The 2016-2021 Outlook for Specialty Herbs in Europe & the Middle East

 Published On: Jul, 2013 |    No of Pages: 73 |  Published By: Icon Group International, Inc | Format: PDF
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This econometric study covers the outlook for specialty herbs in Europe & the Middle East. 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 Europe & the Middle East). This study gives, however, my estimates for the latent demand, or the P.I.E. for specialty herbs in Europe & the Middle East. It also shows how the P.I.E. is divided across the national markets of Europe & the Middle East. 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 7
1.1 Overview 7
1.2 What is Latent Demand and the P.I.E.? 7
1.3 The Methodology 8
1.3.1 Step 1. Product Definition and Data Collection 10
1.3.2 Step 2. Filtering and Smoothing 11
1.3.3 Step 3. Filling in Missing Values 12
1.3.4 Step 4. Varying Parameter, Non-linear Estimation 12
1.3.5 Step 5. Fixed-Parameter Linear Estimation 13
1.3.6 Step 6. Aggregation and Benchmarking 13
1.3.7 Step 7. Latent Demand Density: Allocating Across Cities 13
2 EUROPE & THE MIDDLE EAST 15
2.1 Executive Summary 15
2.2 Afghanistan 16
2.3 Albania 17
2.4 Andorra 18
2.5 Armenia 18
2.6 Austria 19
2.7 Azerbaijan 20
2.8 Bahrain 21
2.9 Belarus 21
2.10 Belgium 22
2.11 Bosnia and Herzegovina 23
2.12 Bulgaria 24
2.13 Croatia 25
2.14 Cyprus 25
2.15 Czech Republic 26
2.16 Denmark 27
2.17 Estonia 28
2.18 Finland 28
2.19 France 29
2.20 Georgia 30
2.21 Germany 31
2.22 Greece 32
2.23 Hungary 33
2.24 Iceland 34
2.25 Iran 35
2.26 Iraq 36
2.27 Ireland 37
2.28 Israel 37
2.29 Italy 38
2.30 Jordan 39
2.31 Kazakhstan 40
2.32 Kuwait 41
2.33 Kyrgyzstan 42
2.34 Latvia 42
2.35 Lebanon 43
2.36 Liechtenstein 44
2.37 Lithuania 44
2.38 Luxembourg 45
2.39 Malta 46
2.40 Moldova 46
2.41 Monaco 47
2.42 Norway 48
2.43 Oman 48
2.44 Pakistan 49
2.45 Palestine 50
2.46 Poland 50
2.47 Portugal 51
2.48 Qatar 52
2.49 Romania 52
2.50 Russia 53
2.51 San Marino 54
2.52 Saudi Arabia 55
2.53 Slovakia 56
2.54 Slovenia 56
2.55 Spain 57
2.56 Sweden 58
2.57 Switzerland 59
2.58 Syrian Arab Republic 60
2.59 Tajikistan 61
2.60 The Netherlands 62
2.61 The United Arab Emirates 63
2.62 The United Kingdom 63
2.63 Turkey 64
2.64 Turkmenistan 65
2.65 Ukraine 66
2.66 Uzbekistan 67
2.67 Yemen 68
2.68 Frequently Asked Questions (FAQ) 68
2.68.1 Category Definition 68
2.68.2 Units 69
2.68.3 Methodology 70
3 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 72
3.1 Disclaimers & Safe Harbor 72
3.2 Icon Group International, Inc. User Agreement Provisions 73

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