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Executive Report on Strategies in Jersey

Product Type: Market Research Report
Published by: Icon Group International, Inc.
Published: June 2007
Product Code: R307-25660
Description
How to Strategically Evaluate Jersey

Perhaps the most efficient way of evaluating Jersey 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 Jersey. Latent demand is largely driven by economic fundamentals.

In Chapter 2, I summarize the economic potential for Jersey 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 Jersey 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 Jersey as an area of dominant influence in Europe and, potentially, the world.

ECONOMIC AND PRODUCT MARKETS IN JERSEY
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 Jersey. The purpose of the studies is to understand the density of demand within Jersey and the extent to which Jersey might be used as a point of distribution within Europe. From an economic perspective, however, Jersey 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 Jersey 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 Jersey 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 Jersey 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 Jersey. Without Jersey, in other words, the market for satellite launch vehicles would be lower for the population in Jersey, Europe, or the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to both Europe and Jersey.

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 Jersey as an area of dominant influence in Europe and, potentially, the world.

Market Potential Estimation Methodology

Overview
This chapter covers the outlook for products in Jersey. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for Jersey (in millions of U.S. dollars). Comparative benchmarks allow the reader to quickly gauge Jersey 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 Jersey. 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 Jersey, 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 Jersey. 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 Jersey. Step 1. Product Definition and Data Collection
Any study of latent demand across countries and within Jersey 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 Jersey 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 Jersey 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 Jersey 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.
Table of Contents
1 INTRODUCTION & METHODOLOGY
1.1 What Does This Report Cover?
1.2 How to Strategically Evaluate Jersey
2 ECONOMIC AND PRODUCT MARKETS IN JERSEY
2.1 Introduction & Methodology
2.1.1 Overview & Methodology
2.1.2 Market Potential Estimation Methodology
2.2 Summary Rankings
2.3 Latent Demand Forecasts
2.3.1 60-Milligram Containers of Fromage Frais
2.3.2 Adhesives and Sealants
2.3.3 Advertising Services
2.3.4 Aerospace and Defense Equipment
2.3.5 Aftermarket Passenger Car Tires
2.3.6 Air Freight Services
2.3.7 Alcoholic Beverages
2.3.8 Ales and Stouts
2.3.9 Alimentary and Metabolism Pharmaceuticals
2.3.10 Alumina Refining
2.3.11 Aluminum Die-Casting Foundries
2.3.12 Amusement and Recreation Services
2.3.13 Analgesics
2.3.14 Analog Color Televisions
2.3.15 Antidepressant Pharmaceuticals
2.3.16 Antiperspirants and Deodorants
2.3.17 Apparel and Accessories
