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Executive Report on Strategies in the U.S. Virgin Islands

Published by: Icon Group International, Inc.

Published: Jun. 27, 2007 - 368 Pages


Table of Contents


1 INTRODUCTION & METHODOLOGY
1.1 What Does This Report Cover?
1.2 How to Strategically Evaluate the U.S. Virgin Islands
2 ECONOMIC AND PRODUCT MARKETS IN THE U.S. VIRGIN ISLANDS
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 Boxed Facial Tissues
2.3.49 Boys’ School Uniforms
2.3.50 Bras and Allied Garments
2.3.51 Bread
2.3.52 Breakfast Cereals
2.3.53 Breweries
2.3.54 Broadband Internet Access
2.3.55 Broadwoven Fabric Finishing Mills
2.3.56 Broom, Brush, and Mop Manufacturing
2.3.57 Brown and Wholemeal Bread
2.3.58 Building Materials and Garden Supplies
2.3.59 Built-In Electric Ovens
2.3.60 Business and School Supplies
2.3.61 Butcher Shops
2.3.62 Butter
2.3.63 Cable TV
2.3.64 CAD/CAM/CAE Software
2.3.65 Cafes and Restaurants
2.3.66 Cakes and Pastries
2.3.67 Camcorders
2.3.68 Camera and Photographic Supplies Stores
2.3.69 Campgrounds and Recreational Vehicle Parks
2.3.70 Candles
2.3.71 Candy
2.3.72 Cans of Lager Beer
2.3.73 Car Aftermarket Products
2.3.74 Casinos and Gambling
2.3.75 Cat Food
2.3.76 CD Players
2.3.77 Ceiling Light Fixtures
2.3.78 Cellular Telephones
2.3.79 Cement Construction Materials
2.3.80 Cemeteries and Crematories
2.3.81 Chemicals
2.3.82 Chewing and Bubble Gum
2.3.83 Children's Chicken Nugget Ready Meals
2.3.84 Chilled and Deli Food
2.3.85 Chips and Crisps
2.3.86 Chocolate Candy
2.3.87 Cigarette Manufacturing
2.3.88 Cigars and Cigarillos
2.3.89 Citrus Fruit
2.3.90 Civil Aerospace Equipment
2.3.91 Clay Building Products
2.3.92 Clothing Accessories
2.3.93 Coated and Flavored Nuts
2.3.94 Coin-Operated Laundries and Dry Cleaners
2.3.95 Colas
2.3.96 Collection Agencies
2.3.97 Color Televisions
2.3.98 Combination Refrigerator-Freezers
2.3.99 Commercial Banking
2.3.100 Communications Services
2.3.101 Compact Discs (CDs)
2.3.102 Complete Dry Dog Food
2.3.103 Computer Hardware
2.3.104 Concrete Building Products
2.3.105 Console Video Games
2.3.106 Construction and Engineering Services
2.3.107 Consumer Chemicals
2.3.108 Contact Lenses
2.3.109 Continental and Specialty Plant Bread
2.3.110 Convenience Stores
2.3.111 Conventional Mineral Oil
2.3.112 Cookies and Crackers
2.3.113 Cooking Ranges
2.3.114 Copper Ores
2.3.115 Corporate Strategy Services
2.3.116 Cosmetics and Toiletries
2.3.117 Costume Jewelry
2.3.118 Cotton Yarn
2.3.119 Cough and Cold Remedies
2.3.120 Craft Bread
2.3.121 Credit Bureaus
2.3.122 Cross/utility Vehicles (CUVs)
2.3.123 Crude Petroleum and Natural Gas Extraction
2.3.124 Cruise Ship Tourism
2.3.125 Crushed and Broken Stone
2.3.126 Crushing Oilseeds and Tree Nuts Excluding Soybeans
2.3.127 Current-Carrying Wiring Device Manufacturing
2.3.128 Curtain and Drapery Mills
2.3.129 Custom Draperies
2.3.130 Daily Newspapers
2.3.131 Dairy Cream
2.3.132 Dark Brandy
2.3.133 Data Processing and Network Services
2.3.134 Defense Industry Equipment
2.3.135 Deli Food
2.3.136 Deluxe and Malt Whiskey
2.3.137 Department Stores
2.3.138 Depository Credit Intermediation
2.3.139 Designer Bath and Shower Products
2.3.140 Desktop Personal Computers
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 Finger Rolls
2.3.191 Fixed-Line Telecommunications Services
2.3.192 Flash Memory
2.3.193 Flat Glass
2.3.194 Floor Coverings
2.3.195 Flour Milling
2.3.196 Folding Paperboard Boxes
2.3.197 Food Advertising
2.3.198 Forestry and Fishing
