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Executive Report on Strategies in San Marino

Product Type: Market Research Report
Published by: Icon Group International, Inc.
Published: June 2007
Product Code: R307-25669
Description
How to Strategically Evaluate San Marino

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

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

ECONOMIC AND PRODUCT MARKETS IN SAN MARINO
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 San Marino. The purpose of the studies is to understand the density of demand within San Marino and the extent to which San Marino might be used as a point of distribution within Europe. From an economic perspective, however, San Marino 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 San Marino 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 San Marino 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 San Marino 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 San Marino. Without San Marino, in other words, the market for satellite launch vehicles would be lower for the population in San Marino, 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 San Marino.

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 San Marino 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 San Marino. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for San Marino (in millions of U.S. dollars). Comparative benchmarks allow the reader to quickly gauge San Marino 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 San Marino. 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 San Marino, 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 San Marino. 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 San Marino.

Step 1. Product Definition and Data Collection
Any study of latent demand across countries and within San Marino 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 San Marino 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 San Marino 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 San Marino 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 San Marino
2 ECONOMIC AND PRODUCT MARKETS IN SAN MARINO
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 Butter
2.3.62 Cable TV
2.3.63 CAD/CAM/CAE Software
2.3.64 Cafes and Restaurants
2.3.65 Cakes and Pastries
2.3.66 Camcorders
2.3.67 Camera and Photographic Supplies Stores
2.3.68 Campgrounds and Recreational Vehicle Parks
2.3.69 Candles
2.3.70 Candy
2.3.71 Cans of Lager Beer
2.3.72 Car Aftermarket Products
2.3.73 Casinos and Gambling
2.3.74 Cat Food
2.3.75 CD Players
2.3.76 Cellular Telephones
2.3.77 Cement Construction Materials
2.3.78 Cemeteries and Crematories
2.3.79 Chemicals
2.3.80 Cherry-Flavored Bottled Water
2.3.81 Chewing and Bubble Gum
2.3.82 Children's Chicken Nugget Ready Meals
2.3.83 Chilled and Deli Food
2.3.84 Chips and Crisps
2.3.85 Chocolate Candy
2.3.86 Cigarette Manufacturing
2.3.87 Cigars and Cigarillos
2.3.88 Citrus Fruit
2.3.89 Civil Aerospace Equipment
2.3.90 Clay Building Products
2.3.91 Clothing Accessories
2.3.92 Coated and Flavored Nuts
2.3.93 Coin-Operated Laundries and Dry Cleaners
2.3.94 Colas
2.3.95 Collection Agencies
2.3.96 Color Televisions
2.3.97 Combination Refrigerator-Freezers
2.3.98 Commercial Banking
2.3.99 Communications Services
2.3.100 Compact Discs (CDs)
2.3.101 Complete Dry Dog Food
2.3.102 Computer Hardware
2.3.103 Concrete Building Products
2.3.104 Console Video Games
