The 2016-2021 Outlook for Aircraft Maintenance, Repair, and Overhaul (MRO) Services in Africa

 Published On: Jul, 2013 |    No of Pages: 64 |  Published By: Icon Group International, Inc | Format: PDF
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This econometric study covers the outlook for aircraft maintenance, repair, and overhaul (mro) services in Africa. For each year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the country in question (in millions of U.S. dollars), the percent share the country is of the region and of the globe. These comparative benchmarks allow the reader to quickly gauge a country vis--vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the countries in Africa). This study gives, however, my estimates for the latent demand, or the P.I.E. for aircraft maintenance, repair, and overhaul (mro) services in Africa. It also shows how the P.I.E. is divided across the national markets of Africa. For each country, I also show my estimates of how the P.I.E. grows over time (positive or negative growth). In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on international strategic planning at graduate schools of business.

Table Of Contents:

1 INTRODUCTION 8
1.1 Overview 8
1.2 What is Latent Demand and the P.I.E.? 8
1.3 The Methodology 9
1.3.1 Step 1. Product Definition and Data Collection 11
1.3.2 Step 2. Filtering and Smoothing 12
1.3.3 Step 3. Filling in Missing Values 13
1.3.4 Step 4. Varying Parameter, Non-linear Estimation 13
1.3.5 Step 5. Fixed-Parameter Linear Estimation 14
1.3.6 Step 6. Aggregation and Benchmarking 14
1.3.7 Step 7. Latent Demand Density: Allocating Across Cities 14
2 AFRICA 16
2.1 Executive Summary 16
2.2 Algeria 17
2.3 Angola 18
2.4 Benin 18
2.5 Botswana 20
2.6 Burkina Faso 21
2.7 Burundi 22
2.8 Cameroon 22
2.9 Cape Verde 23
2.10 Central African Republic 24
2.11 Chad 25
2.12 Comoros 26
2.13 Congo (formerly Zaire) 26
2.14 Cote d'Ivoire 27
2.15 Djibouti 28
2.16 Egypt 29
2.17 Equatorial Guinea 30
2.18 Ethiopia 30
2.19 Gabon 31
2.20 Ghana 32
2.21 Guinea 33
2.22 Guinea-Bissau 33
2.23 Kenya 34
2.24 Lesotho 35
2.25 Liberia 36
2.26 Libya 36
2.27 Madagascar 37
2.28 Malawi 38
2.29 Mali 39
2.30 Mauritania 40
2.31 Mauritius 41
2.32 Morocco 41
2.33 Mozambique 42
2.34 Namibia 43
2.35 Niger 44
2.36 Nigeria 45
2.37 Republic of Congo 46
2.38 Rwanda 47
2.39 Sao Tome E Principe 48
2.40 Senegal 48
2.41 Sierra Leone 49
2.42 Somalia 50
2.43 South Africa 51
2.44 Swaziland 52
2.45 Tanzania 53
2.46 The Gambia 54
2.47 Togo 55
2.48 Tunisia 56
2.49 Uganda 57
2.50 Western Sahara 58
2.51 Zambia 58
2.52 Zimbabwe 59
2.53 Frequently Asked Questions (FAQ) 60
2.53.1 Category Definition 60
2.53.2 Units 60
2.53.3 Methodology 61
3 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 63
3.1 Disclaimers & Safe Harbor 63
3.2 Icon Group International, Inc. User Agreement Provisions 64

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