Executive Report on Strategies in Mayotte
ICON Group International, June 2007, Pages: 368
How to Strategically Evaluate Mayotte
Perhaps the most efficient way of evaluating Mayotte is to consider key dimensions which themselves are composites of multiple factors. Composite portfolio approaches have long been used by strategic planners. The biggest challenge in this approach is to choose the appropriate factors that are the most relevant to international planning. The two measures of greatest relevance are “latent demand” and “market accessibility”. The figure below summarizes the key dimensions and recommendations of such an approach. Using these two composites, one can prioritize all countries of the world. Countries of high latent demand and high relative accessibility (e.g. easier entry for one firm compared to other firms) are given highest priority. The figure below shows two different scenarios. Accessibility is defined as a firm’s ease of entering or supplying from or to a market (the “supply side”), and latent demand is an indicator of the potential in serving from or to the market (the “demand side”).
Framework for Prioritizing Countries
Demand/Market Potential Driven Firm
Relative Accessibility
Accessibility/Supply Averse Firm
Relative Accessibility
In the top figure, the firm is driven by market potential, whereas the bottom figure represents a firm that is driven by costs or by an aversion to difficult markets. This report treats the reader as coming from a “generic firm” approaching the global market - neither a market-driven nor a cost-driven company. Planners must therefore augment this report with their own company-specific factors that might change the priorities. This report provides an overview of factors driving latent demand in Mayotte. Latent demand is largely driven by economic fundamentals.
In Chapter 2, I summarize the economic potential for Mayotte over the next five years for hundreds of industries, categories, and products. The goal of this chapter is to report my findings on the real economic potential, or latent demand, represented by Mayotte when defined as an area of dominant influence. The data presented are the result of various spatial econometric and time-series forecasting models which, for each category presented, are applied to forecast and allocate latent demand across all countries of the world and major distribution centers or centers of dominant influence within each country. This is accomplished knowing that economic fundamentals (e.g. income) generally vary from one country to another within a given country over time. In this chapter, I report the allocation for each category for Mayotte as an area of dominant influence in Africa and, potentially, the world.
ECONOMIC AND PRODUCT MARKETS IN MAYOTTE
Introduction & Methodology
Overview & Methodology
In performing various economic analyses for clients, I have occasionally been asked to investigate the market potential for various products and services in Mayotte. The purpose of the studies is to understand the density of demand within Mayotte and the extent to which Mayotte might be used as a point of distribution within Africa. From an economic perspective, however, Mayotte does not represent a population within rigid geographical boundaries, rather, it represents an area of dominant influence over markets in adjacent areas. This influence varies from one industry to another, but also from one period of time to another.
In what follows, I summarize the economic potential for Mayotte over the next five years for hundreds of industries, categories, and products. The goal of this chapter is to report my findings on the real economic potential, or what an economist calls the latent demand, represented by Mayotte when defined as an area of dominant influence. The reader needs to realize that latent demand may or may not represent real sales. For many items, latent demand is clearly observable in sales, as in the case for food or housing items. Consider, however, the category "satellite launch vehicles". Clearly, there are no launch pads in Mayotte used by the space industry to launch satellites. However, the core benefit of the vehicles (e.g. telecommunications, etc.) is "consumed" by the area served by Mayotte. Without Mayotte, in other words, the market for satellite launch vehicles would be lower for the population in Mayotte, Africa, or the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to both Africa and Mayotte.
The data presented are the result of various spatial econometric and time-series forecasting models which, for each category presented, are applied to forecast and allocate latent demand across all countries of the world and major distribution centers or centers of dominant influence within each country. This is accomplished knowing that economic fundamentals (e.g. income) generally vary from one country to another within a given country over time. In this chapter, I report the allocation for each category for Mayotte as an area of dominant influence in Africa and, potentially, the world.
Market Potential Estimation Methodology
Overview
This chapter covers the outlook for products in Mayotte. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for Mayotte (in millions of U.S. dollars). Comparative benchmarks allow the reader to quickly gauge Mayotte vis-à-vis regional and global totals. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This chapter does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The chapter does not consider short-term cyclicalities that might affect realized sales. The chapter, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.
This chapter does not report actual sales data, but gives, however, my estimates for the latent demand for products and services in Mayotte. For each category, 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.
What Is Latent Demand and the P.I.E.?
The concept of latent demand is rather subtle. The term latent typically refers to something that is dormant, not observable, or not yet realized. Demand is the notion of an economic quantity that a target population or market requires under different assumptions of price, quality, and distribution, among other factors. Latent demand, therefore, is commonly defined by economists as the industry earnings of a market when that market becomes accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E.) or total revenues (not profit) if a market is served in an efficient manner. It is typically expressed as the total revenues potentially extracted by firms. The “market” is defined at a given level in the value chain. There can be latent demand at the retail level, at the wholesale level, the manufacturing level, and the raw materials level (the P.I.E. of higher levels of the value chain being always smaller than the P.I.E. of levels at lower levels of the same value chain, assuming all levels maintain minimum profitability).
