|
|
 |
|
Viewing report
|
|
 |
 |
The 2011 Report on Non-Current-Carrying Wiring Device Manufacturing: World Market Segmentation by City
ICON Group International, Jan 2011, Pages: 334
Market Potential Estimation Methodology Overview This study covers the world outlook for non-current-carrying wiring device manufacturing 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 non-current-carrying wiring device manufacturing. 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 non-current-carrying wiring device manufacturing 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 non-current-carrying wiring device manufacturing 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-current-carrying wiring device manufacturing 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 non-current-carrying wiring device manufacturing 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 non-current-carrying wiring device manufacturing. 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 non-current-carrying wiring device manufacturing. 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 non-current-carrying wiring device manufacturing.
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 “non-current-carrying wiring device manufacturing” 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-current-carrying wiring device manufacturing 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 “non-current-carrying wiring device manufacturing” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). non-current-carrying wiring device manufacturing The NAICS code for non-current-carrying wiring device manufacturing is 335932. It is for this definition of non-current-carrying wiring device manufacturing that the aggregate latent demand estimates are derived. “Non-current-carrying wiring device manufacturing” is specifically defined as follows:
335932 This U.S. industry comprises establishments primarily engaged in manufacturing noncurrent-carrying wiring devices.
3359321 Electrical transmission line and utility pole hardware
33593210 Noncurrent~carrying pole and transmission line hardware
3359321000 Noncurrent~carrying pole and transmission line hardware
3359321002 Pole and transmission line construction materials, also known as overhead and underground line hardware for electric transmission, distribution, and communication lines
3359321004 Pole and transmission line anchors
3359321006 All other pole and transmission line hardware
33593211 Noncurrent_carrying pole and transmission line hardware
3359321100 Noncurrent_carrying pole and transmission line hardware
3359321102 Pole and transmission line construction materials (overhead and underground line hardware for electric transmission, distribution, and communication lines)
3359321104 Pole and transmission line anchors
3359321106 All other pole and transmission line hardware
335932112 Pole and transmission line construction materials, commercially available
335932113 Pole and transmission line anchors
335932114 Pole and transmission line construction materials, not commercially available
335932151 Suspension hardware for high voltage insulators
3359322 Electrical conduit and conduit fittings
33593221 Electrical conduit, raceways, and wireways
335932211 Rigid metal conduit, excluding couplings, nipples, bends and elbows
33593221121 Steel, standard weights
33593221199 All other rigid metal conduit
335932214 Nonmetallic conduit, rigid, including plastics
335932215 Electrical metallic tubing
335932216 Flexible steel conduit
335932217 Flexible nonmetallic conduit, including plastics and liquid-tight
335932218 Metal raceways and wireways, including fittings: surface and underfloor
33593221834 Surface
33593221837 Underfloor
335932219 Metal raceways and wireways, including fittings: ventilated cable trays and accessories
33593228 Electrical conduit fittings
335932281 Rigid metal conduit fittings: cast conduit bodies, covers, and gaskets
335932282 All other rigid metal conduit fittings, including couplings, nipples, bends, and elbows
33593228253 Couplings, connectors and unions
33593228254 Locknuts and bushings
33593228259 All other rigid metal conduit fittings
335932283 Nonmetallic rigid conduit fittings, including plastics
335932284 EMT fittings (couplings and connectors), all types
33593228456 Gland type
33593228457 Set screw type
33593228458 All other types
335932285 Service entrance caps, ells, and connectors
335932286 Cable, cord, and flexible conduit fittings
33593228611 Armored cable, metallic sheathed cable, and flexible conduit fittings
33593228612 Nonmetallic sheathed cable and cord fittings
335932287 All other electrical conduit fittings
3359323 All other noncurrent-carrying wiring devices
33593230 Noncurrent~carrying electrical conduit and conduit fittings, including plastics conduit and conduit fittings
3359323000 Noncurrent~carrying electrical conduit and conduit fittings, including plastics conduit and conduit fittings
33593231 Noncurrent_carrying electrical conduit and conduit fittings, including plastics conduit and conduit fittings
3359323100 Noncurrent_carrying electrical conduit and conduit fittings, including plastics conduit and conduit fittings
3359323101 Electrical conduit and conduit fittings, rigid metallic conduit (excluding couplings, nipples, bends, and elbows)
3359323102 Standard weights (steel) rigid metallic conduit, excluding couplings, nipples, bends, and elbows
3359323104 All other metallic rigid metal conduit, excluding couplings, nipples, bends, and elbows
3359323106 Electrical conduit and conduit fittings, nonmetallic conduit
3359323108 Electrical conduit and conduit fittings, electrical metallic tubing
