The 2007-2012 World Outlook for Manufacturing Medical Equipment and Supplies, Laboratory Apparatus and Furniture, Surgical and Medical Instruments, Surgical Appliances and Supplies, Dental Equipment and Supplies, Orthodontic Goods, Dentures, and Orth

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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances. 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances. 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances.

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 “manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances” 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 “manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). For a complete definition of manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances, please see below. The NAICS code for manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances is 3391. It is for this definition of manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances that the aggregate latent demand estimates are derived. “Manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances” is specifically defined as follows:

3391
Medical Equipment and Supplies Manufacturing

33911
This industry comprises establishments primarily engaged in manufacturing medical equipment and supplies. Examples of products made by these establishments are laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances.



Step 2. Filtering and Smoothing

Based on the aggregate view of manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances 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 manufacturing medical equipment and supplies, laboratory apparatus and furniture, surgical and medical instruments, surgical appliances and supplies, dental equipment and supplies, orthodontic goods, dentures, and orthodontic appliances). 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 14 1.3.3 Step 3. Filling in Missing Values 14 1.3.4 Step 4. Varying Parameter, Non-linear Estimation 14 1.3.5 Step 5. Fixed-Parameter Linear Estimation 15 1.3.6 Step 6. Aggregation and Benchmarking 15 1.3.7 Step 7. Latent Demand Density: Allocating Across Cities 15 2 SUMMARY OF FINDINGS 17 2.1 The Worldwide Market Potential 17 3 AFRICA 19 3.1 Executive Summary 19 3.2 Algeria 21 3.3 Angola 22 3.4 Benin 23 3.5 Botswana 24 3.6 Burkina Faso 25 3.7 Burundi 26 3.8 Cameroon 27 3.9 Cape Verde 28 3.10 Central African Republic 29 3.11 Chad 30 3.12 Comoros 31 3.13 Congo (formerly Zaire) 31 3.14 Cote dIvoire 32 3.15 Djibouti 33 3.16 Egypt 34 3.17 Equatorial Guinea 35 3.18 Ethiopia 35 3.19 Gabon 36 3.20 Ghana 37 3.21 Guinea 38 3.22 Guinea-Bissau 39 3.23 Kenya 40 3.24 Lesotho 41 3.25 Liberia 41 3.26 Libya 42 3.27 Madagascar 43 3.28 Malawi 44 3.29 Mali 45 3.30 Mauritania 46 3.31 Mauritius 47 3.32 Morocco 48 3.33 Mozambique 49 3.34 Namibia 50 3.35 Niger 51 3.36 Nigeria 52 3.37 Republic of Congo 53 3.38 Reunion 54 3.39 Rwanda 55 3.40 Sao Tome E Principe 56 3.41 Senegal 56 3.42 Sierra Leone 57 3.43 Somalia 58 3.44 South Africa 59 3.45 Sudan 60 3.46 Swaziland 61 3.47 Tanzania 62 3.48 The Gambia 63 3.49 Togo 64 3.50 Tunisia 65 3.51 Uganda 66 3.52 Western Sahara 67 3.53 Zambia 67 3.54 Zimbabwe 68 4 ASIA & THE MIDDLE EAST 70 4.1 Executive Summary 70 4.2 Afghanistan 72 4.3 Armenia 73 4.4 Azerbaijan 74 4.5 Bahrain 75 4.6 Bangladesh 76 4.7 Bhutan 77 4.8 Brunei 78 4.9 Burma 78 4.10 Cambodia 79 4.11 China 80 4.12 Hong