The latent demand is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand can be either lower or higher than actual sales if a market is inefficient (i.e., not representative of relatively competitive levels). Inefficiencies arise from a number of factors, including the lack of international openness, cultural barriers to consumption, regulations, and cartel-like behavior on the part of firms. In general, however, latent demand is typically larger than actual sales in a country market. It should be noted that the estimates are “culture blind” and “climate blind”, meaning that sales may in fact be lower than the latent demand due to cultural or exogenous factors, such as religion or climate (e.g. the presence of certain religions can effect the actual sales of certain food and beverage products, in the same way that climatic conditions can affect the actual sales of clothing and/or heating products). The estimates of latent demand do not explicitly control for either these long-run exogenous factors or shot-run exogenous factors that may be present from year to year (e.g. the effects of war, SARS, terrorist activities, civil wars, natural disasters, elections, or similar events).
For reasons discussed later, this chapter does not consider the notion of “unit quantities”, only total latent revenues (i.e., a calculation of price times quantity is never made, though one is implied). The units used in this chapter are U.S. dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends) and not adjusted for future dynamics in exchange rates (i.e., the figures reflect average exchange rates over recent history). If inflation rates or exchange rates vary in a substantial way compared to recent experience, actually sales can also exceed latent demand (when expressed in U.S. dollars, not adjusted for inflation). On the other hand, latent demand can be typically higher than actual sales as there are often distribution inefficiencies that reduce actual sales below the level of latent demand.
As mentioned earlier, this chapter is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. If fact, all the current products or services on the market can cease to exist in their present form (i.e., at a brand, R&D specification, or corporate-image level) and all the players can be replaced by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there will still be an international latent demand at the aggregate level. Product and service offering details, and the actual identity of the players involved, while important for certain issues, are relatively unimportant for estimates of latent demand.
The Methodology
In order to estimate the latent demand for Mayotte, I used a multi-stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In this case, I heavily rely on the use of certain basic economic assumptions. In particular, there is an assumption governing the shape and type of aggregate latent demand functions. Latent demand functions relate the income of a country, city, state, household, or individual to realized consumption. Latent demand (often realized as consumption when an industry is efficient), at any level of the value chain, takes place if an equilibrium is realized. For firms to serve a market, they must perceive a latent demand and be able to serve that demand at a minimal return. The single most important variable determining consumption, assuming latent demand exists, is income (or other financial resources at higher levels of the value chain). Other factors that can pivot or shape demand curves include external or exogenous shocks (i.e., business cycles), and or changes in utility for the product in question.
Ignoring, for the moment, exogenous shocks and variations in utility across countries, the aggregate relation between income and consumption has been a central theme in economics. The figure below concisely summarizes one aspect of problem. In the 1930s, John Meynard Keynes conjectured that as incomes rise, the average propensity to consume would fall. The average propensity to consume is the level of consumption divided by the level of income, or the slope of the line from the origin to the consumption function. He estimated this relationship empirically and found it to be true in the short-run (mostly based on cross-sectional data). The higher the income, the lower the average propensity to consume. This type of consumption function is labeled "A" in the figure below (note the rather flat slope of the curve). In the 1940s, another macroeconomist, Simon Kuznets, estimated long-run consumption functions which indicated that the marginal propensity to consume was rather constant (using time series data across countries). This type of consumption function is show as "B" in the figure below (note the higher slope and zero-zero intercept). The average propensity to consume is constant.
Is it declining or is it constant? A number of other economists, notably Franco Modigliani and Milton Friedman, in the 1950s (and Irving Fisher earlier), explained why the two functions were different using various assumptions on intertemporal budget constraints, savings, and wealth. The shorter the time horizon, the more consumption can depend on wealth (earned in previous years) and business cycles. In the long-run, however, the propensity to consume is more constant. Similarly, in the long run, households, industries, or countries with no income eventually have no consumption (wealth is depleted). While the debate surrounding beliefs about how income and consumption are related and interesting, in this chapter a very particular school of thought is adopted. In particular, we are considering the latent demand across some 230 countries. The smallest have fewer than 10,000 inhabitants. I assume that all of these counties fall along a "long-run" aggregate consumption function. This long-run function applies despite some of these countries having wealth; current income dominates the latent demand. So, latent demand in the long-run has a zero intercept. However, I allow firms to have different propensities to consume (including being on consumption functions with differing slopes, which can account for differences in industrial organization and end-user preferences).
Given this overriding philosophy, I will now describe the methodology used to create the latent demand estimates for Mayotte. Since ICON Group has asked me to apply this methodology to a large number of categories and countries, the rather academic discussion below is general and can be applied to a wide variety of categories and countries, not just Mayotte.
Step 1. Product Definition and Data Collection
Any study of latent demand across countries and within Mayotte requires that some standard be established to define “efficiently served”. Having implemented various alternatives and matched these with market outcomes, I have found that the optimal approach is to assume that certain key countries are more likely to be at or near efficiency than others. These countries are given greater weight than others in the estimation of latent demand compared to other countries for which no known data are available. Of the many alternatives, I have found the assumption that the world’s highest aggregate income and highest income-per-capita markets reflect the best standards for “efficiency”. High aggregate income alone is not sufficient (i.e., China has high aggregate income, but low income per capita and cannot assumed to be efficient). Aggregate income can be operationalized in a number of ways, including gross domestic product (for industrial categories), or total disposable income (for household categories; population times average income per capita, or number of households times average household income per capita). Brunei, Nauru, Kuwait, and Lichtenstein are examples of countries with high income per capita, but not assumed to be efficient, given low aggregate level of income (or gross domestic product); these countries have, however, high incomes per capita but may not benefit from the efficiencies derived from economies of scale associated with large economies. Only countries with high income per capita and large aggregate income are assumed efficient. This greatly restricts the pool of countries to those in the OECD (Organization for Economic Cooperation and Development), like the United States or the United Kingdom (which were earlier than other large OECD economies to liberalize their markets).