3359323111 Electrical conduit and conduit fittings, flexible steel and aluminum conduit
3359323112 Electrical conduit and conduit fittings, flexible nonmetallic conduit
3359323114 Electrical conduit and conduit fittings, raceways and wire ways (including fittings), metal
3359323116 Electrical conduit and conduit fittings, ventilated cable tray and accessories
3359323118 Electrical conduit and conduit fittings, cast conduit bodies, covers, and gaskets
33593232 Other conduit fittings, couplings, nipples, bends, and elbows
3359323221 Rigid conduit couplings, connectors, and unions
3359323222 Rigid conduit locknuts and bushings
3359323224 All other rigid conduit fittings
3359323226 Nonmetallic conduit fittings
3359323228 Gland EMT fittings (couplings and connectors)
3359323231 Set~screw EMT fittings (couplings and connectors)
3359323232 All other EMT fittings (couplings and connectors)
3359323234 Service entrance caps, ells, and connectors
3359323236 Armored cable, metallic sheathed cable, and flexible conduit fittings
3359323238 Liquid~tight flexible conduit fittings
3359323241 Nonmetallic sheathed cable and cord fittings
3359323242 Other electric conduit fittings
33593233 Stamped metal boxes, covers, and accessories, including stamped conduit boxes
335932331 Stamped metal switch and receptacle boxes
335932332 Stamped metal outlet boxes
335932333 Stamped metal covers
335932334 Stamped supports, bar hangers and accessories
33593234 Cast metal boxes, covers, gaskets, and accessories
335932341 FS and FD switch and receptacle types
335932342 Outlet type
335932343 Junction type
33593235 Plastic boxes and covers
33593236 Switch, outlet, FM/TV, and telephone wall plates
33593236535 Metallic
33593236536 Nonmetallic
33593237 All other noncurrent-carrying wiring devices
335932378 Floor boxes and covers
335932379 All other noncurrent-carrying wiring devices, n.e.c.
3359325 OTHER NONCURRENT~CARRYING WIRING DEVICES AND SUPPLIES (BOXES, COVERS, BAR HANGERS, ETC.)
33593250 Other noncurrent~carrying wiring devices and supplies (boxes, covers, bar hangers, etc.)
3359325000 Other noncurrent~carrying wiring devices and supplies (boxes, covers, bar hangers, etc.)
33593251 Stamped metal switch and receptacle boxes
3359325102 Stamped metal switch and receptacle boxes
33593252 Other stamped metal boxes, covers, and accessories
3359325204 Stamped metal outlet boxes
3359325206 Stamped metal covers
3359325208 Stamped metal supports, bar hangers, and other accessories
33593253 Cast metal boxes, covers, gaskets, accessories, switch, outlet walls plates and boxes of other materials
3359325311 Cast metal FS and FD switch and receptacle cast metal boxes, covers, gaskets, and accessories
3359325312 Cast metal outlet boxes, covers, gaskets, and accessories
3359325314 Cast metal junction boxes, covers, gaskets, and accessories
3359325316 Metallic switch, outlet, FM~TV, and telephone wall plates
3359325318 Nonmetallic switch, outlet, FM~TV, and telephone wall plates
3359325321 Noncurrent carrying plastics boxes and covers, including junction, outlet, and receptacle boxes
3359325322 Noncurrent carrying floor boxes and covers
3359325324 Other noncurrent carrying wiring devices and supplies
3359326 OTHER NONCURRENT_CARRYING WIRING DEVICES AND SUPPLIES (BOXES, COVERS, BAR HANGERS, ETC.)
33593261 Other noncurrent_carrying wiring devices and supplies (boxes, covers, bar hangers, etc.)
3359326100 Other noncurrent_carrying wiring devices and supplies (boxes, covers, bar hangers, etc.)
335932M Miscellaneous receipts
335932P Primary products
335932S Secondary products
335932SM Secondary products and miscellaneous receipts
Furthermore, the definition of NAICS code 335932 includes the following:
Boxes, electrical wiring (e.g., junction, outlet, switch), manufacturing Conduits and fittings, electrical, manufacturing Electrical metallic tube (EMTs) manufacturing EMTs (electrical metallic tube) manufacturing Face plates (i.e., outlet or switch covers) manufacturing Hardware, transmission pole and line, manufacturing Insulators, electrical (except glass, porcelain), manufacturing Junction boxes, electrical wiring, manufacturing Outlet boxes, electrical wiring, manufacturing Plates (i.e., outlet or switch covers), face, manufacturing Raceways manufacturing Switch boxes, electrical wiring, manufacturing Transmission pole and line hardware manufacturing.
Step 2. Filtering and Smoothing Based on the aggregate view of non-current-carrying wiring device manufacturing 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 non-current-carrying wiring device manufacturing 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 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 2000 cities, there will always be those cities, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible. For these cities, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a city’s stock of income), but a function of current income (a city’s flow of income). In the long run, if a city has no current income, the latent demand for non-current-carrying wiring device manufacturing is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., cities which earn low levels of income will not use their savings, in the long run, to demand non-current-carrying wiring device manufacturing). In a graphical sense, for low income cities, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, low-income cities are assumed to have a latent demand proportional to their income, based on the city 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 cities 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.
|
 |
|
|