The 2009 Report on Manufacturing Power, Distribution, and Specialty Transformers Excluding Electronic Components: World Market Segmentation by City
ICON Group International, May 2009, Pages: 348
Market Potential Estimation Methodology
Overview
This study covers the world outlook for manufacturing power, distribution, and specialty transformers excluding electronic components across more than 2000 cities. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the city in question (in millions of U.S. dollars), the percent share the city is of the region and of the globe. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.
This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the cities of the world). This study gives, however, my estimates for the worldwide latent demand, or the P.I.E. for manufacturing power, distribution, and specialty transformers excluding electronic components. It also shows how the P.I.E. is divided across the world’s cities. 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 for manufacturing power, distribution, and specialty transformers excluding electronic components 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 city market.
Another reason why sales do not equate to latent demand is exchange rates. In this report, all figures assume the long-run efficiency of currency markets. Figures, therefore, equate values based on purchasing power parities across countries. Short-run distortions in the value of the dollar, therefore, do not figure into the estimates. Purchasing power parity estimates of country income were collected from official sources, and extrapolated using standard econometric models. The report uses the dollar as the currency of comparison, but not as a measure of transaction volume. The units used in this report are: US $ mln.
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 earlier, 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 power, distribution, and specialty transformers excluding electronic components 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 power, distribution, and specialty transformers excluding electronic components on a city-by-city basis, 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 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 power, distribution, and specialty transformers excluding electronic components 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 for manufacturing power, distribution, and specialty transformers excluding electronic components. 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 manufacturing power, distribution, and specialty transformers excluding electronic components. Since ICON Group has asked me to apply this methodology 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 power, distribution, and specialty transformers excluding electronic components.
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, I have found that the optimal approach is to assume that certain key countries or cities are more likely to be at or near efficiency than others. These are given greater weight than others in the estimation of latent demand compared to others 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 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 power, distribution, and specialty transformers excluding electronic components” 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 power, distribution, and specialty transformers excluding electronic components 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 cities 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 power, distribution, and specialty transformers excluding electronic components” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). For a complete definition of manufacturing power, distribution, and specialty transformers excluding electronic components, please refer to the Web site at http://www.icongrouponline.com/codes/NAICS.html. The NAICS code for manufacturing power, distribution, and specialty transformers excluding electronic components is 335311. It is for this definition of manufacturing power, distribution, and specialty transformers excluding electronic components that the aggregate latent demand estimates are derived. “Manufacturing power, distribution, and specialty transformers excluding electronic components” is specifically defined as follows:
335311
This U.S. industry comprises establishments primarily engaged in manufacturing power, distribution, and specialty transformers (except electronic components). Industrial-type and consumer-type transformers in this industry vary (e.g., step up or step down) voltage but do not convert alternating to direct or direct to alternating current.