2.3.18 Appetizers and Dips
2.3.19 Apples
2.3.20 Applications Software
2.3.21 Application-Specific Integrated Circuits (ASICs)
2.3.22 Architectural Services
2.3.23 Athletic Footwear
2.3.24 Audio Components
2.3.25 Auto and Home Supply Stores
2.3.26 Aviation Services
2.3.27 Baby Formula
2.3.28 Bagged Chocolate Candy
2.3.29 Baked Goods
2.3.30 Bakery Products
2.3.31 Bananas
2.3.32 Bar Soap
2.3.33 Base Chemicals
2.3.34 Battery Eggs
2.3.35 Beauty and Barber Shops
2.3.36 Beer
2.3.37 Bicycles and Bicycle Accessories
2.3.38 Biotechnology
2.3.39 Bituminous Coal
2.3.40 Blended Whiskey
2.3.41 Board Games and Puzzles
2.3.42 Boat Building
2.3.43 Boilers
2.3.44 Book Publishing
2.3.45 Bottled Water
2.3.46 Bottles of Lager Beer
2.3.47 Boutique Hotels
2.3.48 Boys’ School Uniforms
2.3.49 Bras and Allied Garments
2.3.50 Bread
2.3.51 Breakfast Cereals
2.3.52 Breweries
2.3.53 Broadband Internet Access
2.3.54 Broadwoven Fabric Finishing Mills
2.3.55 Broom, Brush, and Mop Manufacturing
2.3.56 Brown and Wholemeal Bread
2.3.57 Building Materials and Garden Supplies
2.3.58 Built-In Electric Ovens
2.3.59 Business and School Supplies
2.3.60 Butcher Shops
2.3.61 Cable TV
2.3.62 CAD/CAM/CAE Software
2.3.63 Cafes and Restaurants
2.3.64 Cakes and Pastries
2.3.65 Camcorders
2.3.66 Camera and Photographic Supplies Stores
2.3.67 Campgrounds and Recreational Vehicle Parks
2.3.68 Candles
2.3.69 Candy
2.3.70 Cans of Lager Beer
2.3.71 Car Aftermarket Products
2.3.72 Casinos and Gambling
2.3.73 Cat Food
2.3.74 CD Players
2.3.75 Cellular Telephones
2.3.76 Cement Construction Materials
2.3.77 Cemeteries and Crematories
2.3.78 Chemicals
2.3.79 Cherry-Flavored Bottled Water
2.3.80 Chewing and Bubble Gum
2.3.81 Children's Chicken Nugget Ready Meals
2.3.82 Chilled and Deli Food
2.3.83 Chips and Crisps
2.3.84 Chocolate Candy
2.3.85 Cigarette Manufacturing
2.3.86 Cigars and Cigarillos
2.3.87 Citrus Fruit
2.3.88 Civil Aerospace Equipment
2.3.89 Clay Building Products
2.3.90 Clothing Accessories
2.3.91 Coated and Flavored Nuts
2.3.92 Coin-Operated Laundries and Dry Cleaners
2.3.93 Colas
2.3.94 Collection Agencies
2.3.95 Color Televisions
2.3.96 Combination Refrigerator-Freezers
2.3.97 Commercial Banking
2.3.98 Communications Services
2.3.99 Compact Discs (CDs)
2.3.100 Complete Dry Dog Food
2.3.101 Computer Hardware
2.3.102 Concrete Building Products
2.3.103 Console Video Games
2.3.104 Construction and Engineering Services
2.3.105 Consumer Chemicals
2.3.106 Contact Lenses
2.3.107 Continental and Specialty Plant Bread
2.3.108 Convenience Stores
2.3.109 Conventional Mineral Oil
2.3.110 Cookies and Crackers
2.3.111 Cooking Ranges
2.3.112 Copper Ores
2.3.113 Corporate Strategy Services
2.3.114 Cosmetics and Toiletries
2.3.115 Costume Jewelry
2.3.116 Cotton Yarn
2.3.117 Cough and Cold Remedies
2.3.118 Craft Bread
2.3.119 Credit Bureaus
2.3.120 Cross/utility Vehicles (CUVs)
2.3.121 Crude Petroleum and Natural Gas Extraction
2.3.122 Cruise Ship Tourism
2.3.123 Crushed and Broken Stone
2.3.124 Crushing Oilseeds and Tree Nuts Excluding Soybeans
2.3.125 Current-Carrying Wiring Device Manufacturing
2.3.126 Curtain and Drapery Mills
2.3.127 Custom Draperies
2.3.128 Daily Newspapers
2.3.129 Dairy Cream
2.3.130 Dark Brandy
2.3.131 Data Processing and Network Services
2.3.132 Defense Industry Equipment
2.3.133 Deli Food
2.3.134 Deluxe and Malt Whiskey
