and will be discussed separately below.

Table 2.4-9 The Monetary Value of Costs

Details Minimum Maximum Value

Cancellation The cost of cancelling the flight of a 120 seat - - R 172,033.02 Costs narrow body jet aircraft

Diversion The cost of diverting a regional flight R 8,028.28 R 57,344.83 - Costs The cost of diverting a continental flight R 11,468.97 R 86,017.24 -

Aircraft Estimated aircraft operating costs / hour in Rands - - R 23,330.00 operating (excluding fixed annual overheads) for an average costs aircraft

Accidents/ The average cost to an airline of a fatality - - R 26,378,620.74 incidents The average cost to an Minor injury - R 406,001.38 - airline of an injury Major injury - R 5,502,809.67 -

Note: all values are expressed in constant 2009 Rands.

The first aspect of direct costs that must be taken into account is the cost of cancellation.

Cancellation costs refer to the cost of abandoning a commercial scheduled flight on the day of operation. With more flights expected to be scheduled in an air transportation liberalisation environment, cancellation costs can be expected to rise following implementation of an air transport liberalisation agreement in SADC. These costs include service recovery costs, interline costs, loss of

1 Standard Inputs for EUROCONTROL Cost Benefit Analyses, 2007 Edition

2 Australian Government, Civil Aviation Safety Authority, Standard Economic Values Guidelines, Version 1.0: 2007

3 2007 AUD $ inflated by 6.25% to equal 2009 AUD $. 2009 AUD $ multiplied by 6.8106 to equal 2009 ZAR Rands. 2007 €’s inflated by 6.09% to equal 2009 €’s. 2009 €’s multiplied by 10.8106 to equal 2009 ZAR Rands.

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Muller Associates Department o f Transport P a g e | 98 future value and decrease in operational savings4. The cost above is specifically for a 120 seat narrow body aircraft and is estimated at R172,033.02 per cancellation.

The next cost category considered is the average cost per flight diversion, estimated separately for regional and continental flights. This is the cost of diverting a commercially-scheduled flight. As with cancellations, with more flights expected to be scheduled in an air transportation liberalisation environment, the costs of diversions can be expected to rise following implementation of an air transport liberalisation agreement in SADC. These values are estimated by means of a minimum- maximum bracket, as they can vary depending on the nature of the diversion. For regional flights, the range of cost is R8,028.28 to R 57,344.83, while for continental flights; the range is R 11,468.97 to R 86,017.24.

The cost of fuel, and subsequently the increased rate of fuel burn have been excluded from the table for two reasons. Firstly, data that was available on the cost of jet fuel was extremely generalised and thus generated no valuable information. Secondly, all data that was available in this area was gathered as fuel usage according to the tonnes per flight or kilograms per landing/take-off phase. Information on fuel use per kilometre was not available at this time. For these reasons, the cost of fuel has been excluded.

Aircraft operating costs refers to the average estimated cost of running an aircraft per hour. This cost has been estimated per hour at R 23,330.00. This value excludes all fixed annual overheads.

The value for accidents and incidents is an estimation of the cost to an airline in the event of an accident, whether resulting in injury or death. The possibility exists that implementing an air transport liberalisation agreement in SADC will result in more fatalities, from more flights operating at each airport. The cost to an airline in the event of such accidents and incidents must then be taken into account.

The estimated cost of a fatality is R 26,378,620.74. The cost of injury is estimated with an upper limit only. The cost of a minor injury is R 406,001.38 and the cost of a major injury is R 5,502,809.67. These estimates are the cost incurred to the airline in the event of an injury or a fatality.

4 Source: Cost-Benefit Analysis Methodology, Graham Muller Associates, 2010

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2.4.3 Indirect Impacts

2.4.3.1 Security

The indirect costs of increased air travel within the SADC region would include an increase in the amount of security personnel and infrastructure required to handle increased traffic.

There is currently no public information available for security costs across the SADC region; however a report on security costs in Australia5, a large common flying area revealed some interesting costs on a per passenger basis.

Airport security costs have some element of economies of scale and the per passenger charge in the Australian study was significantly lower for larger airports. Every airport will require security scanners and personnel to man them, but the throughput for an airport with a constant stream of arrivals versus one with few daily flights will obviously vary greatly.

Security mandates at airports under an air transportation liberalisation agreement should adhere to standardised security protocols and procedures and thus costing could be assumed to be similar through all airports of a similar size.

High fixed costs mean that smaller airports have to charge more for the same security functions as larger airports. Additionally international passengers have more security procedures to complete and thus international arrivals cost more. The variation in price for Australia varied from A$16 for a small international airport passenger arrival to A$4 for large airports handling domestic passengers.

Airports pass onto airlines the costs of operating the facilities based on passenger numbers and freight volumes and airlines therefore consider security costs when deciding on which airports to utilise.

Additionally there are two elements to the costing of airport security, one is the cost borne by the airlines and relates directly to their security costs and the other relates to the security of the country as a whole and thus some of the security costs are carried by national government.

The increased flights will result in a turnover in security costs of A$4,90 per passenger for domestic flights and A$8 for international flights. That will account for increased spending of R32,93 per passenger boarding or disembarking for domestic flights and R53,76 for international flights.

5http://www.infrastructure.gov.au/aviation/nap/files_green_paper/Government_of_Northern_Territory- Access%20Economics_att.pdf

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2.4.3.2 Transport

Benefits of an air transportation liberalisation policy to the travel and transport industry will extend to both tourism and freight. The impacts of increased freight would be an increase in the number of air freight routes and more timely arrival of freight to a variety of destinations. However current patterns of air traffic suggest that air freight transportation is dependent on an established passenger air travel service. The impact on the transport industry can be predicted on its own in relation to air arrivals, however the tourism impact section accounts for these impacts by estimating the change in passenger arrivals will have on the country of destination as a whole. The tourism impact includes transport spending and thus in order to avoid double counting we can assume that the impact on the transport section is included in the tourism section.

Some statistics from a Detroit Metropolitan Wayne County Airport Impact Study conducted in 2006 indicate the transport patterns of traveller arrivals. Tourists accounted for 33% of air arrivals and residents accounted for 63% of arrivals. For tourists, the average stay was 3.5 days. Half of tourists, or 16% or air arrivals rented a car for the average 3,14 days. The average spend on car rental was the equivalent of R770 per stay.

2.4.3.3 Pollution

A further consideration as a negative externality which is difficult to quantify is the impact of an air transportation liberalisation policy on pollution in the SADC region.

The standard inputs for EUROCONTROL Cost benefit Analyses 2007 edition suggests two types of pollution; noise emanating from aircraft engines and air pollutants from the of burning fuel.

For the fuel portion they suggest the following rate of pollution:

Table 2.4-10 Cost of Fuel

Pollutant per kg of fuel burned6 Cost7 Burn Rate8 (737- 800) Cost per hour of flying time

CO2 3.149 kg R360 per tonne 2,572 tonnes/h R925,92

H20 1.230 kg R101 per tonne 2,572 tonnes/h R259,72 Total: R1185,67

The 737-800 aircraft was used as it is one of the most likely planes to be used on the SADC routes.

6 http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note_2001_08.pdf

7 “Economic incentives to control the global environmental impact of European aviation/Level of the incentive”, CE, Solutions for environment, economy and technology, Delft, The Netherlands

8 http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf

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Furthermore noise pollution levels in the EUROCONTROL study are costed at R693 per take off and an additional R693 per landing. It must be noted that aircrafts used in Europe are generally newer and therefore create less pollution. The study has maintained the levels set by the EUROCONTROL study, as there is no data that is more relevant to the South African aviation situation.

2.4.3.4 Tourism Impact

Implementation of an air transport liberalisation agreement in SADC will result in increased visitor arrivals and increased overnight visitor stays boosting the tourism industry in participating countries. To estimate the impact of this effect on the economy of the countries involved in the study, tourism data was obtained from the World Travel and Tourism website9. The website contains tourism data for thirteen of the fifteen countries in SADC. The countries omitted are Mozambique and Seychelles, for these countries the data for Tanzania in Mozambique’s case and Mauritius in Seychelles case was used. The economic data search tool on the website allows this data to be edited into a suitable format. The figures for the total impact of tourism on the economy (including indirect and induced spending) in terms of gross domestic product (GDP) and employment, as well as the direct tourism industry impact on GDP and employment for the period 1988 to 2010 was acquired. In addition numbers of international visitors and overnight visitors’ data was obtained in order to translate seat numbers within the model into an overnight tourism figure.

In order to arrive at a usable “multiplier” for the seat numbers data produced by the routes demand model, the following process is carried out. First each data set for each country is averaged over the period (1988 – 2010). As data does not exist for Mozambique and Seychelles, the averages from Tanzania and Mauritius were used respectively, as these countries are likely to have similar circumstances in terms of tourism. This average, for example the total average impact of the tourism industry on a country’s GDP, is divided by the total number of overnight visitors to give the total impact of the tourism industry on a country’s GDP by one overnight visitor. The percentage of the increase in seat numbers from the model that can apply to tourism spend is translated into an overnight visitor figure by taking the average percentage of international visitors between 1988 and 2010 and dividing it by the average overnight visitors for the period. This gives an estimate of how many of the new passengers will contribute to the tourism industry.

The methodology is applied to generate a forecast of total impact of tourism on employment, and direct impact of tourism on GDP and employment. To arrive at the aggregate estimated impact of increased levels of tourism activity resulting from implementation of an air transport liberalisation agreement in SADC for ten five year periods totalling fifty years in all. The results of this process are included in chapter 4.

9 http://www.wttc.org/

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The methodology the WTTC employed to arrive at the figures in the council’s database that the study team used in this process can be found on the WTTC website10.

2.4.4 Airport and Navigational Infrastructure

Adequate airport and navigational infrastructure is essential in creating the platform for airlines to take advantage of air transport liberalisation regulations. Airport capacity and navigational infrastructure is mostly below international standards beyond the borders of South Africa in the SADC region. Airport and navigational infrastructure would need to be upgraded or installed throughout the region to create capacity for all the additional flights and passengers due to air transport liberalisation within the SADC region. All the information and data regarding infrastructure requirements and costs have been provided by Air Traffic & Navigational Services (ATNS) and the Airports Company South Africa (ACSA). The navigational infrastructure costs have been broken into two parts: the first being the navigational equipment required per route; and the second being the navigational equipment required per airport. The airport infrastructure costs are purely an airport cost to create the capacity to handle increased number of passengers.

2.4.4.1 Navigational Infrastructure per Route

Navigational equipment is not only required at the various airports but also at various intervals along each route. The navigational equipment required depends on the nautical miles (NM) separation between aircrafts and the flight level being flown by aircrafts. For the purpose of this study we’ve assumed that all navigational equipment needs to be standardised across the SADC region at South African specifications. This would entail navigational equipment being installed with the technological stipulations to allow aircrafts to travel 5 NM apart from each other. The navigational equipment requirements has been listed in Table 2.4-11 below for 5 NM distance between aircrafts, it can be seen the unit cost has been provided for each piece of equipments, as well as their theoretical coverage in kilometres and the number of these units required to accommodate a distance of 5 NM per aircraft.

With this information displayed in Table 2.4-11 it is possible to calculate the cost of navigational equipment per kilometre for each route within the SADC region. This information has been calculated for both the 145 and 195 flight levels (the upper and lower range of flight levels.) Although the cost of navigational infrastructure is a cost that is incurred every 15 years, for the purpose of our study this cost has been broken down into a weekly cost and can be compared with the other costs and benefits.

10http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_pdf_file/economic_impact_res earch_metho.pdf

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Table 2.4-11 Navigational Equipment Requirements per Route at 5 NM11 Navigational Unit Costs Theoretical Coverage (KM) 5 NM Navigational Requirement Equipment FL 145 FL 195 FL 145 FL 195 DVOR/DME 6,000,000 180 200 1 1 SSR 25,000,000 230 315 2 2 VHF 150,000 230 315 1 1

2.4.4.2 Airport Navigational Equipment Costs

Airport navigational costs have been provided by ATNS. The airport navigational infrastructure that ATNS has recommended is aligned with the navigational systems and standards currently adopted in South African airports. The navigational airport infrastructure has a 15 year life span, after which the navigational equipment needs to be replaced. Table 2.4-12 lists the navigational equipment required depending on the type of airport.

Table 2.4-12 Airport Navigational Equipment Required per Airport Type Facilities Unit Cost Type 1 Type 2 Type 3 DVOR/DME 6,000,000 1 1 1 VDF (Class C) 350,000 1 1 SSR 25,000,000 1 1 PSR 35,000,000 1 VHF 150,000 1 2 3 TCU 10,000,000 1

The number of flights determines the amount of navigational equipment required. For the purposes of this report the airports have been separated into three categories based on the number of passengers passing through the terminals annually. The simplified definitions of the three types of airports are: Type 1 airports have low number of annual passengers; type 2 airports have medium number of annual passengers; and type 3 airports are the major airports in the SADC region. The various classifications of airports have been listed in Table 2.4-13 to Table 2.4 -16.

This information helps determine the cost navigational equipment cost per airport. As this is a sunk capital cost every 15 years, the profitability per airport will be determined over the 50 year period to assess the overall impact of the infrastructure installed per airport.

11 The rand value’s are based on a Euro Rand exchange rate of R11=1 Euro at July 2010prices

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Table 2.4-13 Type 1 Airports in the SADC Region Type 1 Location Country Location Country Location Country Dundo Angola Gemena D.R. Congo Mariental Namibia Huambo Angola Goma D.R. Congo Ondangwa Namibia Kuito Angola Isiro-Matari D.R. Congo Rundu Namibia Lubango Angola Kananga D.R. Congo Mafikeng South Africa Luena Angola Kindu D.R. Congo Polokwane South Africa Malanje Angola Mbandaka D.R. Congo Pilanesberg South Africa Menongue Angola Mbuji-Mayi D.R. Congo Umtata South Africa Namibe Angola Nosy Be Madagascar Welkom South Africa Ondjiva Angola Toliara Madagascar Mtwara Tanzania Saurimo Angola Chimoio Mozambique Mwanza Tanzania Soyo Angola Cuamba Mozambique Kitwe Zambia Uíge Angola Mueda Mozambique Mfuwe Zambia Kasane Botswana Tete Mozambique Ndola Zambia Bukavu D.R. Congo Karabib Namibia Hwange Zimbabwe Buta-Zega D.R. Congo Katima Mulilo Namibia Gbadolite D.R. Congo Keetmanshoop Namibia

Table 2.4-14 Type 2 Airports in the SADC Region Type 2 Location Country Location Country Location Country Cabinda Angola Beira Mozambique Nelspruit South Africa Catumbela Angola Lichinga Mozambique Port Elizabeth South Africa Francistown Botswana Moçimboa da Praia Mozambique Upington South Africa Maun Botswana Nampula Mozambique Manzini Swaziland Kisangani D.R. Congo Grootfontein Namibia Dodoma Tanzania Lubumbashi D.R. Congo Bisho South Africa Kilimanjaro Tanzania Maseru Lesotho Bloemfontein South Africa Livingstone Zambia Mahajanga Madagascar George South Africa Bulawayo Zimbabwe Toamasina Madagascar Johannesburg (Lanseria) South Africa Victoria Falls Zimbabwe Blantyre Malawi Kimberley South Africa

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Table 2.4-15 Type 3 Airports in the SADC Region Type 3 Location Country Location Country Location Country Luanda Angola Maputo Mozambique Dar-Es-Salaam Tanzania Gaborone Botswana Windhoek Namibia Zanzibar Tanzania Kinshasa D.R. Congo Seychelles Seychelles Lusaka Zambia Antanànarìvo Madagascar Cape Town South Africa Harare Zimbabwe Lilongwe Malawi Durban South Africa Port Louis Mauritius Johannesburg South Africa

2.4.4.3 Airport capacity constraints and expansions

Airports are constrained by peak hour capacity limits, as there are a limited number of bays for aeroplanes and a limited amount of trained staff to deal with passengers. Therefore, it is important to assess the additional capacity required based on the demand predicted by this study and determine the cost of airport infrastructure. This study has utilised the ACSA estimate that determines it would roughly cost R 600 million to create an additional airport capacity for one million passengers.

Verifying the capacities for all the airports in the SADC region is extremely difficult, as only the ACSA airports capacities are known. Therefore, capacities have been assumed based on the capacity information provided by ACSA. Table 2-20 SADC airport capacities display the assumed capacities for the airports in the SADC region. Major airports outside of South Africa have been given a 14 million annual passenger capacity (in line with Cape Town International), medium sized airports have been given an annual capacity of 4.5 million passengers (in line with King Shaka International), and small airports have been given an annual capacity of 720,000 passengers (an average of all the smaller ACSA airports.)

The investment in airport infrastructure has been linked with the forecasted number of passengers utilising the airports annually over the 50 year period. As passenger numbers exceed capacities displayed in Table 2.4-16 the ratio of R 600 million for every one million extra passengers is applied. This would yield an increased airport capacity aligned with the passenger forecast growth over the 50 years. The ACSA airports where annual passenger capacities are known are highlighted in red in Table 2.4-16.

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Table 2.4-16 SADC Airport Capacities Location Annual Capacity Location Annual Capacity Location Annual Capacity Cabinda 720,000 Mbuji-Mayi 720,000 Durban 4,500,000 Catumbela 4,500,000 Maseru 4,500,000 George 900,000 Dundo 720,000 Antanànarìvo 14,000,000 Lanseria 720,000 Huambo 720,000 Mahajanga 4,500,000 Johannesburg 28,000,000 Kuito 720,000 Nosy Be 720,000 Kimberley 200,000 Luanda 14,000,000 Toamasina 4,500,000 Mafikeng 720,000 Lubango 720,000 Toliara 720,000 Nelspruit 720,000 Luena 720,000 Blantyre 4,500,000 Polokwane 720,000 Malanje 720,000 Lilongwe 14,000,000 Port Elizabeth 2,000,000 Menongue 720,000 Port Louis 14,000,000 Pilanesberg 40,000 Namibe 720,000 Beira 4,500,000 Umtata 720,000 Ondjiva 720,000 Chimoio 720,000 Upington 100,000 Saurimo 720,000 Cuamba 720,000 Welkom 720,000 Soyo 720,000 Lichinga 720,000 Manzini 4,500,000 Uíge 720,000 Maputo 14,000,000 Dar-Es-Salaam 14,000,000 Francistown 720,000 Moçimboa da Praia 720,000 Dodoma 720,000 Gaborone 14,000,000 Mueda 720,000 Kilimanjaro 4,500,000 Kasane 720,000 Nampula 4,500,000 Mtwara 720,000 Maun 4,500,000 Tete 720,000 Mwanza 720,000 Bukavu 720,000 Grootfontein 4,500,000 Zanzibar 720,000 Buta-Zega 720,000 Karabib 720,000 Kitwe 720,000 Gbadolite 720,000 Katima Mulilo 720,000 Livingstone 4,500,000 Gemena 720,000 Keetmanshoop 720,000 Lusaka 14,000,000 Goma 720,000 Mariental 720,000 Mfuwe 720,000 Isiro-Matari 720,000 Ondangwa 720,000 Ndola 720,000 Kananga 720,000 Rundu 720,000 Bulawayo 720,000 Kindu 720,000 Windhoek 14,000,000 Harare 14,000,000 Kinshasa 14,000,000 Seychelles 14,000,000 Hwange 720,000 Kisangani 4,500,000 Bisho 1,200,000 Victoria Falls 4,500,000 Lubumbashi 4,500,000 Bloemfontein 600,000 Mbandaka 720,000 Cape Town 14,000,000

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2.5 Cost-Benefit Analysis Results

2.5.1 Direct Impacts

2.5.2 Benefit to airlines

As explained in the methodology the number of flights added, at each five year interval, is determined by whether the demand estimate per route is greater than the progressive 0.05 decrease in the demand estimate hurdle rate assumed by the model for every five year period into the future. The model therefore predicts that flights yielding a higher demand will be taken up by airlines in the early stages of implementation of an air transport liberalisation agreement in SADC as they offer the prospect of lowest commercial risk and the highest return in terms of profitability.

During the 35 to 50 year period post full implementation of an air transport liberalisation agreement in SADC, flights still being added by airlines will effectively be serving progressively higher commercial risk and lower profit routes. The reason for this is that all the major routes will be fully operational and there will be reduced market share for additional airlines or additional flights. Airlines will therefore seek to grow their market share by offering flights on these commercially riskier and less profitable routes. Of course, in reality, air fares are likely to be higher on these routes to reflect the higher commercial risk, because fewer airlines will be attracted to the routes with lower commercial potential.

Table 2.5-1, below, shows the forecasted turnover, seat numbers and flights (per week) over a 50 year period starting from the day an air transport liberalisation agreement in SADC is broadly implemented in SADC. This gross turnover included existing turnover on routes flown prior to implementation of an air transport liberalisation agreement in SADC. Unfortunately, for reasons of confidentiality, the airlines responding to the study questionnaire were not willing to disclose existing turnover figures. In consequence, the study only forecasted the gross turnover projections post implementation of an air transport liberalisation agreement in SADC. It can be observed that over a 50 year period the forecasted turnover per week for low cost carriers would total R 21.8 billion (2009 prices).

Table 2.5-1 Forecasted Turnover, Seat Numbers & Number of flights (per week)

Years Turnover Seat Numbers Number of flights 5 R 395,592,569.17 1,157,834 13,024 10 R 615,030,014.60 2,155,705 22,628 15 R 631,437,961.30 2,253,469 23,680 20 R 1,055,829,325.19 3,634,050 39,598 25 R 3,194,221,298.65 7,059,728 82,222 30 R 8,886,816,358.07 15,622,239 197,596

35 R 15,354,301,000.26 24,847,174 333,625 40 R 20,306,047,606.09 32,446,460 456,498 45 R 21,592,032,312.26 34,280,245 489,124 50 R 21,804,364,460.93 34,697,974 498,464

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On average 34.6 million passengers would travel within SADC weekly and there would be almost half a million flight operating across all SADC routes per week. Turnover grows rapidly, especially from the 15th year and indicates the significant benefit to airlines of implementing an air transport liberalisation agreement in SADC.

Figure 2.5-1, below, displays the growth in turnover for low cost carriers over the 50 year period following the implementation of an air transport liberalisation agreement in SADC. It is expected that the graph would encompass an S-bending curve because the initial take up after liberalisation would be slow due to airlines adjusting to the new regulatory environment. It can also be expected that the lower commercial risk and higher return routes will be added to airlines’ routes flown in the early stages of liberalisation, before the higher commercial risk and lower return routes are added. This is reflected in what the model predicts – as shown in Figure 2.5-1. This graph shows that between implementation and 35 years turnover would increase at an increasing rate and then from the 35th to the 50th year turnover would increase at a decreasing rate.

Figure 2.5-1 Forecasted Turnover

R 25,000,000,000.00

R 20,000,000,000.00

R 15,000,000,000.00

R 10,000,000,000.00

R 5,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

The marginal turnover graph can be seen in Figure 2.5-2. This graph shows the amount of additional turnover added at each 5 year interval. It can be seen that at 35 years the amount of turnover being added begins to decrease. This reflects that during the first 35 years route and flight additions would focus on the commercially more feasible and low risk routes. There would be heavy competition amongst airlines operating in the SADC region. The routes added beyond 35 years of implementing an air transport liberalisation agreement in SADC would be higher risk and lower demand and would only be taken up by airlines once the major routes are completely serviced, but airlines seek to further extend their aviation market share.