3353111
POWER AND DISTRIBUTION TRANSFORMERS, EXCEPT PARTS
33531111
Distribution transformers (except general_purpose), overhead type, single_ phase, liquid_immersed, 500 kVA and smaller (except parts)
3353111101
Distribution transformers (except general_purpose), overhead type, single_ phase, liquid_immersed, 500 kVA and smaller (except parts)
33531112
Distribution transformers (except general_purpose), compartmentalized pad_ mounted, single_phase, liquid_immersed, 500 kVA and smaller (except parts)
3353111204
Distribution transformers (except general_purpose), compartmentalized pad_ mounted, single_phase, liquid_immersed, 500 kVA and smaller (except parts)
33531113
Other distribution transformers (except general_purpose), including network transformers, single_phase, and liquid_immersed (all voltages) (except parts)
3353111307
Distribution transformers (except general_purpose), subsurface and subway types, single_phase, liquid_immersed, 500 kVA and smaller (except parts)
3353111311
Distribution three_phase transformers (except general_purpose), liquid_ immersed, all voltages, 500 kVA and smaller (except parts)
3353111313
Distribution network transformers (except general_purpose), all ratings, excluding network protectors (except parts)
3353111316
Distribution transformers (except general_purpose), single_phase and three_ phase, pad_mounted (dry), 500 kVA and smaller (except parts)
33531114
Small conventional and power transformers, single_ and three_phase (all voltages), primary and secondary unit substations
3353111419
Small power transformers, liquid_immersed, single_ and three_phase (all voltages), compartmentalized pad_mounted, subsurface underground and conventional subway type, 501 kVA through 2500 kVA
3353111422
Small conventional transformers and autotransformers, liquid_immersed, single_ and three_phase (all voltages), primary unit and single circuit unit substations, 501 kVA through 2500 kVA
3353111425
Small power transformers, single_ and three_phase (all voltages), liquid_ immersed conventionals, primary unit and single circuit unit substations, 2501 kVA through 10,000 kVA
3353111428
Dry_type small conventional power transformers, single_ and three_phase, all voltages, primary unit substation (including core and coil units)
3353111431
Secondary unit substation power transformers, liquid_immersed, all kVA ratings
3353111434
Secondary unit substation power transformers, dry_type, all kVA ratings
33531115
Large liquid_immersed power transformers with and without load_tap_changing
3353111537
Large liquid immersed power transformers with load_tap_changing, 10,001 kVA, OA to 30,000 kVA, OA (50,000 kVA, top FOA)
3353111541
Large liquid immersed power transformers without load_tap_changing, 10,001 kVA, OA to 30,000 kVA, OA (50,000 kVA, top FOA)
3353111543
Large liquid_immersed power transformers with load_tap_changing, 30,001 kVA, OA (50,000 kVA, top FOA) to 100,000 kVA, OA (167,000 kVA, top FOA)
3353111546
Large liquid_immersed power transformers without load_tap_changing, 30,001 kVA, OA (50,001 kVA, top FOA) to 100,000 kVA, OA (167,000 kVA, top FOA)
3353111549
Large liquid_immersed power transformers with load_tap_changing, 100,001 kVA, OA (167,001 kVA, top FOA) and larger
3353111552
Large liquid_immersed power transformers without load_tap_changing, 100,001 kVA, OA (167,001 kVA, top FOA) and larger
3353113
Fluorescent lamp ballast
33531131
Specialty transformers, except fluorescent lamp ballasts
3353113101
Open core and coil units, excluding machine tool control transformers and all units end_bell enclosed (250 VA and under)
3353113104
Machine tool control transformers
3353113107
Transformers for arc welders
3353113109
Indoor and outdoor current instrument transformers
3353113113
Indoor and outdoor voltage instrument transformers
3353113115
High intensity discharge lamp transformers (ballasts)
3353113116
All other specialty transformers (including luminous tube and ignition transformers), excluding internal combustion engine ignition