2.3.135 Department Stores
2.3.136 Depository Credit Intermediation
2.3.137 Designer Bath and Shower Products
2.3.138 Desktop Personal Computers
2.3.139 Diabetes Monitoring Devices
2.3.140 Dial-Up Internet Access
2.3.141 Diesel Trucks
2.3.142 Dietary Supplements
2.3.143 Digestion Aids
2.3.144 Digital Cameras
2.3.145 Dining Out
2.3.146 Dips
2.3.147 Direct Selling Establishments
2.3.148 Discount Superstores
2.3.149 Discrete Semiconductors
2.3.150 Dishwashing Products
2.3.151 Disposable Health Care Equipment and Supplies
2.3.152 Distillate Fuel Oil
2.3.153 Distilleries
2.3.154 Dog Food
2.3.155 Dolls and Figures
2.3.156 Domestic Water Utilities
2.3.157 DRAM (dynamic Random Access Memory)
2.3.158 Draught Lager Beer
2.3.159 Dried Food
2.3.160 Drink Concentrates
2.3.161 Drug Delivery Systems
2.3.162 Durable Goods
2.3.163 DVD Players
2.3.164 Eating and Drinking Places
2.3.165 Economy Disposable Diapers
2.3.166 Edible Oils
2.3.167 Education and Training Services
2.3.168 Electron Tubes
2.3.169 Elementary and Secondary Schools
2.3.170 Engineering Services
2.3.171 Envelope Manufacturing
2.3.172 Environmental Consulting Services
2.3.173 Ethnic Hair Care Products
2.3.174 Everyday Cookies
2.3.175 Explosives Manufacturing
2.3.176 Extended Stay and Business Suite Motels
2.3.177 Exterminating and Pest Control Services
2.3.178 External Sanitary Protection Products
2.3.179 Facial Cosmetics
2.3.180 Family Clothing Stores
2.3.181 Farm Machinery and Equipment
2.3.182 Fast Food
2.3.183 Fax Machines
2.3.184 Feminine Sanitary Protection
2.3.185 Fermented Sauces
2.3.186 Fiber-Optic Cable Manufacturing
2.3.187 Film Cameras
2.3.188 Financial Services
2.3.189 Fixed-Line Telecommunications Services
2.3.190 Flash Memory
2.3.191 Flat Glass
2.3.192 Floor Coverings
2.3.193 Flour Milling
2.3.194 Folding Paperboard Boxes
2.3.195 Food Advertising
2.3.196 Forestry and Fishing
2.3.197 Fossil Fuel-Powered Electric Power Generation
2.3.198 Fragrances
2.3.199 Franchising
2.3.200 Free-Range Eggs
2.3.201 Freestanding Electric Ranges
2.3.202 Freeze-Dried Instant Coffee
2.3.203 Fresh Beef and Veal
2.3.204 Fruit Drinks
2.3.205 Fuel Dealers
2.3.206 Funeral Homes
2.3.207 Gambling
2.3.208 Gaming Computer Systems
2.3.209 Gardening Supplies, Outdoor Furniture, and Plants
2.3.210 General Merchandise stores
2.3.211 Generic Prescription Drugs
2.3.212 Gift, Novelty, and Souvenir Stores
2.3.213 Gifts
2.3.214 Gin
2.3.215 Girls' Dresses and Blouses
2.3.216 Glass Container Manufacturing
2.3.217 Global Positioning System (GPS) Receivers
2.3.218 Gold Ores
2.3.219 Golf Equipment
2.3.220 Gourmet Potato Chips
2.3.221 Government Public Health Activities
2.3.222 Granola Bars and Breakfast Cereal Bars
2.3.223 Grape Juice
2.3.224 Graphic Design Services
2.3.225 Green Vegetables
2.3.226 Greeting Cards
2.3.227 Grocery Discounters
2.3.228 GSM-Based Cellular Telephones
2.3.229 Guided Missiles and Space Vehicles
2.3.230 Gypsum Products
2.3.231 Hair Tinting and Coloring Products
2.3.232 Hard Cheese
2.3.233 HDTV
2.3.234 Health Care Equipment and Supplies
2.3.235 Heating and Cooling Appliances
2.3.236 Highly Refined Mineral Oil
2.3.237 Highway and Street Construction
2.3.238 Hispanic Music Television
2.3.239 Hi-Tech Logistics
2.3.240 Hobby, Toy, and Game Stores
2.3.241 Home Improvement Retailers
2.3.242 Hospital Food Service