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The marginal cost curves and all other marginal benefit curves, with the exception of the marginal benefit to passengers graph display a similar shape, peaking at 35 years. The marginal benefit to passengers did not peak at the 35 year. This graph is displayed and discussed at a later stage in this section.

The rest of these graphs have not been included in this report but can be viewed in the accompanying Microsoft Excel economic forecast model.

Figure 2.5-2 Marginal turnover

R 7,000,000,000.00

R 6,000,000,000.00

R 5,000,000,000.00

R 4,000,000,000.00

R 3,000,000,000.00

R 2,000,000,000.00

R 1,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50

Figure 2.5-3, overleaf, indicates the growth in seat numbers purchased over a 50 year period after implementing an air transport liberalisation agreement in SADC based on the assumption that 75% of seats on offer are taken up. Similarly to Figure 2.5-1, which indicates growth in turnover over the same 50 year time frame, an s-bend curve is observed. As seat numbers are closely correlated with turnover the s-bend similar to that of turnover is expected.

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Figure 2.5-3 Growth in Seat Numbers

40,000,000

35,000,000

30,000,000

25,000,000

20,000,000

15,000,000

10,000,000

5,000,000

- 5 10 15 20 25 30 35 40 45 50 Year

It can also be expected that growth in the number of flights per week over the 50 year period following the implementation of an air transport liberalisation agreement in SADC will increase in a similar way to that of turnover and seat numbers, since the number of flights is directly related to the number of seats demanded and sold. The s-bending curve for the number of flights per week can be seen in Figure 2.5-4, below. Once again the same reasoning is applicable, where flights are added to the low commercial risk and high return routes during the initial 35 year period and thereafter, with limited opportunity for additional flights on these routes, flights being added to the higher commercial risk and lower return routes are embarked on in the 35 to 50 year period.

Figure 2.5-4 Growth in Number of Flights per Week

600,000

500,000

400,000

300,000

200,000

100,000

- 5 10 15 20 25 30 35 40 45 50 Year

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2.5.3 Benefits to passengers

As discussed in the methodology there are primarily two benefits that would accrue to passengers following a liberalisation of aviation regulations. Firstly the benefit of decreased ticket prices and secondly time savings from flights bypassing hub airports and flying directly from the points of origin to destinations that passengers actually want to fly to. It has already been noted that it proved impossible to account for the benefit from the decrease in ticket prices due to the limited commercial information received from airlines currently operating in SADC. However the study team has calculated the time saving benefit that would accrue to passengers due to time savings of flying directly to a destination, bypassing hub airports and flying directly.

2.5.3.1 Time savings

The assumptions that are spelled out in the methodology section of this report have informed the results that follow. It has been estimated that there will be a 7.9 million kilometre (per week) decrease in the distance flown by passengers to reach their final destinations. If the average cruising speed of an aircraft is 900km/h then approximately 8805 hours would be saved in air travel for all routes within SADC. Table 2.5-2 below shows how this time saving was estimated in 2009 Rands if a person values an hour saved at the entirely notional value of R200 per hour. Table 2.5-2 indicates that time saving by passengers over a 50 year period would total R 13.9 billion. Regardless of the notional value per hour chosen for passenger time this indicates that the value of this aggregate benefit will be substantial.

Table 2.5-2 Passenger Time Saving Benefit Years Value of Passenger Time Saved at a Value of R200/hour 5 R 80,704,142.39 10 R 148,353,788.17 15 R 152,429,875.57 20 R 265,108,382.22 25 R 766,732,401.87 30 R 2,961,410,846.08 35 R 7,207,220,265.68 40 R 12,429,642,407.48 45 R 13,703,434,148.72 50 R 13,957,174,567.04

Once again, as can be seen in Figure 2.5-5 overleaf, an S-bend shaped curve describes the relationship between the values of passengers’ time saved over a 50 year period. Again this is expected as initially routes that exhibit generally low commercial risk and high returns would be adopted by low cost carriers. As the results from the model indicate that routes operating to or from hub airports generally exhibit lower commercial risk and higher returns due to higher population concentrations and higher levels of business activities, this means that relatively limited time savings to passengers would be

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Muller Associates Department o f Transport P a g e | 112 generated in the early years post implementation of an air transport liberalisation agreement in SADC. A number of these routes are currently being operated by national flag carriers and therefore a low cost carrier operating on these routes would be able to fairly easily win business, at relatively low commercial risk, on these routes, in a de-regulated operating environment. As more commercially challenging routes that bypass the hub airports, are added in later years, time savings to passengers would begin to increase, exponentially at first and then tapering off as the overall SADC aviation market approaches saturation.

Figure 2.5-5 Passengers Time Saving Benefit

R 16,000,000,000.00

R 14,000,000,000.00

R 12,000,000,000.00

R 10,000,000,000.00

R 8,000,000,000.00

R 6,000,000,000.00

R 4,000,000,000.00

R 2,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

Figure 2.5-6 shows the marginal benefits resulting from passengers’ time saving in each five year period post implementation of an air transport liberalisation agreement in SADC. As mentioned earlier in the report, the 5 year marginal benefit from passengers’ time peaks at year 40 post implementation of an air transport liberalisation agreement in SADC, somewhat later than for other benefits predicted by the cost-benefit model, the quantum of which peak in year 35 post implementation of an air transport liberalisation agreement in SADC. This is again a reflection that the largest time benefits to passengers are experienced as the highest commercial risk and lowest return routes (which tend to be those that bypass hub airports) are added to the route networks of low cost carriers.

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Figure 2.5-6 Marginal benefits from passengers’ time saving

R 6,000,000,000.00

R 5,000,000,000.00

R 4,000,000,000.00

R 3,000,000,000.00

R 2,000,000,000.00

R 1,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Year

2.5.3.2 Ticket pricing and distances flown per week

Table 2.5-3 below displays the average ticket price per flight, the distance flown per week and the average distance flown per flight. Each of the columns in Table 2.5-3 has been graphed and this is displayed in Figures 2.5-7, 2.5-8, and 2.5-9.

Table 2.5-3 Additional flight information

Years Average Ticket Price per flight Distance flown per Average distance flown (2009 Rands) week (km) per flight (km) 5 R 341.67 13,727,109.91 1,053.99 10 R 285.30 20,009,690.53 884.31 15 R 280.21 20,536,909.37 867.27 20 R 290.54 35,158,912.46 887.89 25 R 452.46 114,571,046.97 1,393.43 30 R 568.86 343,103,208.33 1,736.38 35 R 617.95 627,218,254.45 1,880.01 40 R 625.83 865,880,913.94 1,896.79 45 R 629.87 934,034,723.71 1,909.61 50 R 628.40 948,018,098.80 1,901.88

Figure 2.5-7 shows the average ticket price per flight in constant 2009 Rands. Initially the average ticket price decreases to R280 and then increases before stabilising at roughly R625. One of the key

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Muller Associates Department o f Transport P a g e | 114 determinants of the price of an air ticket is the distance flown. The model predicts that domestic routes that are by their nature relatively shorter are targeted first as these are commercially less risky.

Figure 2.5-7 Average ticket price per flight

R 700.00

R 600.00

R 500.00

R 400.00

R 300.00

R 200.00

R 100.00

R - 5 10 15 20 25 30 35 40 45 50 Year

This is confirmed in Figure 2.5-9, where the average distance flown per flight correlates. As more routes, including international routes that involve longer distances and flying times are added there will be a associated increase in the average price of air tickets sold in the region. The average air ticket prices stabilise at around 35 years post implementation of an air transport liberalisation agreement in SADC, as routes with origins and destinations further apart are added by the low cost airlines. Once these are added the effects of distance on the average price of air tickets is reflected it is once again moderated. The total distance flown per week over the 50 year period is reflected in Figure 2.5-8 overleaf.

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Figure 2.5-8 Total distance flown per week (km)

1,000,000,000.00 900,000,000.00 800,000,000.00 700,000,000.00 600,000,000.00 500,000,000.00 400,000,000.00 300,000,000.00 200,000,000.00 100,000,000.00 - 5 10 15 20 25 30 35 40 45 50 Year

Figure 2.5-9 shows the predicted average distance flown per flight throughout SADC over the 50 year period post implementation of an air transport liberalisation agreement in SADC. Figure 2.5-9 confirms that initially shorter routes are adopted by low cost airlines; this directly lowers the price of air tickets and allows airlines to attract new customers. As longer routes are added, it can be seen that the average distance flown increases and this directly impacts the average price of tickets throughout the region. The average price of tickets graph rises steeply at first from year 20 to year 30 post implementation of an air transport liberalisation agreement in SADC and then rises more moderately from year 35 post implementation.

Figure 2.5-9 Average distance flown per flight (km)

2,500.00

2,000.00

1,500.00

1,000.00

500.00

- 5 10 15 20 25 30 35 40 45 50 Year

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Tables 2.5-4 and 2.5-5 below show the direct costs to airlines and the projection of these costs over a 50 year period. In Table 2.5-4, the five direct costs to an airline are listed in the first column. In the second column, an estimate of the frequency, in terms of how often the airline would incur this cost, is provided. This is estimated by means of a percentage of the flights within the region over the 50 year period and then the costs have been calculated to reflect a per week cost to an airlines. For example, if 0.1% of flights in a week are diverted, that cost is estimated by the study team at R32,686.56 per week. The third column of Table 2.5-4 shows the estimated cost per week in 2009 Rands.

Table 2.5-4 Assumptions, Weights, Proportions and Figures Used

COST TO AIRLINES Frequency Cost to an Airline per week (2009 Rands) Cost of flight cancellation 1.0% R 172,033.02 Cost of flight diversion 0.1% R 32,686.56 Cost of fatality 0.0000321% R 26,378,620.74 Cost of minor injury 0.0000321% R 406,001.38 Cost of major injury 0.0000321% R 5,502,809.67

Table 2.5-5 below shows all the direct costs to airlines over a 50 year period in 2009 Rands. To determine these costs, the frequency of each cost has been multiplied by the projected number of flights projected under an air transportation liberalisation agreement, and then multiplied by the estimated cost in Rands, over the next 50 years. For example, if it is projected that in the next 5 years, there will be 9649 flights and 1% if those flights will be cancelled, then there will be 96.49 cancelled flights. If the cost is estimated at R172,033.02 per cancellation, then the cost to airlines of cancellations in the first 5 years is R16,598,813.09. In Table 2.5-4 above, the most prominent of all costs is the cost of cancellation. This is not surprising since it is also the cost with the highest predicted frequency of occurrence. The cost of diversion is the second highest cost, followed by the cost of fatality, major injury and then minor injury. A graphed comparison of these costs in relation to each other is shown in the figure overleaf.

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Table 2.5-5 Results Over 50 Year Period

Years Cost of flight Cost of flight Cost of accident Cost of minor injury Cost of major injury cancellations diversions resulting in fatality during flight during flight

5 R 16,598,813.09 R 315,380.21 R 81,714.64 R 1,257.69 R 17,046.38 10 R 30,904,371.61 R 315,380.21 R 95,086.12 R 1,447.96 R 17,703.70 15 R 32,305,924.57 R 768,932.95 R 199,229.61 R 3,066.40 R 41,561.03 20 R 52,098,054.07 R 1,204,203.34 R 312,007.65 R 4,802.20 R 65,087.51 25 R 101,208,861.28 R 2,207,196.63 R 571,882.02 R 8,802.01 R 119,299.56 30 R 223,961,749.86 R 4,561,179.38 R 1,181,796.15 R 18,189.38 R 246,532.95 35 R 356,211,204.63 R 7,081,209.60 R 1,834,732.98 R 28,238.93 R 382,741.25 40 R 465,155,209.94 R 9,153,406.58 R 2,371,636.76 R 36,502.58 R 494,744.05 45 R 491,444,508.29 R 9,652,907.63 R 2,501,056.88 R 38,494.53 R 521,742.21 50 R 497,433,106.58 R 9,766,691.99 R 2,530,538.28 R 38,948.28 R 527,892.29

Figure 2.5-10 Total Costs to Airlines

R 600,000,000.00

R 500,000,000.00 Cost of major injury during flight R 400,000,000.00 Cost of minor injury during flight R 300,000,000.00 Cost of accident resulting in fatality Cost of flight R 200,000,000.00 diversions Cost of flight R 100,000,000.00 cancellation

R - 5 10 15 20 25 30 35 40 45 50 Years

Over the 50 year period, the cost of cancelled flights would be the most significant cost to airlines under an air transportation liberalisation agreement (Figure 2.5-10).

The trend in Table 2.5-5 above follows a distinctive S bend in the curve, in that marginal cost to airlines will increase over time, reach a peak and then decrease in later years. The graphs of each cost indicate that the steepest point on all graphs (the point of inflection) is between the 30 year and 35 year mark.

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Even before the costs to airlines are increasing at an increasing rate, in that the difference in cost between each consecutive year gets bigger. After the inflection point in the graph, the difference in the cost between consecutive years gets smaller. The reason for the S bend shape is that as the air transportation liberalisation agreement matures in the SADC region, more flights would be added each year. For the first 30-35 years of an air transportation liberalisation operation, more flights would be added in each 5-year period. The flights added in this period will be the most attractive to airlines, and which will therefore also tend to be the most profitable. In the years after the inflection point (at 30-35 years and beyond) the number of flights added per five year period will tend to be fewer and fewer each year, as these are the routes that are less popular with airlines, being the less profitable, generally longer and lower trafficked routes. Because more flights are added in the earlier period, the direct costs to airlines will also be higher in this period (because the cost to airlines is correlated with the number of flights undertaken). In the later period, fewer flights added per 5 years will also translate into lower additional direct cost to airlines in each 5 year period.

Figure 2.5-11 Cost of Flight Cancellation

R 600,000,000.00

R 500,000,000.00

R 400,000,000.00

R 300,000,000.00

R 200,000,000.00

R 100,000,000.00

R - 5 10 15 20 25 30 35 40 45 50

Year

The cost of flight cancellations is illustrated in Figure 2.5-11 above. The steepest point on the curve is between 30 and 35 years. This reflects a cost of flight cancellation between R 223.9 million and R 356.2 million respectively.

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Figure 2.5-12 Cost of Flight Diversions

R 12,000,000.00

R 10,000,000.00

R 8,000,000.00

R 6,000,000.00

R 4,000,000.00

R 2,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

The cost of flight diversions is shown above in Figure 2.5-12. As above, the steepest point on the curve is between 30 and 35 years. This reflects a cost of flight diversions between R 4.5 million and R 7 million respectively.

Figure 2.5-13 Cost of Accident Resulting in Fatality

R 3,000,000.00

R 2,500,000.00

R 2,000,000.00

R 1,500,000.00

R 1,000,000.00

R 500,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

The cost of accident resulting in fatality has been illustrated in Figure 2.5-13 above. The S-bend can be seen clearly in this figure, reaching its steepest point at 30-35 years. This reflects a cost of accident resulting in fatality between R 1.1 million and R 1.8 million respectively.

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Figure 2.5-14 Cost of Accident Resulting in Minor Injury

R 45,000.00 R 40,000.00 R 35,000.00 R 30,000.00 R 25,000.00 R 20,000.00 R 15,000.00 R 10,000.00 R 5,000.00 R - 5 10 15 20 25 30 35 40 45 50 Years

Figure 2.5-14 shows the cost of accidents resulting in minor injury. The steepest point on the line is between 30 and 35 years after implementation of an air transport liberalisation agreement in SADC, as in the previous figure. This reflects a cost of accident resulting in minor injury between R 18,189 and R 28,238 respectively.

Figure 2.5-15 Cost of Accident Resulting in Major Injury

R 600,000.00

R 500,000.00

R 400,000.00

R 300,000.00

R 200,000.00

R 100,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

Figure 2.5-15 shows the cost of accidents resulting in major injury. The curve follows the same shape as previous figures – an S-bend with the steepest point between 30 and 35 years after implementation of

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YD, as in the previous figures. This reflects a cost of accident resulting in major injury between R 0.25 million and R 0.38 million respectively.

Figure 2.5-16 Potential Turnover and Costs to Airlines

R 25,000,000,000.00

R 20,000,000,000.00 Potential R 15,000,000,000.00 Turnover

R 10,000,000,000.00 Total Costs To Airlines

R 5,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50

Years

The final figure above, Figure 2.5-16, shows these costs in relation to airline turnover. Although the costs look quite large when graphed alone, relative to turnover, the identified costs are minimal. However, expect the graph to change after aircraft operational costs are incorporated (this information was not provided by the airlines.)

2.5.4 Indirect Impacts

2.5.4.1 Tourism Impact Over 50 Years

The SADC airport routes demand forecast model is able to give the impact on tourism, measured as impact on GDP and impact on Employment, of various routes opening up for different countries at different times. The below Table 2.5-6 is an aggregate summary of the impact an air transport liberalisation agreement in SADC would have on the economies of the countries within SADC, from five years after implementation to fifty years after implementation.

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Table 2.5-6 Tourism Impact Over 50 Years

Tourism impact Years Total Impact On GDP Direct Impact On GDP Total Impact on Direct Impact on (2009 Rands) (2009 Rands) Employment Employment

5 38 153 667 234 7 552 340 410 18 834 396 2 946 352 10 52 495 280 062 13 205 292 139 20 148 872 3 552 166 15 56 242 018 920 13 673 144 858 22 474 400 3 803 567 20 168 404 489 659 28 251 360 599 96 497 793 11 969 962 25 283 584 702 100 50 738 372 512 153 113 422 20 618 568 30 592 312 694 411 105 672 816 915 292 815 107 42 028 595 35 965 917 528 251 165 457 639 030 479 527 314 70 831 341 40 1 325 217 246 927 217 448 285 885 641 150 459 96 702 448 45 1 398 653 761 279 228 121 055 753 662 282 465 101 085 855 50 1 410 118 459 326 229 837 249 447 667 355 671 101 896 069

The data illustrates that there are four distinct growth periods over the next fifty years in terms of tourism which will impact GDPs of countries within SADC. For the first fifteen years growth is lower as few routes would have been opened up or had little time to establish new tourist industries, but as more routes are enabled growth would pick up between years fifteen and twenty-five. Beyond year twenty-five these routes would have established new tourism areas and industries, and even more routes would be opening up leading to the steep growth seen on the following figures. At around year forty most of the routes that would have been established and given the restraints built into the model it can be seen that growth slows which could reflect a maturing tourism situation within SADC. Overleaf is the graphical representation of the total and direct impact on GDP and employment over the fifty years. Each of the four stages impact data is represented in the following sub-sections.

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Figure 2.5-17 TotalTotal and & Direct Direct Impact onImpact GDP (2009 on Rands) GDP (2009 Rands) R 1 600 000 000 000.00

R 1 400 000 000 000.00

R 1 200 000 000 000.00

R 1 000 000 000 000.00 Total Impact On GDP R 800 000 000 000.00 (2009 Rands) R 600 000 000 000.00 Direct Impact On GDP (2009 Rands) R 400 000 000 000.00

R 200 000 000 000.00

R - 5 10 15 20 25 30 35 40 45 50

Years

Figure 2.5-18 Total Totaland Direct & Impact Direct on Employment Impact of Employment

800 000 000

700 000 000

600 000 000

500 000 000

400 000 000 Total Impact on Employment 300 000 000 Direct Impact on Employment

200 000 000

100 000 000

- 5 10 15 20 25 30 35 40 45 50

Years

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2.5.4.1.1 Year 5

Table 2.5-7 below, which has been derived from the routed forecast model, shows the impact that tourism will have on SADC countries five years after an air transport liberalisation agreement in SADC has been implemented.

Table 2.5-7 Tourism Impact in Year 5

Countries Routes Total Impact On Direct Impact On Total Impact of Direct Impact of GDP (2009 Rands) GDP (2009 Rands) Employment Employment Angola 15 22 542 071 514 2 732 989 045 15 303 371 1 618 571 Botswana 7 460 066 146 145 079 268 44 953 19 510 Democratic Republic of Congo 7 4 468 444 338 429 890 342 540 779 67 928 Lesotho 1 87 726 912 31 076 572 10 485 4 247 Madagascar 5 1 208 731 887 492 479 095 731 726 298 908 Malawi 3 204 833 615 81 897 543 76 255 31 919 Mauritius 3 491 704 994 188 788 352 59 760 25 475 Mozambique 8 1 329 509 622 541 169 345 771 621 319 812 Namibia 0 0 0 0 0 Seychelles 2 347 137 813 142 322 615 39 656 18 154 South Africa 33 5 855 278 401 2 302 594 211 633 534 285 533 Swaziland 0 0 0 0 0 Tanzania 6 945 480 236 385 258 461 571 007 236 433 Zambia 3 92 097 194 32 674 791 31 413 11 540 Zimbabwe 4 120 584 561 46 120 769 19 835 8 322 Total 97 38 153 667 234 7 552 340 410 18 834 396 2 946 352

There would be ninety seven routes opened, thirty three of which would be in South Africa and fifteen from Angola. The results are distorted due to Angola’s figures, which are much higher than any of the other countries leading to a shift in the overall impact on tourism. Angola is an oil-producing country which has benefitted massively from the oil production and increased business being attracted because of this. The model is suggesting it will be one of the major beneficiaries of air transportation liberalisation. It also has the effect of skewing forecast data since it is unlikely to have the same level of economic performance as it has had in recent years; however it is this data which has to be used in forecasting.

2.5.4.1.2 Year 15

Ten years from an air transport liberalisation agreement in SADC it would be seen that 81 routes would be expected to have opened up, increasing the impact of tourism on total GDP by R18 billion and on jobs by 4 million, in SADC. The major differences are between the year five scenario and the year fifteen scenario, the 73 new routes available to and from South Africa, which would have a major impact on South Africa’s GDP and employment increasing total impact on GDP almost 4 fold to R20 billion and total impact of employment almost 3 fold to 1.9 million.

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Table 2.5-8 Tourism Impact in Year 15

Countries Routes Total Impact On Direct Impact On Total Impact of Direct Impact GDP (2009 Rands) GDP (2009 Rands) Employment of Employment Angola 17 25 828 044 557 3 124 166 392 17 549 572 1 855 239 Botswana 8 509 009 242 158 356 285 49 901 21 590 Democratic Republic of Congo 7 4 468 444 338 429 890 342 540 779 67 928 Lesotho 1 87 726 912 31 076 572 10 485 4 247 Madagascar 5 1 208 731 887 492 479 095 731 726 298 908 Malawi 3 204 833 615 81 897 543 76 255 31 919 Mauritius 3 491 704 994 188 788 352 59 760 25 475 Mozambique 8 1 329 509 622 541 169 345 771 621 319 812 Namibia 5 411 822 719 63 398 355 74 380 12 653 Seychelles 2 347 137 813 142 322 615 39 656 18 154 South Africa 106 20 196 891 229 7 955 545 940 1 948 009 891 346 Swaziland 0 0 0 0 0 Tanzania 6 945 480 236 385 258 461 571 007 236 433 Zambia 3 92 097 194 32 674 791 31 413 11 540 Zimbabwe 4 120 584 561 46 120 769 19 835 8 322 Total 178 56 242 018 920 13 673 144 858 22 474 400 3 803 567

2.5.4.1.3 Year 25

Twenty five years after the implementation of air transportation liberalisation, there would be a total of 623 routes available to airlines (445 more than the previous scenario). The impact on GDP would have increased by over five times its level at year fifteen, and employment by an even larger margin.

