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The 2016-2021 World Outlook for Women's Suits

April 2015 | 242 pages | ID: 2C533B57B40EN
ICON Group International

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This econometric study covers the world outlook for women's suits across more than 200 countries. 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-à-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 230 countries of the world). This study gives, however, my estimates for the worldwide latent demand, or the P.I.E., for women's suits. It also shows how the P.I.E. is divided across the world’s regional and national markets. 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.
1 INTRODUCTION

1.1 Overview
1.2 What is Latent Demand and the P.I.E.?
1.3 The Methodology
  1.3.1 Step 1. Product Definition and Data Collection
  1.3.2 Step 2. Filtering and Smoothing
  1.3.3 Step 3. Filling in Missing Values
  1.3.4 Step 4. Varying Parameter, Non-linear Estimation
  1.3.5 Step 5. Fixed-Parameter Linear Estimation
  1.3.6 Step 6. Aggregation and Benchmarking
  1.3.7 Step 7. Latent Demand Density: Allocating Across Cities
1.4 Frequently Asked Questions (FAQ)
  1.4.1 Category Definition
  1.4.2 Units
  1.4.3 Methodology

2 SUMMARY OF FINDINGS

2.1 The Worldwide Market Potential

3 AFRICA, EUROPE & THE MIDDLE EAST

3.1 Executive Summary
3.2 Afghanistan
3.3 Albania
3.4 Algeria
3.5 Andorra
3.6 Angola
3.7 Armenia
3.8 Austria
3.9 Azerbaijan
3.10 Bahrain
3.11 Belarus
3.12 Belgium
3.13 Benin
3.14 Bosnia and Herzegovina
3.15 Botswana
3.16 Bulgaria
3.17 Burkina Faso
3.18 Burundi
3.19 Cameroon
3.20 Cape Verde
3.21 Central African Republic
3.22 Chad
3.23 Comoros
3.24 Congo (formerly Zaire)
3.25 Cote d'Ivoire
3.26 Croatia
3.27 Cyprus
3.28 Czech Republic
3.29 Denmark
3.30 Djibouti
3.31 Egypt
3.32 Equatorial Guinea
3.33 Eritrea
3.34 Estonia
3.35 Ethiopia
3.36 Finland
3.37 France
3.38 Gabon
3.39 Georgia
3.40 Germany
3.41 Ghana
3.42 Greece
3.43 Guinea
3.44 Guinea-Bissau
3.45 Hungary
3.46 Iceland
3.47 Iran
3.48 Iraq
3.49 Ireland
3.50 Israel
3.51 Italy
3.52 Jordan
3.53 Kazakhstan
3.54 Kenya
3.55 Kosovo
3.56 Kuwait
3.57 Kyrgyzstan
3.58 Latvia
3.59 Lebanon
3.60 Lesotho
3.61 Liberia
3.62 Libya
3.63 Liechtenstein
3.64 Lithuania
3.65 Luxembourg
3.66 Macedonia
3.67 Madagascar
3.68 Malawi
3.69 Mali
3.70 Malta
3.71 Mauritania
3.72 Mauritius
3.73 Moldova
3.74 Monaco
3.75 Montenegro
3.76 Morocco
3.77 Mozambique
3.78 Namibia
3.79 Niger
3.80 Nigeria
3.81 North Sudan
3.82 Norway
3.83 Oman
3.84 Pakistan
3.85 Palestine
3.86 Poland
3.87 Portugal
3.88 Qatar
3.89 Republic of Congo
3.90 Romania
3.91 Russia
3.92 Rwanda
3.93 San Marino
3.94 Sao Tome E Principe
3.95 Saudi Arabia
3.96 Senegal
3.97 Serbia
3.98 Sierra Leone
3.99 Slovakia
3.100 Slovenia
3.101 Somalia
3.102 South Africa
3.103 South Sudan
3.104 Spain
3.105 Swaziland
3.106 Sweden
3.107 Switzerland
3.108 Syrian Arab Republic
3.109 Tajikistan
3.110 Tanzania
3.111 The Gambia
3.112 The Netherlands
3.113 The United Arab Emirates
3.114 The United Kingdom
3.115 Togo
3.116 Tunisia
3.117 Turkey
3.118 Turkmenistan
3.119 Uganda
3.120 Ukraine
3.121 Uzbekistan
3.122 Western Sahara
3.123 Yemen
3.124 Zambia
3.125 Zimbabwe

4 ASIA

4.1 Executive Summary
4.2 Bangladesh
4.3 Bhutan
4.4 Brunei
4.5 Burma
4.6 Cambodia
4.7 China
4.8 Hong Kong
4.9 India
4.10 Indonesia
4.11 Japan
4.12 Laos
4.13 Macau
4.14 Malaysia
4.15 Maldives
4.16 Mongolia
4.17 Nepal
4.18 North Korea
4.19 Papua New Guinea
4.20 Philippines
4.21 Seychelles
4.22 Singapore
4.23 South Korea
4.24 Sri Lanka
4.25 Taiwan
4.26 Thailand
4.27 Timor - Leste, Democratic Republic of
4.28 Vietnam

5 LATIN AMERICA

5.1 Executive Summary
5.2 Argentina
5.3 Belize
5.4 Bolivia
5.5 Brazil
5.6 Chile
5.7 Colombia
5.8 Costa Rica
5.9 Ecuador
5.10 El Salvador
5.11 Guatemala
5.12 Guyana
5.13 Honduras
5.14 Mexico
5.15 Nicaragua
5.16 Panama
5.17 Paraguay
5.18 Peru
5.19 Suriname
5.20 The Falkland Islands
5.21 Uruguay
5.22 Venezuela

6 NORTH AMERICA & THE CARIBBEAN

6.1 Executive Summary
6.2 Antigua and Barbuda
6.3 Aruba
6.4 Barbados
6.5 Bermuda
6.6 Canada
6.7 Cuba
6.8 Dominica
6.9 Dominican Republic
6.10 Greenland
6.11 Grenada
6.12 Haiti
6.13 Jamaica
6.14 Puerto Rico
6.15 St. Kitts and Nevis
6.16 St. Lucia
6.17 St. Vincent and the Grenadines
6.18 The Bahamas
6.19 The British Virgin Islands
6.20 The Cayman Islands
6.21 The U.S. Virgin Islands
6.22 The United States
6.23 Trinidad and Tobago

7 OCEANA

7.1 Executive Summary
7.2 American Samoa
7.3 Australia
7.4 Christmas Island
7.5 Cook Islands
7.6 Fiji
7.7 French Polynesia
7.8 Guam
7.9 Kiribati
7.10 Marshall Islands
7.11 Micronesia Federation
7.12 Nauru
7.13 New Caledonia
7.14 New Zealand
7.15 Niue
7.16 Norfolk Island
7.17 Palau
7.18 Solomon Islands
7.19 The Northern Mariana Island
7.20 Tonga
7.21 Tuvalu
7.22 Vanuatu
7.23 Wallis and Futuna
7.24 Western Samoa

8 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS

8.1 Disclaimers & Safe Harbor
8.2 ICON Group International, Inc. User Agreement Provisions


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