3353115
FLUORESCENT LAMP BALLASTS
33531150
Fluorescent lamp ballasts
3353115000
Fluorescent lamp ballasts
33531151
Fluorescent lamp ballasts
3353115100
Fluorescent lamp ballasts
3353115103
Fluorescent lamp ballasts, magnetic type, uncorrected power_factor type (less than 85 percent power factor), preheat start, single_ended compact lamps
3353115105
Fluorescent lamp ballasts, magnetic type, uncorrected power_factor type (less than 85 percent power factor), preheat start, linear and circline lamps, up to and including 20 watts
3353115107
Fluorescent lamp ballasts, magnetic type, uncorrected power_factor type (less than 85 percent power factor), preheat start, linear and circline lamps, 21 watts and over
3353115109
Fluorescent lamp ballasts, magnetic type, uncorrected power_factor type (less than 85 percent power factor), all other, including rapid start
3353115111
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), slimline and instant start, two_lamp, 75W/ 96T12/IS and 57W/72T12/IS
3353115113
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), other slimline and instant start
3353115115
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), rapid start, one_lamp, 40W/48T12/RS
3353115117
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), rapid start, two_lamp, 40W/48T12/RS
3353115119
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), rapid start, two_lamp, 32W/48T8/RS
3353115121
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), all other rapid start, 800 to 1,000 mA
3353115123
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), all other rapid start, 1,500 mA
3353115125
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), all other rapid start, other
3353115127
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), preheat start, single_ended compact lamps
3353115129
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), preheat start, linear and circline lamps
3353115131
Fluorescent lamp ballasts, magnetic type, corrected power_factor type (85 percent power factor or above), all other
3353115133
Fluorescent lamp ballasts, electronic type, uncorrected power_factor type (less than 90 percent power factor), single_ended compact lamps
3353115135
Fluorescent lamp ballasts, electronic type, uncorrected power_factor type (less than 90 percent power factor), all other
3353115137
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), instant start, one_ and two_lamp, 32W/ 48T8
3353115139
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), instant start, three_ and four_lamp, 32W/ 48T8
3353115141
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), instant start, two_lamp, 59W/96T8
3353115143
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), instant start, two_lamp, 75W/96T12/IS
3353115144
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), instant start, linear T5
3353115145
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), instant start, all other
3353115147
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, all 32W/48T8
3353115149
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, all other T8, 4 ft. and less
3353115151
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, two_lamp, 40W/ 48T12/RS
3353115153
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, 800 mA
3353115154
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, compact fluorescent up to and including 26W
3353115155
All other rapid start electronic corrected power~factor type (90 percent power factor or above)
3353115156
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, compact fluorescent 27W and over
3353115157
All other electronic corrected power~factor type (90 percent power factor or above)
3353115158
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, linear T5, normal output
3353115160
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, linear T5, high output
3353115162
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, dimming, linear
3353115164