Table 2.5-9 Tourism Impact in Year 25

Countries Routes Total Impact On Direct Impact On Total Impact of Direct Impact of GDP (2009 Rands) GDP (2009 Rands) Employment Employment Angola 176 206 275 515 037 26 296 691 304 137 284 187 14 687 694 Botswana 67 6 197 312 531 2 229 768 612 650 991 285 051 Democratic Republic of Congo 25 17 354 854 704 1 697 127 175 2 092 519 264 345 Lesotho 2 177 302 632 62 808 070 21 191 8 583 Madagascar 23 5 171 444 341 2 099 346 216 2 947 490 1 205 281 Malawi 9 735 139 917 292 620 305 208 890 88 334 Mauritius 19 3 203 946 435 1 279 421 571 415 698 185 774 Mozambique 37 5 900 823 034 2 392 080 268 3 052 249 1 268 299 Namibia 71 7 028 653 501 1 886 638 075 971 494 254 526 Seychelles 15 2 499 592 802 1 024 805 052 285 548 130 721 South Africa 156 26 327 026 112 10 380 713 543 3 619 753 1 594 586 Swaziland 0 0 0 0 0 Tanzania 15 2 468 401 787 1 006 351 685 1 500 286 621 194 Zambia 4 124 104 705 43 879 868 43 292 15 857 Zimbabwe 4 120 584 561 46 120 769 19 835 8 322 Total 623 283 584 702 100 50 738 372 512 153 113 422 20 618 568

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A significant difference between this scenario and the previous is that ten of the fourteen countries would have had a significant increase in the number of routes opened up, which would result in the steep increase in the impact from this scenario to the next (year forty).

This could be due to the fact that other SADC countries (other than South Africa) would require a significantly higher level of investment in infrastructure in order to let certain routes open up. Since the number of routes within this analysis is based on the factors set out by the routes demand forecast model, it is clear that by twenty five years after implementation of an air transport liberalisation agreement in SADC these factors would have all improved to a level that tourism within SADC would have a widespread impact.

2.5.4.1.4 Year 40

Table 2.5-10 Tourism Impact in Year 40

Countries Routes Total Impact On GDP Direct Impact On Total Impact of Direct Impact (2009 Rands) GDP (2009 Rands) Employment of Employment Angola 1 086 840 729 260 494 110 081 377 944 530 634 836 60 918 028 Botswana 276 36 180 665 295 8 039 926 585 7 650 628 2 500 990 Democratic Republic of Congo 640 274 261 929 632 33 068 514 393 39 027 428 7 328 414 Lesotho 49 3 326 557 540 1 124 708 069 1 179 321 462 570 Madagascar 244 39 294 600 212 15 655 428 090 22 254 205 9 058 674 Malawi 90 5 865 157 643 2 243 125 495 2 614 027 1 065 563 Mauritius 47 6 852 074 474 2 699 642 431 1 394 296 593 033 Mozambique 352 42 555 722 679 16 687 713 112 19 760 528 8 130 856 Namibia 260 22 798 196 513 6 712 238 710 4 728 699 1 571 337 Seychelles 29 4 124 427 991 1 698 478 633 714 190 313 647 South Africa 310 42 777 340 455 16 879 369 876 7 688 656 3 318 649 Swaziland 12 559 326 724 197 665 089 262 611 107 940 Tanzania 52 5 327 530 384 2 153 568 234 3 088 480 1 274 761 Zambia 16 414 380 714 149 128 603 127 870 47 630 Zimbabwe 5 150 076 178 57 400 621 24 686 10 358 Total 3 468 1 325 217 246 927 217 448 285 885 641 150 459 96 702 448

The routes open would have increased by 2845 and the impact on the economies of the SADC countries would have increased by a large amount from year 25, as can be seen in Table 2.5-10.

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2.5.4.1.5 Year 50

Table 2.5-11 Tourism Impact in Year 50

Countries Routes Total Impact On Direct Impact On Total Impact of Direct Impact GDP (2009 Rands) GDP (2009 Rands) Employment of Employment Angola 1 123 862 950 838 267 112 675 025 388 543 271 426 62 293 308 Botswana 280 36 270 819 793 8 067 334 439 7 669 855 2 508 281 Democratic Republic of Congo 815 330 399 812 171 40 350 699 246 49 313 945 9 817 931 Lesotho 54 3 524 207 131 1 191 180 670 1 269 359 498 283 Madagascar 265 41 633 774 979 16 606 041 230 23 760 119 9 673 330 Malawi 96 5 982 259 593 2 289 193 433 2 689 300 1 096 182 Mauritius 48 6 923 003 100 2 727 923 957 1 405 943 598 009 Mozambique 381 44 448 322 970 17 438 104 141 20 800 309 8 557 940 Namibia 273 23 214 179 360 6 802 166 393 4 815 759 1 593 254 Seychelles 30 4 189 945 857 1 725 545 242 725 092 318 304 South Africa 321 43 445 362 666 17 137 934 573 7 779 967 3 356 839 Swaziland 14 590 922 702 206 202 692 267 877 109 959 Tanzania 62 5 919 157 876 2 390 848 574 3 417 929 1 410 268 Zambia 20 475 776 685 171 648 848 144 106 53 824 Zimbabwe 5 150 076 178 57 400 621 24 686 10 358 Total 3 787 1 410 118 459 326 229 837 249 447 667 355 671 101 896 069

Table 2.5-11 displays the impact increased tourism as a result of an air transport liberalisation agreement would have on SADC in the final year of the forecast. There would be 3787 routes open, and the impact on GDP and Employment in the region would have increased greatly over the fifty year period.

2.5.4.2 Impact of Atmospheric Pollution, Noise Pollution and Security Over 50 Years

Three major indirect costs were highlighted in this study. An air transportation liberalisation policy will increase atmospheric pollutants in the air, create more noise pollution and increase the burden of security at airports. These costs have been calculated using the impact model and the results are shown in Table 2.5-12. The calculations for the units used in the model are discussed in Section 2.4.3. The results are in Table 2.4-10.

In the US the Federal Aviation Agency defines airline noise pollution as that which is loud enough to disturb a family watching television. This definition is used to define noise pollution in this study as well. Noise pollution impacts on property values and quality of life. The Eurocontrol measure of noise pollution places it at R693 per takeoff and landing and as air transportation liberalisation policy takes effect the impact will increase significantly over time, reaching R345m per annum in fifty years from implementation. The short term (5 year) impact is rather small at R8,8m per annum and relatively insignificant in terms of the overall positive impact.

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Table 2.5-12 Cost of Pollution and Security

Indirect Costs

Years Cost of Pollution Cost of noise pollution Cost of Security

5 R 8,913,136.87 R 8,843,296.00 R 44,638,920.25

10 R 13,051,507.63 R 15,498,560.00 R 77,498,800.90 15 R 13,398,789.61 R 16,227,904.00 R 80,718,169.30 20 R 23,030,384.28 R 27,259,232.00 R 132,556,756.40

25 R 75,339,598.46 R 56,797,664.00 R 306,044,392.79 30 R 225,875,002.76 R 136,752,000.00 R 753,253,360.05 35 R 413,023,162.06 R 231,019,712.00 R 1,247,466,816.32 40 R 570,231,581.77 R 316,170,624.00 R 1,656,004,413.96 45 R 615,124,874.90 R 338,780,288.00 R 1,754,588,698.25

50 R 624,335,801.75 R 345,253,216.00 R 1,777,045,808.69

Figure 2.5-19 Cost of Noise Pollution

R 400,000,000.00

R 350,000,000.00

R 300,000,000.00

R 250,000,000.00

R 200,000,000.00

R 150,000,000.00

R 100,000,000.00

R 50,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

Aircraft pollution from emissions is an emotive issue as people often have the perception that aeroplanes are large contributors to CO2 emissions. However, currently aircraft atmospheric emissions

(70% of which are CO2) contribute only 3% of EU total CO2 emissions. The total calculated cost of pollution in the fifth year of air transportation liberalisation implementation is R8,9m rising steadily with an exponential increase from the 17th year as the impact of an air transportation liberalisation policy takes effect. The total cost of pollution increases to R645m at the fifty year mark as total flying hours

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Figure 2.5-20 Cost of Pollution

R 700,000,000.00

R 600,000,000.00

R 500,000,000.00

R 400,000,000.00

R 300,000,000.00

R 200,000,000.00

R 100,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

Currently most security costs are carried by the carrier airlines and vary between international flights (R53.76) and domestic flights (R32.93). These costs are based on the Australian costing model and are per passenger. Not all costs are carried by airlines and some of the total spending would be a burden of the state where the flights originate and end. Airline security is a national security interest. Airport security costs as a result of air transportation liberalisation policy will rise to R1,8bn in the fiftieth year, and as such will become a large industry as a result of the air transportation liberalisation policy across the SADC region. Even in the fifth year a boost of R45m into regional airports will contribute significantly to employment. An increase in airport security costs will be good for the economy as it will lead to increased spending on employment.

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Figure 2.5-21 Cost of Security

R 2,000,000,000.00 R 1,800,000,000.00 R 1,600,000,000.00 R 1,400,000,000.00 R 1,200,000,000.00 R 1,000,000,000.00 R 800,000,000.00 R 600,000,000.00 R 400,000,000.00 R 200,000,000.00 R - 5 10 15 20 25 30 35 40 45 50 Years

Whilst the security costs will be the largest contributor to indirect costs it is the easiest one to quantify. The true cost of noise and fuel burning pollution could be much higher. From a fairly modest level of R63m in the fifth year, indirect costs from an air transportation liberalisation policy will balloon up to R2,7bn at current prices by the fiftieth year of operation.

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Figure 2.5-22 Total Indirect Costs

R 3,000,000,000.00

R 2,500,000,000.00

R 2,000,000,000.00 Cost of Security R 1,500,000,000.00 Cost of noise pollution Cost of Pollution R 1,000,000,000.00

R 500,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

2.5.5 Airport and navigational infrastructure

2.5.5.1 Navigational infrastructure per route

As discussed in the methodology we can estimate the cost of navigational infrastructure required per route at flight level 145 and 195. The weekly costs for this infrastructure is displayed in Table 2.5-13 below, as can be observed the weekly costs exceed R 1 billion after 50 years as the number of routes being flown increases. The weekly cost of navigational infrastructure per route has been graphically represented by Figure 2.5-23. The graph once again adopts the s bend curve that is present in all the graphs before.

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Table 2.5-13 Weekly cost navigational infrastructure per route Years Flight Level 145 Flight Level 195 5 R 20,021,153.85 R 16,192,628.21 10 R 30,307,051.28 R 27,660,512.82 15 R 31,258,269.23 R 29,897,051.28 20 R 53,547,307.69 R 50,750,128.21 25 R 162,721,282.05 R 141,441,858.97 30 R 473,688,910.26 R 384,301,410.26 35 R 858,029,358.97 R 683,673,269.23 40 R 1,184,967,692.31 R 937,951,794.87 45 R 1,277,056,025.64 R 1,009,440,641.03 50 R 1,296,504,038.46 R 1,024,944,166.67

Figure 2.5-23 Weekly cost navigational infrastructure per route

R 1,400,000,000.00

R 1,200,000,000.00

R 1,000,000,000.00

R 800,000,000.00 Flight Level 145 R 600,000,000.00 Flight Level 195 R 400,000,000.00

R 200,000,000.00

R - 5 10 15 20 25 30 35 40 45 50

2.5.5.2 Airport navigational infrastructure

All the results up to this point have been exhibited as per route weekly costs. In order to correctly estimate the cost of airport navigational infrastructure and the cost of airport expansions to increase airport capacity we’ve calculated these costs annually and per airport. These results are to be viewed separately from previous results, and will be brought in line with other results in sections to come.

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Figure 2.5-24 below displays the cost of airport navigational infrastructure over the 50 year period. As the number of origin and destination airports increase, the costs for navigational infrastructure at the various airports in the SADC region are required.

Figure 2.5-24 Airport navigational infrastructure

R 1,230,000,000.00

R 1,220,000,000.00

R 1,210,000,000.00

R 1,200,000,000.00

R 1,190,000,000.00 Airport Navigational R 1,180,000,000.00 Infrastructure R 1,170,000,000.00

R 1,160,000,000.00

R 1,150,000,000.00

R 1,140,000,000.00

R 1,130,000,000.00 5 10 15 20 25 30 35 40 45 50

Table 2.5-14 displays the total airport navigational infrastructure costs over the 50 year forecast. The cost are higher at airports with higher passenger numbers. It can be seen that in excess of R 12 billion (2009 Rands) would be required to cover the airports navigational infrastructure costs over the 50 year period.

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Table 2.5-14 Airport Navigational Infrastructure Location Airport Navigational Location Airport Location Airport Navigational Infrastructure Navigational Infrastructure Infrastructure Cabinda R 105,500,000.00 Mbuji-Mayi R 21,666,666.67 Durban R 521,500,000.00 Catumbela R 105,500,000.00 Maseru R 105,500,000.00 George R -

Dundo R - Antanànarìvo R 521,500,000.00 Lanseria R 105,500,000.00 Huambo R 21,666,666.67 Mahajanga R 105,500,000.00 Johannesburg R 521,500,000.00 Kuito R 21,666,666.67 Nosy Be R 13,000,000.00 Kimberley R 105,500,000.00

Luanda R 521,500,000.00 Toamasina R 105,500,000.00 Mafikeng R 21,666,666.67 Lubango R 21,666,666.67 Toliara R 21,666,666.67 Nelspruit R 105,500,000.00 Luena R 21,666,666.67 Blantyre R 105,500,000.00 Polokwane R 21,666,666.67

Malanje R 21,666,666.67 Lilongwe R 521,500,000.00 Port Elizabeth R 105,500,000.00 Menongue R 21,666,666.67 Port Louis R 521,500,000.00 Pilanesberg R 19,500,000.00 Namibe R 21,666,666.67 Beira R 105,500,000.00 Umtata R 21,666,666.67

Ondjiva R 21,666,666.67 Chimoio R 15,166,666.67 Upington R 105,500,000.00 Saurimo R 21,666,666.67 Cuamba R 13,000,000.00 Welkom R 19,500,000.00 Soyo R 21,666,666.67 Lichinga R 105,500,000.00 Manzini R 105,500,000.00

Uíge R 17,333,333.33 Maputo R 521,500,000.00 Dar-Es- R 521,500,000.00 Salaam Francistown R 105,500,000.00 Moçimboa da Praia R 105,500,000.00 Dodoma R 105,500,000.00 Gaborone R 521,500,000.00 Mueda R 13,000,000.00 Kilimanjaro R 105,500,000.00 Kasane R 21,666,666.67 Nampula R 105,500,000.00 Mtwara R 21,666,666.67

Maun R 105,500,000.00 Tete R 21,666,666.67 Mwanza R 21,666,666.67 Bukavu R 13,000,000.00 Grootfontein R 84,400,000.00 Zanzibar R 521,500,000.00 Buta-Zega R 13,000,000.00 Karabib R 15,166,666.67 Kitwe R -

Gbadolite R 21,666,666.67 Katima Mulilo R 17,333,333.33 Livingstone R 105,500,000.00 Gemena R 13,000,000.00 Keetmanshoop R 17,333,333.33 Lusaka R 521,500,000.00 Goma R 13,000,000.00 Mariental R 15,166,666.67 Mfuwe R 8,666,666.67

Isiro-Matari R 13,000,000.00 Ondangwa R 17,333,333.33 Ndola R 21,666,666.67 Kananga R 13,000,000.00 Rundu R 17,333,333.33 Bulawayo R 105,500,000.00 Kindu R 13,000,000.00 Windhoek R 521,500,000.00 Harare R 521,500,000.00

Kinshasa R 521,500,000.00 Seychelles R 521,500,000.00 Hwange R 21,666,666.67 Kisangani R 105,500,000.00 Bisho R 105,500,000.00 Victoria Falls R 105,500,000.00 Lubumbashi R 105,500,000.00 Bloemfontein R 105,500,000.00 TOTAL R 12,076,400,000.00 Mbandaka R 13,000,000.00 Cape Town R 521,500,000.00

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2.5.5.3 Airport Infrastructure Costs

As explained in the previous section airport infrastructure costs have been reported per airport displaying all costs incurred over the 50 year period. The airport infrastructure costs have been pegged to the forecasted number of passengers per airport over the 50 year period. When the number of forecasted passengers exceeds the airports annual capacity, the airport infrastructure costs are incurred (the cost ratio applied for addition infrastructure is one million additional passenger capacity is the equivalent of R 600 million spend on airport infrastructure.) Figure 2.5-25 displays the escalation of airport infrastructure costs over the 50 year period as additional routes are added thereby increasing the number of passengers utilising air transport as it becomes increasingly cheaper to fly and as flights become more direct.

Figure 2.5-25 Airport Infrastructure Costs

R 600,000,000,000.00

R 500,000,000,000.00

R 400,000,000,000.00 Airport Infrastructure R 300,000,000,000.00 Costs

R 200,000,000,000.00

R 100,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Year

Table 2.5-15 below indicates the total investment required in airport infrastructure over the 50 year period per airport. It can be seen that mostly the South African airports require the largest investment over the 50 year period; this is due to the higher demand for flights from other SADC regions to South Africa, as business and leisure activities are more developed and available when compared to other SADC partners. Interestingly Lanseria Airport in Johannesburg requires the largest investment in airport infrastructure to take advantage of all the added demand for flights in and out of the Johannessburg/Pretoria area.

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Table 2.5-15 Airport Infrastructure Costs Location Airport Infrastructure Location Airport Infrastructure Location Airport Infrastructure Costs Costs Costs Cabinda R 30,762,646,164.32 Mbuji-Mayi R 24,753,794,341.17 Durban R 38,705,155,564.19 Catumbela R 21,704,608,870.95 Maseru R 15,845,658,240.17 George R - Dundo R - Antanànarìvo R 8,121,960,885.89 Lanseria R 50,916,414,646.06 Huambo R 32,799,705,107.64 Mahajanga R 16,996,112,278.87 Johannesburg R - Kuito R 31,326,914,030.96 Nosy Be R 21,804,839,914.27 Kimberley R 44,083,043,709.13 Luanda R 14,454,353,582.72 Toamasina R 19,094,988,395.56 Mafikeng R 40,811,869,973.20 Lubango R 31,374,951,738.71 Toliara R 22,937,552,849.95 Nelspruit R 42,677,327,210.89 Luena R 27,386,961,412.25 Blantyre R 17,641,591,388.30 Polokwane R 42,265,713,353.11 Malanje R 31,857,532,088.63 Lilongwe R 6,055,562,817.46 Port Elizabeth R 41,889,245,560.08 Menongue R 30,677,820,412.50 Port Louis R 12,345,883,086.00 Pilanesberg R 40,046,339,330.98 Namibe R 31,967,122,412.18 Beira R 20,113,697,084.71 Umtata R 40,306,034,452.31 Ondjiva R 29,117,281,210.36 Chimoio R 23,705,642,728.46 Upington R 42,797,693,603.02 Saurimo R 30,955,943,213.46 Cuamba R 21,423,216,316.07 Welkom R 42,529,814,312.88 Soyo R 29,976,647,083.97 Lichinga R 23,590,797,888.70 Manzini R 17,821,283,568.37 Uíge R 30,352,589,997.88 Maputo R 7,783,416,063.19 Dar-Es-Salaam R 8,424,782,414.41 Francistown R 35,135,585,164.11 Moçimboa da R 19,933,260,259.03 Dodoma R 24,775,748,996.14 Praia Gaborone R 11,489,436,347.38 Mueda R 19,705,744,750.39 Kilimanjaro R 21,088,863,923.42 Kasane R 27,894,701,088.10 Nampula R 20,528,698,093.77 Mtwara R 24,211,283,509.89 Maun R 26,245,742,033.60 Tete R 23,765,714,787.34 Mwanza R 27,957,419,377.31 Bukavu R 20,836,679,462.91 Grootfontein R 21,432,237,428.37 Zanzibar R 27,027,185,020.59 Buta-Zega R 18,670,970,710.90 Karabib R 24,282,126,980.62 Kitwe R - Gbadolite R 19,005,255,956.46 Katima Mulilo R 28,014,954,576.04 Livingstone R 18,800,111,355.35 Gemena R 21,174,304,236.40 Keetmanshoop R 28,306,690,156.58 Lusaka R 8,921,260,503.81 Goma R 21,571,107,574.57 Mariental R 27,107,878,848.06 Mfuwe R 8,502,307,048.99 Isiro-Matari R 21,672,433,830.73 Ondangwa R 27,454,733,325.99 Ndola R 27,766,951,019.44 Kananga R 23,874,821,942.88 Rundu R 29,184,572,232.87 Bulawayo R 23,414,456,927.59 Kindu R 21,663,633,278.31 Windhoek R 9,559,680,304.59 Harare R 6,518,897,872.57 Kinshasa R 8,183,067,356.52 Seychelles R 8,749,277,162.18 Hwange R 17,155,638,948.89 Kisangani R 17,332,241,664.06 Bisho R 38,724,314,820.06 Victoria Falls R 10,761,251,323.26 Lubumbashi R 19,548,909,955.13 Bloemfontein R 42,568,700,235.46 TOTAL R 2,133,076,262,959.25 Mbandaka R 22,957,803,412.03 Cape Town R 19,395,099,852.65

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2.6 Impact of an air transport liberalisation agreement in the Southern African Development Community (SADC)

In this section of the report the focuses on the overall impact of implementing an air transport liberalisation agreement in SADC.

2.6.1 Total Computable Benefits

Table 2.6-1 below shows the total computable benefits (in constant 2009 Rands) arising from implementation of an air transport liberalisation agreement in SADC. It can be seen that initially the total computable benefit occurring throughout SADC equals R 8 billion per week. After 50 years this would grow to R 265 billion per week. In calculating total impact of an air transport liberalisation agreement on SADC, the direct impact of tourism on GDP was used as this captures the direct impact felt by the tourism industry as the number of passengers using air travel increase over the 50 year period.

Table 2.6-1 Total Benefits from the implementation of an air transport liberalisation agreement in SADC

Years* BENEFITS Potential Turnover Time Saving (Rand per Direct Impact On GDP (2009 TOTAL BENEFITS KM) Rands)

5 R 395,592,569.17 R 80,704,142.39 R 7,552,340,410.36 R 8,028,637,121.92 10 R 615,030,014.60 R 148,353,788.17 R 13,205,292,139.30 R 13,968,675,942.07 15 R 631,437,961.30 R 152,429,875.57 R 13,673,144,858.21 R 14,457,012,695.08 20 R 1,055,829,325.19 R 265,108,382.22 R 28,251,360,598.84 R 29,572,298,306.25 25 R 3,194,221,298.65 R 766,732,401.87 R 50,738,372,511.99 R 54,699,326,212.51 30 R 8,886,816,358.07 R 2,961,410,846.08 R 105,672,816,915.10 R 117,521,044,119.25 35 R 15,354,301,000.26 R 7,207,220,265.68 R 165,457,639,030.49 R 188,019,160,296.43 40 R 20,306,047,606.09 R 12,429,642,407.48 R 217,448,285,885.45 R 250,183,975,899.02 45 R 21,592,032,312.26 R 13,703,434,148.72 R 228,121,055,753.45 R 263,416,522,214.43 50 R 21,804,364,460.93 R 13,957,174,567.04 R 229,837,249,446.98 R 265,598,788,474.95 *post implementation of an air transport liberalisation agreement in SADC

Figure 2.6-1 exhibits the breakdown of total benefit incurred by the implementation of an air transport liberalisation agreement in SADC. It can be seen that the largest contributor to total benefits is the impact on the tourism industry followed by the benefit accruing to airlines. The passengers benefit due to time saving is relatively minimal, however if the anticipated general decrease in airline ticket prices was quantifiable and was taken into account this would increase the benefits considerably.