2.3.105 Construction and Engineering Services
2.3.106 Consumer Chemicals
2.3.107 Contact Lenses
2.3.108 Continental and Specialty Plant Bread
2.3.109 Convenience Stores
2.3.110 Conventional Mineral Oil
2.3.111 Cookies and Crackers
2.3.112 Cooking Ranges
2.3.113 Copper Ores
2.3.114 Corporate Strategy Services
2.3.115 Cosmetics and Toiletries
2.3.116 Costume Jewelry
2.3.117 Cotton Yarn
2.3.118 Cough and Cold Remedies
2.3.119 Craft Bread
2.3.120 Credit Bureaus
2.3.121 Cross/utility Vehicles (CUVs)
2.3.122 Crude Petroleum and Natural Gas Extraction
2.3.123 Cruise Ship Tourism
2.3.124 Crushed and Broken Stone
2.3.125 Crushing Oilseeds and Tree Nuts Excluding Soybeans
2.3.126 Current-Carrying Wiring Device Manufacturing
2.3.127 Curtain and Drapery Mills
2.3.128 Custom Draperies
2.3.129 Daily Newspapers
2.3.130 Dairy Cream
2.3.131 Dark Brandy
2.3.132 Data Processing and Network Services
2.3.133 Defense Industry Equipment
2.3.134 Deli Food
2.3.135 Deluxe and Malt Whiskey
2.3.136 Department Stores
2.3.137 Depository Credit Intermediation
2.3.138 Designer Bath and Shower Products
2.3.139 Desktop Personal Computers
2.3.140 Diabetes Monitoring Devices
2.3.141 Dial-Up Internet Access
2.3.142 Diesel Trucks
2.3.143 Dietary Supplements
2.3.144 Digestion Aids
2.3.145 Digital Cameras
2.3.146 Dining Out
2.3.147 Dips
2.3.148 Direct Selling Establishments
2.3.149 Discount Superstores
2.3.150 Discrete Semiconductors
2.3.151 Dishwashing Products
2.3.152 Disposable Health Care Equipment and Supplies
2.3.153 Distillate Fuel Oil
2.3.154 Distilleries
2.3.155 Dog Food
2.3.156 Dolls and Figures
2.3.157 Domestic Water Utilities
2.3.158 DRAM (dynamic Random Access Memory)
2.3.159 Draught Lager Beer
2.3.160 Dried Food
2.3.161 Drink Concentrates
2.3.162 Drug Delivery Systems
2.3.163 Durable Goods
2.3.164 DVD Players
2.3.165 Eating and Drinking Places
2.3.166 Economy Disposable Diapers
2.3.167 Edible Oils
2.3.168 Education and Training Services
2.3.169 Electron Tubes
2.3.170 Elementary and Secondary Schools
2.3.171 Engineering Services
2.3.172 Envelope Manufacturing
2.3.173 Environmental Consulting Services
2.3.174 Ethnic Hair Care Products
2.3.175 Everyday Cookies
2.3.176 Explosives Manufacturing
2.3.177 Extended Stay and Business Suite Motels
2.3.178 Exterminating and Pest Control Services
2.3.179 External Sanitary Protection Products
2.3.180 Facial Cosmetics
2.3.181 Family Clothing Stores
2.3.182 Farm Machinery and Equipment
2.3.183 Fast Food
2.3.184 Fax Machines
2.3.185 Feminine Sanitary Protection
2.3.186 Fermented Sauces
2.3.187 Fiber-Optic Cable Manufacturing
2.3.188 Film Cameras
2.3.189 Financial Services
2.3.190 Fixed-Line Telecommunications Services
2.3.191 Flash Memory
2.3.192 Flat Glass
2.3.193 Floor Coverings
2.3.194 Flour Milling
2.3.195 Folding Paperboard Boxes
2.3.196 Food Advertising
2.3.197 Forestry and Fishing
2.3.198 Fossil Fuel-Powered Electric Power Generation
2.3.199 Fragrances
2.3.200 Franchising
2.3.201 Free-Range Eggs
2.3.202 Freestanding Electric Ranges
2.3.203 Freeze-Dried Instant Coffee
2.3.204 Fresh Beef and Veal
2.3.205 Fruit Drinks
2.3.206 Fuel Dealers
2.3.207 Funeral Homes
2.3.208 Gambling
2.3.209 Gaming Computer Systems
2.3.210 Gardening Supplies, Outdoor Furniture, and Plants
2.3.211 General Merchandise stores
2.3.212 Generic Prescription Drugs
2.3.213 Gift, Novelty, and Souvenir Stores
2.3.214 Gifts
2.3.215 Gin
2.3.216 Girls' Dresses and Blouses
2.3.217 Glass Container Manufacturing