The selection of countries is further reduced by the fact that not all countries in the OECD report industry revenues at the category level. Countries that typically have ample data at the aggregate level that meet the efficiency criteria include the United States, the United Kingdom and in some cases France and Germany.
Latent demand for Mayotte is therefore estimated using data collected for relatively efficient markets from independent data sources (e.g. Euromonitor, Mintel, Thomson Financial Services, the U.S. Industrial Outlook, the World Resources Institute, the Organization for Economic Cooperation and Development, various agencies from the United Nations, industry trade associations, the International Monetary Fund, and the World Bank). Depending on original data sources used, the definition of a category is established. In the case of this chapter, the data were reported at the aggregate level, with no further breakdown or definition. In other words, any potential product or service that might be incorporated within a category falls under the broadest definition of the category. Public sources rarely report data at the disaggregated level in order to protect private information from individual firms that might dominate a specific product-market. These sources will therefore aggregate across components of a category and report only the aggregate to the public. While private data are certainly available, this chapter only relies on public data at the aggregate level without reliance on the summation of various category components. In other words, this chapter does not aggregate a number of components to arrive at the “whole”. Rather, it starts with the “whole”, and estimates the whole for all countries and the world at large (without needing to know the specific parts that went into the whole in the first place). All figures in this chapter are for sales resulting from retail channels.
Step 2. Filtering and Smoothing
Based on the aggregate view of categories as defined above, data were then collected for as many similar countries as possible for that same definition, at the same level of the value chain. This generates a convenience sample of countries from which comparable figures are available. If the series in question do not reflect the same accounting period, then adjustments are made. In order to eliminate short-term effects of business cycles, the series are smoothed using an 2 year moving average weighting scheme (longer weighting schemes do not substantially change the results). If data are available for a country, but these reflect short-run aberrations due to exogenous shocks (such as would be the case of beef sales in a country stricken with foot-and-mouth disease), these observations were dropped or "filtered" from the analysis.
Step 3. Filling in Missing Values
In some cases, data are available for countries on a sporadic basis. In other cases, data from a country may be available for only one year. From a Bayesian perspective, these observations should be given greatest weight in estimating missing years. Assuming that other factors are held constant, the missing years are extrapolated using changes and growth in aggregate national income. Based on the overriding philosophy of a long-run consumption function (defined earlier), countries which have missing data for any given year, are estimated based on historical dynamics of aggregate income for that country.
Step 4. Varying Parameter, Non-Linear Estimation
Given the data available from the first three steps, the latent demand in additional countries is estimated using a “varying-parameter cross-sectionally pooled time series model”. Simply stated, the effect of income on latent demand is assumed to be constant across countries unless there is empirical evidence to suggest that this effect varies (i.e., . the slope of the income effect is not necessarily same for all countries). This assumption applies across countries along the aggregate consumption function, but also over time (i.e., not all countries are perceived to have the same income growth prospects over time and this effect can vary from country to country as well). Another way of looking at this is to say that latent demand is more likely to be similar across countries that have similar characteristics in terms of economic development (i.e., African countries will have similar latent demand structures controlling for the income variation across the pool of African countries).
This approach is useful across countries for which some notion of non-linearity exists in the aggregate cross-country consumption function. For some categories, however, the reader must realize that the numbers will reflect the contribution of Mayotte to global latent demand and may never be realized in the form of local sales. For certain country-category combinations this will result in what at first glance will be odd results. For example, the latent demand for the category “space vehicles” will exist for “Togo” even though they have no space program. The assumption is that if the economies in these countries did not exist, the world aggregate for these categories would be lower. The share attributed to these countries is based on a proportion of their income (however small) being used to consume the category in question (i.e., perhaps via resellers).
Step 5. Fixed-Parameter Linear Estimation
Non-linearities are assumed in cases where filtered data exist along the aggregate consumption function. Because the world consists of more than 200 countries, there will always be those countries, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible. For these countries, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a country’s stock of income), but a function of current income (a country’s flow of income). In the long run, if a country has no current income, the latent demand is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., countries which earn low levels of income will not use their savings, in the long run, to demand). In a graphical sense, for low income countries, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, low-income countries are assumed to have a latent demand proportional to their income, based on the country closest to it on the aggregate consumption function.
Step 6. Aggregation and Benchmarking
Based on the models described above, latent demand figures are estimated for all countries of the world, for Mayotte and for the smallest economies. These are then aggregated to get world totals and regional totals. To make the numbers more meaningful, regional and global demand figures are presented. Figures are rounded, so minor inconsistencies may exist across tables.