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Figure 2.6-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC

R 300,000,000,000.00

R 250,000,000,000.00

R 200,000,000,000.00

Direct Impact On R 150,000,000,000.00 GDP (2009 Rands) Time Saving (Rand per KM) R 100,000,000,000.00 Potential Turnover R 50,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Year

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2.6.2 Total Costs

The breakdown of total computable costs arising from the implementation of an air transport liberalisation agreement in SADC is shown in Table 2.6-2 below. When both direct and indirect costs are totalled initially cost incurred total R 99 million per week, this increases to R 4.5 billion per week after 50 years.

Table 2.6-2 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC Years Cost of flight Cost of flight Cost of accident Cost of minor Cost of major Cost of Cost of noise Cost of Security Navigation TOTAL COSTS cancellation diversions resulting in injury during injury during Pollution pollution Route Costs (FL fatality flight flight 145) 5 R 16,598,813 R 315,380 R 81,715 R 1,258 R 17,046 R 8,913,137 R 8,843,296 R 44,638,920 R 20,021,154 R 99,430,719 10 R 30,904,372 R 694,787 R 180,018 R 2,771 R 37,553 R 13,051,508 R 15,498,560 R 77,498,801 R 30,307,051 R 168,175,421 15 R 32,305,925 R 768,933 R 199,230 R 3,066 R 41,561 R 13,398,790 R 16,227,904 R 80,718,169 R 31,258,269 R 174,921,847 20 R 52,098,054 R 1,204,203 R 312,008 R 4,802 R 65,088 R 23,030,384 R 27,259,232 R 132,556,756 R 53,547,308 R 290,077,835 25 R 101,208,861 R 2,207,197 R 571,882 R 8,802 R 119,300 R 75,339,598 R 56,797,664 R 306,044,393 R 162,721,282 R 705,018,979 30 R 223,961,750 R 4,561,179 R 1,181,796 R 18,189 R 246,533 R 225,875,003 R 136,752,000 R 753,253,360 R 473,688,910 R 1,819,538,721 35 R 356,211,205 R 7,081,210 R 1,834,733 R 28,239 R 382,741 R 413,023,162 R 231,019,712 R 1,247,466,816 R 858,029,359 R 3,115,077,177 40 R 465,155,210 R 9,153,407 R 2,371,637 R 36,503 R 494,744 R 570,231,582 R 316,170,624 R 1,656,004,414 R 1,184,967,692 R 4,204,585,812 45 R 491,444,508 R 9,652,908 R 2,501,057 R 38,495 R 521,742 R 615,124,875 R 338,780,288 R 1,754,588,698 R 1,277,056,026 R 4,489,708,596 50 R 497,433,107 R 9,766,692 R 2,530,538 R 38,948 R 527,892 R 624,335,802 R 345,253,216 R 1,777,045,809 R 1,296,504,038 R 4,553,436,042 *post implementation of an air transport liberalisation agreement in SADC

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As can be seen in Figure 2.6-2, below, the cost of navigational infrastructure per route, security, pollution, noise pollution and flight cancellation make up the largest proportions of total costs incurred. Due to low proportion of aircraft accidents and injuries, the cost of accidents resulting in fatality, minor injury and major injury per flight is relatively inconsequential. Likewise the cost of diverting a flight is slight due to infrequency of such flights.

Figure 2.6-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC

R 5,000,000,000 R 4,500,000,000 Navigation Route Costs (FL 145) R 4,000,000,000 Cost of Security R 3,500,000,000

2.6.3 Impact of an air transport liberalisation agreement in the Southern African Development Community

The impact of implementation of an air transport liberalisation agreement in SADC is overwhelming positive when one considers the total benefits and costs computed in Table 2.6-1 and 2.6-2 above. It must be noted that aircraft operational costs have been excluded due to lack of information provided by airlines. Computable benefits are larger than computable costs by a factor ranging between 1000 during the first five year period to 78 at the end of the 50 year modelling period. This is because the existence of excess capacity in aviation infrastructure within SADC at the start of the implementation process keeps initial costs relatively modest. The required investment to sustain implementation of an air transport liberalisation agreement in SADC also grows substantially over the 50 year study period. Nevertheless the net benefit at the end of the 50 year study period still totals a very significant R249.7 billion per week, growing from an initial net benefit totalling R7.8 billion per week during the first 5 years post the an air transport liberalisation agreement implementation. This would indicate that over a 50 year period the net benefit would grow at a real rate of 7.98% annually, an annual real growth rate

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Figure 2.6-3 below, graphs the total computable impact of an air transport liberalisation agreement in SADC over the 50 year period. It can be seen that total costs (in red) are slight in comparison to total benefits (in blue). The net computable benefits comprise the blue area alone. The total computable benefits are signified by the red and blue areas put together, while the red area alone indicates total computable costs.

Figure 2.6-3 The total impact of an air transport liberalisation agreement in SADC being implemented in the Southern African Development community

R 300,000,000,000.00

R 250,000,000,000.00

R 200,000,000,000.00

R 150,000,000,000.00 TOTAL BENEFITS TOTAL COSTS R 100,000,000,000.00

R 50,000,000,000.00

R - 5 10 15 20 25 30 35 40 45 50 Years

12 International Monetary Fund, 2007. http://www.imf.org/external/pubs/ft/weo/2007/02/weodata/index.aspx

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2.7 Impact of an air transport liberalisation agreement reflecting the investment and capital expenditure in airport and navigational infrastructure

Table 2.7-1 below displays the total impact of air transport liberalisation over the 50 year period per airport. The benefit less costs column takes into account all the weekly benefits less costs mentioned in previous sections, this displays the impact per airport. The airport infrastructure costs indicate the total cost of expanding annual passenger capacities over the 50 year period per airport. The airport navigational systems column display the total cost of navigational infrastructure per airport over the 50 year period. The last column ‘Total impact after infrastructure costs’ measures the financial impact of air transport liberalisation in SADC when taking into account all capital and infrastructural investments required to take advantage of this liberalisation.

Most importantly there are 5 airports that have a negative impact over the 50 year period; these airports are Cabinda, Catumbela, Huambo and Kuito from Angola; and Kitwe from Zambia. Although these airports have a negative impact over the 50 year period, the total impact in the region is overwhelmingly positive, even when taking into account the additional airport and navigational infrastructural requirements. For a comprehensive and detailed list of impacts over the 50 year period per airport please refer to Appendix G.

Table 2.7-1 Total impact over 50 years after infrastructure costs are taken into account per airport Location Benefits less costs Airport Airport Total impact after infrastructure navigational infrastructure costs systems Cabinda R 13,135,594,876 R 30,762,646,164 R 105,500,000 R -17,732,551,288 Catumbela R 15,135,950,379 R 21,704,608,871 R 105,500,000 R -6,674,158,492 Dundo R - R - R - R - Huambo R 18,968,271,072 R 32,799,705,108 R 21,666,667 R -13,853,100,703 Kuito R 18,689,215,470 R 31,326,914,031 R 21,666,667 R -12,659,365,227 Luanda R 35,312,114,184 R 14,454,353,583 R 521,500,000 R 20,336,260,601 Lubango R 32,307,418,877 R 31,374,951,739 R 21,666,667 R 910,800,471 Luena R 37,396,632,803 R 27,386,961,412 R 21,666,667 R 9,988,004,724 Malanje R 33,419,030,001 R 31,857,532,089 R 21,666,667 R 1,539,831,245 Menongue R 42,194,390,670 R 30,677,820,412 R 21,666,667 R 11,494,903,591 Namibe R 52,565,917,229 R 31,967,122,412 R 21,666,667 R 20,577,128,150 Ondjiva R 55,206,012,572 R 29,117,281,210 R 21,666,667 R 26,067,064,695 Saurimo R 66,112,557,006 R 30,955,943,213 R 21,666,667 R 35,134,947,126 Soyo R 73,599,566,822 R 29,976,647,084 R 21,666,667 R 43,601,253,072 Uíge R 60,701,876,855 R 30,352,589,998 R 17,333,333 R 30,331,953,524 Francistown R 112,435,059,703 R 35,135,585,164 R 105,500,000 R 77,193,974,539 Gaborone R 126,747,019,578 R 11,489,436,347 R 521,500,000 R 114,736,083,231 Kasane R 87,449,683,593 R 27,894,701,088 R 21,666,667 R 59,533,315,838

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Maun R 104,737,840,516 R 26,245,742,034 R 105,500,000 R 78,386,598,482 Bukavu R 91,974,793,085 R 20,836,679,463 R 13,000,000 R 71,125,113,622 Buta-Zega R 90,872,827,828 R 18,670,970,711 R 13,000,000 R 72,188,857,118 Gbadolite R 97,660,364,082 R 19,005,255,956 R 21,666,667 R 78,633,441,459 Gemena R 102,803,308,089 R 21,174,304,236 R 13,000,000 R 81,616,003,852 Goma R 108,712,929,432 R 21,571,107,575 R 13,000,000 R 87,128,821,857 Isiro-Matari R 120,400,614,619 R 21,672,433,831 R 13,000,000 R 98,715,180,789 Kananga R 97,178,167,198 R 23,874,821,943 R 13,000,000 R 73,290,345,255 Kindu R 102,167,901,405 R 21,663,633,278 R 13,000,000 R 80,491,268,127 Kinshasa R 146,328,475,939 R 8,183,067,357 R 521,500,000 R 137,623,908,582 Kisangani R 131,214,272,888 R 17,332,241,664 R 105,500,000 R 113,776,531,224 Lubumbashi R 155,406,013,907 R 19,548,909,955 R 105,500,000 R 135,751,603,952 Mbandaka R 127,269,799,143 R 22,957,803,412 R 13,000,000 R 104,298,995,731 Mbuji-Mayi R 125,232,224,584 R 24,753,794,341 R 21,666,667 R 100,456,763,576 Maseru R 167,101,320,224 R 15,845,658,240 R 105,500,000 R 151,150,161,984 Antanànarìvo R 309,736,207,278 R 8,121,960,886 R 521,500,000 R 301,092,746,392 Mahajanga R 231,990,742,240 R 16,996,112,279 R 105,500,000 R 214,889,129,962 Nosy Be R 225,102,887,915 R 21,804,839,914 R 13,000,000 R 203,285,048,001 Toamasina R 295,708,091,889 R 19,094,988,396 R 105,500,000 R 276,507,603,493 Toliara R 239,258,253,432 R 22,937,552,850 R 21,666,667 R 216,299,033,915 Blantyre R 190,228,104,292 R 17,641,591,388 R 105,500,000 R 172,481,012,904 Lilongwe R 181,331,634,287 R 6,055,562,817 R 521,500,000 R 174,754,571,469 Port Louis R 606,131,604,552 R 12,345,883,086 R 521,500,000 R 593,264,221,466 Beira R 217,136,053,533 R 20,113,697,085 R 105,500,000 R 196,916,856,448 Chimoio R 170,895,781,172 R 23,705,642,728 R 15,166,667 R 147,174,971,776 Cuamba R 159,194,864,421 R 21,423,216,316 R 13,000,000 R 137,758,648,105 Lichinga R 177,744,106,905 R 23,590,797,889 R 105,500,000 R 154,047,809,016 Maputo R 285,106,971,134 R 7,783,416,063 R 521,500,000 R 276,802,055,071 Moçimboa da R 202,459,822,345 R 19,933,260,259 R 105,500,000 R 182,421,062,085 Praia Mueda R 187,439,099,382 R 19,705,744,750 R 13,000,000 R 167,720,354,631 Nampula R 269,697,762,029 R 20,528,698,094 R 105,500,000 R 249,063,563,935 Tete R 195,888,132,266 R 23,765,714,787 R 21,666,667 R 172,100,750,812 Grootfontein R 248,492,530,242 R 21,432,237,428 R 84,400,000 R 226,975,892,814 Karabib R 221,958,472,576 R 24,282,126,981 R 15,166,667 R 197,661,178,929 Katima Mulilo R 229,639,103,367 R 28,014,954,576 R 17,333,333 R 201,606,815,458 Keetmanshoop R 309,841,858,605 R 28,306,690,157 R 17,333,333 R 281,517,835,115 Mariental R 269,882,924,036 R 27,107,878,848 R 15,166,667 R 242,759,878,521 Ondangwa R 258,900,704,039 R 27,454,733,326 R 17,333,333 R 231,428,637,379 Rundu R 257,454,998,068 R 29,184,572,233 R 17,333,333 R 228,253,092,501 Windhoek R 396,517,070,883 R 9,559,680,305 R 521,500,000 R 386,435,890,578

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Seychelles R 703,501,657,625 R 8,749,277,162 R 521,500,000 R 694,230,880,462 Bisho R 554,445,228,667 R 38,724,314,820 R 105,500,000 R 515,615,413,847 Bloemfontein R 518,236,753,001 R 42,568,700,235 R 105,500,000 R 475,562,552,766 Cape Town R 850,893,805,391 R 19,395,099,853 R 521,500,000 R 830,977,205,539 Durban R 680,019,685,523 R 38,705,155,564 R 521,500,000 R 640,793,029,959 George R - R - R - R - Lanseria R 623,425,486,875 R 50,916,414,646 R 105,500,000 R 572,403,572,229 Johannesburg R 599,808,390,969 R - R 521,500,000 R 599,286,890,969 Kimberley R 520,597,571,517 R 44,083,043,709 R 105,500,000 R 476,409,027,808 Mafikeng R 456,878,656,267 R 40,811,869,973 R 21,666,667 R 416,045,119,627 Nelspruit R 511,508,260,400 R 42,677,327,211 R 105,500,000 R 468,725,433,189 Polokwane R 459,727,696,484 R 42,265,713,353 R 21,666,667 R 417,440,316,465 Port Elizabeth R 757,947,901,871 R 41,889,245,560 R 105,500,000 R 715,953,156,311 Pilanesberg R 458,020,497,838 R 40,046,339,331 R 19,500,000 R 417,954,658,507 Umtata R 589,451,162,905 R 40,306,034,452 R 21,666,667 R 549,123,461,786 Upington R 564,438,760,296 R 42,797,693,603 R 105,500,000 R 521,535,566,693 Welkom R 539,261,292,507 R 42,529,814,313 R 19,500,000 R 496,711,978,194 Manzini R 337,187,877,496 R 17,821,283,568 R 105,500,000 R 319,261,093,927 Dar-Es-Salaam R 640,241,051,391 R 8,424,782,414 R 521,500,000 R 631,294,768,976 Dodoma R 460,907,809,563 R 24,775,748,996 R 105,500,000 R 436,026,560,566 Kilimanjaro R 601,328,818,794 R 21,088,863,923 R 105,500,000 R 580,134,454,871 Mtwara R 463,076,216,765 R 24,211,283,510 R 21,666,667 R 438,843,266,588 Mwanza R 599,323,031,470 R 27,957,419,377 R 21,666,667 R 571,343,945,426 Zanzibar R 575,823,890,548 R 27,027,185,021 R 521,500,000 R 548,275,205,528 Kitwe R -770,778,388 R - R - R -770,778,388 Livingstone R 370,996,780,292 R 18,800,111,355 R 105,500,000 R 352,091,168,937 Lusaka R 456,850,384,931 R 8,921,260,504 R 521,500,000 R 447,407,624,427 Mfuwe R 95,333,266,016 R 8,502,307,049 R 8,666,667 R 86,822,292,300 Ndola R 430,933,005,132 R 27,766,951,019 R 21,666,667 R 403,144,387,446 Bulawayo R 307,810,325,118 R 23,414,456,928 R 105,500,000 R 284,290,368,191 Harare R 382,745,641,210 R 6,518,897,873 R 521,500,000 R 375,705,243,338 Hwange R 238,906,513,453 R 17,155,638,949 R 21,666,667 R 221,729,207,837 Victoria Falls R 228,987,817,785 R 10,761,251,323 R 105,500,000 R 218,121,066,462 TOTAL R 24,566,019,405,225 R 2,133,076,262,959 R 12,076,400,000 R 22,420,866,742,266

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Conclusion

There is overwhelming evidence that implementation of an air transport liberalisation agreement in SADC will produce significant and sustainable benefits to the economy of the region (even when the additional infrastructural requirements are taken into account.) The forecast growth in the aviation market and tourism markets together with the wider economic benefits that will flow from this are so vast and far reaching that not only are the computable costs to be regarded as insignificant (when excluding the aircrafts operational costs), but in all likelihood, it can be considered that the unquantifiable costs identified as associated with such an initiative will, similarly, be no obstacle to success.

Based on the results discussed in this study an air transport liberalisation agreement in the Southern African Development Community would have an overwhelming impact in this region. It would encourage and stimulate tourism and the numbers of passengers utilising air transport as a primary means of transport between two major cities in SADC would increase significantly. The only potential inhibitor to this agreement would be the additional navigational and airport infrastructure required to make an agreement such as this successful, this would need to be funded by airports authorities or governments in the region. Furthermore, the establishment of a regional regulatory and competition authority is essential to monitor the implementation of this agreement and ensure that no country or airlines acts in an uncompetitive manner.

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References

List of References World Trade and Tourism Website o http://www.wttc.org/ o http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_p df_file/economic_impact_research_metho.pdf Source for pollutant volumes: “Forecasting Civil Aviation Fuel Burn and Emissions in Europe, EEC

Note No. 8/2001”, EUROCONTROL Experimental Centre, May 2001

http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note _2001_08.pdf

Source for cost of pollutants: “Economic incentives to control the global environmental impact of European aviation/Level of the incentive”, CE, Solutions for environment, economy and technology, Delft, The Netherlands. Draft preliminary study, 2 May 2001 suggests the medium costs of aviation pollution as follows: Source for Burn Rate: “Evaluating the true cost to airlines of one minute of airborne or ground delay”, University of Westminster, May 2004

(http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf)

Type here (replace this text) Conversions are based on the following websites Australian Dollar (AUD) inflation

http://www.rateinflation.com/consumer-price-index/australia-historical-cpi.php?form=auscpi

Australian Dollar - South African Rand (AUD-ZAR) exchange rate history

http://www.exchangerates.org.uk/AUD-ZAR-exchange-rate-history.html

Average for last 150 days (from 5 March, back 150 days)

Euro inflation

http://www.ecb.europa.eu/stats/prices/hicp/html/inflation.en.html

Euro – South African Rand (EUR-ZAR) exchange rate history

http://www.exchangerates.org.uk/EUR-ZAR-exchange-rate-history.html

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Average for last 150 days (from 14 March, back 150 days) Bureau of Transportation Statistics

http://www.bts.gov/press_releases/2003/dot016_03.html

“The consumer report includes BTS data on the number of domestic flights cancelled by the reporting carriers. In January, the carriers cancelled 2.5 percent of their scheduled domestic flights, higher than the 2.3 percent rate recorded in January 2009 but lower than December 2009's rate of 2.8.”

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List of Tables

Table 1.1-1 Definition of air freedom rights ...... vi

Table 1.1-2 Total number of domestic and international airline passengers, by region ...... vii

Table 1.1-3 Total Benefits incurred by the implementation of an air transport liberalisation aagreement in SADC ...... xvii

Table 1.1-4 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC ...... xix

Table 1.1-5 impact over 50 years after infrastructure costs are taken into account per airport ...... xxii

Table 1.2-1 Definition of air freedom rights ...... 4

Table 1.5-1 Capacity and Traffic Growth for All Europe, 1990-2002 ...... 21

Table 1.5-2 Summary of Intra-EU transport packages ...... 21

Table 1.5-3 : Capacity Shares of Low Cost Carriers ...... 22

Table 1.5-4 Frequency market shares at the beginning of IATA Summer 2004 and 2006 seasons ...... 24

Table 1.6-1 Section analysis of regression on transport costs ...... 28

Table 1.6-2 Forecasts in North-East Asian travel to North America ...... 31

Table 2.2-1 Airports in SADC – Total Passengers ...... 64

Table 2.3-1 Airlines Data ...... 70

Table 2.3-2 Airports Data ...... 74

Table 2.3-3 Stakeholders Data ...... 77

Table 2.4-1 Gross Domestic Product Per Capita, Current 2007 Prices ...... 83

Table 2.4-2 Urban Population by Country ...... 84

Table 2.4-3 Business, Political and Development Indicators for SADC Country ...... 85

Table 2.4-4 Tourism Infrastructure Index by Country ...... 86

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Table 2.4-5 Airport Infrastructure ...... 86

Table 2.4-6 Example of Calculated Indices by Airport ...... 90

Table 2.4-7 Determining the Demand Estimate for Routes ...... 91

Table 2.4-8 Potential Turnover and Seat Numbers ...... 94

Table 2.4-9 The Monetary Value of Costs ...... 97

Table 2.4-10 Cost of Fuel ...... 100

Table 2.4-11 Navigational Equipment Requirements per Route at 5 NM ...... 103

Table 2.4-12 Airport Navigational Equipment Required per Airport Type ...... 103

Table 2.4-13 Type 1 Airports in the SADC Region ...... 104

Table 2.4-14 Type 2 Airports in the SADC Region ...... 104

Table 2.4-15 Type 3 Airports in the SADC Region ...... 105

Table 2.4-16 SADC Airport Capacities ...... 106

Table 2.5-1 Forecasted Turnover, Seat Numbers & Number of flights (per week) ...... 107

Table 2.5-2 Passenger Time Saving Benefit ...... 111

Table 2.5-3 Additional flight information ...... 113

Table 2.5-4 Assumptions, Weights, Proportions and Figures Used ...... 116

Table 2.5-5 Results Over 50 Year Period ...... 117

Table 2.5-6 Tourism Impact Over 50 Years ...... 122

Table 2.5-7 Tourism Impact in Year 5 ...... 124

Table 2.5-8 Tourism Impact in Year 15 ...... 125

Table 2.5-9 Tourism Impact in Year 25 ...... 125

Table 2.5-10 Tourism Impact in Year 40 ...... 126

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Table 2.5-11 Tourism Impact in Year 50 ...... 127

Table 2.5-12 Cost of Pollution and Security ...... 128

Table 2.5-13 Weekly cost navigational infrastructure per route ...... 132

Table 2.5-14 Airport Navigational Infrastructure ...... 134

Table 2.5-15 Airport Infrastructure Costs ...... 136

Table 2.6-1 Total Benefits from the implementation of an air transport liberalisation agreement in SADC ...... 137

Table 2.6-2 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC ...... 139

Table 2.7-1 Total impact over 50 years after infrastructure costs are taken into account per airport .... 142

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List of Figures

Figure 1.1-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC ...... xviii

Figure 1.1-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC ...... xx

Figure 1.1-3 The total impact of an air transport liberalisation agreement being implemented in the Southern African Development community ...... xxi

Figure 1.3-1 South African Airways International Route Map ...... 6

Figure 1.3-2 Demand Curve for both a Pure and Normal Monopoly ...... 8

Figure 1.3-3 Total number of domestic and international airline passengers, by region ...... 11