2.3.243 Household Textiles and Soft Furnishings
2.3.244 Human Resource Management Services
2.3.245 Hunting, Trapping, and Game Propagation
2.3.246 Ice Cream
2.3.247 Imported Whiskey
2.3.248 Impulse Ice Cream
2.3.249 In Vitro Diagnostic Equipment
2.3.250 IP-Based Enterprise Networking Equipment
2.3.251 Iron Ore Mining
2.3.252 Janitorial Services
2.3.253 Jewelry Stores
2.3.254 Juice
2.3.255 Kiln Furniture
2.3.256 Kitchen Appliances
2.3.257 Knitwear
2.3.258 Kraft Foods Brand Cookies
2.3.259 Lager Beer
2.3.260 Laptop Computers
2.3.261 Large Household Appliances
2.3.262 Lawn and Garden Equipment and Supplies Stores
2.3.263 Leather and Leather Products
2.3.264 Legal Services
2.3.265 Leisure Education
2.3.266 Lemonade
2.3.267 Lemon-Flavored Bottled Water
2.3.268 Life Insurance Sold by Life Insurance Companies
2.3.269 Linen and Uniform Supply
2.3.270 Lingerie
2.3.271 Lip and Multiuse Color Cosmetics
2.3.272 Liquefied Petroleum Gas
2.3.273 Liqueurs
2.3.274 Local and Interurban Passenger Transit
2.3.275 Logging
2.3.276 Logistics for the Pharmaceutical Industry
2.3.277 Low-Carbohydrate Beer
2.3.278 Low-Fat Spreads
2.3.279 Luggage Manufacturing
2.3.280 Lumber and Wood Products
2.3.281 Machine Tools
2.3.282 Machining Precision Turned Products
2.3.283 Magazines
2.3.284 Mainstream Tea
2.3.285 Malt Beverages
2.3.286 Management Consulting Services
2.3.287 Manifold Business Forms
2.3.288 Manmade Fabric Mills
2.3.289 Manufactured Mobile Home Dealers
2.3.290 Manufacturing Dog and Cat Food
2.3.291 Marine Freight Services
2.3.292 Marketing Research and Public Opinion Polling
2.3.293 Mass Reproduction of Computer Software
2.3.294 Materials Handling Machinery
2.3.295 Meal Replacement Drinks
2.3.296 Measuring and Controlling Instruments
2.3.297 Meat and Poultry
2.3.298 Media Advertising
2.3.299 Medical Biotechnology
2.3.300 Medicated Skin Care
2.3.301 Medium and Heavy Trucks
2.3.302 Men’s Accessories
2.3.303 Men's Grooming Products
2.3.304 Menswear
2.3.305 Menthol Cigarettes
2.3.306 Millwork
2.3.307 Mineral Water
2.3.308 Mink Fur Coats
2.3.309 Mixing Ingredients to Make Fertilizer
2.3.310 Model Wheeled Vehicles
2.3.311 Modems
2.3.312 Moist Cat Food
2.3.313 Morning Bakery Goods
2.3.314 Motor Vehicles and Motor Vehicle Equipment
2.3.315 Mountain Bikes
2.3.316 Mushrooms
2.3.317 Music and Video Game Stores
2.3.318 NAND Flash Memory Cards
2.3.319 National Newspapers
2.3.320 Net, Lace, and Voile Curtains
2.3.321 Network Hubs
2.3.322 New Car Dealers
2.3.323 Nitrogenous Fertilizer Manufacturing
2.3.324 Non-Airport Car Rentals
2.3.325 Non-Chocolate Confectionery Manufacturing
2.3.326 Non-Citrus Fruit
2.3.327 Non-Current-Carrying Wiring Device Manufacturing
2.3.328 Non-Daily Newspapers
2.3.329 Non-Depository Credit Intermediation
2.3.330 Non-Durable Goods
2.3.331 Non-Farm Housing Services
2.3.332 Non-Ferrous Forging
2.3.333 Non-Food Retail Sales
2.3.334 Non-Interest Commercial Banking
2.3.335 Non-Metallic Mineral Mining and Quarrying
2.3.336 Non-Residential Construction and Engineering
2.3.337 Non-Store Retailers and Mail Order
2.3.338 Non-Wood Office Furniture Manufacturing
2.3.339 Nonwoven Fabric Mills
2.3.340 Nuclear Electric Power Generation
2.3.341 Nursery, Garden Center, and Farm Supply Stores
2.3.342 Nursing Homes
2.3.343 Office Supplies and Stationery Stores
2.3.344 Oil
2.3.345 Oil, Gas, and Mining Exploration Services