1 INTRODUCTION & METHODOLOGY 13
1.1 What Does This Report Cover? 13
1.2 How to Strategically Evaluate Mayotte 13
2 ECONOMIC AND PRODUCT MARKETS IN MAYOTTE 16
2.1 Introduction & Methodology 16
2.1.1 Overview & Methodology 16
2.1.2 Market Potential Estimation Methodology 16
2.2 Summary Rankings 22
2.3 Latent Demand Forecasts 37
2.3.1 60-Milligram Containers of Fromage Frais 37
2.3.2 AC Drives 37
2.3.3 Adhesives and Sealants 38
2.3.4 Advertising Services 38
2.3.5 Aerospace and Defense Equipment 39
2.3.6 Aftermarket Passenger Car Tires 39
2.3.7 Air Freight Services 40
2.3.8 Alcoholic Beverages 40
2.3.9 Ales and Stouts 41
2.3.10 Alimentary and Metabolism Pharmaceuticals 41
2.3.11 Alumina Refining 42
2.3.12 Aluminum Die-Casting Foundries 42
2.3.13 Amusement and Recreation Services 43
2.3.14 Analgesics 43
2.3.15 Analog Color Televisions 44
2.3.16 Antidepressant Pharmaceuticals 44
2.3.17 Antiperspirants and Deodorants 45
2.3.18 Apparel and Accessories 45
2.3.19 Appetizers and Dips 46
2.3.20 Apples 46
2.3.21 Applications Software 47
2.3.22 Architectural Services 47
2.3.23 Athletic Footwear 48
2.3.24 Audio Components 48
2.3.25 Auto and Home Supply Stores 49
2.3.26 Aviation Services 49
2.3.27 Baby Formula 50
2.3.28 Bagged Chocolate Candy 50
2.3.29 Baked Goods 51
2.3.30 Bakery Products 51
2.3.31 Bananas 52
2.3.32 Bar Soap 52
2.3.33 Base Chemicals 53
2.3.34 Battery Eggs 53
2.3.35 Beauty and Barber Shops 54
2.3.36 Beer 54
2.3.37 Bicycles and Bicycle Accessories 55
2.3.38 Biotechnology 55
2.3.39 Bituminous Coal 56
2.3.40 Blended Whiskey 56
2.3.41 Board Games and Puzzles 57
2.3.42 Boat Building 57
2.3.43 Boilers 58
2.3.44 Book Publishing 58
2.3.45 Bottled Water 59
2.3.46 Bottles of Lager Beer 59
2.3.47 Boxed Facial Tissues 60
2.3.48 Boys’ School Uniforms 60
2.3.49 Bras and Allied Garments 61
2.3.50 Bread 61
2.3.51 Breakfast Cereals 62
2.3.52 Breweries 62
2.3.53 Broadband Internet Access 63
2.3.54 Broadwoven Fabric Finishing Mills 63
2.3.55 Broom, Brush, and Mop Manufacturing 64
2.3.56 Brown and Wholemeal Bread 64
2.3.57 Budweiser Lager Beer 65
2.3.58 Building Materials and Garden Supplies 65
2.3.59 Built-In Electric Ovens 66
2.3.60 Business and School Supplies 66
2.3.61 Butcher Shops 67
2.3.62 Butter 67
2.3.63 Cable TV 68
2.3.64 CAD/CAM/CAE Software 68
2.3.65 Cafes and Restaurants 69
2.3.66 Cakes and Pastries 69
2.3.67 Camcorders 70
2.3.68 Camera and Photographic Supplies Stores 70
2.3.69 Campgrounds and Recreational Vehicle Parks 71
2.3.70 Candles 71
2.3.71 Candy 72
2.3.72 Canned Beans 72
2.3.73 Cans of Lager Beer 73
2.3.74 Car Aftermarket Products 73
2.3.75 Casinos and Gambling 74
2.3.76 Cat Food 74
2.3.77 CD Players 75
2.3.78 Ceiling Light Fixtures 75
2.3.79 Cellular Telephones 76
2.3.80 Cement Construction Materials 76
2.3.81 Cemeteries and Crematories 77
2.3.82 Ceramic Housewares 77
2.3.83 Chemicals 78
2.3.84 Chewing and Bubble Gum 78
2.3.85 Childrens Chicken Nugget Ready Meals 79
2.3.86 Chilled and Deli Food 79
2.3.87 Chips and Crisps 80
2.3.88 Chocolate Candy 80
2.3.89 Cigarette Manufacturing 81
2.3.90 Cigars and Cigarillos 81
2.3.91 Citrus Fruit 82
2.3.92 Civil Aerospace Equipment 82
2.3.93 Clay Building Products 83
2.3.94 Clothing Accessories 83
2.3.95 Coated and Flavored Nuts 84
2.3.96 Coin-Operated Laundries and Dry Cleaners 84
2.3.97 Colas 85
2.3.98 Collection Agencies 85
2.3.99 Color Televisions 86
2.3.100 Combination Refrigerator-Freezers 86
2.3.101 Commercial Banking 87
2.3.102 Communications Services 87
2.3.103 Compact Discs (CDs) 88
2.3.104 Complete Dry Dog Food 88
2.3.105 Computer Hardware 89
2.3.106 Concrete Building Products 89
2.3.107 Construction and Engineering Services 90
2.3.108 Consumer Chemicals 90
2.3.109 Contact Lenses 91
2.3.110 Continental and Specialty Plant Bread 91
2.3.111 Convenience Stores 92
2.3.112 Conventional Mineral Oil 92
2.3.113 Cookies and Crackers 93
2.3.114 Cooking Ranges 93
2.3.115 Copper Ores 94
