The 2007-2012 World Outlook for Non-Ferrous Metal Rolling, Drawing, and Extruding Excluding Aluminum and Copper
ICON Group International, May 2006, Pages: 202
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 for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand can be lower 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.
For reasons discussed later, this report 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 report 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 in the introduction, this study 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 for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper 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 non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper on a worldwide basis, we used a multi-stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In this case, we 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 in 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 study a very particular school of thought is adopted. In particular, we are considering the latent demand for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper across some 230 countries. The smallest have fewer than 10,000 inhabitants. we 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 for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper. So, latent demand in the long-run has a zero intercept. However, we 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, we will now describe the methodology used to create the latent demand estimates for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper. Since this methodology has been applied to a large number of categories, the rather academic discussion below is general and can be applied to a wide variety of categories, not just non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper.
Step 1. Product Definition and Data Collection
Any study of latent demand across countries requires that some standard be established to define “efficiently served”. Having implemented various alternatives and matched these with market outcomes, we 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, we 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 can not 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 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 “non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper” is established. In the case of this report, 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 non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper falls under this 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 report only relies on public data at the aggregate level without reliance on the summation of various category components. In other words, this report 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).
Given this caveat, this study covers “non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). For a complete definition of non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper, please see below. The NAICS code for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper is 331491. It is for this definition of non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper that the aggregate latent demand estimates are derived. “Non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper” is specifically defined as follows:
331491
This U.S. industry comprises establishments primarily engaged in (1) rolling, drawing, or extruding shapes (e.g., bar, plate, sheet, strip, tube) from purchased nonferrous metals) and/or (2) recovering nonferrous metals from scrap and rolling, drawing, and/or extruding shapes (e.g., bar, plate, sheet, strip, tube) in integrated mills.
3314911
Nickel and nickel-base alloy mill shapes, including nickel copper alloys
3314912
NICKEL AND NICKEL_BASE ALLOY MILL SHAPES
3314913
Titanium and titanium-base alloy mill shapes, excluding wire
3314915
BARE NONFERROUS METAL WIRE (EXCEPT ALUMINUM AND COPPER), MADE IN NONFERROUS PLANTS THAT DRAW WIRE
3314917
NONFERROUS WIRE CLOTH AND WOVEN WIRE PRODUCTS
3314919
Precious metal mill shapes
331491A
PRECIOUS METAL MILL SHAPES
331491C
All other nonferrous metal mill shapes
331491D
ALL OTHER NONFERROUS METAL MILL SHAPES
331491E
APPARATUS WIRE AND CORD AND FLEXIBLE CORD SETS (EXCEPT WIRING HARNESSES), MADE IN PLANTS THAT DRAW WIRE
331491F
APPARATUS WIRE AND CORD AND FLEXIBLE CORD SETS (EXCEPT ALUMINUM, COPPER, WIRING HARNESSES AND FIBER OPTIC), MADE IN PLANTS THAT DRAW WIRE
331491G
MAGNET WIRE, MADE IN PLANTS THAT DRAW WIRE
331491H
MAGNET WIRE, (EXCEPT ALUMINUM AND COPPER), MADE IN PLANTS THAT DRAW WIRE
331491M
Miscellaneous receipts
331491P
Primary products
331491S
Secondary products
Furthermore, the definition of NAICS code 331491 includes the following:
Aircraft and automotive wire and cable (except aluminum, copper) made from purcha
Apparatus wire and cord (except aluminum, copper) made from purchased nonferrous
Bar, nonferrous metals (except aluminum, copper), made from purchased metals in w
Coaxial cable, nonferrous metals (except aluminum, copper), made from purchased n
Communications wire or cable, nonferrous metals (except aluminum, copper), made f
Cord sets, flexible, nonferrous metals (except aluminum, copper), made from purch
Energy wire or cable, nonferrous metals (except aluminum, copper), made from purc
Foil, gold, made by rolling purchased metals or scrap