Figure 1.3-4 Break down of the Yamoussoukro Decision implementation organs ...... 12

Figure 1.4-1 Gravity forecast fails to fit actual data, European Region ...... 17

Figure 1.5-1 Air market share between U.S. carriers and U.K. carriers ...... 19

Figure 1.5-2 Growth in UK-India direct services 2000-2006 ...... 23

Figure 1.5-3 Breakdown of direct services to India in summer 2004 and 2006 ...... 24

Figure 1.5-4 Growth of direct point-to-point markets from the UK to India ...... 25

Figure 1.6-1 The effect of air transportation liberalisation agreements on air transport costs over time 30

Figure 1.6-2 Actual air travel between North-East Asia and North America ...... 31

Figure 2.2-1 Fleet size – Airlines in Angola ...... 36

Figure 2.2-2 Air Botswana Financial data...... 37

Figure 2.2-3 Air Botswana Domestic and International departures ...... 38

Figure 2.2-4 Air Botswana Domestic and International passengers ...... 38

Figure 2.2-5 Air Botswana Fleet ...... 39

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Figure 2.2-6 Fleet size – DRC Airlines ...... 40

Figure 2.2-7 Air Lesotho Domestic and International Departures ...... 40

Figure 2.2-8 Air Madagascar Domestic and International departures ...... 41

Figure 2.2-9 Air Madagascar Domestic and International passenger numbers ...... 42

Figure 2.2-10 Air Madagascar Financial Data ...... 43

Figure 2.2-11 Fleet size – Madagascar airlines ...... 43

Figure 2.2-12 Air Malawi domestic and international departures ...... 44

Figure 2.2-13 Air Malawi Domestic and International Passengers ...... 44

Figure 2.2-14 Air Malawi Fleet ...... 45

Figure 2.2-15 Air Mauritius Domestic and International departures ...... 46

Figure 2.2-16 Air Mauritius Domestic and International passengers ...... 46

Figure 2.2-17 Air Mauritius Fleet ...... 47

Figure 2.2-18 LAM Domestic and International Departures ...... 48

Figure 2.2-19 LAM Domestic and International Passengers ...... 48

Figure 2.2-20 LAM Fleet ...... 49

Figure 2.2-21 Air Namibia Domestic and International Departures ...... 49

Figure 2.2-22 Air Namibia Domestic and International Passengers ...... 50

Figure 2.2-23 Air Namibia Fleet ...... 50

Figure 2.2-24 Air Seychelles Domestic and International Departures ...... 51

Figure 2.2-25 Air Seychelles Domestic and International passengers ...... 52

Figure 2.2-26 Air Seychelles Fleet ...... 52

Figure 2.2-27 South African Airways Domestic and International departures ...... 53

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Figure 2.2-28 South African Airways Domestic and International passengers ...... 54

Figure 2.2-29 SA Airlink Domestic and International departures ...... 54

Figure 2.2-30 SA Airlink Domestic and International passengers ...... 55

Figure 2.2-31 Comair Domestic and International departures ...... 56

Figure 2.2-32 Comair Domestic and International passenger numbers ...... 56

Figure 2.2-33 Fleet size – South African Airlines ...... 57

Figure 2.2-34 Air Tanzania Domestic and International departures ...... 58

Figure 2.2-35 Air Tanzania Domestic and International Passengers ...... 58

Figure 2.2-36 Air Tanzania Financial data ...... 59

Figure 2.2-37 Fleet size – Tanzania airlines...... 60

Figure 2.2-38 Zambia Airways Domestic and International departures ...... 60

Figure 2.2-39 Zambezi Airlines Fleet ...... 61

Figure 2.2-40 Air Zimbabwe Domestic and International Departures ...... 62

Figure 2.2-41 Air Zimbabwe Domestic and International passengers ...... 62

Figure 2.2-42 Air Zimbabwe Financial Data ...... 63

Figure 2.2-43 Airports with highest frequency: ...... 65

Figure 2.2-44 Airports with mid to high frequency: ...... 66

Figure 2.2-45 International Airports with low frequency: ...... 67

Figure 2.2-46 Domestic Airports with low frequency: ...... 67

Figure 2.2-47 Fleet Size (2007) ...... 69

Figure 2.4-1 GDP per Capita Index ...... 88

Figure 2.4-2 Flow chart showing methodology for the section ...... 92

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Figure 2.4-3 Showing how passengers’ benefits fit into the overall methodology ...... 95

Figure 2.4-4 Assumed flight patterns between origins and destinations pre air transport liberalisation in SADC ...... 96

Figure 2.5-1 Forecasted Turnover ...... 108

Figure 2.5-2 Marginal turnover ...... 109

Figure 2.5-3 Growth in Seat Numbers ...... 110

Figure 2.5-4 Growth in Number of Flights per Week ...... 110

Figure 2.5-5 Passengers Time Saving Benefit ...... 112

Figure 2.5-6 Marginal benefits from passengers’ time saving ...... 113

Figure 2.5-7 Average ticket price per flight ...... 114

Figure 2.5-8 Total distance flown per week (km) ...... 115

Figure 2.5-9 Average distance flown per flight (km)...... 115

Figure 2.5-10 Total Costs to Airlines ...... 117

Figure 2.5-11 Cost of Flight Cancellation ...... 118

Figure 2.5-12 Cost of Flight Diversions ...... 119

Figure 2.5-13 Cost of Accident Resulting in Fatality ...... 119

Figure 2.5-14 Cost of Accident Resulting in Minor Injury ...... 120

Figure 2.5-15 Cost of Accident Resulting in Major Injury ...... 120

Figure 2.5-16 Potential Turnover and Costs to Airlines ...... 121

Figure 2.5-17 Total and Direct Impact on GDP (2009 Rands) ...... 123

Figure 2.5-18 Total and Direct Impact on Employment ...... 123

Figure 2.5-19 Cost of Noise Pollution ...... 128

Figure 2.5-20 Cost of Pollution ...... 129

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Figure 2.5-21 Cost of Security ...... 130

Figure 2.5-22 Total Indirect Costs ...... 131

Figure 2.5-23 Weekly cost navigational infrastructure per route ...... 132

Figure 2.5-24 Airport navigational infrastructure ...... 133

Figure 2.5-25 Airport Infrastructure Costs ...... 135

Figure 2.6-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC ...... 138

Figure 2.6-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC ...... 140

Figure 2.6-3 The total impact of an air transport liberalisation agreement in SADC being implemented in the Southern African Development community ...... 141

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List of Boxes

Box 2.4-1 ...... 87

Box 2.4-2 ...... 87

Box 2.4-3 ...... 90

Box 2.4-4 ...... 91

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Appendix A – Signing States of the Chicago Convention 1944

Afghanistan Democratic Republic of the Lithuania Saint Vincent and the Congo Grenadines Albania Denmark Luxembourg Samoa Algeria Djibouti Macedonia San Marino Andorra Dominican Republic Madagascar Sao Tome and Principe Angola Ecuador Malawi Saudi Arabia Antigua and Barbuda Egypt Malaysia Senegal Argentina El Salvador Maldives Serbia Armenia Equatorial Guinea Mali Seychelles Australia Eritrea Malta Sierra Leone Austria Estonia Marshall Islands Singapore Azerbaijan Ethiopia Mauritania Slovakia Bahamas Fiji Mauritius Slovenia Bahrain Finland Mexico Solomon Islands Bangladesh France Micronesia (Federated States Somalia of) Barbados Gabon Monaco South Africa Belarus Gambia Mongolia Spain Belgium Georgia Montenegro Sri Lanka Belize Germany Morocco Sudan Benin Ghana Mozambique Suriname Bhutan Greece Myanmar Swaziland Bolivia Grenada Namibia Sweden Bosnia and Herzegovina Guatemala Nauru Switzerland Botswana Guinea-Bissau Nepal Syrian Arab Republic Brazil Guinea Guyana Netherlands Tajikistan Brunei Haiti Honduras New Zealand Thailand Darussalam Hungary Iceland Nicaragua Timor-Leste Bulgaria India Nigeria Togo Burkina Faso Indonesia Niger Tonga Burundi Iran (Islamic Republic of) Norway Trinidad and Tobago Cambodia Iraq Oman Tunisia Cameroon Ireland Pakistan Turkey Canada Israel Palau Turkmenistan Cape Verde Italy Panama Uganda Central African Republic Jamaica Papua New Guinea Ukraine Chad Japan Paraguay United Arab Emirates Chile Jordan People's Republic of Korea United Kingdom China Kazakhstan Peru United Republic of Tanzania Colombia Kenya Philippines United States Comoros Kiribati Poland Uruguay Congo Kuwait Portugal Uzbekistan Cook Islands Kyrgyzstan Qatar Republic of Vanuatu Costa Rica Lao People's Korea Republic of Moldova Venezuela Croatia Democratic Republic Latvia Romania Viet Nam Cuba Lebanon Russian Federation Yemen Cyprus Lesotho Rwanda Zambia Czech Republic Liberia Saint Kitts and Nevis Zimbabwe Côte d'Ivoire Democratic Libyan Arab Jamahiriya Saint Lucia

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Appendix B – United States Air transportation liberalisation Partners and status of the agreement

Partner Application Date All-cargo 7th air Concluded freedom Albania In Force 9/24/2003 Yes Armenia C&R 8/7/2010 Yes Aruba In Force 9/18/1997 Yes Australia C&R 2/14/2008 Yes Austria In Force 6/14/1995 Bahrain In Force 5/24/1999 Yes Belgium Provisional 3/1/1995

Benin N/A 11/28/2000 Yes[1] Bosnia and Herzegovina In Force 11/22/2005 Yes Brunei In Force 6/20/1997 Yes Bulgaria Provisional 4/30/2007 Yes 3/30/08 Burkina Faso In Force 2/9/2000 Yes1 Cameroon In Force 2/16/2006 Yes1 Canada In Force 7/12/2003 Yes Cape Verde In Force 6/21/2002 Yes1 Chad Provisional 5/31/2006 Yes1 Chile In Force 10/28/1997 Yes Cook Islands In Force 2/28/2006 Yes Costa Rica In Force 5/8/1997 Croatia N/A 3/13/2008 Yes Cyprus Provisional 4/30/2007 Yes 3/30/08 Czech Republic In Force 12/8/1995 Yes Denmark In Force 4/26/1995 El Salvador In Force 5/8/1997 Yes Estonia Provisional 4/30/2007 Yes 3/30/08 Ethiopia Provisional 5/17/2005 Yes Finland In Force 3/24/1995 France In Force 10/19/2001 Yes Gabon In Force 5/26/2004 Yes1 Gambia In Force 5/2/2000 Yes1 Georgia In Force 7/6/2012 Yes Germany Provisional 2/29/1996 Yes Ghana In Force 3/16/2000 Yes1 Greece Provisional 4/30/2007 Yes 3/30/08 Guatemala In Force 5/8/1997 Yes Honduras Provisional 5/8/1997 Yes Hungary Provisional 4/30/2007 Yes 3/30/08 Iceland In Force 6/14/1995 Yes India In Force 1/15/2005 Yes Indonesia C&R 7/26/2004 Yes

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Ireland Provisional 4/30/2007 Yes 3/30/08 Italy C&R 11/11/1998 Jamaica In Force 10/30/2008 Jordan In Force 11/10/1996 Kenya C&R 5/30/08 --[1] Korea In Force 4/23/1998 Kuwait In Force 5/27/2007 Yes Laos C&R 8/3/2010 Yes Latvia Provisional 4/30/2007 Yes 3/30/08 Liberia In Force 2/15/2007 Yes Lithuania Provisional 4/30/2007 Yes 3/30/08 Luxembourg In Force 6/6/1995 Yes Madagascar Provisional 4/10/2003 Yes1 Malaysia In Force 6/21/1997 Yes Maldives In Force 5/5/2005 Yes Mali In Force 10/17/2005 Yes1 Malta In Force 10/12/2000 Yes Morocco In Force 10/5/2000 Yes Namibia C&R 2/4/2000 1 Netherland Antilles In Force 7/14/1998 Yes Netherlands In Force 10/14/92 New Zealand In Force 5/29/1997 Yes Nicaragua In Force 5/8/1997 Chart Only Nigeria Provisional 8/26/2000 Yes1 Norway In Force 4/26/1995 Oman C&R 9/16/2001 Yes Pakistan In Force 4/29/1999 Yes Panama In Force 5/8/1997 Yes Paraguay In Force 5/2/2005 Yes Peru In Force 6/10/1998 Yes Poland In Force 5/31/2001 Yes Portugal In Force 12/22/1999 Yes Qatar Provisional 1/3/2010 Yes Romania In Force 7/15/1998 Rwanda N/A 10/11/2000 Yes1 Samoa In Force 2/4/2007 Yes Senegal C&R 12/15/2000 Yes1 Singapore In Force 1/22/1997 Yes Slovak Republic In Force 1/7/2000 Yes Slovenia Provisional 4/30/2007 Yes 3/30/08 Spain Provisional 4/30/2007 Yes

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3/30/08 Sri Lanka In Force 1/1/2011 Sweden In Force 4/26/1995 Switzerland In Force 6/15/1995 Taiwan In Force 2/28/1997

Tanzania Provisional 11/3/1999 Yes[2] Thailand In Force 9/19/2005 Yes Tonga In Force 9/19/2003 Yes Turkey In Force 3/22/2000 U.A.E. In Force 4/13/1999 Yes Uganda C&R 2/4/2006 Yes1 United Kingdom Provisional 4/30/2007 Yes 3/30/08 Uruguay Provisional 10/20/2004 Yes Uzbekistan In Force 2/27/1998 Yes Source: http://www.state.gov/e/eeb/rls/othr/ata/114805.htm, accessed 17/07/2009

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Appendix C – State ownership for international flag carriers

Country Airline Designated State-owned Afghanistan Ariana Afghan Airlines Yes Majority Albania Albanian Airlines Yes Joint-Venture Andorra AeroKing Andorra Yes Joint-Venture Algeria Air Algérie Yes Majority[1] Angola TAAG Angola Airlines Yes Full1 Åland Islands Air Åland Argentina Aerolíneas Argentinas Yes Full Armenia Armavia Yes No Australia Qantas Yes No Austria Austrian Airlines Yes Minority (42.75%) Azerbaijan Azerbaijan Airlines Yes Full Bahamas Bahamasair Yes Full Bahrain Gulf Air Yes Full Bangladesh Biman Bangladesh Airlines Yes Full Barbados LIAT No No Belarus Belavia Yes Full Belgium Brussels Airlines Yes No Belize Maya Island Air No No Benin Benin Golf Air Yes No1 Bhutan Drukair Yes Full Bolivia AeroSur Yes Minority (48%) Bosnia and Herzegovina B&H Airlines Yes Majority (51%) Botswana Air Botswana Yes Full1 Brazil TAM Airlines Yes No Brunei Royal Brunei Airlines Yes Full Bulgaria Bulgaria Air Yes No Hemus Air Yes No Burkina Faso Air Burkina Yes Majority1 Burundi Air Burundi Yes Full1 Cambodia Royal Khmer Airlines Yes Full Cameroon Cameroon Airlines Yes Canada Air Canada Yes No (privatised in 1988) Cape Verde TACV Cabo Verde Airlines Yes Full1 Cayman Islands Cayman Airways Yes Chad Toumaï Air Tchad 1 Chile LAN Airlines No China Air China Yes Majority Colombia Avianca Yes No Comoros Air Comores International

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Republic of the Congo Trans Air Congo Full[2] Democratic Republic of the Hewa Bora Airways Full1 Congo Costa Rica Lacsa (now part of TACA) Côte d'Ivoire Air Ivoire 1 Croatia Croatia Airlines Yes Majority Cuba Cubana de Aviación Yes Full Cyprus Cyprus Airways Yes Majority Northern Cyprus Cyprus Turkish Airlines Czech Republic Czech Airlines Yes Full Denmark Scandinavian Airlines System Yes Joint-Venture Djibouti Air Djibouti 1 Dominican Republic Air Dominicana Yes Minority (33%) Ecuador TAME Egypt EgyptAir Yes Full El Salvador TACA Equatorial Guinea Ecuato Guineana Eritrea Eritrean Airlines Yes Full Estonia Estonian Air Yes Minority Ethiopia Ethiopian Airlines Yes Full1 Faroe Islands Atlantic Airways Fiji Air Pacific Finland Finnair Yes Majority France Air France No Minority French Guiana Air Guyane Yes French Polynesia Air Tahiti Nui Yes Gabon Gabon Airlines 1 Gambia Gambia International Yes 1 Airlines Georgia Georgian Airways Yes Guernsey Aurigny Air Services Yes Full Germany Lufthansa Yes No Ghana Ghana International Airlines Yes 1 Greece Olympic Airlines Yes Majority Greenland Air Greenland Yes Guadeloupe Air Caraïbes Guam Continental Micronesia Guatemala Aviateca (now part of TACA) Guinea Air Guinee Express Yes Guyana Caribbean Airlines No Haiti Tortug' Air Honduras TACA Hong Kong Cathay Pacific Yes No Hungary Malév Yes No Iceland Icelandair Yes No

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Indonesia Garuda Indonesia Yes Full India Air India Yes Full Indian Yes Full Iran Iran Air Yes Full Iraq Iraqi Airways Yes Full Ireland Aer Lingus Yes Minority (28%) Israel El Al Yes Minority (30%) Italy Alitalia Yes No (Privatised in 2009) Jamaica Air Jamaica Yes Japan Japan Airlines Yes No Jordan Royal Jordanian Airlines Yes Kazakhstan Air Astana Yes 0.51 Kenya Kenya Airways Yes [3] Kiribati Air Kiribati Yes North Korea Air Koryo Yes Full South Korea Korean Air Yes No Kuwait Kuwait Airways Yes Full Kyrgyzstan Kyrgyzstan Airlines Yes Majority Laos Lao Airlines Yes Full Latvia Air Baltic Yes Majority Lebanon Middle East Airlines Full Liberia Air Liberia Yes 1 Libya Libyan Arab Airlines Yes 1 Lithuania Luxembourg Luxair Yes Minority Macau Air Macau Yes No Macedonia MAT Macedonian Airlines Yes No Madagascar Air Madagascar Yes Majority1 Malawi Air Malawi Yes Full1 Malaysia Malaysia Airlines Yes Minority Maldives Maldivian Yes Full Mali Air Mali International Yes No Malta Air Malta Yes Majority Marshall Islands Air Marshall Islands Yes Full Martinique Air Caraïbes Yes No Mauritania Mauritania Airways Minority Mauritius Air Mauritius Yes Minority1 Mexico Aeromexico Mexicana Yes Federated States of Continental Micronesia Micronesia Moldova Air Moldova Yes Mongolia MIAT Mongolian Airlines Yes Montenegro Montenegro Airlines Yes Montserrat Air Montserrat

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Morocco Royal Air Maroc Yes Mozambique Linhas Aéreas de Yes Full[4] Moçambique Myanmar Myanma Airways Yes Yes Namibia Air Namibia Yes Majority1 Nauru Our Airline Yes Nepal Nepal Airlines Yes Netherlands KLM Yes No Netherlands Antilles Dutch Antilles Express New Caledonia Aircalin New Zealand Air New Zealand Yes Majority Nicaragua NICA (now part of TACA) Yes Nigeria Virgin Nigeria Airways Yes No1 Norway Scandinavian Airlines System Yes Minority Oman Oman Air Yes Majority (82.4%) Pakistan Pakistan International Yes Majority (87%) Airlines (PIA) Palestinian Authority Palestinian Airlines Full Panama Copa Airlines Yes No Papua New Guinea Air Niugini Paraguay Regional Paraguaya Yes No Peru Air Perú Philippines Philippine Airlines Yes Joint-Venture Poland LOT Polish Airlines Yes Majority (67.97%) Portugal TAP Portugal Yes Full Qatar Qatar Airways Yes Republic of China China Airlines[8] No Majority (54%) Réunion Air Austral Romania TAROM Yes Majority (95%) Russia Rossiya Yes Full Aeroflot Yes Majority (51%) Rwanda Rwandair Express Yes 1 Samoa Polynesian Blue São Tomé and Príncipe STP Airways 1 Saudi Arabia Saudi Arabian Airlines Yes Full Senegal Air Sénégal International Yes 1 Serbia Jat Airways Yes Full Seychelles Air Seychelles Yes 1 Sierra Leone Sierra National Airlines Yes [5] Singapore Singapore Airlines Yes Majority (54%)

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Slovakia Air Slovakia Slovenia Adria Airways Solomon Islands Solomon Airlines Yes Somalia Somali Airlines[10] Yes South Africa South African Airways Yes Full1 Spain Iberia Yes Minority (5%) Sri Lanka SriLankan Airlines Yes Sudan Sudan Airways Yes 1 Suriname Surinam Airways Yes Sweden Scandinavian Airlines System Yes Joint-Venture Swaziland Royal Swazi National 1 Airways Switzerland Swiss International Air Yes No Lines [12] Syria Syrian Air Yes Full Tajikistan Tajik Air Yes Tanzania Air Tanzania Yes Thailand Thai Airways International Yes Majority (53%) Togo Air Togo Yes Tonga Trinidad and Tobago Caribbean Airlines Yes Full Tunisia Tunisair Yes Turkey Turkish Airlines Yes Majority Turkmenistan Turkmenistan Airlines Yes Turks and Caicos Islands Air Turks and Caicos Yes Uganda Air Uganda Yes 1 Ukraine Ukraine International Yes Majority Airlines United Arab Emirates Etihad Airways Yes Yes Emirates Yes Yes United Kingdom British Airways Yes No (Privatised in 1987) United States N/A N/A N/A Uruguay PLUNA Yes Minority (25%) Uzbekistan Uzbekistan Airways Yes Majority Vanuatu Air Vanuatu Yes Venezuela Conviasa Yes Full Vietnam Vietnam Airlines Yes Full Yemen Yemenia Yes Zambia Zambian Airways Yes 1 Zimbabwe Air Zimbabwe Yes 1

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Appendix D – Spider Diagram

New Routes

Benefits Expansion on existing routes

Increase in Airlines cancellations

Increase in diversions Costs Increase in minor/major Direct Impacts injury

Increase in fatalities

Reduction in time travelled Passengers Benefits Reduction in airfares Impact of YD (SADC) Direct impact on GDP Tourism Impacts Benefits Total impact on GDP

International security personnel Security Cost Indirect Impacts Domestic security personnel

Increased fuel Pollution Cost burn

Noise Pollution Cost Increased flights

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Appendix E – Questionnaires

Air transportation liberalisation Questionnaire for Southern African Airlines Graham Muller Associates is an economic consultancy who has been appointed by the South African Department of Transport to measure the impacts of a Yamoussoukro Decision (Air transportation liberalisation Aviation Agreement) within the Southern African Development Community (SADC) region. In order for the impacts to be measured as accurately as possible it is essential that we gather information from airlines, airports and other aviation industry stakeholders within the Southern Africa region. We therefore implore that your company/organisation takes part in this survey and complete the questionnaire that follows. The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine three things:

1. Determine the understanding that airlines within Southern Africa have of the Yamoussoukro Decision (an African aviation agreement from 1999) 2. Determine the information about all the current routes flown by airlines in Southern Africa 3. Determine the effects of an air transportation liberalisation agreement among the SADC countries.