2.3.346 Oils and Fats
2.3.347 Onions and Shallots
2.3.348 Online Analytical Processing (OLAP)
2.3.349 Operations Management Services
2.3.350 Ophthalmic Goods Manufacturing
2.3.351 Optical Goods and Eye Care Products
2.3.352 Oral Drug Delivery Systems
2.3.353 Orange Juice
2.3.354 Organic Beverages
2.3.355 OTC Healthcare Products
2.3.356 Outdoor Games
2.3.357 Outerwear Clothing and Accessories
2.3.358 Outsourcing Services
2.3.359 Ovens and Stoves
2.3.360 Over-The-Counter Drugs
2.3.361 Packaged Nuts
2.3.362 Packaging and Labeling Services
2.3.363 Paid Internet Search Advertising
2.3.364 Paint and Wallpaper Stores
2.3.365 Paper Towels
2.3.366 Parking Lots, Garages, and Valet Parking Services
2.3.367 Passenger Transportation
2.3.368 Passive Components
2.3.369 Pasta and Noodles
2.3.370 PC Video Game Software
2.3.371 Pears
2.3.372 Periodicals
2.3.373 Perishable Prepared Foods Manufacturing
2.3.374 Permanent Employment Services
2.3.375 Personal Stationery
2.3.376 Pet Care Products
2.3.377 Pharmacies and Drug Stores
2.3.378 Phosphatic Fertilizer Manufacturing
2.3.379 Photo Printers
2.3.380 Physicians' Services
2.3.381 Pizzas
2.3.382 Plant Bread
2.3.383 Plastic Housewares
2.3.384 Plumbing Products
2.3.385 Plush Toys
2.3.386 Pollution Control Equipment and Services
2.3.387 Polymerase Chain Reaction (PCR) Machines
2.3.388 Popcorn
2.3.389 Pork Pies
2.3.390 Port and Shipbuilding Equipment
2.3.391 Potash, Soda, and Boratic Minerals Mining
2.3.392 Potato Chips
2.3.393 Poultry Products
2.3.394 Powder Detergents
2.3.395 Precious Metal Jewelry and Personal Articles
2.3.396 Prefabricated Metal Buildings
2.3.397 Pre-Recorded Cassettes
2.3.398 Prerecorded Tape, Compact Disc, and Record Stores
2.3.399 Prescription Eyeglass Frames
2.3.400 Presentation Materials
2.3.401 Primary Metal Industries
2.3.402 Printed Circuit Boards
2.3.403 Printers
2.3.404 Printing Special Business Forms and Checkbooks
2.3.405 Private Residential Construction
2.3.406 Professional Computer Services
2.3.407 Programmable Logic Devices
2.3.408 Property and Casualty Insurance
2.3.409 Public Residential Construction
2.3.410 Publishing Advertising
2.3.411 Pubs, Clubs, and Nightclubs
2.3.412 Pulmonary Drug Delivery Systems
2.3.413 Pulp Mills
2.3.414 Radiators and Pumps
2.3.415 Radio and Television Broadcasting
2.3.416 Railroad Freight Services
2.3.417 Ready Pasta
2.3.418 Real Jewelry
2.3.419 Reconstituted Wood Products
2.3.420 Recorded Music
2.3.421 Recreational Vehicle Dealers
2.3.422 Red Meat
2.3.423 Refining Cane Sugar from Raw Cane Sugar
2.3.424 Refrigeration Appliances
2.3.425 Regional Newspapers
2.3.426 Relays and Industrial Controls
2.3.427 Remediation Services
2.3.428 Rendering Animal Fat, Bones, and Meat Scraps
2.3.429 Renewable Energy Equipment
2.3.430 Replacement Tires for Cars and Light Vans
2.3.431 Residential Construction
2.3.432 Residual Fuel Oil
2.3.433 Retail Logistics
2.3.434 Retirement Savings Plans
2.3.435 Reupholstery and Furniture Repair
2.3.436 Rice Milling
2.3.437 Ride-On Toys
2.3.438 Root Vegetables
2.3.439 Salad Accompaniments
2.3.440 Salon Hair Care Products
2.3.441 Salt and Vinegar Potato Chips
2.3.442 Sandwich Spreads
2.3.443 Sanitary Protection Products
2.3.444 Sauces, Salad Dressings, and Condiments
2.3.445 Savory Snacks
2.3.446 Sawmills
2.3.447 Scanners
2.3.448 School Food Service
2.3.449 Scrap Recycling