Foil, nickel, made by rolling purchased metals or scrap
Foil, silver, made by rolling purchased metals or scrap
Gold and gold alloy bar, sheet, strip, and tubing made from purchased metals or s
Gold foil made by rolling purchased metals or scrap
Gold rolling and drawing purchased metals or scrap
Iridium bar, rod, sheet, strip and tubing made from purchased metals or scrap
Lead and lead alloy bar, pipe, plate, rod, sheet, strip, and tubing made from pur
Lead rolling, drawing, or extruding purchased metals or scrap
Magnesium and magnesium alloy bar, rod, shape, sheet, strip, and tubing made from
Magnesium foil made by rolling purchased metals or scrap
Magnesium rolling, drawing, or extruding purchased metals or scrap
Magnet wire, nonferrous metals (except aluminum, copper), made from purchased non
Mesh, wire, nonferrous metals (except aluminum, copper), made from purchased nonf
Molybdenum and molybdenum alloy bar, plate, pipe, rod, sheet, tubing, and wire ma
Molybdenum rolling, drawing, or extruding purchased metals or scrap
Nails, nonferrous metals (except aluminum, copper), made from purchased nonferrou
Nickel and nickel alloy pipe, plate, sheet, strip, and tubing made from purchased
Nickel rolling, drawing, or extruding purchased metals or scrap
Nonferrous metal shapes (except aluminum, copper) made by rolling, drawing, or ex
Nonferrous metal shapes (except aluminum, copper) made in integrated secondary sm
Nonferrous metal shapes (except aluminum, copper) made in integrated secondary sm
Nonferrous metal shapes (except aluminum, copper) made in integrated secondary sm
Nonferrous wire (except aluminum, copper) made from purchased nonferrous metals (
Nonferrous wire (except aluminum, copper) made in integrated secondary smelting m
Pipe, nonferrous metals (except aluminum, copper), made from purchased metals or
Plate, nonferrous metals (except aluminum, copper), made from purchased metals or
Platinum and platinum alloy rolling, drawing, or extruding from purchased metals
Platinum and platinum alloy sheet and tubing made from purchased metals or scrap
Precious metal bar, rod, sheet, strip, and tubing made from purchased metals or s
Rod, nonferrous metals (except aluminum, copper), made from purchased metals or s
Selenium bar, rod, sheet, strip, and tubing made from purchased metals or scrap
Silver and silver alloy bar, rod, sheet, strip, and tubing made from purchased me
Silver foil made by rolling purchased metals or scrap
Silver rolling, drawing, or extruding purchased metals or scrap
Solder wire, nonferrous metals (except aluminum, copper), made from purchased met
Strip, nonferrous metals (except aluminum, copper), made from purchased metals or
Tin and tin alloy bar, pipe, rod, sheet, strip, and tubing made from purchased me
Tin rolling, drawing, or extruding purchased metals or scrap
Titanium and titanium alloy bar, billet, rod, sheet, strip, and tubing made from
Titanium rolling, drawing, or extruding purchased metals or scrap
Tubing, nonferrous metals (except aluminum, copper), made from purchased metals o
Tungsten bar, rod, sheet, strip, and tubing made by rolling, drawing, or extrudin
Welding rod, uncoated, nonferrous metals (except aluminum, copper), made from pur
Wire cloth, nonferrous metals (except aluminum, copper), made from purchased meta
Wire screening, nonferrous metals (except aluminum, copper), made from purchased
Wire, nonferrous metals (except aluminum, copper), made from purchased nonferrous
Wire, nonferrous metals (except aluminum, copper), made in integrated secondary s
Zinc and zinc alloy bar, plate, pipe, rod, sheet, tubing, and wire made from purc
Zinc rolling, drawing, or extruding purchased metals or scrap
Zirconium and zirconium alloy bar, rod, billet, sheet, strip, and tubing made fro
Zirconium rolling, drawing, or extruding purchased metals or scrap.
Step 2. Filtering and Smoothing
Based on the aggregate view of non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper 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 for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper 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 a country’s contribution 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
Nonlinearities 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 for non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper 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 non-ferrous metal rolling, drawing, and extruding excluding aluminum and copper). 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, including 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 averages are presented. Figures are rounded, so minor inconsistencies may exist across tables.
Step 7. Latent Demand Density: Allocating Across Cities
With the advent of a “borderless world”, cities become a more important criteria in prioritizing markets, as opposed to regions, continents, or countries. This report also covers the world’s top 2000 cities. The purpose is to understand the density of demand within a country and the extent to which a city might be used as a point of distribution within its region. From an economic perspective, however, a city does not represent a population within rigid geographical boundaries. To an economist or strategic planner, a city 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.