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, program start, dimming, compact fluorescent
3353115166
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), rapid start, all other
3353115168
Fluorescent lamp ballasts, electronic type, corrected power_factor type (90 percent power factor or above), all other
3353116
Commercial, institutional and industrial general purpose transformers
3353117
Power regulators, boosters, and other transformers and parts for all transformer
33531171
Commercial, institutional, and industrial general_purpose transformers, all voltages
3353117101
Commercial, institutional, and industrial general_purpose transformers, single_ and three_phase, 3 kVA and below, all voltages
3353117104
Commercial, institutional, and industrial general_purpose transformers, single_ and three_phase, 3.01 kVA through 15 kVA, all voltages
3353117107
Commercial, institutional, and industrial general_purpose transformers, single_ and three_phase, 15.01 kVA through 100 kVA, all voltages
3353117111
Commercial, institutional, and industrial general_purpose transformers, single_ and three_phase, 100.01 kVA and above, all voltages
3353117113
Other commercial, institutional, and industrial general_purpose transformers, including saturable core reactors and voltage regulating transformers
3353118
Specialty transformers, except fluorescent lamp ballast
3353119
Power and distribution transformers, except parts
33531191
Power regulators, boosters, and other transformers and parts for all transformers
3353119101
Transmission and distribution voltage regulators, boosters, and other special_ purpose transformers
3353119104
Parts, including renewal and repair parts, subassemblies and accessories for all transformers
335311MM
Miscellaneous receipts
335311P
Primary products
335311SM
Secondary products and miscellaneous receipts
335311SS
Secondary products
Furthermore, the definition of NAICS code 335311 includes the following:
Airport lighting transformers manufacturing
Arc-welding transformers, separate solid-state, manufacturing
Autotransformers for switchboards (except telephone switchboards) manufacturing
Autotransformers manufacturing
Ballasts (i.e., transformers) manufacturing
Boosters, feeder voltage (i.e., electrical transformers), manufacturing
Burner ignition transformers manufacturing
Control transformers manufacturing
Current limiting reactors, electrical, manufacturing
Distribution transformers, electric, manufacturing
Electric furnace transformers manufacturing
Feeder voltage regulators and boosters (i.e., electrical transformers) manufactur
Fluorescent ballasts (i.e., transformers) manufacturing
Fluorescent lighting transformers manufacturing
Generator voltage regulators, electric induction and step-type (except engine ele
Instrument transformers (except complete instruments) for metering or protective
Isolation transformers manufacturing
Lamp ballasts manufacturing
Lighting transformers manufacturing
Lighting transformers, street and airport, manufacturing
Line voltage regulators (i.e., electric transformers) manufacturing
Luminous tube transformers manufacturing
Machine tool transformers manufacturing
Power transformers, electric, manufacturing
Regulating transformers, power system-type, manufacturing
Regulators (i.e., electric transformers), feeder voltage, manufacturing
Saturable transformers manufacturing
Signaling transformers, electric, manufacturing
Specialty transformers, electric, manufacturing
Substation transformers, electric power distribution, manufacturing
Transformers, electric power, manufacturing
Transformers, ignition, for use on domestic fuel burners, manufacturing
Transformers, reactor, manufacturing
Transformers, separate solid-state arc-welding, manufacturing
Transmission and distribution voltage regulators manufacturing
Voltage regulating transformers, electric power, manufacturing
Voltage regulators, transmission and distribution, manufacturing.
Step 2. Filtering and Smoothing