It would be greatly appreciated if you could take 20 minute to complete this questionnaire and return it to Graham Muller Associates (no later than a week from receiving the questionnaire, please). Answers are to be completed in the boxes that follow the questions.

Please NOTE that answer boxes will expand in size as you type your answers.

1. Please complete the following information:

Company/Organisation

Country of airport

Name

Position held

Email address

Contact number

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Date completed

2. What type of airline are you? Please tick √ the correct box and explain where necessary (Tick can be cut and pasted). TICK BRIEFLY EXPLAIN

National flag carrier

Low cost carrier Domestic

International

High end (luxury) Domestic carrier International

Freight Carrier Domestic

International

Chartered Carrier

Franchise Who are you franchised from?

Code Sharing Who are code sharing partners? Both domestic and international?

Alliance Who are your alliance partners? Both domestic and international?

Block Space Who do you have block space agreements with? Both domestic and international?

a. If your airline does not fall within the above categories please explain?

b. Very briefly explain the functions of your company/organisation and how it fits into the aviation industry within the Southern African Region?

3. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)

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4. Please √ tick the correct box and explain where necessary?

QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN a. Has your airline What was the subsidy you been subsidised by received in proportion to your government in the turnover? last 5 years? b. Is your airline What is the percentage of wholly or partly government ownership? owned by government? c. Is your airline Please tick Sole privately owned? the structure proprietorship of private ownership for A partnership your airline Close Corporation

Company

Non-profit d. Is your airline What is the percentage of owned by a foreign governments’ FOREIGN ownership? government? e. Is your airline Please tick Sole privately owned by the structure proprietorship FOREIGN owners or of private shareholders? ownership for A partnership your airline Close Corporation

Company

Non-profit

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5. Please ONLY answer this question if there is more than one shareholder. If the ownership of your airport(s) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below? Yes: No:

6. Are you familiar with air transportation liberalisation agreements in regions or between countries? Please tick as appropriate: Yes: No:

7. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate: Yes: No:

If your answer to either question 6 or 7 is yes, please answer questions 7a – 7h. These questions relate directly to the Yamoussoukro Decision, which looks to establish an air transportation liberalisation agreement between African countries for African airlines. Otherwise if you’ve answered “ NO” for both questions 6 and 7 please continue to question 8:

a. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate: Very poor

Poor

Fair Why?

Good

Very good

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OWNERS Eg. %

Domestic Government 33%

Foreign Government 0%

Domestic Private Ownership 50%

Foreign Private Ownership 17%

b. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate: Very poor

Poor

Fair Why?

Good

Very good

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Lack of SACD commitment OTHER PLEASE SPECIFY BELOW: to YD

National flag carriers disapproval of YD

Lack of competition law regionally

Lack of competition law within your country

Corruption

Poor legislation

Political instability in other African countries

Poor/substandard airport infrastructure in Africa

d. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?

e. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?

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f. How do you see the Yamoussoukro Decision impacting on your company? i. Frequency of flights ii. Capacity (number of seats on offer) iii. Pricing iv. Volume of freight business v. No. of competitors on each route vi. Your market share on each route

a. Which airlines would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?

AIRLINES EXPLAIN

Most benefit from YD

Least benefit from YD

b. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as: (Please answer yes or no and give a reason for ‘yes’ answers)

YES / NO: EXPLAIN WHERE ‘YES’:

Air traffic control

Airport runway capacity (slots)

Airport runway length

Baggage handling

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Security

Freight logistics capacity

Other (specify):

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8. Could you please list the following airline fleet information in the table below: a. What aircrafts does your fleet consist of? b. What runway lengths are required for the takeoff and landing of each aeroplane model, at various capacities? (eg. 100% full, 90% full or 80% full)

AEROPLANE MODEL NUMBER IN RUNWAY CAPACITY FLEET LENGTH (ft) 100% 90% 80%

Eg. Airbus A320 3 TAKE OFF 6600 5400 4300

LANDING 4800 4225 3650

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

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LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

9. What other airport requirements, besides runway length, does your airline require to fly to a destination both domestically and internationally? (Please tick as appropriate) TICK

Air traffic control

Baggage Handling

Customs facilities

Airport Security

Other (please specify)

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10. How many passengers were served in the various markets from 2004 to 2008? 2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

11. How much freight (in tons) did your airline handle in the various markets from 2004 to 2008? 2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

12. How many flights operated in the various markets from 2004 to 2008? 2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

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13. What routes do you currently cover both domestically and internationally? (please answer this in table below) BOXES WILL EXPAND AS YOU WRTIE YOUR ANSWERS IN THEM a. On these various routes please detail the: i. Airport code of origin and destination? ii. Frequency of flights? iii. Capacity (number of seats on offer)? iv. Pricing? v. Demand (take up of capacity)? vi. Volume of freight business? vii. No. of competitors on each route? viii. Your market share – has this increased or decreased? ix. If this route operates under an air transportation liberalisation agreement? x. How would this route change under an air transportation liberalisation agreement?

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destinati Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business vii. No. of competitors on route

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ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation Eg. Would fly liberalisation agreement 10 more flights on this route per

month

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

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vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation

liberalisation agreement

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destination Destinati Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

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vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation

liberalisation agreement

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS igin

Origin Origin Origin Or Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

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iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation liberalisation agreement

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PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

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x. Change under air transportation liberalisation agreement

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The following question looks at the possible changes in the aviation industry if the Southern African Development Community (SADC) had a regional air transportation liberalisation agreement. This would give SADC airlines the option of flying to ANY airport within the SADC region an unlimited amount of times.

14. If the SADC had a comprehensive air transportation liberalisation agreement, how would this impact your airline ? (How would it change?) Please list where appropriate the changed staff, aircraft and other related requirements:

b. Would you fly any new routes if there were a SADC air transportation liberalisation agreement? What frequency of flights would you fly on these new routes, as well as the estimated capacity for freight and passengers? Please add rows if needed

NEW ROUTE FREQUENCY OF PASSENGER CAPACITY FREIGHT CAPACITY PRICE FLIGHTS

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c. What would be the changes in the current routes you fly if there were a SADC air transportation liberalisation agreement? Please list the change in frequency, as well as the estimated capacity for freight and passengers? Please add rows if needed CHANGE TO CURRENT FREQUENCY OF PASSENGER FREIGHT CAPACITY PRICE ROUTES FLIGHTS CAPACITY

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Air transportation liberalisation Questionnaire for Southern African Airlines

Graham Muller Associates is an economic consultancy who has been appointed by the South African Department of Transport to measure the impacts of a Yamoussoukro Decision (Air transportation liberalisation Aviation Agreement) within the Southern African Development Community (SADC) region. In order for the impacts to be measured as accurately as possible it is essential that we gather information from airlines, airports and other aviation industry stakeholders within the Southern Africa region. We therefore implore that your company/organisation takes part in this survey and complete the questionnaire that follows.

The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine three things:

Please NOTE that answer boxes will expand in size as you type your answers.

4. Please complete the following information:

Company/Organisation

Country of airport

Name

Position held

Email address

Contact number

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Date completed

5. What type of airline are you? Please tick √ the correct box and explain where necessary (Tick can be cut and pasted).

TICK BRIEFLY EXPLAIN

National flag carrier

Low cost carrier Domestic

International

High end (luxury) Domestic carrier International

Freight Carrier Domestic

International

Chartered Carrier

Franchise Who are you franchised from?

Code Sharing Who are code sharing partners? Both domestic and international?

Alliance Who are your alliance partners? Both domestic and international?

Block Space Who do you have block space agreements with? Both domestic and international?

c. If your airline does not fall within the above categories please explain?

d. Very briefly explain the functions of your company/organisation and how it fits into the aviation industry within the Southern African Region?

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6. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)

7. Please √ tick the correct box and explain where necessary?

Company

Non-profit

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8. Please ONLY answer this question if there is more than one shareholder. If the ownership of your airport(s) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?

OWNERS Eg. %

Domestic Government 33%

Foreign Government 0%

Domestic Private Ownership 50%

Foreign Private Ownership 17%

9. Are you familiar with the air transportation liberalisation agreements in regions or between countries? Please tick as appropriate: Yes: No:

10. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate: Yes: No:

Poor

Fair Why?

Good

Very good

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h. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate: Very poor

Poor

Fair Why?

Good

Very good i. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please tick as appropriate Lack of government Airport security commitment to YD concerns

Lack of SACD commitment OTHER PLEASE SPECIFY BELOW: to YD

National flag carriers disapproval of YD

Lack of competition law regionally

Lack of competition law within your country

Corruption

Poor legislation

Political instability in other African countries

Poor/substandard airport infrastructure in Africa j. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?

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k. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?

l. How do you see the Yamoussoukro Decision impacting on your company? i. Frequency of flights ii. Capacity (number of seats on offer) iii. Pricing iv. Volume of freight business v. No. of competitors on each route vi. Your market share on each route

a. Which airlines would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why? AIRLINES EXPLAIN

Most benefit from YD

Least benefit from YD

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Airport runway length Baggage handling Security Freight logistics capacity Other (specify):

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11. Could you please list the following airline fleet information in the table below: c. What aircrafts does your fleet consist of? d. What runway lengths are required for the takeoff and landing of each aeroplane model, at various capacities? (eg. 100% full, 90% full or 80% full)

AEROPLANE MODEL NUMBER IN RUNWAY CAPACITY FLEET LENGTH (ft) 100% 90% 80%

Eg. Airbus A320 3 TAKE OFF 6600 5400 4300

LANDING 4800 4225 3650

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

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12. What other airport requirements, besides runway length, does your airline require to fly to a destination both domestically and internationally? (Please tick as appropriate) TICK

Air traffic control

Baggage Handling

Customs facilities

Airport Security

Other (please specify)

13. How many passengers were served in the various markets from 2004 to 2008? 2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

14. How much freight (in tons) did your airline handle in the various markets from 2004 to 2008? 2004 2005 2006 2007 2008 Domestic SADC Region Africa Rest of the world TOTAL

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15. How many flights operated in the various markets from 2004 to 2008? 2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

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16. What routes do you currently cover both domestically and internationally? (please answer this in table below) BOXES WILL EXPAND AS YOU WRTIE YOUR ANSWERS IN THEM d. On these various routes please detail the: i. Airport code of origin and destination? ii. Frequency of flights? iii. Capacity (number of seats on offer)? iv. Pricing? v. Demand (take up of capacity)? vi. Volume of freight business? vii. No. of competitors on each route? viii. Your market share – has this increased or decreased? ix. If this route operates under an air transportation liberalisation agreement?

x. How would this route change under an air transportation liberalisation agreement?

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business vii. No. of competitors on route

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ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation Eg. Would fly liberalisation agreement 10 more flights on this route per

month

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

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vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation

liberalisation agreement

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destinati Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

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vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation

liberalisation agreement

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS igin

Origin Origin Or Origin Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

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iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

x. Change under air transportation liberalisation agreement

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Department of Transport P a g e | 202

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS

Origin Origin Origin Origin Origin

TO THE RIGHT: Origin

Destination Destination Destination Destination Destination Destination

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business vii. No. of competitors on route viii. Current market share of route viii. Has market share increased or decreased? Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation? Please answer YES or NO

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x. Change under air transportation liberalisation agreement

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17. If the SADC had a comprehensive air transportation liberalisation agreement, how would this impact your airline ? (How would it change?) Please list where appropriate the changed staff, aircraft and other related requirements:

e. Would you fly any new routes if there were a SADC air transportation liberalisation agreement? What frequency of flights would you fly on these new routes, as well as the estimated capacity for freight and passengers? Please add rows if needed

NEW ROUTE FREQUENCY OF PASSENGER CAPACITY FREIGHT CAPACITY PRICE FLIGHTS

f. What would be the changes in the current routes you fly if there were a SADC air transportation liberalisation agreement? Please list the change in frequency, as well as the estimated capacity for freight and passengers? Please add rows if needed CHANGE TO CURRENT FREQUENCY OF PASSENGER FREIGHT CAPACITY PRICE ROUTES FLIGHTS CAPACITY

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Air transportation liberalisation Questionnaire for other Southern Africa Aviation Industry Stakeholders

The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine two things:

1. Determine the understanding that your company/organisation has of the Yamoussoukro Decision (an African aviation agreement from 1999) 2. Determine the effects of an air transportation liberalisation agreement among the SADC countries will have on your company/organisation.

Please NOTE that answer boxes will expand in size as you type your answers.

3. Please complete the following information: Company/Organisation

Country

Name

Position held

Email address

Contact number

Date completed

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4. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)

5. Please list your main sources of income?

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6. Please tick √ the correct box and explain where necessary? (Tick can be cut and pasted).

QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN (if necessary) a. Has your company What was the subsidy you been subsidised by received in proportion to your government in the turnover? last 5 years? b. Is your company What is the percentage of wholly or partly government ownership? owned by government? c. Is your company Please tick Sole privately owned? the structure proprietorship of private ownership for A partnership your company Close Corporation

Company

Non-profit d. Is your company What is the percentage of owned by a foreign governments’ FOREIGN ownership? government? e. Is your company Please tick Sole privately owned by the structure proprietorship FOREIGN owners or of private shareholders? ownership for A partnership your company Close Corporation

Company

Non-profit

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7. Please ONLY answer this question if there is more than one shareholder. If the ownership of your business(es) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?

OWNERS Eg. %

Domestic Government 33%

Foreign Government 0%

Domestic Private Ownership 50%

Foreign Private Ownership 17%

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8. Are you familiar with air transportation liberalisation agreements in regions or between countries? Please tick as appropriate: Yes: No:

9. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate: Yes: No:

Poor

Fair Why?

Good

Very good

n. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate: Very poor

Poor

Fair Why?

Good

Very good

o. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please tick as appropriate

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Lack of government Airport security commitment to YD concerns

Lack of SACD commitment OTHER PLEASE SPECIFY BELOW: to YD

National flag carriers disapproval of YD

Lack of competition law regionally

Lack of competition law within your country

Corruption

Poor legislation

Political instability in other African countries

Poor/substandard airport infrastructure in Africa

p. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?

q. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?

r. How do you see the Yamoussoukro Decision impacting on your company? Please explain in detail in the space below, which will expand as you type.

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s. Which companies/organistions would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why? COMPANIES/ORGANISATIONS EXPLAIN

Most benefit from YD

Least benefit from YD

t. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as: (Please answer yes or no and give a reason for ‘yes’ answers)

YES / NO: EXPLAIN WHERE ‘YES’:

Air traffic control

Airport runway capacity (slots)

Airport runway length

Baggage handling

Security

Freight logistics capacity

Other (specify):

10. If the ‘Southern African Development Community’ (SADC) had a comprehensive air transportation liberalisation agreement, how would your company change? Please answer in detail, specify staff, infrastructure and capital changes:

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Appendix F – Destinations within SADC

City COUNTRY POPULATION Luanda Angola 3,060,137 Huambo Angola 220,835 Lobito Angola 174,785 Benguela Angola 171,096 Namibe Angola 169,061 Kuito Angola 112,834 Lubango Angola 96,424 Malanje Angola 91,082 M'banza-Kongo Angola 85,993 Uige Angola 62,332 Cabinda Angola 56,990 Saurimo Angola 52,410 Lucapa Angola 45,668 Chissamba Angola 40,580 Waku-Kungo Angola 37,908 Sumbe Angola 32,438 Caxito Angola 31,293 Soyo Angola 30,021 Menongue Angola 29,512 Caala Angola 29,131 Caluquembe Angola 28,368 N'dalatando Angola 28,368 Longonjo Angola 25,060 Catabola Angola 23,152 Catumbela Angola 20,989 Luena Angola 20,481 Luau Angola 17,428 Camacupa Angola 16,919 Catchiungo Angola 16,156 Leua Angola 15,901 N'zeto Angola 15,138 Camabatela Angola 14,756 Cazaje Angola 14,375 Lumeje Angola 14,247 Ondjiva Angola 12,721 Caconda Angola 10,304 Gaborone Botswana 191,223 Francistown Botswana 85,360 Molepolole Botswana 56,141 Selibe Phikwe Botswana 51,255 Maun Botswana 45,027 Serowe Botswana 43,686 Kanye Botswana 41,770 Mahalapye Botswana 40,812 Mochudi Botswana 38,034 Mogoditshane Botswana 33,723 Lobatse Botswana 30,561 Palapye Botswana 27,016 Tlokweng Botswana 21,747 Ramotswa Botswana 21,268

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Thamaga Botswana 18,586 Moshupa Botswana 17,436 Tonota Botswana 16,095 Jwaneng Botswana 15,616 Letlhakane Botswana 15,424 Bobonong Botswana 15,041 Tutume Botswana 14,083 Mmadinare Botswana 11,209 Gabane Botswana 10,730 Ghanzi Botswana 10,251 Orapa Botswana 9,389 Kasane Botswana 7,856 Shoshong Botswana 7,664 Tsabong Botswana 6,802 Gumare Botswana 6,227 Letlhakeng Botswana 6,227 Lerala Botswana 5,940 Kopong Botswana 5,748 Maitengwe Botswana 5,461 Otse Botswana 5,365 Mmankgodi Botswana 5,173 Molapowabojang Botswana 4,982 Tsienyane Botswana 4,694 Mmathethe Botswana 4,503 Shakawe Botswana 4,503 Tati Botswana 4,503 Tumasera Seleka Botswana 4,407 Lotlhakane Botswana 4,311 Nata Botswana 4,311 Sefhare Botswana 4,311 Gweta Botswana 4,215 Metsimotlhaba Botswana 4,215 Lentsweletau Botswana 4,120 Mathangwane Botswana 4,120 Bokaa Botswana 3,928 Hukuntsi Botswana 3,928 Sefophe Botswana 3,928 Kang Botswana 3,832 Mmopane Botswana 3,641 Nkange Botswana 3,641 Ramokgonami Botswana 3,641 Mogoditshane Botswana Defence Force Botswana 3,545 Oodi Botswana 3,545 Tsetsebjwe Botswana 3,545 Kumakwane Botswana 3,257 Manyana Botswana 3,257 Maunatlala Botswana 3,257 Masunga Botswana 3,161 Mopipi Botswana 3,161 Water Util-Dukwe Refugee Camp Botswana 3,161 Borolong Botswana 3,066 Pitsane Botswana 3,066 Chadibe Botswana 2,970

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Good Hope Botswana 2,970 Sowa Botswana 2,970 Sebina Botswana 2,874 Digawana Botswana 2,778 Morwa Botswana 2,778 Radisele Botswana 2,778 Etsha Botswana 2,682 Mandunyane Botswana 2,682 Moiyabana Botswana 2,682 Ranaka Botswana 2,682 Thebephatshwa Botswana 2,682 Lecheng Botswana 2,587 Ramotswa Station-Taung Botswana 2,587 Senete Botswana 2,587 Modipane Botswana 2,491 Rasesa Botswana 2,491 Malolwane Botswana 2,395 Mookane Botswana 2,395 Thabala Botswana 2,395 Kalamare Botswana 2,299 Lesetlhane Botswana 2,299 Ratholo Botswana 2,299 Serule Botswana 2,299 Lesenepole Botswana 2,203 Shashe Mooke Botswana 2,203 Khakhea Botswana 2,108 Machaneng Botswana 2,108 Mmathubudukwane Botswana 2,108 Mogobane Botswana 2,108 Mogorosi Botswana 2,108 Paje Botswana 2,108 Shashe-Semotswane Botswana 2,108 Sojwe Botswana 2,108 Etsha 13 Botswana 2,012 Nlakhwane Botswana 2,012 Werda Botswana 2,012 Charles Hill Botswana 1,916 Dukwi Botswana 1,916 Khudumelapye Botswana 1,916 Mathathane Botswana 1,916 Ditshegwane Botswana 1,820 Mabeleapudi Botswana 1,820 Mogapi Botswana 1,820 Mokobeng Botswana 1,820 Molalatau Botswana 1,820 Moroka Botswana 1,820 Mosolotshane Botswana 1,820 Nswazwi Botswana 1,820 Ntlhantlhe Botswana 1,820 Tobane Botswana 1,820 Kazungula Botswana 1,724 Kobojango Botswana 1,724 Lehututu Botswana 1,724

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Mabutsane Botswana 1,724 Majwaneng Botswana 1,724 Matshelagabedi Botswana 1,724 Mosetse Botswana 1,724 Nshakashokwe Botswana 1,724 Salajwe Botswana 1,724 Seronga Botswana 1,724 Tsamaya Botswana 1,724 Mabule Botswana 1,629 Makwate Botswana 1,629 Mapoka Botswana 1,629 Marapong Botswana 1,629 Mmashoro Botswana 1,629 Nokaneng Botswana 1,629 Pandamatenga Botswana 1,629 Pitshane Molopo Botswana 1,629 Sikwane Botswana 1,629 Takatokwane Botswana 1,629 Xhumo Botswana 1,629 Artisia Botswana 1,533 Dagwi Botswana 1,533 Makopong Botswana 1,533 Morope Botswana 1,533 Motokwe Botswana 1,533 Ramokgwebana Botswana 1,533 Sehithwa Botswana 1,533 Sepopa Botswana 1,533 Sese Botswana 1,533 Tshesebe Botswana 1,533 Tshimoyapula Botswana 1,533 Zwenshambe Botswana 1,533 Gootau Botswana 1,437 Kgomokasitwa Botswana 1,437 Matsiloje Botswana 1,437 Mogapinyana Botswana 1,437 Moletemane Botswana 1,437 Moshopha Botswana 1,437 Ncojane Botswana 1,437 Nkoyaphiri Botswana 1,437 Senyawe Botswana 1,437 Themashanga Botswana 1,437 Tsootsha Botswana 1,437 Gaphatshwa Botswana 1,341 Kgagodi Botswana 1,341 Kudumatse Botswana 1,341 Lokgwabe Botswana 1,341 Makuta Botswana 1,341 Marobela Botswana 1,341 Matobo Botswana 1,341 Mohembo West Botswana 1,341 Mokoboxane Botswana 1,341 Moshaneng Botswana 1,341 Motlhabaneng Botswana 1,341

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Nxamasere Botswana 1,341 Pilikwe Botswana 1,341 Seolwane Botswana 1,341 Sesung Botswana 1,341 Siviya Botswana 1,341 Topisi Botswana 1,341 Tsao Botswana 1,341 Kinshasa Democratic Republic Of Congo 5,874,688 Lubumbashi Democratic Republic Of Congo 984,609 Mbuji-Mayi Democratic Republic Of Congo 840,292 Kolwezi Democratic Republic Of Congo 745,638 Kananga Democratic Republic Of Congo 498,880 Kisangani Democratic Republic Of Congo 463,752 Likasi Democratic Republic Of Congo 343,056 Boma Democratic Republic Of Congo 324,886 Tshikapa Democratic Republic Of Congo 308,880 Bukavu Democratic Republic Of Congo 212,669 Matadi Democratic Republic Of Congo 203,670 Kikwit Democratic Republic Of Congo 202,200 Uvira Democratic Republic Of Congo 191,557 Mwene-Ditu Democratic Republic Of Congo 188,443 Mbandaka Democratic Republic Of Congo 187,751 Butembo Democratic Republic Of Congo 138,953 Goma Democratic Republic Of Congo 138,607 Isiro Democratic Republic Of Congo 124,504 Bunia Democratic Republic Of Congo 121,389 Gemena Democratic Republic Of Congo 111,266 Kindu Democratic Republic Of Congo 109,622 Bandundu Democratic Republic Of Congo 107,805 Ilebo Democratic Republic Of Congo 97,423 Kalemie Democratic Republic Of Congo 95,087 Beni Democratic Republic Of Congo 90,934 Gandajika Democratic Republic Of Congo 83,839 Bumba Democratic Republic Of Congo 79,426 Mbanza-Ngungu Democratic Republic Of Congo 78,648 Kipushi Democratic Republic Of Congo 75,792 Kamina Democratic Republic Of Congo 64,372 Lisala Democratic Republic Of Congo 63,939 Lodja Democratic Republic Of Congo 61,689 Binga Democratic Republic Of Congo 54,768 Kabinda Democratic Republic Of Congo 53,297 Kasongo Democratic Republic Of Congo 46,548 Kalima Democratic Republic Of Congo 46,462 Mweka Democratic Republic Of Congo 46,116 Gbadolite Democratic Republic Of Congo 46,029 Bulungu Democratic Republic Of Congo 44,126 Buta Democratic Republic Of Congo 41,876 Basoko Democratic Republic Of Congo 40,059 Lusambo Democratic Republic Of Congo 37,464 Nioki Democratic Republic Of Congo 37,117 Inongo Democratic Republic Of Congo 36,598 Tshela Democratic Republic Of Congo 35,387 Mangai Democratic Republic Of Congo 33,916