2.3.116 Corporate Strategy Services 94
2.3.117 Cosmetics and Toiletries 95
2.3.118 Costume Jewelry 95
2.3.119 Cotton Yarn 96
2.3.120 Cough and Cold Remedies 96
2.3.121 Craft Bread 97
2.3.122 Credit Bureaus 97
2.3.123 Cross/utility Vehicles (CUVs) 98
2.3.124 Crude Petroleum and Natural Gas Extraction 98
2.3.125 Cruise Ship Tourism 99
2.3.126 Crushed and Broken Stone 99
2.3.127 Crushing Oilseeds and Tree Nuts Excluding Soybeans 100
2.3.128 Current-Carrying Wiring Device Manufacturing 100
2.3.129 Curtain and Drapery Mills 101
2.3.130 Custom Draperies 101
2.3.131 Daily Newspapers 102
2.3.132 Dairy Cream 102
2.3.133 Dark Brandy 103
2.3.134 Data Processing and Network Services 103
2.3.135 Defense Industry Equipment 104
2.3.136 Deli Food 104
2.3.137 Deluxe and Malt Whiskey 105
2.3.138 Department Stores 105
2.3.139 Depository Credit Intermediation 106
2.3.140 Designer Bath and Shower Products 106
2.3.141 Desktop Personal Computers 107
2.3.142 Dial-Up Internet Access 107
2.3.143 Diesel Trucks 108
2.3.144 Dietary Supplements 108
2.3.145 Digestion Aids 109
2.3.146 Digital Cameras 109
2.3.147 Dining Out 110
2.3.148 Dips 110
2.3.149 Direct Selling Establishments 111
2.3.150 Discount Superstores 111
2.3.151 Discrete Semiconductors 112
2.3.152 Dishwashing Products 112
2.3.153 Disposable Health Care Equipment and Supplies 113
2.3.154 Distillate Fuel Oil 113
2.3.155 Distilleries 114
2.3.156 Dog Food 114
2.3.157 Dolls and Figures 115
2.3.158 Domestic Water Utilities 115
2.3.159 Draught Lager Beer 116
2.3.160 Dried Food 116
2.3.161 Drink Concentrates 117
2.3.162 Drug Delivery Systems 117
2.3.163 Durable Goods 118
2.3.164 DVD Players 118
2.3.165 Eating and Drinking Places 119
2.3.166 Economy Disposable Diapers 119
2.3.167 Edible Oils 120
2.3.168 Education and Training Services 120
2.3.169 Electron Tubes 121
2.3.170 Elementary and Secondary Schools 121
2.3.171 Engineering Services 122
2.3.172 Envelope Manufacturing 122
2.3.173 Environmental Consulting Services 123
2.3.174 Ethnic Hair Care Products 123
2.3.175 Everyday Cookies 124
2.3.176 Explosives Manufacturing 124
2.3.177 Extended Stay and Business Suite Motels 125
2.3.178 Exterminating and Pest Control Services 125
2.3.179 External Sanitary Protection Products 126
2.3.180 Fabric Softeners 126
2.3.181 Facial Cosmetics 127
2.3.182 Family Clothing Stores 127
2.3.183 Farm Machinery and Equipment 128
2.3.184 Fast Food 128
2.3.185 Feminine Sanitary Protection 129
2.3.186 Fermented Sauces 129
2.3.187 Fiber-Optic Cable Manufacturing 130
2.3.188 Film Cameras 130
2.3.189 Financial Services 131
2.3.190 Finger Rolls 131
2.3.191 Fixed-Line Telecommunications Services 132
2.3.192 Flat Glass 132
2.3.193 Floor Coverings 133
2.3.194 Flour Milling 133
2.3.195 Folding Paperboard Boxes 134
2.3.196 Food Advertising 134
2.3.197 Forestry and Fishing 135
2.3.198 Fossil Fuel-Powered Electric Power Generation 135
2.3.199 Foster’s Lager Beer 136
2.3.200 Fragrances 136
2.3.201 Franchising 137
2.3.202 Free-Range Eggs 137
2.3.203 Freestanding Electric Ranges 138
2.3.204 Freeze-Dried Instant Coffee 138
2.3.205 Fresh Beef and Veal 139
2.3.206 Fruit Drinks 139
2.3.207 Fuel Dealers 140
2.3.208 Funeral Homes 140
2.3.209 Gambling 141
2.3.210 Gardening Supplies, Outdoor Furniture, and Plants 141
2.3.211 Garlic Bread 142
2.3.212 General Merchandise stores 142
2.3.213 Generic Prescription Drugs 143
2.3.214 Geophysical Surveying and Mapping Services 143
2.3.215 Gift, Novelty, and Souvenir Stores 144
2.3.216 Gifts 144
2.3.217 Gin 145
2.3.218 Girls Dresses and Blouses 145
2.3.219 Girls’ School Uniforms 146
2.3.220 Glass Container Manufacturing 146
2.3.221 Gold Ores 147
2.3.222 Gourmet Potato Chips 147
2.3.223 Government Public Health Activities 148
2.3.224 Granola Bars and Breakfast Cereal Bars 148
2.3.225 Grape Juice 149
2.3.226 Graphic Design Services 149
2.3.227 Green Vegetables 150
2.3.228 Greeting Cards 150
2.3.229 Grocery Discounters 151