Similar to country-level data, the reader needs to realize that latent demand allocated to a city 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, again, the category “satellite launch vehicles.” Clearly, there are no launch pads in most cities of the world. However, the core benefit of the vehicles (e.g. telecommunications, etc.) is "consumed" by residents or industries within the worlds cities. Without certain cities, in other words, the world market for satellite launch vehicles would be lower for the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to regions, countries and cities. This report takes the broader definition and considers, therefore, a city as a part of the global market. we allocate latent demand across areas of dominant influence based on the relative economic importance of cities within its home country, within its region and across the world total. Not all cities are estimated within each country as demand may be allocated to adjacent areas of influence. Since some cities have higher economic wealth than others within the same country, a city’s population is not generally used to allocate latent demand. Rather, the level of economic activity of the city vis-à-vis others.
1 INTRODUCTION 10
1.1 Overview 10
1.2 What is Latent Demand and the P.I.E.? 10
1.3 The Methodology 11
1.3.1 Step 1. Product Definition and Data Collection 12
1.3.2 Step 2. Filtering and Smoothing 16
1.3.3 Step 3. Filling in Missing Values 16
1.3.4 Step 4. Varying Parameter, Non-linear Estimation 16
1.3.5 Step 5. Fixed-Parameter Linear Estimation 17
1.3.6 Step 6. Aggregation and Benchmarking 17
1.3.7 Step 7. Latent Demand Density: Allocating Across Cities 18
2 SUMMARY OF FINDINGS 19
2.1 The Worldwide Market Potential 19
3 AFRICA 21
3.1 Executive Summary 21
3.2 Algeria 22
3.3 Angola 23
3.4 Benin 24
3.5 Botswana 25
3.6 Burkina Faso 26
3.7 Burundi 26
3.8 Cameroon 27
3.9 Cape Verde 28
3.10 Central African Republic 28
3.11 Chad 29
3.12 Comoros 30
3.13 Congo (formerly Zaire) 30
3.14 Cote dIvoire 31
3.15 Djibouti 32
3.16 Egypt 33
3.17 Equatorial Guinea 34
3.18 Ethiopia 34
3.19 Gabon 35
3.20 Ghana 36
3.21 Guinea 37
3.22 Guinea-Bissau 37
3.23 Kenya 38
3.24 Lesotho 39
3.25 Liberia 39
3.26 Libya 40
3.27 Madagascar 41
3.28 Malawi 41
3.29 Mali 42
3.30 Mauritania 43
3.31 Mauritius 43
3.32 Morocco 44
3.33 Mozambique 45
3.34 Namibia 45
3.35 Niger 46
3.36 Nigeria 47
3.37 Republic of Congo 48
3.38 Reunion 48
3.39 Rwanda 49
3.40 Sao Tome E Principe 50
3.41 Senegal 50
3.42 Sierra Leone 51
3.43 Somalia 52
3.44 South Africa 53
3.45 Sudan 54
3.46 Swaziland 55
3.47 Tanzania 55
3.48 The Gambia 56
3.49 Togo 57
3.50 Tunisia 58
3.51 Uganda 59
3.52 Western Sahara 60
3.53 Zambia 60
3.54 Zimbabwe 61
4 ASIA 63
4.1 Executive Summary 63
4.2 Bangladesh 64
4.3 Bhutan 65
4.4 Brunei 66
4.5 Burma 67
4.6 Cambodia 68
4.7 China 68
4.8 Hong Kong 69
4.9 India 70
4.10 Indonesia 71
4.11 Japan 72
4.12 Laos 73
4.13 Macau 73
4.14 Malaysia 74
4.15 Maldives 75
4.16 Mongolia 76
4.17 Nepal 76
4.18 North Korea 77
4.19 Papua New Guinea 78
4.20 Philippines 78
4.21 Seychelles 79
4.22 Singapore 80