Based on the aggregate view of manufacturing power, distribution, and specialty transformers excluding electronic components as defined above, data were then collected for as many similar countries and cities as possible for that same definition, at the same level of the value chain. This generates a convenience sample 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 or cities on a sporadic basis. In other cases, data 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), cities 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 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 cities 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 cities along the aggregate consumption function, but also over time (i.e., not all cities are perceived to have the same income growth prospects over time and this effect can vary from city to city as well). Another way of looking at this is to say that latent demand for manufacturing power, distribution, and specialty transformers excluding electronic components is more likely to be similar across cities that have similar characteristics in terms of economic development (i.e., African cities will have similar latent demand structures controlling for the income variation across the pool of African cities).
This approach is useful across cities for which some notion of non-linearity exists in the aggregate consumption function. For some categories, however, the reader must realize that the numbers will reflect a city’s contribution to global latent demand and may never be realized in the form of local sales. For certain 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 cities in “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 cities is based on a proportion of their income (however small) being used to consume the categor
1 INTRODUCTION & METHODOLOGY 11
1.1 Overview and Definitions 11
1.2 Market Potential Estimation Methodology 11
1.2.1 Overview 11
1.2.2 What is Latent Demand and the P.I.E.? 12
1.2.3 The Methodology 12
1.2.3.1 Step 1. Product Definition and Data Collection 14
1.2.3.2 Step 2. Filtering and Smoothing 21
1.2.3.3 Step 3. Filling in Missing Values 21
1.2.3.4 Step 4. Varying Parameter, Non-linear Estimation 22
1.2.3.5 Step 5. Fixed-Parameter Linear Estimation 22
1.2.3.6 Step 6. Aggregation and Benchmarking 23
2 USING THE DATA 24
3 CITY SEGMENTS RANKED BY MARKET SIZE 25
3.1 Top 15 Markets 25
3.2 Markets 16 to 30 26
3.3 Remaining Cities by Market Rank 27
4 CITY SEGMENTS IN ALPHABETICAL ORDER 130
4.1 A: from Aalborg to Az Zawiyah 130
4.2 B: from Bacolod to Bydgoszcz 137
4.3 C: from Caaguazu to Cyangugu 145
4.4 D: from Da Nang to Dzhizak 153
4.5 E: from East London to Esteli 157
4.6 F: from Fagatogo to Funchal 159
4.7 G: from Gabes to Gyumri 162
4.8 H: from Hachinohe to Hyderabad 166
4.9 I: from Iasi to Izmir 170
4.10 J: from Jaboatao to Jyvaskyla 173
4.11 K: from Kabul to Kzyl-Orda 175
4.12 L: from La Ceiba to Lyon 183
4.13 M: from Macae to Mzuzu 189
4.14 N: from Nacala to Nzerekore 199
4.15 O: from Oaklahoma City to Oyem 204
4.16 Ö: from Örebro to Örebro 206
4.17 P: from Pago Pago to Pyuthan 207
4.18 Q: from Qandahar to Quito 214
4.19 R: from Rabat to Rustavi 215
4.20 S: from S. Luis Potosi to Szombathely 218
4.21 T: from Tabligbo to Tyre 230
4.22 U: from Uberaba to Utulei 237
4.23 V: from Vacoas-Phoenix to Vukovar 239
4.24 W: from Wadi Medani to Wuhan 242
4.25 X: from Xalapa to Xian 243
4.26 Y: from Yamagata to Yungkang 244
4.27 Z: from Zadar to Zvishavane 245
5 CITY SEGMENTS RANKED BY COUNTRY 246
5.1 Afghanistan 246
5.2 Albania 246
5.3 Algeria 247
5.4 American Samoa 247
5.5 Andorra 247
5.6 Angola 248
5.7 Antigua and Barbuda 248
5.8 Argentina 249
5.9 Armenia 250
5.10 Aruba 250
5.11 Australia 251
5.12 Austria 251
5.13 Azerbaijan 252
5.14 Bahrain 252
5.15 Bangladesh 253
5.16 Barbados 253
5.17 Belarus 254
5.18 Belgium 254
5.19 Belize 255
5.20 Benin 255
5.21 Bermuda 255
5.22 Bhutan 256
5.23 Bolivia 256
5.24 Bosnia and Herzegovina 256
5.25 Botswana 257
5.26 Brazil 258
5.27 Brunei 263