Kong 81 4.13 India 81 4.14 Indonesia 82 4.15 Iran 83 4.16 Iraq 84 4.17 Israel 85 4.18 Japan 86 4.19 Jordan 87 4.20 Kuwait 88 4.21 Kyrgyzstan 89 4.22 Laos 90 4.23 Lebanon 91 4.24 Macau 92 4.25 Malaysia 92 4.26 Maldives 93 4.27 Mongolia 94 4.28 Nepal 95 4.29 North Korea 96 4.30 Oman 97 4.31 Pakistan 97 4.32 Palestine 98 4.33 Papua New Guinea 99 4.34 Philippines 100 4.35 Qatar 101 4.36 Saudi Arabia 101 4.37 Seychelles 102 4.38 Singapore 103 4.39 South Korea 104 4.40 Sri Lanka 105 4.41 Syrian Arab Republic 106 4.42 Taiwan 107 4.43 Tajikistan 108 4.44 Thailand 109 4.45 Turkey 110 4.46 Turkmenistan 111 4.47 United Arab Emirates 111 4.48 Uzbekistan 112 4.49 Vietnam 113 4.50 Yemen 114 5 EUROPE 115 5.1 Executive Summary 115 5.2 Albania 117 5.3 Andorra 118 5.4 Austria 118 5.5 Belarus 119 5.6 Belgium 120 5.7 Bosnia and Herzegovina 121 5.8 Bulgaria 122 5.9 Croatia 123 5.10 Cyprus 124 5.11 Czech Republic 125 5.12 Denmark 126 5.13 Estonia 127 5.14 Finland 128 5.15 France 129 5.16 Georgia 130 5.17 Germany 131 5.18 Greece 132 5.19 Hungary 133 5.20 Iceland 134 5.21 Ireland 135 5.22 Italy 136 5.23 Kazakhstan 137 5.24 Latvia 138 5.25 Liechtenstein 139 5.26 Lithuania 140 5.27 Luxembourg 141 5.28 Malta 142 5.29 Moldova 143 5.30 Monaco 143 5.31 Netherlands 144 5.32 Norway 145 5.33 Poland 146 5.34 Portugal 147 5.35 Romania 148 5.36 Russia 149 5.37 San Marino 150 5.38 Slovakia 150 5.39 Slovenia 151 5.40 Spain 152 5.41 Sweden 153 5.42 Switzerland 154 5.43 Ukraine 155 5.44 United Kingdom 156 6 LATIN AMERICA 157 6.1 Executive Summary 157 6.2 Argentina 158 6.3 Belize 159 6.4 Bolivia 160 6.5 Brazil 161 6.6 Chile 162 6.7 Colombia 163 6.8 Costa Rica 164 6.9 Ecuador 165 6.10 El Salvador 166 6.11 Falkland Islands 167 6.12 French Guiana 167 6.13 Guatemala 168 6.14 Guyana 169 6.15 Honduras 170 6.16 Mexico 171 6.17 Nicaragua 172 6.18 Panama 173 6.19 Paraguay 174 6.20 Peru 175 6.21 Suriname 176 6.22 Uruguay 177 6.23 Venezuela 178 7 NORTH AMERICA & THE CARIBBEAN 179 7.1 Executive Summary 179 7.2 Antigua and Barbuda 181 7.3 Aruba 181 7.4 Bahamas 182 7.5 Barbados 183 7.6 Bermuda 183 7.7 British Virgin Islands 184 7.8 Canada 185 7.9 Cayman Islands 186 7.10 Cuba 186 7.11 Dominica 187 7.12 Dominican Republic 188 7.13 Greenland 189 7.14 Grenada 190 7.15 Guadeloupe 190 7.16 Haiti 191 7.17 Jamaica 192 7.18 Martinique 193 7.19 Netherlands Antilles 194 7.20 Puerto Rico 194 7.21 St. Kitts and Nevis 195 7.22 St. Lucia 196 7.23 St. Vincent and the Grenadines 197 7.24 Trinidad and Tobago 197 7.25 United States 198 7.26 Virgin Islands, US 199 8 OCEANA 201 8.1 Executive Summary 201 8.2 American Samoa 203 8.3 Australia 204 8.4 Christmas Island 205 8.5 Cook Islands 205 8.6 Fiji 206 8.7 French Polynesia 207 8.8 Guam 208 8.9 Kiribati 209 8.10 Marshall Islands 209 8.11 Micronesia Federation 210 8.12 Nauru 211 8.13 New Caledonia 211 8.14 New Zealand 212 8.15 Niue 213 8.16 Norfolk Island 214 8.17 Northern Mariana Island 215 8.18 Palau 215 8.19 Solomon Islands 216 8.20 Tokelau 217 8.21 Tonga 217 8.22 Tuvalu 218 8.23 Vanuatu 219 8.24 Wallis and Futuna 219 8.25 Western Samoa 220 9 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 221 9.1 Disclaimers & Safe Harbor 221 9.2 User Agreement Provisions 222

Order Online - visit http://www.researchandmarkets.com/reports/1582661

Order by Fax - using the order form below

Order By Post - print the order form below and send to

Research and Markets,
Guinness Centre,
Taylors Lane,
Dublin 8,
Ireland.