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Kenge Democratic Republic Of Congo 33,743 Bukama Democratic Republic Of Congo 33,397 Yangambi Democratic Republic Of Congo 32,618 Manono Democratic Republic Of Congo 32,359 Aketi Democratic Republic Of Congo 32,272 Luebo Democratic Republic Of Congo 32,013 Kambove Democratic Republic Of Congo 31,580 Lubao Democratic Republic Of Congo 30,196 Mushie Democratic Republic Of Congo 30,196 Kabare Democratic Republic Of Congo 29,850 Boende Democratic Republic Of Congo 29,244 Kampene Democratic Republic Of Congo 28,033 Yakoma Democratic Republic Of Congo 27,773 Kongolo Democratic Republic Of Congo 27,514 Yandongi Democratic Republic Of Congo 26,822 Simba Democratic Republic Of Congo 26,648 Titule Democratic Republic Of Congo 26,562 Kutu Democratic Republic Of Congo 26,475 Businga Democratic Republic Of Congo 26,389 Kabalo Democratic Republic Of Congo 25,697 Moba Democratic Republic Of Congo 25,697 Bolobo Democratic Republic Of Congo 25,437 Kasangulu Democratic Republic Of Congo 25,437 Kaniama Democratic Republic Of Congo 25,351 Libenge Democratic Republic Of Congo 24,658 Gwane Democratic Republic Of Congo 24,572 Watsa Democratic Republic Of Congo 22,495 Faradje Democratic Republic Of Congo 22,149 Demba Democratic Republic Of Congo 20,246 Basankusu Democratic Republic Of Congo 19,640 Shinkolobwe Democratic Republic Of Congo 19,640 Kasongo-Lunda Democratic Republic Of Congo 18,256 Idiofa Democratic Republic Of Congo 17,737 Tshilenge Democratic Republic Of Congo 17,650 Mobayi-Mbongo Democratic Republic Of Congo 17,218 Niangara Democratic Republic Of Congo 17,218 Bodalangi Democratic Republic Of Congo 16,439 Bondo Democratic Republic Of Congo 16,352 Kahemba Democratic Republic Of Congo 16,352 Kama Democratic Republic Of Congo 16,179 Itoko Democratic Republic Of Congo 16,006 Wamba Democratic Republic Of Congo 15,920 Yumbi Democratic Republic Of Congo 15,574 Dilolo Democratic Republic Of Congo 15,314 Katako-Kombe Democratic Republic Of Congo 15,228 Lubefu Democratic Republic Of Congo 15,141 Lusanga Democratic Republic Of Congo 15,141 Aba Democratic Republic Of Congo 14,968 Kole Democratic Republic Of Congo 14,622 Mambasa Democratic Republic Of Congo 14,622 Muanda Democratic Republic Of Congo 14,622 Kimpese Democratic Republic Of Congo 14,536 Tshofa Democratic Republic Of Congo 14,016

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Bosobolo Democratic Republic Of Congo 13,238 Mongbwalu Democratic Republic Of Congo 13,065 Bafwasende Democratic Republic Of Congo 12,459 Kazumba Democratic Republic Of Congo 12,459 Kibombo Democratic Republic Of Congo 12,372 Nyunzu Democratic Republic Of Congo 12,372 Gungu Democratic Republic Of Congo 12,286 Makanza Democratic Republic Of Congo 12,199 Madimba Democratic Republic Of Congo 12,113 Kiri Democratic Republic Of Congo 11,940 Zongo Democratic Republic Of Congo 11,853 Ikela Democratic Republic Of Congo 11,680 Ubundu Democratic Republic Of Congo 10,296 Djugu Democratic Republic Of Congo 10,209 Poko Democratic Republic Of Congo 10,209 Banalia Democratic Republic Of Congo 10,036 Sakania Democratic Republic Of Congo 9,950 Le Marinel Democratic Republic Of Congo 8,739 Mwanza Democratic Republic Of Congo 8,479 Malemba-Nkulu Democratic Republic Of Congo 7,614 Lubudi Democratic Republic Of Congo 7,527 Mulongo Democratic Republic Of Congo 7,441 Kikondjo Democratic Republic Of Congo 7,354 Dibaya Democratic Republic Of Congo 4,153 Bongandanga Democratic Republic Of Congo 3,720 Maseru Lesotho 132,168 Mafeteng Lesotho 26,653 Maputsoa Lesotho 24,122 Teyateyaneng Lesotho 21,508 Hlotse Lesotho 17,712 Mohale's Hoek Lesotho 15,519 Quthing Lesotho 11,386 Butha Buthe Lesotho 7,928 Qacha's Nek Lesotho 6,241 Mokhotlong Lesotho 5,651 Thaba-Tseka Lesotho 4,723 Antananarivo Madagascar 1,161,056 Toamasina Madagascar 187,057 Antsirabe Madagascar 167,563 Fianarantsoa Madagascar 150,667 Mahajanga Madagascar 141,755 Toliary Madagascar 106,200 AntsiranìˆAna Madagascar 76,772 Antanifotsy Madagascar 66,561 Ambovombe Madagascar 64,704 Amparafaravola Madagascar 47,159 TaolanìˆAro Madagascar 43,724 Ambatondrazaka Madagascar 39,454 Soavinandriana Madagascar 38,061 Mananara Madagascar 37,690 Nosy Varika Madagascar 37,226 Mahanoro Madagascar 36,483 Soanierana Ivongo Madagascar 35,926

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Morondava Madagascar 35,648 Manakara Madagascar 35,555 Faratsiho Madagascar 35,369 Amboasary Madagascar 34,998 Antalaha Madagascar 34,162 Vavatenina Madagascar 33,791 Ikongo Madagascar 32,491 Sambava Madagascar 31,563 Fandriana Madagascar 31,470 Ambanja Madagascar 30,635 Ambositra Madagascar 30,449 Betioky Madagascar 30,171 Manjakandriana Madagascar 29,985 Marovoay Madagascar 29,799 Tsihombe Madagascar 28,871 Ambalavao Madagascar 28,128 Betafo Madagascar 28,035 Mananjary Madagascar 27,757 Ambatolampy Madagascar 26,829 Moramanga Madagascar 26,736 Ambatofinandrahana Madagascar 26,086 Tsiroanomandidy Madagascar 25,529 Ankazoabo Madagascar 25,158 Ampanihy Madagascar 24,879 Farafangana Madagascar 24,786 Anosibe An'ala Madagascar 24,136 Marolambo Madagascar 23,951 Vangaindrano Madagascar 23,579 Vohibinany Madagascar 23,208 Belon'i Tsiribihina Madagascar 23,115 Antsirambazaha Madagascar 22,651 Beloha Madagascar 22,280 Maroantsetra Madagascar 21,816 Ambato Boina Madagascar 21,444 Sakaraha Madagascar 21,166 Andapa Madagascar 20,794 Arivonimamo Madagascar 20,702 Antsohihy Madagascar 20,330 Miandrivazo Madagascar 19,959 Vondrozo Madagascar 19,959 Fenoarivo Atsinanana Madagascar 19,216 Manandriana Madagascar 19,031 Fenoarivo Madagascar 18,474 Andilamena Madagascar 18,102 Beroroha Madagascar 18,010 Anjozorobe Madagascar 17,917 Ifanadiana Madagascar 17,545 Ihosy Madagascar 16,988 Bealanana Madagascar 16,153 Tsaratanana Madagascar 15,967 Ikalamavony Madagascar 15,596 Ankazobe Madagascar 14,853 Ambilobe Madagascar 14,668

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Ambodifototra Madagascar 10,861 Andevoranto Madagascar 9,562 Blantyre Malawi 520,101 Lilongwe Malawi 474,232 Mzuzu Malawi 94,698 Zomba Malawi 69,729 Karonga Malawi 30,241 Mangochi Malawi 29,408 Kasungu Malawi 28,391 Salima Malawi 22,102 Nkhotakota Malawi 21,085 Nsanje Malawi 18,403 Liwonde Malawi 17,109 Dedza Malawi 16,554 Balaka Malawi 15,629 Rumphi Malawi 15,167 Mzimba Malawi 15,074 Mulanje Malawi 13,687 Mchinji Malawi 12,485 Mponela Malawi 10,820 Chilumba Malawi 10,728 Nkhata Bay Malawi 10,265 Luchenza Malawi 9,618 Monkey Bay Malawi 9,525 Mwanza Malawi 8,785 Ntcheu Malawi 8,785 Chitipa Malawi 7,768 Chikwawa Malawi 7,398 Ntchisi Malawi 5,826 Thyolo Malawi 5,826 Livingstonia Malawi 5,179 Dowa Malawi 4,901 Phalombe Malawi 2,774 Chipoka Malawi 2,404 Chiradzulu Malawi 1,665 Machinga Malawi 1,387 Port Louis Mauritius 140,310 Beau Bassin-Rose Hill Mauritius 108,164 Vascoas-Phoenix Mauritius 102,008 Curepipe Mauritius 78,070 Quatre Bornes Mauritius 74,748 Triolet Mauritius 21,594 Goodlands Mauritius 19,933 Bel Air Mauritius 17,295 Central Flacq Mauritius 16,708 Le Hochet Mauritius 16,611 Saint Pierre Mauritius 14,950 Mahebourg Mauritius 14,852 Baie Du Tombeau Mauritius 14,266 Bambous Mauritius 12,604 Rose Belle Mauritius 11,823 Chemin Grenier Mauritius 11,725 Surinam Mauritius 11,725

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Grand Baie Mauritius 11,627 Pailles Mauritius 11,432 Plaine Magnien Mauritius 11,041 Riviere Du Rempart Mauritius 10,553 Terre Rouge Mauritius 10,455 New Grove Mauritius 10,064 Lalmatie Mauritius 9,673 Petit Raffray Mauritius 9,185 Riviere Des Anguilles Mauritius 8,892 Grand Bois Mauritius 8,208 Pointe Aux Piments Mauritius 8,208 Montagne Blanche Mauritius 7,914 Moka Mauritius 7,817 Beau Vallon Mauritius 7,719 L'escalier Mauritius 7,719 Pamplemousse Mauritius 7,719 Dagotiere Mauritius 7,426 Plaines Des Papayes Mauritius 7,328 Bon Accueil Mauritius 7,230 Nouvelle France Mauritius 7,035 Grand Gaube Mauritius 6,937 Medine-Camp De Masque Mauritius 6,937 Long Mountain Mauritius 6,644 Brisee Verdiere Mauritius 6,449 Laventure Mauritius 6,351 Poste De Flacq Mauritius 6,253 Quatre Cocos Mauritius 6,253 Quartier Militaire Mauritius 6,156 Ecroignard Mauritius 6,058 Port Mathurin Mauritius 5,960 Trou D'eau Douce Mauritius 5,960 Morcellement Saint Andre Mauritius 5,569 Fond Du Sac Mauritius 5,374 Poudre D'or Mauritius 5,374 Roches Noires Mauritius 5,374 Cap Malheureux Mauritius 5,276 Sebastopol Mauritius 5,276 Chamouny Mauritius 5,179 Calebasses Mauritius 4,983 Camp Diable Mauritius 4,983 Piton Mauritius 4,983 Midlands Mauritius 4,788 Mare D'albert Mauritius 4,690 D'epinay Mauritius 4,495 Belle Vue Maurel Mauritius 4,397 Petite Riviere Mauritius 4,397 Richelieu Mauritius 4,397 Camp Ithier Mauritius 4,299 Notre Dame Mauritius 4,201 Camp De Masque Pave Mauritius 4,104 Trois Boutiques Mauritius 4,006 Union Park Mauritius 4,006 Souillac Mauritius 3,908

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Tamarin Mauritius 3,908 Lataniers-Mont Lubin Mauritius 3,811 Plaine Des Roches Mauritius 3,811 Bois Cheri Mauritius 3,615 Petit Gabriel Mauritius 3,615 Saint Hubert Mauritius 3,615 Olivia Mauritius 3,518 The Vale Mauritius 3,518 Cottage Mauritius 3,420 Roche Terre Mauritius 3,420 Quatre Soeurs Mauritius 3,322 Albion Mauritius 3,224 Saint Julien D'hotman Mauritius 3,224 Riviere Des Creoles Mauritius 3,127 Providence Mauritius 3,029 Old Grand Port Mauritius 2,931 Riviere Cocos Mauritius 2,931 Dubreuil Mauritius 2,834 Gros Cailloux Mauritius 2,834 Mangues-Quatre Vents Mauritius 2,834 Plaine Corail-La Fouche Corail Mauritius 2,834 Ripailles Mauritius 2,834 Port Sud-Est Mauritius 2,736 Saint Julien Mauritius 2,736 Arsenal Mauritius 2,638 Creve Coeur Mauritius 2,638 Mare Tabac Mauritius 2,638 Oyster Bay Mauritius 2,638 Amaury Mauritius 2,540 Camp De Masque Mauritius 2,540 Cascavelle Mauritius 2,540 Queen Victoria Mauritius 2,540 Bel Ombre Mauritius 2,443 L'avenir Mauritius 2,443 Amitie-Gokhoola Mauritius 2,247 Baie Du Cap Mauritius 2,247 Riviere Du Poste Mauritius 2,247 Villebague Mauritius 2,247 Benares Mauritius 2,150 Grand River South East Mauritius 2,150 Grand Sable Mauritius 2,150 Camp Thorel Mauritius 2,052 Clemencia Mauritius 2,052 Esperance Trebuchet Mauritius 2,052 Flic En Flac Mauritius 2,052 Poudre D'or Hamlet Mauritius 2,052 Roche Bon Dieu-Trefles Mauritius 2,052 Coromandel-Graviers Mauritius 1,954 Grande Riviere Noire Mauritius 1,954 Mare La Chaux Mauritius 1,954 Maputo Mozambique 1,060,424 Matola Mozambique 483,997 Beira Mozambique 452,940

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Nampula Mozambique 345,726 Chimoio Mozambique 194,994 Nacala Mozambique 180,395 Quelimane Mozambique 168,120 Tete Mozambique 115,118 Xai-Xai Mozambique 113,351 Garue Mozambique 111,305 Maxixe Mozambique 106,656 Lichinga Mozambique 97,729 Pemba Mozambique 96,799 Dondo Mozambique 70,019 Angoche Mozambique 66,393 Cuamba Mozambique 65,184 Montepuez Mozambique 64,347 Mocuba Mozambique 61,371 Inhambane Mozambique 59,419 Chokwe Mozambique 56,722 Chibuto Mozambique 52,631 Mocambique Mozambique 48,353 Manica Mozambique 22,689 Quissico Mozambique 19,620 Lumbo Mozambique 17,110 Nazombe Mozambique 16,645 Inharrime Mozambique 16,087 Panda Mozambique 13,576 Macia Mozambique 12,925 Marrupa Mozambique 12,181 Chongoene Mozambique 10,694 Homoine Mozambique 10,136 Manhica Mozambique 10,136 Bela Vista Mozambique 10,043 Guija Mozambique 9,950 Magude Mozambique 9,485 Zumbo Mozambique 9,206 Jangamo Mozambique 9,020 Maniamba Mozambique 9,020 Marracuene Mozambique 9,020 Moamba Mozambique 9,020 Mandimba Mozambique 8,927 Namaacha Mozambique 8,927 Chidenguele Mozambique 8,741 Manjacaze Mozambique 8,648 Windhoek Namibia 245,334 Rundu Namibia 46,675 Walvis Bay Namibia 44,146 Oshakati Namibia 29,658 Swakopmund Namibia 26,352 Katima Mulilo Namibia 23,824 Rehoboth Namibia 22,365 Otjiwarongo Namibia 20,615 Grootfontein Namibia 17,309 Keetmanshoop Namibia 16,336 Okahandja Namibia 14,878

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Gobabis Namibia 14,586 Tsumeb Namibia 13,808 Luderitz Namibia 12,544 Mariental Namibia 10,988 Ondangwa Namibia 10,696 Khorixas Namibia 10,599 Oranjemund Namibia 10,016 Bethanien Namibia 9,043 Ongwediva Namibia 8,363 Omaruru Namibia 6,515 Karasburg Namibia 6,321 Outjo Namibia 6,321 Arandis Namibia 5,834 Opuwo Namibia 5,737 Karibib Namibia 5,543 Okakarara Namibia 5,056 Otavi Namibia 4,765 Usakos Namibia 4,570 Otjimbingwe Namibia 3,792 Aranos Namibia 3,501 Eenhana Namibia 3,403 Ongandjera Namibia 3,014 Outapi Namibia 2,820 Oshikango Namibia 2,723 Maltahohe Namibia 2,625 Warmbad Namibia 2,431 Henties Bay Namibia 2,139 Okombahe Namibia 2,139 Victoria Seychelles 26,974 Anse Royal Seychelles 3,914 Cascade Seychelles 2,539 Takamaka Seychelles 2,327 Anse Boileau Seychelles 2,116 Cape Town South Africa 2,901,473 Durban South Africa 2,461,210 Johannesburg South Africa 1,920,800 Pretoria South Africa 1,432,992 Soweto South Africa 1,424,630 Port Elizabeth South Africa 754,319 Benoni South Africa 474,196 Vereeniging South Africa 449,985 Pietermaritzburg South Africa 445,027 East London South Africa 411,774 Tembisa South Africa 366,172 Bloemfontein South Africa 339,336 Boksburg South Africa 338,461 Vanderbijlpark South Africa 328,641 Newcastle South Africa 300,833 Krugersdorp South Africa 264,857 Welkom South Africa 239,286 Brakpan South Africa 222,367 Carltonville South Africa 214,297 Springs South Africa 208,658

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Uitenhage South Africa 193,295 Witbank South Africa 193,004 Alberton South Africa 191,934 Botshabelo South Africa 180,753 Paarl South Africa 168,599 Midrand South Africa 164,029 Kimberley South Africa 161,501 Klerksdorp South Africa 158,195 Verwoerdburg South Africa 148,666 Westonaria South Africa 148,666 Somerset West South Africa 135,151 Bisho South Africa 134,082 Randfontein South Africa 127,373 Middelburg South Africa 120,275 Rustenburg South Africa 119,594 Nigel South Africa 119,011 Potchefstroom South Africa 118,719 George South Africa 113,080 Nelspruit South Africa 109,288 Phalaborwa South Africa 106,079 Emnambithi South Africa 103,551 Pietersburg South Africa 101,120 Potgietersrus South Africa 98,009 Epumalanga South Africa 94,995 Mabopane South Africa 93,925 Worcester South Africa 92,370 Embalenhle South Africa 89,939 Kroonstad South Africa 88,286 Richards Bay South Africa 84,397 Orkney South Africa 84,299 Louis Trichardt South Africa 84,202 Umtata South Africa 76,813 Sasolburg South Africa 75,160 Stellenbosch South Africa 71,659 Garankuwa South Africa 66,312 Oudtshoorn South Africa 64,367 Standerton South Africa 63,589 Lichtenburg South Africa 63,492 Grahamstown South Africa 62,520 Virginia South Africa 61,936 Vryheid South Africa 61,839 Stilfontein South Africa 59,992 Atlantis South Africa 59,019 Bethlehem South Africa 58,144 Kutlwanong South Africa 57,950 Brits South Africa 57,269 Heidelberg South Africa 54,255 Queenstown South Africa 54,255 Saldanha South Africa 53,574 Mosselbay South Africa 52,408 Upington South Africa 52,213 Mmabatho South Africa 49,491 Bethal South Africa 49,393

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Temba South Africa 45,504 Parys South Africa 44,143 Ermelo South Africa 43,365 Thohoyandou South Africa 42,684 Phuthaditjhaba South Africa 42,587 Delmas South Africa 41,809 Esikhawini South Africa 38,212 Vryburg South Africa 38,212 Thaba Nchu South Africa 37,726 Kgotsong South Africa 37,142 Knysna South Africa 37,045 Warmbad South Africa 36,170 Ekangala South Africa 35,684 Stanger South Africa 35,684 Beaufort-West South Africa 34,420 Graaff-Reinet South Africa 34,420 Siyabuswa South Africa 34,420 Harrismith South Africa 34,225 Port Shepstone South Africa 33,739 Butterworth South Africa 33,545 Margate South Africa 33,156 Mondlo South Africa 32,961 Piet Retief South Africa 31,795 Fochville South Africa 31,308 Richmond South Africa 31,211 Wembezi South Africa 29,947 Schweizer Reneke South Africa 29,461 Cradock South Africa 29,364 Secunda South Africa 29,364 Dundee South Africa 28,975 Barberton South Africa 28,683 Empangeni South Africa 28,683 Ceres South Africa 27,225 Malmesbury South Africa 26,252 Bronkhorstspruit South Africa 25,961 Lulekani South Africa 25,863 Phola South Africa 25,863 Fort Beaufort South Africa 25,669 De Aar South Africa 25,572 Lebohang South Africa 24,988 Wolmaranstad South Africa 24,794 Heilbron South Africa 24,599 Lady Frere South Africa 24,502 Lebowakgomo South Africa 24,502 Kokstad South Africa 24,405 Viljoenskroon South Africa 24,405 Balfour South Africa 24,113 Cullinan South Africa 24,113 Hermanus South Africa 24,016 Duiwelskloof South Africa 23,822 Wesselsbron South Africa 23,822 Volksrust South Africa 23,335 Scottsburgh South Africa 23,044