2.3.230 GSM-Based Cellular Telephones 151
2.3.231 Guided Missiles and Space Vehicles 152
2.3.232 Gypsum Products 152
2.3.233 Hair Tinting and Coloring Products 153
2.3.234 Hard Cheese 153
2.3.235 HDTV 154
2.3.236 Health Care Equipment and Supplies 154
2.3.237 Heating and Cooling Appliances 155
2.3.238 Highly Refined Mineral Oil 155
2.3.239 Highway and Street Construction 156
2.3.240 Hispanic Music Television 156
2.3.241 Hi-Tech Logistics 157
2.3.242 Hobby, Toy, and Game Stores 157
2.3.243 Home Improvement Retailers 158
2.3.244 Hospital Food Service 158
2.3.245 Household Textiles and Soft Furnishings 159
2.3.246 Human Resource Management Services 159
2.3.247 Hunting, Trapping, and Game Propagation 160
2.3.248 Ice Cream 160
2.3.249 Imported Whiskey 161
2.3.250 Impulse Ice Cream 161
2.3.251 In Vitro Diagnostic Equipment 162
2.3.252 IP-Based Enterprise Networking Equipment 162
2.3.253 Iron Ore Mining 163
2.3.254 Janitorial Services 163
2.3.255 Jewelry Stores 164
2.3.256 Juice 164
2.3.257 Kitchen Appliances 165
2.3.258 Knitwear 165
2.3.259 Kraft Foods Brand Cookies 166
2.3.260 Lager Beer 166
2.3.261 Lampshades 167
2.3.262 Laptop Computers 167
2.3.263 Large Household Appliances 168
2.3.264 Lawn and Garden Equipment and Supplies Stores 168
2.3.265 Leather and Leather Products 169
2.3.266 Legal Services 169
2.3.267 Leisure Education 170
2.3.268 Lemonade 170
2.3.269 Libraries 171
2.3.270 Life Insurance Sold by Life Insurance Companies 171
2.3.271 Linen and Uniform Supply 172
2.3.272 Lingerie 172
2.3.273 Lip and Multiuse Color Cosmetics 173
2.3.274 Liquefied Petroleum Gas 173
2.3.275 Liqueurs 174
2.3.276 Local and Interurban Passenger Transit 174
2.3.277 Logging 175
2.3.278 Logistics for the Pharmaceutical Industry 175
2.3.279 Long Grain Rice 176
2.3.280 Lower-Fat Potato Snacks 176
2.3.281 Low-Fat Spreads 177
2.3.282 Luggage Manufacturing 177
2.3.283 Lumber and Wood Products 178
2.3.284 Luxury Yogurts 178
2.3.285 Machine Tools 179
2.3.286 Machining Precision Turned Products 179
2.3.287 Magazines 180
2.3.288 Mainstream Tea 180
2.3.289 Malt Beverages 181
2.3.290 Management Consulting Services 181
2.3.291 Manifold Business Forms 182
2.3.292 Manmade Fabric Mills 182
2.3.293 Manufactured Mobile Home Dealers 183
2.3.294 Manufacturing Dog and Cat Food 183
2.3.295 Marine Freight Services 184
2.3.296 Marketing Research and Public Opinion Polling 184
2.3.297 Mass Reproduction of Computer Software 185
2.3.298 Materials Handling Machinery 185
2.3.299 Meal Replacement Drinks 186
2.3.300 Measuring and Controlling Instruments 186
2.3.301 Meat and Poultry 187
2.3.302 Media Advertising 187
2.3.303 Medical Biotechnology 188
2.3.304 Medicated Skin Care 188
2.3.305 Medium and Heavy Trucks 189
2.3.306 Men’s Accessories 189
2.3.307 Mens Grooming Products 190
2.3.308 Menswear 190
2.3.309 Menthol Cigarettes 191
2.3.310 Millwork 191
2.3.311 Mineral Water 192
2.3.312 Mixing Ingredients to Make Fertilizer 192
2.3.313 Model Wheeled Vehicles 193
2.3.314 Modems 193
2.3.315 Moist Cat Food 194
2.3.316 Morning Bakery Goods 194
2.3.317 Motor Vehicles and Motor Vehicle Equipment 195
2.3.318 Mushrooms 195
2.3.319 Music and Video Game Stores 196
2.3.320 Narrow Fabric Mills 196
2.3.321 National Newspapers 197
2.3.322 Net, Lace, and Voile Curtains 197
2.3.323 Network Hubs 198
2.3.324 New Car Dealers 198
2.3.325 Nitrogenous Fertilizer Manufacturing 199
2.3.326 Non-Airport Car Rentals 199
2.3.327 Non-Chocolate Confectionery Manufacturing 200
2.3.328 Non-Citrus Fruit 200
2.3.329 Non-Current-Carrying Wiring Device Manufacturing 201
2.3.330 Non-Daily Newspapers 201
2.3.331 Non-Depository Credit Intermediation 202
2.3.332 Non-Durable Goods 202
2.3.333 Non-Farm Housing Services 203
2.3.334 Non-Ferrous Forging 203
2.3.335 Non-Food Retail Sales 204
2.3.336 Non-Interest Commercial Banking 204
2.3.337 Non-Metallic Mineral Mining and Quarrying 205
2.3.338 Non-Residential Construction and Engineering 205