2.3.199 Fossil Fuel-Powered Electric Power Generation
2.3.200 Fragrances
2.3.201 Franchising
2.3.202 Free-Range Eggs
2.3.203 Freestanding Electric Ranges
2.3.204 Freeze-Dried Instant Coffee
2.3.205 Fresh Beef and Veal
2.3.206 Fruit Drinks
2.3.207 Fuel Dealers
2.3.208 Funeral Homes
2.3.209 Gambling
2.3.210 Gaming Computer Systems
2.3.211 Gardening Supplies, Outdoor Furniture, and Plants
2.3.212 Garlic Bread
2.3.213 General Merchandise stores
2.3.214 Generic Prescription Drugs
2.3.215 Gift, Novelty, and Souvenir Stores
2.3.216 Gifts
2.3.217 Gin
2.3.218 Girls' Dresses and Blouses
2.3.219 Glass Container Manufacturing
2.3.220 Global Positioning System (GPS) Receivers
2.3.221 Gold Ores
2.3.222 Golf Equipment
2.3.223 Gourmet Potato Chips
2.3.224 Government Public Health Activities
2.3.225 Granola Bars and Breakfast Cereal Bars
2.3.226 Grape Juice
2.3.227 Graphic Design Services
2.3.228 Green Vegetables
2.3.229 Greeting Cards
2.3.230 Grocery Discounters
2.3.231 GSM-Based Cellular Telephones
2.3.232 Guided Missiles and Space Vehicles
2.3.233 Gypsum Products
2.3.234 Hair Tinting and Coloring Products
2.3.235 Hard Cheese
2.3.236 HDTV
2.3.237 Health Care Equipment and Supplies
2.3.238 Heating and Cooling Appliances
2.3.239 Highly Refined Mineral Oil
2.3.240 Highway and Street Construction
2.3.241 Hispanic Music Television
2.3.242 Hi-Tech Logistics
2.3.243 Hobby, Toy, and Game Stores
2.3.244 Home Improvement Retailers
2.3.245 Hospital Food Service
2.3.246 Household Textiles and Soft Furnishings
2.3.247 Human Resource Management Services
2.3.248 Hunting, Trapping, and Game Propagation
2.3.249 Ice Cream
2.3.250 Imported Whiskey
2.3.251 Impulse Ice Cream
2.3.252 In Vitro Diagnostic Equipment
2.3.253 IP-Based Enterprise Networking Equipment
2.3.254 Iron Ore Mining
2.3.255 Janitorial Services
2.3.256 Jewelry Stores
2.3.257 Juice
2.3.258 Kiln Furniture
2.3.259 Kitchen Appliances
2.3.260 Knitwear
2.3.261 Kraft Foods Brand Cookies
2.3.262 Lager Beer
2.3.263 Laptop Computers
2.3.264 Large Household Appliances
2.3.265 Lawn and Garden Equipment and Supplies Stores
2.3.266 Leather and Leather Products
2.3.267 Legal Services
2.3.268 Leisure Education
2.3.269 Lemonade
2.3.270 Lemon-Flavored Bottled Water
2.3.271 Life Insurance Sold by Life Insurance Companies
2.3.272 Linen and Uniform Supply
2.3.273 Lingerie
2.3.274 Lip and Multiuse Color Cosmetics
2.3.275 Liquefied Petroleum Gas
2.3.276 Liqueurs
2.3.277 Local and Interurban Passenger Transit
2.3.278 Logging
2.3.279 Logistics for the Pharmaceutical Industry
2.3.280 Low-Carbohydrate Beer
2.3.281 Lower-Fat Potato Snacks
2.3.282 Low-Fat Spreads
2.3.283 Luggage Manufacturing
2.3.284 Lumber and Wood Products
2.3.285 Luxury Yogurts
2.3.286 Machine Tools
2.3.287 Machining Precision Turned Products
2.3.288 Magazines
2.3.289 Mainstream Tea
2.3.290 Malt Beverages
2.3.291 Management Consulting Services
2.3.292 Manifold Business Forms
2.3.293 Manmade Fabric Mills
2.3.294 Manufactured Mobile Home Dealers
2.3.295 Manufacturing Dog and Cat Food
2.3.296 Marine Freight Services
2.3.297 Marketing Research and Public Opinion Polling
2.3.298 Mass Reproduction of Computer Software
2.3.299 Materials Handling Machinery
2.3.300 Meal Replacement Drinks
2.3.301 Measuring and Controlling Instruments
2.3.302 Meat and Poultry
2.3.303 Media Advertising
2.3.304 Medical Biotechnology
2.3.305 Medicated Skin Care
2.3.306 Medium and Heavy Trucks
2.3.307 Men’s Accessories
2.3.308 Men's Grooming Products
2.3.309 Menswear
2.3.310 Menthol Cigarettes
2.3.311 Millwork
2.3.312 Mineral Water