2.3.450 Screw Machine Products
2.3.451 Seafood Canning
2.3.452 Seasonal Cookies
2.3.453 Secondary Smelting and Alloying of Aluminum
2.3.454 Security and Commodity Brokers and Dealers
2.3.455 Sensors
2.3.456 Services
2.3.457 Sewer Facilities
2.3.458 Sewing, Needlework, and Piece Goods Stores
2.3.459 Shampoo
2.3.460 Shaving Razors and Blades
2.3.461 Sheer Window Furnishings
2.3.462 Shellfish
2.3.463 Ship Building and Repairing
2.3.464 Silicone Contact Lenses
2.3.465 Single-Serving Dry Ambient Snacks
2.3.466 Skin Care Products
2.3.467 Slaughtering Animals Excluding Poultry
2.3.468 Sliced Cooked Meat
2.3.469 Slow-Release Household Fresheners
2.3.470 Smart Cars
2.3.471 Smoothies
2.3.472 Socks, Stockings, and Tights
2.3.473 Soup
2.3.474 Space Heaters
2.3.475 Spice and Extract Manufacturing
2.3.476 Sporting Goods Retailers
2.3.477 Sports and Energy Drinks
2.3.478 Spreads and Margarines
2.3.479 Stacking Potato Chips
2.3.480 Standard and Bulk Ice Cream
2.3.481 Stationary Bicycles
2.3.482 Steel Mill Products
2.3.483 Stella Artois Lager Beer
2.3.484 Still Bottled Water
2.3.485 Stone Fruit
2.3.486 Storage Battery Manufacturing
2.3.487 Sugar Candy
2.3.488 Support Activities for Air Transportation
2.3.489 Surface Cleaners
2.3.490 Sweet Spreads
2.3.491 Switchgear and Switchboard Apparatus
2.3.492 Synthetic Rubber
2.3.493 Table Lamps
2.3.494 Taxicabs
2.3.495 Telecommunications Equipment
2.3.496 Telephone and Telegraph Facilities
2.3.497 Television Broadcasting
2.3.498 Temporary Employment Services
2.3.499 Tequila and Mescal Spirits
2.3.500 Testing Laboratories
2.3.501 Textile Fabrics
2.3.502 Tire Cord and Tire Fabric Mills
2.3.503 Tissues
2.3.504 Tobacco Products
2.3.505 Tortilla Manufacturing
2.3.506 Toy Stores
2.3.507 Traditional Toys
2.3.508 Trail Mix
2.3.509 Transformers
2.3.510 Transportation Equipment
2.3.511 Travel Trailer and Camper Manufacturing
2.3.512 Truck Trailer Manufacturing
2.3.513 Turkey Pieces
2.3.514 Ultra Disposable Diapers
2.3.515 Underwear, Nightwear, and Swimwear
2.3.516 Underwire Bras
2.3.517 Unleaded Gasoline
2.3.518 Upholstered Household Furniture Manufacturing
2.3.519 Used Car Dealers
2.3.520 Utilities
2.3.521 Vacuum Cleaners
2.3.522 Valves and Pipe Fittings
2.3.523 Vegetarian Foods
2.3.524 Venture Capital
2.3.525 Vertical Blinds
2.3.526 Video Cassette Recorders (VCRs)
2.3.527 Vienna and French Bread
2.3.528 Vodka
2.3.529 VoIP Telephone Service
2.3.530 Washing Machines
2.3.531 Watches
2.3.532 Water Utilities
2.3.533 Web Servers
2.3.534 Wedding Dresses
2.3.535 Weft Knit Fabric Mills
2.3.536 Welding and Soldering Equipment Manufacturing
2.3.537 Whiskey
2.3.538 White Bread
2.3.539 Whole Chicken Poultry
2.3.540 Window Blinds
2.3.541 Wine
2.3.542 Wineries
2.3.543 Wipes
2.3.544 Wireless Communication Services
2.3.545 Wiring Devices
2.3.546 Women’s Apparel and Accessories
2.3.547 Womenswear and Lingerie
2.3.548 Wood Preservation
2.3.549 Wool Yarn
2.3.550 Workers' Compensation Insurance
2.3.551 Writing Instruments
2.3.552 Yarn Spinning Mills
2.3.553 Yellow Fats
2.3.554 Yogurt with Live Cultures
2.3.555 Definition of Terms
3 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS
3.1 Disclaimers & Safe Harbor
3.2 ICON Group International, Inc. User Agreement Provisions
Ordering and More Information
Price and Delivery Options


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