2.3.218 Global Positioning System (GPS) Receivers
2.3.219 Gold Ores
2.3.220 Golf Equipment
2.3.221 Gourmet Potato Chips
2.3.222 Government Public Health Activities
2.3.223 Granola Bars and Breakfast Cereal Bars
2.3.224 Grape Juice
2.3.225 Graphic Design Services
2.3.226 Green Vegetables
2.3.227 Greeting Cards
2.3.228 Grocery Discounters
2.3.229 GSM-Based Cellular Telephones
2.3.230 Guided Missiles and Space Vehicles
2.3.231 Gypsum Products
2.3.232 Hair Tinting and Coloring Products
2.3.233 Hard Cheese
2.3.234 HDTV
2.3.235 Health Care Equipment and Supplies
2.3.236 Heating and Cooling Appliances
2.3.237 Highly Refined Mineral Oil
2.3.238 Highway and Street Construction
2.3.239 Hispanic Music Television
2.3.240 Hi-Tech Logistics
2.3.241 Hobby, Toy, and Game Stores
2.3.242 Home Improvement Retailers
2.3.243 Hospital Food Service
2.3.244 Household Textiles and Soft Furnishings
2.3.245 Human Resource Management Services
2.3.246 Hunting, Trapping, and Game Propagation
2.3.247 Ice Cream
2.3.248 Imported Whiskey
2.3.249 Impulse Ice Cream
2.3.250 In Vitro Diagnostic Equipment
2.3.251 IP-Based Enterprise Networking Equipment
2.3.252 Iron Ore Mining
2.3.253 Janitorial Services
2.3.254 Jewelry Stores
2.3.255 Juice
2.3.256 Kiln Furniture
2.3.257 Kitchen Appliances
2.3.258 Knitwear
2.3.259 Kraft Foods Brand Cookies
2.3.260 Lager Beer
2.3.261 Laptop Computers
2.3.262 Large Household Appliances
2.3.263 Lawn and Garden Equipment and Supplies Stores
2.3.264 Leather and Leather Products
2.3.265 Legal Services
2.3.266 Leisure Education
2.3.267 Lemonade
2.3.268 Lemon-Flavored Bottled Water
2.3.269 Life Insurance Sold by Life Insurance Companies
2.3.270 Linen and Uniform Supply
2.3.271 Lingerie
2.3.272 Lip and Multiuse Color Cosmetics
2.3.273 Liquefied Petroleum Gas
2.3.274 Liqueurs
2.3.275 Local and Interurban Passenger Transit
2.3.276 Logging
2.3.277 Logistics for the Pharmaceutical Industry
2.3.278 Low-Carbohydrate Beer
2.3.279 Low-Fat Spreads
2.3.280 Luggage Manufacturing
2.3.281 Lumber and Wood Products
2.3.282 Machine Tools
2.3.283 Machining Precision Turned Products
2.3.284 Magazines
2.3.285 Mainstream Tea
2.3.286 Malt Beverages
2.3.287 Management Consulting Services
2.3.288 Manifold Business Forms
2.3.289 Manmade Fabric Mills
2.3.290 Manufactured Mobile Home Dealers
2.3.291 Manufacturing Dog and Cat Food
2.3.292 Marine Freight Services
2.3.293 Marketing Research and Public Opinion Polling
2.3.294 Mass Reproduction of Computer Software
2.3.295 Materials Handling Machinery
2.3.296 Meal Replacement Drinks
2.3.297 Measuring and Controlling Instruments
2.3.298 Meat and Poultry
2.3.299 Media Advertising
2.3.300 Medical Biotechnology
2.3.301 Medicated Skin Care
2.3.302 Medium and Heavy Trucks
2.3.303 Men’s Accessories
2.3.304 Men's Grooming Products
2.3.305 Menswear
2.3.306 Menthol Cigarettes
2.3.307 Millwork
2.3.308 Mineral Water
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 Nuts
2.3.344 Office Supplies and Stationery Stores
2.3.345 Oil
2.3.346 Oil, Gas, and Mining Exploration Services
2.3.347 Oils and Fats
2.3.348 Onions and Shallots
2.3.349 Online Analytical Processing (OLAP)
2.3.350 Operations Management Services
2.3.351 Ophthalmic Goods Manufacturing
2.3.352 Optical Goods and Eye Care Products
2.3.353 Oral Drug Delivery Systems
2.3.354 Orange Juice
2.3.355 Organic Beverages
2.3.356 OTC Healthcare Products
2.3.357 Outdoor Games
2.3.358 Outerwear Clothing and Accessories
2.3.359 Outsourcing Services