2.3.313 Mixing Ingredients to Make Fertilizer
2.3.314 Model Wheeled Vehicles
2.3.315 Modems
2.3.316 Moist Cat Food
2.3.317 Morning Bakery Goods
2.3.318 Motor Vehicles and Motor Vehicle Equipment
2.3.319 Mountain Bikes
2.3.320 Mushrooms
2.3.321 Music and Video Game Stores
2.3.322 NAND Flash Memory Cards
2.3.323 National Newspapers
2.3.324 Net, Lace, and Voile Curtains
2.3.325 Network Hubs
2.3.326 New Car Dealers
2.3.327 Nitrogenous Fertilizer Manufacturing
2.3.328 Non-Airport Car Rentals
2.3.329 Non-Chocolate Confectionery Manufacturing
2.3.330 Non-Citrus Fruit
2.3.331 Non-Current-Carrying Wiring Device Manufacturing
2.3.332 Non-Daily Newspapers
2.3.333 Non-Depository Credit Intermediation
2.3.334 Non-Durable Goods
2.3.335 Non-Farm Housing Services
2.3.336 Non-Ferrous Forging
2.3.337 Non-Food Retail Sales
2.3.338 Non-Interest Commercial Banking
2.3.339 Non-Metallic Mineral Mining and Quarrying
2.3.340 Non-Residential Construction and Engineering
2.3.341 Non-Store Retailers and Mail Order
2.3.342 Non-Wood Office Furniture Manufacturing
2.3.343 Nonwoven Fabric Mills
2.3.344 Nuclear Electric Power Generation
2.3.345 Nursery, Garden Center, and Farm Supply Stores
2.3.346 Nursing Homes
2.3.347 Nuts
2.3.348 Office Supplies and Stationery Stores
2.3.349 Oil
2.3.350 Oil, Gas, and Mining Exploration Services
2.3.351 Oils and Fats
2.3.352 Onions and Shallots
2.3.353 Online Analytical Processing (OLAP)
2.3.354 Operations Management Services
2.3.355 Ophthalmic Goods Manufacturing
2.3.356 Optical Goods and Eye Care Products
2.3.357 Oral Drug Delivery Systems
2.3.358 Orange Juice
2.3.359 Organic Beverages
2.3.360 OTC Healthcare Products
2.3.361 Outdoor Games
2.3.362 Outerwear Clothing and Accessories
2.3.363 Outsourcing Services
2.3.364 Ovens and Stoves
2.3.365 Over-The-Counter Drugs
2.3.366 Packaged Nuts
2.3.367 Packaging and Labeling Services
2.3.368 Paid Internet Search Advertising
2.3.369 Paint and Wallpaper Stores
2.3.370 Paper Towels
2.3.371 Parking Lots, Garages, and Valet Parking Services
2.3.372 Passenger Transportation
2.3.373 Passive Components
2.3.374 Pasta and Noodles
2.3.375 PC Video Game Software
2.3.376 Pears
2.3.377 Periodicals
2.3.378 Perishable Prepared Foods Manufacturing
2.3.379 Permanent Employment Services
2.3.380 Personal Stationery
2.3.381 Pet Care Products
2.3.382 Pharmacies and Drug Stores
2.3.383 Phosphatic Fertilizer Manufacturing
2.3.384 Physicians' Services
2.3.385 Pizzas
2.3.386 Plant Bread
2.3.387 Plastic Housewares
2.3.388 Plumbing Products
2.3.389 Plush Toys
2.3.390 Pollution Control Equipment and Services
2.3.391 Popcorn
2.3.392 Pork Pies
2.3.393 Port and Shipbuilding Equipment
2.3.394 Potash, Soda, and Boratic Minerals Mining
2.3.395 Potato Chips
2.3.396 Poultry Products
2.3.397 Powder Detergents
2.3.398 Precious Metal Jewelry and Personal Articles
2.3.399 Prefabricated Metal Buildings
2.3.400 Pre-Recorded Cassettes
2.3.401 Prerecorded Tape, Compact Disc, and Record Stores
2.3.402 Prescription Eyeglass Frames
2.3.403 Presentation Materials
2.3.404 Primary Metal Industries
2.3.405 Printed Circuit Boards
2.3.406 Printers
2.3.407 Printing Special Business Forms and Checkbooks
2.3.408 Private Residential Construction
2.3.409 Professional Computer Services
2.3.410 Programmable Logic Devices
2.3.411 Property and Casualty Insurance
2.3.412 Public Residential Construction
2.3.413 Publishing Advertising
2.3.414 Pubs, Clubs, and Nightclubs
2.3.415 Pulmonary Drug Delivery Systems
2.3.416 Pulp Mills
2.3.417 Radiators and Pumps
2.3.418 Radio and Television Broadcasting