4.23 South Korea 81
4.24 Sri Lanka 82
4.25 Taiwan 83
4.26 Thailand 84
4.27 Vietnam 85
5 EUROPE & THE MIDDLE EAST 86
5.1 Executive Summary 86
5.2 Afghanistan 87
5.3 Albania 88
5.4 Andorra 89
5.5 Armenia 90
5.6 Austria 91
5.7 Azerbaijan 92
5.8 Bahrain 93
5.9 Belarus 93
5.10 Belgium 94
5.11 Bosnia and Herzegovina 95
5.12 Bulgaria 96
5.13 Croatia 97
5.14 Cyprus 98
5.15 Czech Republic 98
5.16 Denmark 99
5.17 Estonia 100
5.18 Finland 101
5.19 France 102
5.20 Georgia 103
5.21 Germany 104
5.22 Greece 105
5.23 Hungary 106
5.24 Iceland 107
5.25 Iran 108
5.26 Iraq 109
5.27 Ireland 110
5.28 Israel 110
5.29 Italy 111
5.30 Jordan 112
5.31 Kazakhstan 113
5.32 Kuwait 114
5.33 Kyrgyzstan 115
5.34 Latvia 116
5.35 Lebanon 116
5.36 Liechtenstein 117
5.37 Lithuania 118
5.38 Luxembourg 118
5.39 Malta 119
5.40 Moldova 120
5.41 Monaco 120
5.42 Netherlands 121
5.43 Norway 122
5.44 Oman 123
5.45 Pakistan 123
5.46 Palestine 124
5.47 Poland 125
5.48 Portugal 126
5.49 Qatar 127
5.50 Romania 127
5.51 Russia 128
5.52 San Marino 129
5.53 Saudi Arabia 130
5.54 Slovakia 131
5.55 Slovenia 131
5.56 Spain 132
5.57 Sweden 133
5.58 Switzerland 134
5.59 Syrian Arab Republic 135
5.60 Tajikistan 136
5.61 Turkey 137
5.62 Turkmenistan 138
5.63 Ukraine 138
5.64 United Arab Emirates 139
5.65 United Kingdom 140
5.66 Uzbekistan 141
5.67 Yemen 142
6 LATIN AMERICA 143
6.1 Executive Summary 143
6.2 Argentina 144
6.3 Belize 145
6.4 Bolivia 146
6.5 Brazil 147
6.6 Chile 148
6.7 Colombia 149
6.8 Costa Rica 150
6.9 Ecuador 150
6.10 El Salvador 151
6.11 Falkland Islands 152
6.12 French Guiana 152
6.13 Guatemala 153
6.14 Guyana 154
6.15 Honduras 154
6.16 Mexico 155
6.17 Nicaragua 156
6.18 Panama 157
6.19 Paraguay 158
6.20 Peru 159
6.21 Suriname 160
6.22 Uruguay 160
6.23 Venezuela 161
7 NORTH AMERICA & THE CARIBBEAN 163
7.1 Executive Summary 163
7.2 Antigua and Barbuda 164
7.3 Aruba 165
7.4 Bahamas 166
7.5 Barbados 166
7.6 Bermuda 167
7.7 British Virgin Islands 168
7.8 Canada 168
7.9 Cayman Islands 169
7.10 Cuba 170
7.11 Dominica 171
7.12 Dominican Republic 171
7.13 Greenland 172
7.14 Grenada 173
7.15 Guadeloupe 174
7.16 Haiti 175
7.17 Jamaica 175
7.18 Martinique 176
7.19 Netherlands Antilles 177
7.20 Puerto Rico 177
7.21 St. Kitts and Nevis 178
7.22 St. Lucia 179
7.23 St. Vincent and the Grenadines 179
7.24 Trinidad and Tobago 180
7.25 United States 181
7.26 Virgin Islands, US 182
8 OCEANA 183
8.1 Executive Summary 183
8.2 American Samoa 184
8.3 Australia 185
8.4 Christmas Island 186
8.5 Cook Islands 186
8.6 Fiji 187
8.7 French Polynesia 188
8.8 Guam 188
8.9 Kiribati 189
8.10 Marshall Islands 190
8.11 Micronesia Federation 190
8.12 Nauru 191
8.13 New Caledonia 192
8.14 New Zealand 192
8.15 Niue 193
8.16 Norfolk Island 194
8.17 Northern Mariana Island 194
8.18 Palau 195
8.19 Solomon Islands 196
8.20 Tokelau 196
8.21 Tonga 197
8.22 Tuvalu 198
8.23 Vanuatu 198
8.24 Wallis and Futuna 199
8.25 Western Samoa 200
9 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 201
9.1 Disclaimers & Safe Harbor 201
9.2 User Agreement Provisions 202
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