2.3.339 Non-Store Retailers and Mail Order 206
2.3.340 Non-Wood Office Furniture Manufacturing 206
2.3.341 Nonwoven Fabric Mills 207
2.3.342 Nuclear Electric Power Generation 207
2.3.343 Nursery, Garden Center, and Farm Supply Stores 208
2.3.344 Nursing Homes 208
2.3.345 Nuts 209
2.3.346 Office Supplies and Stationery Stores 209
2.3.347 Oil 210
2.3.348 Oil, Gas, and Mining Exploration Services 210
2.3.349 Oil-, Solid Fuel-, and Electric-Powered Boilers 211
2.3.350 Oils and Fats 211
2.3.351 Onions and Shallots 212
2.3.352 Operations Management Services 212
2.3.353 Ophthalmic Goods Manufacturing 213
2.3.354 Optical Goods and Eye Care Products 213
2.3.355 Oral Drug Delivery Systems 214
2.3.356 Orange Juice 214
2.3.357 Organic Beverages 215
2.3.358 OTC Healthcare Products 215
2.3.359 Outdoor Games 216
2.3.360 Outerwear Clothing and Accessories 216
2.3.361 Outsourcing Services 217
2.3.362 Ovens and Stoves 217
2.3.363 Over-The-Counter Drugs 218
2.3.364 Packaged Nuts 218
2.3.365 Packaging and Labeling Services 219
2.3.366 Pagers 219
2.3.367 Paint and Wallpaper Stores 220
2.3.368 Paper Towels 220
2.3.369 Parking Lots, Garages, and Valet Parking Services 221
2.3.370 Passenger Transportation 221
2.3.371 Passive Components 222
2.3.372 Pasta and Noodles 222
2.3.373 Pears 223
2.3.374 Periodicals 223
2.3.375 Perishable Prepared Foods Manufacturing 224
2.3.376 Permanent Employment Services 224
2.3.377 Personal Stationery 225
2.3.378 Pet Care Products 225
2.3.379 Pharmacies and Drug Stores 226
2.3.380 Phosphate Rock Mining 226
2.3.381 Phosphatic Fertilizer Manufacturing 227
2.3.382 Physicians Services 227
2.3.383 Pizzas 228
2.3.384 Plant Bread 228
2.3.385 Plastic Housewares 229
2.3.386 Plumbing Products 229
2.3.387 Plush Toys 230
2.3.388 Pollution Control Equipment and Services 230
2.3.389 Popcorn 231
2.3.390 Pork Pies 231
2.3.391 Port and Shipbuilding Equipment 232
2.3.392 Potash, Soda, and Boratic Minerals Mining 232
2.3.393 Potato Chips 233
2.3.394 Poultry Products 233
2.3.395 Powder Detergents 234
2.3.396 Prawn Appetizers and Dips 234
2.3.397 Precious Metal Jewelry and Personal Articles 235
2.3.398 Prefabricated Metal Buildings 235
2.3.399 Pre-Recorded Cassettes 236
2.3.400 Prerecorded Tape, Compact Disc, and Record Stores 236
2.3.401 Prescription Eyeglass Frames 237
2.3.402 Presentation Materials 237
2.3.403 Primary Metal Industries 238
2.3.404 Printed Circuit Boards 238
2.3.405 Printers 239
2.3.406 Printing Special Business Forms and Checkbooks 239
2.3.407 Private Residential Construction 240
2.3.408 Professional Computer Services 240
2.3.409 Property and Casualty Insurance 241
2.3.410 Public Residential Construction 241
2.3.411 Publishing Advertising 242
2.3.412 Pubs, Clubs, and Nightclubs 242
2.3.413 Pulmonary Drug Delivery Systems 243
2.3.414 Pulp Mills 243
2.3.415 Radiators and Pumps 244
2.3.416 Radio and Television Broadcasting 244
2.3.417 Railroad Freight Services 245
2.3.418 Ready Pasta 245
2.3.419 Real Jewelry 246
2.3.420 Reconstituted Wood Products 246
2.3.421 Recorded Music 247
2.3.422 Recreational Vehicle Dealers 247
2.3.423 Red Meat 248
2.3.424 Refining Cane Sugar from Raw Cane Sugar 248
2.3.425 Refrigeration Appliances 249
2.3.426 Regional Newspapers 249
2.3.427 Relays and Industrial Controls 250
2.3.428 Remediation Services 250
2.3.429 Rendering Animal Fat, Bones, and Meat Scraps 251
2.3.430 Renewable Energy Equipment 251
2.3.431 Replacement Tires for Cars and Light Vans 252
2.3.432 Residential Construction 252
2.3.433 Residual Fuel Oil 253
2.3.434 Retail Logistics 253
2.3.435 Retirement Savings Plans 254
2.3.436 Reupholstery and Furniture Repair 254
2.3.437 Rice Milling 255
2.3.438 Ride-On Toys 255
2.3.439 Rooming and Boarding Houses 256
2.3.440 Root Vegetables 256
2.3.441 Salad Accompaniments 257
2.3.442 Salon Hair Care Products 257
2.3.443 Salt and Vinegar Potato Chips 258
2.3.444 Sandwich Spreads 258