2.3.419 Railroad Freight Services
2.3.420 Ready Pasta
2.3.421 Real Jewelry
2.3.422 Reconstituted Wood Products
2.3.423 Recorded Music
2.3.424 Recreational Vehicle Dealers
2.3.425 Red Meat
2.3.426 Refining Cane Sugar from Raw Cane Sugar
2.3.427 Refrigeration Appliances
2.3.428 Regional Newspapers
2.3.429 Relays and Industrial Controls
2.3.430 Remediation Services
2.3.431 Rendering Animal Fat, Bones, and Meat Scraps
2.3.432 Renewable Energy Equipment
2.3.433 Replacement Tires for Cars and Light Vans
2.3.434 Residential Construction
2.3.435 Residual Fuel Oil
2.3.436 Retail Logistics
2.3.437 Retirement Savings Plans
2.3.438 Reupholstery and Furniture Repair
2.3.439 Rice Milling
2.3.440 Ride-On Toys
2.3.441 Root Vegetables
2.3.442 Salad Accompaniments
2.3.443 Salon Hair Care Products
2.3.444 Salt and Vinegar Potato Chips
2.3.445 Sandwich Spreads
2.3.446 Sanitary Protection Products
2.3.447 Sauces, Salad Dressings, and Condiments
2.3.448 Savory Snacks
2.3.449 Sawmills
2.3.450 Scanners
2.3.451 School Food Service
2.3.452 Scrap Recycling
2.3.453 Screw Machine Products
2.3.454 Seafood Canning
2.3.455 Seasonal Cookies
2.3.456 Secondary Smelting and Alloying of Aluminum
2.3.457 Security and Commodity Brokers and Dealers
2.3.458 Sensors
2.3.459 Services
2.3.460 Sewer Facilities
2.3.461 Sewing, Needlework, and Piece Goods Stores
2.3.462 Shampoo
2.3.463 Shaving Razors and Blades
2.3.464 Sheer Window Furnishings
2.3.465 Shellfish
2.3.466 Ship Building and Repairing
2.3.467 Single-Serving Dry Ambient Snacks
2.3.468 Skin Care Products
2.3.469 Slaughtering Animals Excluding Poultry
2.3.470 Sliced Cooked Meat
2.3.471 Slow-Release Household Fresheners
2.3.472 Smoothies
2.3.473 Socks, Stockings, and Tights
2.3.474 Soup
2.3.475 Space Heaters
2.3.476 Spice and Extract Manufacturing
2.3.477 Sporting Goods Retailers
2.3.478 Sports and Energy Drinks
2.3.479 Spreads and Margarines
2.3.480 Stacking Potato Chips
2.3.481 Standard and Bulk Ice Cream
2.3.482 Stationary Bicycles
2.3.483 Steel Mill Products
2.3.484 Stella Artois Lager Beer
2.3.485 Still Bottled Water
2.3.486 Stone Fruit
2.3.487 Storage Battery Manufacturing
2.3.488 Sugar Candy
2.3.489 Support Activities for Air Transportation
2.3.490 Surface Cleaners
2.3.491 Sweet Spreads
2.3.492 Switchgear and Switchboard Apparatus
2.3.493 Synthetic Rubber
2.3.494 Table Lamps
2.3.495 Taxicabs
2.3.496 Telecommunications Equipment
2.3.497 Telephone and Telegraph Facilities
2.3.498 Television Broadcasting
2.3.499 Temporary Employment Services
2.3.500 Tequila and Mescal Spirits
2.3.501 Testing Laboratories
2.3.502 Textile Fabrics
2.3.503 Tire Cord and Tire Fabric Mills
2.3.504 Tissues
2.3.505 Tobacco Products
2.3.506 Tortilla Manufacturing
2.3.507 Toy Stores
2.3.508 Traditional Toys
2.3.509 Trail Mix
2.3.510 Transformers
2.3.511 Transportation Equipment
2.3.512 Travel Trailer and Camper Manufacturing
2.3.513 Truck Trailer Manufacturing
2.3.514 Turkey Pieces
2.3.515 Ultra Disposable Diapers
2.3.516 Underwear, Nightwear, and Swimwear
2.3.517 Underwire Bras
2.3.518 Unleaded Gasoline
2.3.519 Upholstered Household Furniture Manufacturing
2.3.520 Used Car Dealers
2.3.521 Utilities
2.3.522 Vacuum Cleaners
2.3.523 Valves and Pipe Fittings
2.3.524 Vegetarian Foods
2.3.525 Venture Capital
2.3.526 Vertical Blinds
2.3.527 Video Cassette Recorders (VCRs)
2.3.528 Vienna and French Bread
2.3.529 Vodka
2.3.530 VoIP Telephone Service
2.3.531 Washing Machines
2.3.532 Watches
2.3.533 Water Utilities
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