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Aliwal North South Africa 22,655 Giyani South Africa 22,558 Hennenman South Africa 22,266 Robertson South Africa 21,099 Pampierstad South Africa 21,002 Theunissen South Africa 20,710 Lydenburg South Africa 20,613 Ekuphumleni South Africa 20,516 Mpophomeni South Africa 20,516 Frankfort South Africa 20,321 Stutterheim South Africa 20,224 Nylstroom South Africa 19,932 Allanridge South Africa 19,738 Bulfontein South Africa 19,738 Senekal South Africa 19,641 Umkomaas South Africa 19,641 Messina South Africa 19,543 Nkowakowa South Africa 19,349 Grabouw South Africa 19,252 Kruisfontein South Africa 18,571 Plettenberg Bay South Africa 18,571 Ezibeleni South Africa 17,891 Middelburg South Africa 17,696 Howick South Africa 17,599 Port Alfred South Africa 17,502 Warrenton South Africa 17,404 Ncotshane South Africa 17,307 Postmasburg South Africa 17,210 Zeerust South Africa 17,113 Christiana South Africa 16,918 Ladybrand South Africa 16,821 Ballitoville South Africa 16,627 Bloemhof South Africa 16,529 Tzaneen South Africa 16,432 Reitz South Africa 16,238 Somerset East South Africa 15,751 Randvaal South Africa 15,168 Ventersdorp South Africa 15,168 Witrivier South Africa 15,168 Hendrina South Africa 15,071 Ellisras South Africa 14,876 Ulundi South Africa 14,779 Eshowe South Africa 14,293 Kriel South Africa 14,293 Vrede South Africa 14,293 Bredasdorp South Africa 14,196 Sundumbili South Africa 14,196 Vredendal South Africa 14,099 Ekuvukeni South Africa 13,807 Swellendam South Africa 13,710 Empuluzi South Africa 13,418 Greytown South Africa 13,418 Needscamp South Africa 13,321

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Jan Kempdorp South Africa 13,126 Letsopa South Africa 13,126 Glencoe South Africa 13,029 Hoopstad South Africa 12,348 Burgersdorp South Africa 12,251 Mankweng South Africa 12,154 Zastron South Africa 12,154 Clocolan South Africa 12,057 Colesberg South Africa 12,057 Deneysville South Africa 12,057 Adelaide South Africa 11,959 Breyten South Africa 11,862 Brandfort South Africa 11,765 Whittlesea South Africa 11,765 Koster South Africa 11,668 Elliot South Africa 11,570 Jeffreys Bay South Africa 11,473 Barkly West South Africa 11,279 Belfast South Africa 11,279 Thulamahashe South Africa 11,279 Koppies South Africa 11,182 Mogwase South Africa 11,182 Villiers South Africa 10,987 Prieska South Africa 10,890 Winburg South Africa 10,793 Ilinge South Africa 10,598 Marquard South Africa 10,598 Ventersburg South Africa 10,404 Vredefort South Africa 10,404 Springbok South Africa 10,112 Thabazimbi South Africa 10,015 Kirkwood South Africa 9,918 Koffiefontein South Africa 9,918 Mooreesburg South Africa 9,918 Danielskuil South Africa 9,820 Molteno South Africa 9,820 Mooi River South Africa 9,723 Ritchie South Africa 9,723 Alice South Africa 9,529 Dordrecht South Africa 8,945 Kathu South Africa 8,945 Wepener South Africa 8,945 Kuruman South Africa 8,848 Paulpietersburg South Africa 8,265 Heidelberg South Africa 8,070 Victoria-West South Africa 7,973 Calvinia South Africa 7,876 Vredenburg South Africa 7,487 Inyala South Africa 7,390 Barkly East South Africa 7,292 Ixopo South Africa 7,195 Velddrif South Africa 7,098 Willowmore South Africa 6,903

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Keimoes South Africa 6,709 Hertzogville South Africa 6,223 Mandeni South Africa 5,931 Umzimvubu South Africa 5,834 Carnarvon South Africa 5,639 Matatiele South Africa 5,639 Komga South Africa 5,542 Tarkastad South Africa 4,959 Manzini Swaziland 87,492 Mbabane Swaziland 64,453 Matsapha Swaziland 19,839 Big Bend Swaziland 10,422 Mhlume Swaziland 8,502 Malkerns Swaziland 8,228 Nhlangano Swaziland 7,222 Hluti Swaziland 6,491 Simunye Swaziland 6,217 Pigg's Peak Swaziland 5,120 Siteki Swaziland 4,663 Ngomane Swaziland 4,297 Lobamba Swaziland 4,023 Vuvulane Swaziland 4,023 Kwaluseni Swaziland 3,017 Mondi Swaziland 3,017 Bhunya Swaziland 2,926 Mhlambanyatsi Swaziland 2,834 Thabankulu Swaziland 2,834 Bulembu Swaziland 2,743 Tshaneni Swaziland 2,468 Mpaka Swaziland 2,377 Hlatikulu Swaziland 2,286 Kubuta Swaziland 1,920 Sidvokodvo Swaziland 1,737 Ezulwini Swaziland 1,554 Lavumisa Swaziland 1,280 Mankayane Swaziland 1,189 Nsoko Swaziland 1,097 Ngwenya Swaziland 914 Dar Es Salaam Tanzania 2,419,179 Mwanza Tanzania 381,544 Zanzibar Tanzania 354,951 Arusha Tanzania 285,181 Mbeya Tanzania 258,874 Morogoro Tanzania 223,227 Tanga Tanzania 210,550 Dodoma Tanzania 160,605 Kigoma Tanzania 146,117 Moshi Tanzania 145,545 Tabora Tanzania 136,395 Songea Tanzania 109,707 Musoma Tanzania 109,135 Iringa Tanzania 107,610 Uvinza Tanzania 106,466

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Katumba Tanzania 100,080 Shinyanga Tanzania 93,694 Mtwara Tanzania 93,408 Kilosa Tanzania 88,833 Ushirombo Tanzania 88,547 Sumbawanga Tanzania 81,017 Bagamoyo Tanzania 71,867 Bukoba Tanzania 62,145 Mpanda Tanzania 60,811 Singida Tanzania 58,618 Uyovu Tanzania 56,712 Kalangalala Tanzania 52,900 Makambako Tanzania 51,470 Mishoma Tanzania 50,517 Sengerama Tanzania 50,231 Buseresere Tanzania 49,564 Mererani Tanzania 48,420 Bunda Tanzania 46,609 Katoro Tanzania 46,418 Ifakara Tanzania 46,037 Utengule Usongwe Tanzania 44,512 Siha Kati Tanzania 42,796 Njombe Tanzania 42,701 Lindi Tanzania 41,938 Nkome Tanzania 39,270 Kiranyi Tanzania 39,174 Nkololo Tanzania 39,079 Vwawa Tanzania 38,126 Gairo Tanzania 35,934 Kidadu Tanzania 35,552 Nguruka Tanzania 35,171 Tunduma Tanzania 34,790 Masasi Tanzania 34,504 Korogwe Tanzania 34,409 Kidodi Tanzania 34,123 Kasulu Tanzania 33,932 Mafinga Tanzania 33,932 Newala Tanzania 33,646 Isagehe Tanzania 33,360 Mikindani Tanzania 33,265 Missungwi Tanzania 33,265 Mlimba Tanzania 33,169 Igunga Tanzania 33,074 Chalinze Tanzania 32,788 Kahama Tanzania 32,598 Lusaka Zambia 1,210,941 Ndola Zambia 418,345 Kitwe Zambia 406,047 Kabwe Zambia 197,374 Chingola Zambia 164,578 Mufulira Zambia 136,582 Luanshya Zambia 129,083 Livingstone Zambia 108,886

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Kasama Zambia 82,889 Chipata Zambia 81,589 Chililabombwe Zambia 60,892 Kalulushi Zambia 58,892 Mazabuka Zambia 52,593 Kafue Zambia 51,193 Mongu Zambia 49,493 Mansa Zambia 45,794 Choma Zambia 45,094 Kansanshi Zambia 37,995 Kapiri Mposhi Zambia 30,396 Mpika Zambia 28,896 Monze Zambia 27,496 Nchelenge Zambia 23,097 Kawambwa Zambia 19,997 Samfya Zambia 19,697 Mbala Zambia 18,898 Mumbwa Zambia 17,798 Petauke Zambia 16,298 Sesheke Zambia 15,498 Siavonga Zambia 14,598 Chambishi Zambia 14,498 Kaoma Zambia 13,798 Maamba Zambia 12,898 Chinsali Zambia 12,798 Isoka Zambia 12,798 Kalomo Zambia 12,298 Mwinilunga Zambia 11,998 Mkushi Zambia 11,798 Mpongwe Zambia 11,798 Katete Zambia 11,598 Sinazongwe Zambia 11,598 Nakambala Zambia 10,999 Mwanzakombe Zambia 10,799 Nakonde Zambia 10,399 Senanga Zambia 10,299 Chilanga Zambia 10,199 Lundazi Zambia 10,199 Serenje Zambia 9,599 Kalabo Zambia 8,399 Limulunga Zambia 8,399 Mpulungu Zambia 8,399 Itezhi-Tezhi Zambia 7,699 Zambezi Zambia 7,499 Kalengwa Zambia 7,299 Mungwi Zambia 6,699 Kabompo Zambia 6,499 Luwingu Zambia 5,999 Mufumbwe Zambia 5,999 Chongwe Zambia 5,799 Kasempa Zambia 5,499 Namwala Zambia 4,499 Harare Zimbabwe 2,265,437

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Bulawayo Zimbabwe 1,150,485 Chitungwiza Zimbabwe 485,778 Mutare Zimbabwe 223,862 Gweru Zimbabwe 180,533 Kadoma Zimbabwe 126,431 Masvingo Zimbabwe 95,482 Kwekwe Zimbabwe 93,419 Marondera Zimbabwe 83,790 Zvishavane Zimbabwe 83,676 Chinhoyi Zimbabwe 69,806 Hwange Zimbabwe 67,285 Chegutu Zimbabwe 46,079 Redcliffe Zimbabwe 41,494 Kariba Zimbabwe 39,889 Bindura Zimbabwe 30,490 Victoria Falls Zimbabwe 27,739 Sakubva Zimbabwe 27,051 Norton Zimbabwe 26,593 Karoi Zimbabwe 23,957 Rusape Zimbabwe 23,727 Shurugwi Zimbabwe 22,008 Chiredzi Zimbabwe 16,735 Plumtree Zimbabwe 15,933 Mount Darwin Zimbabwe 15,016 Chipinge Zimbabwe 14,213 Gwanda Zimbabwe 14,099 Tuli Zimbabwe 12,723 Chimanimani Zimbabwe 11,692 Nyanga Zimbabwe 11,692 Chivhu Zimbabwe 10,431 Mutoko Zimbabwe 10,316 Gaths Zimbabwe 9,972 West Nicholson Zimbabwe 9,285 Mvuma Zimbabwe 8,368 Beitbridge Zimbabwe 6,075

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Appendix G Total impact per airport over the 50 year period less airport/navigational infrastructure costs (R Millions)

Location 5 Years 10 Years 15 Years 20 Years 25 Years 30 Years 35 Years 40 Years 45 Years 50 Years TOTAL Cabinda -3.41 -3.41 -3.41 -1555.07 -380.12 -2985.60 -2369.01 -4391.83 -1576.26 -4464.42 -17732.55 Catumbela -3.03 -3.03 -3.03 786.63 701.61 -883.63 -935.52 -3005.74 -325.72 -3002.72 -6674.16 Dundo 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Huambo 7.85 7.85 17.34 -577.23 60.07 -2373.49 -2945.19 -2697.68 -2573.37 -2779.25 -13853.10 Kuito 8.63 8.63 8.63 -424.35 684.54 -2371.07 -2098.33 -3403.71 -1589.07 -3483.26 -12659.37 Luanda 2034.37 2034.37 2038.57 2242.34 3053.54 983.09 2508.28 1497.87 2421.35 1522.48 20336.26 Lubango 683.08 683.08 683.08 1128.09 2237.11 -804.10 -445.62 -1665.40 153.34 -1741.87 910.80 Luena 784.40 784.40 784.40 2537.35 2772.99 1563.33 1487.84 -1026.67 1152.78 -852.84 9988.00 Malanje 335.97 335.97 335.97 1280.29 2597.23 -468.04 -8.15 -1676.01 560.87 -1754.25 1539.83 Menongue 813.28 813.28 813.28 2418.22 3866.02 1011.59 1575.99 -997.29 2226.29 -1045.76 11494.90 Namibe 739.40 739.40 1234.06 3778.53 4658.83 2051.70 1704.46 1776.21 2194.78 1699.74 20577.13 Ondjiva 936.77 936.77 936.77 3738.74 5643.66 3426.84 3971.10 955.87 4540.65 979.89 26067.06 Saurimo 800.76 800.76 800.76 5897.83 7118.67 4605.51 4851.32 2402.59 5534.29 2322.46 35134.95 Soyo 298.54 298.54 298.54 6448.73 8292.71 5855.36 6478.95 4211.64 7253.61 4164.63 43601.25 Uíge 0.00 0.00 216.68 4945.03 6660.87 3987.02 4795.89 2232.08 5270.35 2224.04 30331.95 Francistown 7.13 7.13 -157.54 -776.65 -141.47 14158.03 16080.64 16010.69 15984.09 16021.93 77193.97 Gaborone 429.29 429.29 429.29 466.31 2756.95 21836.15 21780.30 22453.88 21685.41 22469.22 114736.08 Kasane 779.36 779.36 1114.65 1274.34 1138.14 3261.45 10578.56 14905.53 10887.11 14814.82 59533.32 Maun 1431.80 1431.80 1431.80 1513.70 2403.98 12533.81 14244.64 14578.59 14330.77 14485.71 78386.60 Bukavu 0.00 0.00 0.00 0.00 22.27 -1231.81 5008.61 21032.85 23867.52 22425.68 71125.11 Buta-Zega 0.00 0.00 0.00 0.00 18.90 -800.48 4445.29 17524.50 24589.82 26410.83 72188.86 Gbadolite 16.03 16.03 16.03 16.03 16.03 -1051.33 5824.68 20717.28 26128.99 26933.68 78633.44 Gemena 0.00 0.00 0.00 0.00 13.47 -356.26 7768.70 22958.63 26508.32 24723.14 81616.00 Goma 0.00 0.00 0.00 0.00 23.48 939.59 8271.83 24135.17 28072.84 25685.91 87128.82 Isiro-Matari 0.00 0.00 0.00 0.00 23.61 1029.36 9439.06 27545.71 31309.00 29368.43 98715.18 Kananga 0.00 0.00 0.00 0.00 26.42 3247.67 10757.33 18278.27 22661.60 18319.06 73290.35 Kindu 0.00 0.00 0.00 0.00 16.96 1860.49 8620.85 21789.45 25073.49 23130.04 80491.27 Kinshasa 1036.57 1036.57 1036.57 1036.57 8816.88 15585.23 26360.21 27478.42 27832.52 27404.36 137623.91 Kisangani 1059.34 1059.34 1059.34 1059.34 1096.60 5374.53 13754.03 29045.85 31120.41 29147.73 113776.53 Lubumbashi 1401.39 1401.39 1401.39 1401.39 3513.78 13948.75 22247.96 29247.69 31956.38 29231.47 135751.60

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Mbandaka 0.00 0.00 0.00 0.00 1886.95 6517.25 13732.70 26030.37 29799.95 26331.77 104299.00 Mbuji-Mayi 796.11 796.11 796.11 796.11 2167.66 7376.35 15821.63 22395.55 27079.87 22431.27 100456.76 Maseru -4.62 -4.62 -4.62 -4.62 1.12 2703.74 13514.55 34730.50 50640.41 49578.30 151150.16 Antanànarìvo 26.00 26.00 26.00 26.00 249.97 14290.87 54041.04 77559.25 77367.97 77479.66 301092.75 Mahajanga 309.03 309.03 309.03 309.03 373.12 5371.20 21127.29 52829.00 67420.96 66531.44 214889.13 Nosy Be 0.00 0.00 0.00 0.00 623.64 99.78 14787.69 50160.31 69519.63 68093.99 203285.05 Toamasina 164.64 164.64 164.64 164.64 1192.46 7777.80 42703.68 71554.37 76224.14 76396.59 276507.60 Toliara 565.42 565.42 565.42 565.42 2738.42 6124.57 19340.62 49468.13 69202.73 67162.89 216299.03 Blantyre 36.33 36.33 36.33 36.33 108.07 4062.34 22534.33 46544.15 49257.69 49829.11 172481.01 Lilongwe 169.25 169.25 169.25 169.25 267.18 4536.03 25507.92 45154.77 50486.87 48124.81 174754.57 Port Louis 1265.37 1265.37 1265.37 1438.94 15548.12 84419.78 121950.90 122102.56 121872.83 122134.97 593264.22 Beira 15.88 15.88 15.88 15.88 175.83 5358.12 30068.20 51392.45 54724.95 55133.79 196916.86 Chimoio 0.00 0.00 0.00 10.79 -340.17 2914.28 11695.73 34957.00 50340.81 47596.54 147174.97 Cuamba 0.00 0.00 0.00 0.00 525.75 -213.44 6141.83 31797.32 50863.46 48643.72 137758.65 Lichinga 14.29 14.29 14.29 14.29 1002.50 2011.79 12167.71 38209.56 51652.98 48946.13 154047.81 Maputo 1986.45 1986.45 1986.45 2662.00 3899.75 12546.66 44782.34 69101.47 68832.98 69017.50 276802.06 Moçimboa da Praia 1587.63 1587.63 1587.63 1587.63 2553.51 3648.92 11386.06 37976.22 60575.29 59930.55 182421.06 Mueda 0.00 0.00 0.00 0.00 2428.66 3395.27 10716.64 36354.23 57121.00 57704.57 167720.35 Nampula 2011.91 2011.91 2011.91 2011.91 4815.73 11478.20 37113.11 59868.76 64279.95 63460.16 249063.56 Tete 1624.01 1624.01 1624.01 1624.01 2455.77 6949.10 14089.50 38751.64 53181.07 50177.64 172100.75 Grootfontein 0.00 0.00 -4.18 48.01 176.90 5282.55 32235.21 63212.93 62891.32 63133.15 226975.89 Karabib 0.00 0.00 0.00 237.03 -303.33 3765.55 13720.43 48537.65 67146.98 64556.87 197661.18 Katima Mulilo 0.00 0.00 15.17 798.92 925.91 4694.36 28177.42 55373.46 56333.15 55288.43 201606.82 Keetmanshoop 0.00 0.00 6.13 1215.27 1452.25 7199.55 36821.76 77893.59 79110.54 77818.75 281517.84 Mariental 0.00 0.00 0.00 1015.76 1216.69 5698.82 25077.46 66502.11 72718.36 70530.68 242759.88 Ondangwa 0.00 0.00 7.54 2104.58 2432.52 7831.16 29422.19 60570.18 65170.77 63889.69 231428.64 Rundu 0.00 0.00 8.68 2450.58 2587.75 6860.17 32837.05 61098.66 61393.78 61016.42 228253.09 Windhoek 3617.00 3617.00 6357.30 6658.80 10827.12 36606.53 74693.33 82555.89 79033.03 82469.88 386435.89 Seychelles 102.46 102.46 102.46 236.68 10266.94 60259.99 140264.25 161552.92 159863.16 161479.56 694230.88 Bisho 38.15 -1647.26 179.89 -1647.26 12825.12 64464.75 112410.19 108321.27 112325.13 108345.44 515615.41 Bloemfontein -280.00 -1292.03 325.47 972.41 17467.61 69399.41 99550.96 94970.10 99457.88 94990.75 475562.55 Cape Town 17212.70 17396.75 17396.75 21759.01 74988.69 135447.41 138013.11 135358.67 138045.44 135358.67 830977.21 Durban 2769.71 2455.64 2883.35 14698.58 62987.35 111209.99 110772.43 111110.68 110794.61 111110.68 640793.03 George 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Lanseria 15263.41 17662.18 15318.49 19411.69 48125.01 88453.01 90511.29 93564.91 90528.67 93564.91 572403.57

Impact of the Yamoussoukro Decision: 12th April 2010 - report prepared by Graham Muller Associates Department of Transport P a g e | 235

Johannesburg 2144.65 3453.98 3453.98 15075.88 66228.86 101775.09 101775.09 101793.12 101793.12 101793.12 599286.89 Kimberley 1489.32 1326.70 2899.43 1326.70 16027.41 63351.65 99702.98 95326.13 99612.05 95346.67 476409.03 Mafikeng 527.70 2007.42 4324.18 2007.42 13526.42 48925.35 88576.40 83824.97 88483.57 83841.70 416045.12 Nelspruit 908.73 3759.50 6298.77 3759.50 18700.07 62309.05 95784.23 90750.70 95688.43 90766.44 468725.43 Polokwane 300.68 4036.25 6572.51 4036.25 15491.01 50548.42 86533.32 81735.57 86437.42 81748.89 417440.32 Port Elizabeth 1088.46 7440.16 9094.35 15217.50 51391.24 108832.21 132010.30 129465.13 131921.00 129492.81 715953.16 Pilanesberg 0.00 3579.72 5873.56 3579.72 14968.05 47145.88 87800.81 83642.19 87707.22 83657.50 417954.66 Umtata 1372.29 5411.66 7719.39 5411.66 19750.05 63165.63 113296.58 109882.02 113210.13 109904.05 549123.46 Upington 1308.87 8212.50 10349.20 8212.50 21439.74 57166.35 105055.27 102400.43 104968.74 102421.96 521535.57 Welkom 0.00 4509.04 6874.97 4509.04 21166.99 66837.52 100729.91 95714.36 100636.52 95733.63 496711.98 Manzini 510.17 510.17 510.17 510.17 2064.23 14215.41 47651.11 81765.32 85462.82 86061.53 319261.09 Dar-Es-Salaam 3332.27 3332.27 3332.27 5570.79 29180.71 64818.11 119827.06 134255.85 133478.46 134166.97 631294.77 Dodoma 345.40 345.40 345.40 91.25 4192.22 34671.37 64264.35 103795.05 115272.77 112703.35 436026.56 Kilimanjaro -3.66 -3.66 -3.66 767.50 14710.11 52384.64 110811.12 134074.65 133405.28 133992.14 580134.45 Mtwara 356.83 356.83 356.83 1116.95 3008.64 33636.63 63939.98 104318.89 117167.73 114583.95 438843.27 Mwanza 3163.74 3163.74 3163.74 3692.37 15924.03 53018.10 101985.22 128784.99 129744.46 128703.55 571343.95 Zanzibar 642.27 642.27 642.27 1301.20 13689.13 48691.20 99145.39 127719.37 128165.44 127636.67 548275.21 Kitwe -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -770.78 Livingstone 2525.99 2525.99 2525.99 2536.90 4640.43 21610.36 54967.69 86976.14 86805.54 86976.14 352091.17 Lusaka 2428.44 2428.44 2428.44 3523.06 21561.07 44754.28 82799.13 96355.77 94773.22 96355.77 447407.62 Mfuwe 0.00 0.00 0.00 0.00 0.00 0.00 882.18 5101.67 19585.42 61253.02 86822.29 Ndola 231.69 231.69 231.69 800.19 9881.81 34333.10 77186.75 94157.68 91932.11 94157.68 403144.39 Bulawayo 519.34 569.36 519.34 569.36 953.23 12563.28 32803.83 67823.72 85170.24 82798.67 284290.37 Harare 6022.29 6022.29 6022.29 6022.29 9762.06 25050.44 53280.88 83853.89 91076.30 88592.52 375705.24 Hwange 997.51 997.51 997.51 997.51 997.51 3934.91 16905.05 45261.05 73228.30 77412.33 221729.21 Victoria Falls 728.39 728.39 728.39 728.39 728.39 4057.69 18915.69 40772.00 72817.74 77916.00 218121.07 TOTAL 93752.97 127970.55 152841.86 211310.85 746270.63 2020195.17 3668038.46 4848948.65 5310977.47 5240560.13 22420866.74

Impact of the Yamoussoukro Decision: 12th April 2010 - report prepared by Graham Muller Associates