2.3.360 Ovens and Stoves
2.3.361 Over-The-Counter Drugs
2.3.362 Packaged Nuts
2.3.363 Packaging and Labeling Services
2.3.364 Paid Internet Search Advertising
2.3.365 Paint and Wallpaper Stores
2.3.366 Paper Towels
2.3.367 Parking Lots, Garages, and Valet Parking Services
2.3.368 Passenger Transportation
2.3.369 Passive Components
2.3.370 Pasta and Noodles
2.3.371 PC Video Game Software
2.3.372 Pears
2.3.373 Periodicals
2.3.374 Perishable Prepared Foods Manufacturing
2.3.375 Permanent Employment Services
2.3.376 Personal Stationery
2.3.377 Pet Care Products
2.3.378 Pharmacies and Drug Stores
2.3.379 Phosphatic Fertilizer Manufacturing
2.3.380 Photo Printers
2.3.381 Physicians' Services
2.3.382 Pizzas
2.3.383 Plant Bread
2.3.384 Plastic Housewares
2.3.385 Plumbing Products
2.3.386 Plush Toys
2.3.387 Pollution Control Equipment and Services
2.3.388 Polymerase Chain Reaction (PCR) Machines
2.3.389 Popcorn
2.3.390 Pork Pies
2.3.391 Port and Shipbuilding Equipment
2.3.392 Potash, Soda, and Boratic Minerals Mining
2.3.393 Potato Chips
2.3.394 Poultry Products
2.3.395 Powder Detergents
2.3.396 Precious Metal Jewelry and Personal Articles
2.3.397 Prefabricated Metal Buildings
2.3.398 Pre-Recorded Cassettes
2.3.399 Prerecorded Tape, Compact Disc, and Record Stores
2.3.400 Prescription Eyeglass Frames
2.3.401 Presentation Materials
2.3.402 Primary Metal Industries
2.3.403 Printed Circuit Boards
2.3.404 Printers
2.3.405 Printing Special Business Forms and Checkbooks
2.3.406 Private Residential Construction
2.3.407 Professional Computer Services
2.3.408 Programmable Logic Devices
2.3.409 Property and Casualty Insurance
2.3.410 Public Residential Construction
2.3.411 Publishing Advertising
2.3.412 Pubs, Clubs, and Nightclubs
2.3.413 Pulmonary Drug Delivery Systems
2.3.414 Pulp Mills
2.3.415 Radiators and Pumps
2.3.416 Radio and Television Broadcasting
2.3.417 Railroad Freight Services
2.3.418 Ready Pasta
2.3.419 Real Jewelry
2.3.420 Reconstituted Wood Products
2.3.421 Recorded Music
2.3.422 Recreational Vehicle Dealers
2.3.423 Red Meat
2.3.424 Refining Cane Sugar from Raw Cane Sugar
2.3.425 Refrigeration Appliances
2.3.426 Regional Newspapers
2.3.427 Relays and Industrial Controls
2.3.428 Remediation Services
2.3.429 Rendering Animal Fat, Bones, and Meat Scraps
2.3.430 Renewable Energy Equipment
2.3.431 Replacement Tires for Cars and Light Vans
2.3.432 Residential Construction
2.3.433 Residual Fuel Oil
2.3.434 Retail Logistics
2.3.435 Retirement Savings Plans
2.3.436 Reupholstery and Furniture Repair
2.3.437 Rice Milling
2.3.438 Ride-On Toys
2.3.439 Root Vegetables
2.3.440 Salad Accompaniments
2.3.441 Salon Hair Care Products
2.3.442 Salt and Vinegar Potato Chips
2.3.443 Sandwich Spreads
2.3.444 Sanitary Protection Products
2.3.445 Sauces, Salad Dressings, and Condiments
2.3.446 Savory Snacks
2.3.447 Sawmills
2.3.448 Scanners
2.3.449 School Food Service
2.3.450 Scrap Recycling
2.3.451 Screw Machine Products
2.3.452 Seafood Canning
2.3.453 Seasonal Cookies
2.3.454 Secondary Smelting and Alloying of Aluminum
2.3.455 Security and Commodity Brokers and Dealers
2.3.456 Sensors
2.3.457 Services
2.3.458 Sewer Facilities
2.3.459 Sewing, Needlework, and Piece Goods Stores
2.3.460 Shampoo
2.3.461 Shaving Razors and Blades
2.3.462 Sheer Window Furnishings
2.3.463 Shellfish
2.3.464 Ship Building and Repairing
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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