Abstract

How to Strategically Evaluate the U.S. Virgin Islands

Perhaps the most efficient way of evaluating the U.S. Virgin Islands 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 the U.S. Virgin Islands. Latent demand is largely driven by economic fundamentals.

In Chapter 2, I summarize the economic potential for the U.S. Virgin Islands 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 the U.S. Virgin Islands 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 the U.S. Virgin Islands as an area of dominant influence in North America & the Caribbean and, potentially, the world.

ECONOMIC AND PRODUCT MARKETS IN THE U.S. VIRGIN ISLANDS
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 Virgin Islands, US. The purpose of the studies is to understand the density of demand within Virgin Islands, US and the extent to which Virgin Islands, US might be used as a point of distribution within North America & the Caribbean. From an economic perspective, however, Virgin Islands, US 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 Virgin Islands, US 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 Virgin Islands, US 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 Virgin Islands, US 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 Virgin Islands, US. Without Virgin Islands, US, in other words, the market for satellite launch vehicles would be lower for the population in Virgin Islands, US, North America & the Caribbean, or the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to both North America & the Caribbean and Virgin Islands, US.

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 Virgin Islands, US as an area of dominant influence in North America & the Caribbean and, potentially, the world.

Market Potential Estimation Methodology

Overview
This chapter covers the outlook for products in Virgin Islands, US. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for Virgin Islands, US (in millions of U.S. dollars). Comparative benchmarks allow the reader to quickly gauge Virgin Islands, US 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 Virgin Islands, US. 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 Virgin Islands, US, 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 Virgin Islands, US. 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 Virgin Islands, US.

Step 1. Product Definition and Data Collection
Any study of latent demand across countries and within Virgin Islands, US 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 Virgin Islands, US 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 Virgin Islands, US 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 Virgin Islands, US 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.

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