2.3.445 Sanitary Protection Products 259
2.3.446 Sauces, Salad Dressings, and Condiments 259
2.3.447 Savory Snacks 260
2.3.448 Sawmills 260
2.3.449 Scanners 261
2.3.450 School Food Service 261
2.3.451 Scrap Recycling 262
2.3.452 Screw Machine Products 262
2.3.453 Seafood Canning 263
2.3.454 Seasonal Cookies 263
2.3.455 Secondary Smelting and Alloying of Aluminum 264
2.3.456 Security and Commodity Brokers and Dealers 264
2.3.457 Services 265
2.3.458 Sewer Facilities 265
2.3.459 Sewing, Needlework, and Piece Goods Stores 266
2.3.460 Shaving Razors and Blades 266
2.3.461 Sheer Window Furnishings 267
2.3.462 Shellfish 267
2.3.463 Ship Building and Repairing 268
2.3.464 Single-Serving Dry Ambient Snacks 268
2.3.465 Skin Care Products 269
2.3.466 Slaughtering Animals Excluding Poultry 269
2.3.467 Sliced Cooked Meat 270
2.3.468 Slow-Release Household Fresheners 270
2.3.469 Smoked Salmon 271
2.3.470 Smoothies 271
2.3.471 Snack Fruit Pies 272
2.3.472 Socks, Stockings, and Tights 272
2.3.473 Soft Cheese 273
2.3.474 Soup 273
2.3.475 Space Heaters 274
2.3.476 Spice and Extract Manufacturing 274
2.3.477 Sporting Goods Retailers 275
2.3.478 Sports and Energy Drinks 275
2.3.479 Spreads and Margarines 276
2.3.480 Stacking Potato Chips 276
2.3.481 Standard and Bulk Ice Cream 277
2.3.482 Stationary Bicycles 277
2.3.483 Steel Mill Products 278
2.3.484 Stella Artois Lager Beer 278
2.3.485 Still Bottled Water 279
2.3.486 Stone Fruit 279
2.3.487 Storage Battery Manufacturing 280
2.3.488 Sugar Candy 280
2.3.489 Support Activities for Air Transportation 281
2.3.490 Surface Cleaners 281
2.3.491 Sweet Spreads 282
2.3.492 Switchgear and Switchboard Apparatus 282
2.3.493 Synthetic Rubber 283
2.3.494 Table Lamps 283
2.3.495 Taxicabs 284
2.3.496 Telecommunications Equipment 284
2.3.497 Telephone and Telegraph Facilities 285
2.3.498 Television Broadcasting 285
2.3.499 Temporary Employment Services 286
2.3.500 Tequila and Mescal Spirits 286
2.3.501 Testing Laboratories 287
2.3.502 Textile Fabrics 287
2.3.503 Tire Cord and Tire Fabric Mills 288
2.3.504 Tissues 288
2.3.505 Tobacco Products 289
2.3.506 Tortilla Manufacturing 289
2.3.507 Toy Stores 290
2.3.508 Traditional Toys 290
2.3.509 Trail Mix 291
2.3.510 Transformers 291
2.3.511 Transportation Equipment 292
2.3.512 Travel Trailer and Camper Manufacturing 292
2.3.513 Truck Trailer Manufacturing 293
2.3.514 Turkey Pieces 293
2.3.515 Ultra Disposable Diapers 294
2.3.516 Underwear, Nightwear, and Swimwear 294
2.3.517 Underwire Bras 295
2.3.518 Unleaded Gasoline 295
2.3.519 Upholstered Household Furniture Manufacturing 296
2.3.520 Used Car Dealers 296
2.3.521 Utilities 297
2.3.522 Vacuum Cleaners 297
2.3.523 Valves and Pipe Fittings 298
2.3.524 Vegetarian Foods 298
2.3.525 Venture Capital 299
2.3.526 Vertical Blinds 299
2.3.527 Video Cassette Recorders (VCRs) 300
2.3.528 Vienna and French Bread 300
2.3.529 Vodka 301
2.3.530 VoIP Telephone Service 301
2.3.531 Wallets and Purses 302
2.3.532 Washing Machines 302
2.3.533 Watches 303
2.3.534 Water Utilities 303
2.3.535 Weft Knit Fabric Mills 304
2.3.536 Welding and Soldering Equipment Manufacturing 304
2.3.537 Whiskey 305
2.3.538 White Bread 305
2.3.539 Whole Chicken Poultry 306
2.3.540 Window Blinds 306
2.3.541 Wine 307
2.3.542 Wineries 307
2.3.543 Wipes 308
2.3.544 Wireless Communication Services 308
2.3.545 Wiring Devices 309
2.3.546 Women’s Apparel and Accessories 309
2.3.547 Womenswear and Lingerie 310
2.3.548 Wood Preservation 310
2.3.549 Wool Yarn 311
2.3.550 Workers Compensation Insurance 311
2.3.551 Writing Instruments 312
2.3.552 Yarn Spinning Mills 312
2.3.553 Yellow Fats 313
2.3.554 Yogurt with Live Cultures 313
2.3.555 Definition of Terms 314
3 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 366
3.1 Disclaimers & Safe Harbor 366
3.2 ICON Group International, Inc. User Agreement Provisions 367
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