5.28 Bulgaria 263
5.29 Burkina Faso 264
5.30 Burma 264
5.31 Burundi 264
5.32 Cambodia 265
5.33 Cameroon 265
5.34 Canada 266
5.35 Cape Verde 266
5.36 Central African Republic 267
5.37 Chad 267
5.38 Chile 268
5.39 China 268
5.40 Christmas Island 269
5.41 Colombia 269
5.42 Comoros 269
5.43 Congo (formerly Zaire) 270
5.44 Cook Islands 270
5.45 Costa Rica 270
5.46 Cote dIvoire 271
5.47 Croatia 271
5.48 Cuba 272
5.49 Cyprus 272
5.50 Czech Republic 273
5.51 Denmark 273
5.52 Djibouti 274
5.53 Dominica 274
5.54 Dominican Republic 274
5.55 Ecuador 275
5.56 Egypt 275
5.57 El Salvador 276
5.58 Equatorial Guinea 276
5.59 Estonia 276
5.60 Ethiopia 277
5.61 Fiji 277
5.62 Finland 278
5.63 France 278
5.64 French Guiana 279
5.65 French Polynesia 279
5.66 Gabon 279
5.67 Georgia 280
5.68 Germany 280
5.69 Ghana 281
5.70 Greece 281
5.71 Greenland 282
5.72 Grenada 282
5.73 Guadeloupe 283
5.74 Guam 283
5.75 Guatemala 283
5.76 Guinea 284
5.77 Guinea-Bissau 284
5.78 Guyana 284
5.79 Haiti 285
5.80 Honduras 285
5.81 Hong Kong 285
5.82 Hungary 286
5.83 Iceland 286
5.84 India 287
5.85 Indonesia 288
5.86 Iran 289
5.87 Iraq 289
5.88 Ireland 290
5.89 Israel 290
5.90 Italy 291
5.91 Jamaica 291
5.92 Japan 292
5.93 Jordan 295
5.94 Kazakhstan 295
5.95 Kenya 296
5.96 Kiribati 296
5.97 Kuwait 296
5.98 Kyrgyzstan 297
5.99 Laos 297
5.100 Latvia 297
5.101 Lebanon 298
5.102 Lesotho 298
5.103 Liberia 298
5.104 Libya 299
5.105 Liechtenstein 299
5.106 Lithuania 299
5.107 Luxembourg 300
5.108 Macau 300
5.109 Madagascar 300
5.110 Malawi 301
5.111 Malaysia 301
5.112 Maldives 302
5.113 Mali 302
5.114 Malta 302
5.115 Marshall Islands 303
5.116 Martinique 303
5.117 Mauritania 303
5.118 Mauritius 304
5.119 Mexico 305
5.120 Micronesia Federation 306
5.121 Moldova 306
5.122 Monaco 306
5.123 Mongolia 307
5.124 Morocco 307
5.125 Mozambique 308
5.126 Namibia 308
5.127 Nauru 308
5.128 Nepal 309
5.129 New Caledonia 309
5.130 New Zealand 310
5.131 Nicaragua 310
5.132 Niger 311
5.133 Nigeria 311
5.134 Niue 312
5.135 Norfolk Island 312
5.136 North Korea 312
5.137 Norway 313
5.138 Oman 313
5.139 Pakistan 314
5.140 Palau 314
5.141 Palestine 314
5.142 Panama 315
5.143 Papua New Guinea 315
5.144 Paraguay 316
5.145 Peru 316
5.146 Philippines 317
5.147 Poland 317
5.148 Portugal 318
5.149 Puerto Rico 318
5.150 Qatar 319
5.151 Republic of Congo 319
5.152 Reunion 319
5.153 Romania 320
5.154 Russia 320
5.155 Rwanda 321
5.156 San Marino 321
5.157 Sao Tome E Principe 321
5.158 Saudi Arabia 322
5.159 Senegal 322
5.160 Seychelles 323
5.161 Sierra Leone 323
5.162 Singapore 323
5.163 Slovakia 323
5.164 Slovenia 324
5.165 Solomon Islands 324
5.166 Somalia 324
5.167 South Africa 325
5.168 South Korea 325
5.169 Spain 326
5.170 Sri Lanka 326
5.171 St. Kitts and Nevis 327
5.172 St. Lucia 327
5.173 St. Vincent and the Grenadines 327
5.174 Sudan 328
5.175 Suriname 328
5.176 Swaziland 328
5.177 Sweden 329
5.178 Switzerland 329
5.179 Syrian Arab Republic 330
5.180 Taiwan 331
5.181 Tajikistan 332
5.182 Tanzania 332
5.183 Thailand 333
5.184 The Bahamas 333
5.185 The British Virgin Islands 333
5.186 The Cayman Islands 334
5.187 The Falkland Islands 334
5.188 The Gambia 334
5.189 The Netherlands 335
5.190 The Netherlands Antilles 335
5.191 The Northern Mariana Island 335
5.192 The U.S. Virgin Islands 336
5.193 The United Arab Emirates 336
5.194 The United Kingdom 336
5.195 The United States 337
5.196 Togo 338
5.197 Tokelau 338
5.198 Tonga 339
5.199 Trinidad and Tobago 339
5.200 Tunisia 339
5.201 Turkey 340
5.202 Turkmenistan 340
5.203 Tuvalu 340
5.204 Uganda 341
5.205 Ukraine 341
5.206 Uruguay 342
5.207 Uzbekistan 342
5.208 Vanuatu 343
5.209 Venezuela 343
5.210 Vietnam 344
5.211 Wallis and Futuna 344
5.212 Western Sahara 344
5.213 Western Samoa 344
5.214 Yemen 345
5.215 Zambia 345
5.216 Zimbabwe 346
6 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 347
6.1 Disclaimers & Safe Harbor 347
6.2 ICON Group International, Inc. User Agreement Provisions 348
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