Market Potential Estimation Methodology
Overview
This study covers the world outlook for non-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture 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-upholstered wood household furniture manufacturing” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). non-upholstered wood household furniture manufacturing The NAICS code for non-upholstered wood household furniture manufacturing is 337122. It is for this definition of non-upholstered wood household furniture manufacturing that the aggregate latent demand estimates are derived. “Non-upholstered wood household furniture manufacturing” is specifically defined as follows:
337122
This U.S. industry comprises establishments primarily engaged in manufacturing nonupholstered wood household-type furniture and freestanding cabinets (except television, radio, and sewing machine cabinets). The furniture may be made on a stock or custom basis and may be assembled or unassembled (i.e., knockdown).
3371221
WOOD HOUSEHOLD DEN, FAMILY ROOM, LIBRARY, AND LIVING ROOM FURNITURE (EXCEPT CUSTOM SOLD DIRECTLY TO THE CUSTOMER AT RETAIL)
33712211
Wood household den, family room, library, and living room tables (except custom sold directly to the customer at retail), excluding card and telephone tables
3371221111
Wood household den, family room, library, and living room tables (except custom sold directly to the customer at retail), excluding card and telephone tables
33712212
Wood household den, family room, library, and living room cabinets, desks, bookcases, bookshelves, credenzas, and wall units (except custom sold directly to the customer at retail)
3371221211
Wood household den, family room, library, and living room cabinets (except custom sold directly to the customer at retail), including audio and television, excluding cabinets used as housings
3371221221
Wood household den, family room, library, and living room desks (except custom sold directly to the customer at retail)
3371221231
Wood household den, family room, living room, and library bookcases, bookshelves, and credenzas (except custom sold directly to the customer at retail), excluding wall units
3371221241
Wood household den, family room, library, and living room wall units (except custom sold directly to the customer at retail), including bookcase, desk, and storage units
33712213
Wood living room, library, family room, and den chairs, except dining room
3371221311
Wood living room, library, family room, and den chairs and seating, except dining room
3371221321
Wood living room, library, family room, and den rockers
3371221391
Other nonupholstered wood living room, library, family room, and den seating, including settees, loveseats, benches, stools, etc.
3371221395
Custom~made wood household furniture, except cabinets, nonupholstered
33712214
Other nonupholstered wood household den, family room, library, and living room furniture (except custom sold directly to the customer at retail), excluding dining room and kitchen chairs
3371221411
Nonupholstered wood household chairs (except custom sold directly to the customer at retail), excluding dining room, kitchen, and rocking chairs
3371221421
Nonupholstered wood household den, family room, library, and living room rocking chairs (except custom sold directly to the customer at retail)
3371221491
Other nonupholstered wood household den, family room, library, and living room seating (except custom sold directly to the customer at retail), including benches, loveseats, settees, and stools
3371221493
Other nonupholstered wood den, family room, library, and living room furniture (except custom sold directly to the customer at retail), including bars, breakfronts, hanging shelves, and magazine racks
3371222
Wood living room, library, family room and den furniture
337122219
Cabinets, except sewing machine cabinets
337122231
Chairs, except dining room (including rockers)
337122241
Tables, except card and telephone tables
337122251
Desks
337122271
Credenzas, bookcases, and bookshelves
337122298
Other nonupholstered living room furniture
33712229811
Wall units (desk, bookcase, and storage type)
33712229899
All other living room furniture
3371223
Wood dining room and kitchen furniture, except cabinets
337122311
Tables, dining room, 30 x 40 inches and greater
337122331
Dining room chairs, incl. upholstered and nonupholstered
337122351
Buffets and servers, dining room
337122371
China and corner cabinets, dining room
337122398
Other dining room and kitchen furniture
3371224
WOOD DINING ROOM AND KITCHEN FURNITURE (EXCEPT CUSTOM SOLD DIRECTLY TO THE CUSTOMER AT RETAIL), EXCLUDING KITCHEN CABINETS
33712241
Wood dining room tables (except custom sold directly to the customer at retail), 30 inches by 40 inches and larger
3371224111
Wood dining room tables (except custom sold directly to the customer at retail), 30 inches by 40 inches and larger
33712242
Wood dining room chairs (except custom sold directly to the customer at retail)
3371224211
Wood dining room chairs (except custom sold directly to the customer at retail)
33712243
Other wood dining room and kitchen furniture (except custom sold directly to the customer at retail)
3371224311
Wood dining room buffets and servers (except custom sold directly to the customer at retail)
3371224321
Wood dining room china and corner cabinets (except custom sold directly to the customer at retail)
3371224391
Other nonupholstered wood dining room and kitchen seating
3371224395
Other nonupholstered wood dining room and kitchen furniture, including junior dining furniture sets
3371224396
Other nonupholstered wood dining and kitchen furniture (except custom sold directly to the customer at retail), including dining room and kitchen seating and junior dining furniture sets
3371225
Wood bedroom furniture
337122511
Beds, incl. bunk and water beds, excl crib and headboard beds
337122513
Headboards and headboard sets
337122521
Dressers, vanities and dressing tables
337122533
Wardrobes, chifforobes, armoires, & wardrobe-type cabinets
337122535
Chests of drawers, including cedar chests
337122561
Night tables and stands
337122598
Other nonupholstered bedroom furniture
3371225A
Beds, headboards and footboards
3371226
Infants' and children's wood furniture
3371227
Unpainted, unassembled, knock-down, and outdoor furniture
33712271
Wood bedroom furniture, including beds, headboards, bunk beds, cribs, cradles, etc.
3371227111
Wood beds, excluding headboards, headboard beds, bunk beds, cribs, cradles, hollywood beds, and youth beds
3371227121
Wood headboards and headboard beds, including padded
3371227131
Wood bunk beds, excluding mattresses and detachable springs
3371227141
Wood conventional water beds
33712272
Wood bedroom dressers, vanities, and dressing tables
3371227211
Wood bedroom dressers, vanities, and dressing tables
33712273
Wood bedroom chests of drawers
3371227311
Wood bedroom chests of drawers
33712274
Wood bedroom wardrobes, chifforobes, armoires, wardrobe~type cabinets, cedar chests, and night tables and stands
337122741
Unpainted wood furniture
3371227411
Wood bedroom wardrobes, chifforobes, armoires, and wardrobe~type cabinets
3371227421
Wood bedroom cedar chests
3371227431
Wood bedroom night tables and stands
3371227491
Other nonupholstered wood bedroom furniture, including commodes, bed rails, chairs, valet stands, etc
337122751
Unassembled, knock-down, and outdoor furniture
3371228
WOOD BEDROOM FURNITURE (EXCEPT CUSTOM SOLD DIRECTLY TO THE CUSTOMER AT RETAIL)
33712281
Wood beds and headboards (except custom sold directly to the customer at retail), excluding cribs, cradles, hollywood beds, and youth beds
3371228111
Wood beds (except custom sold directly to the customer at retail), excluding bunk beds, cribs, cradles, headboards, headboard beds, hollywood beds, water beds, and youth beds
3371228121
Wood headboards and headboard beds (except custom sold directly to the customer at retail), including padded
3371228131
Wood bunk beds (except custom sold directly to the customer at retail), excluding mattresses and detachable springs
3371228141
Conventional wood waterbeds (except custom sold directly to the customer at retail)
33712282
Wood bedroom dressers, dressing tables, and vanities (except custom sold directly to the customer at retail)
3371228211
Wood bedroom dressers, dressing tables, and vanities (except custom sold directly to the customer at retail)
33712283
Wood bedroom chests of drawers (except custom sold directly to the customer at retail)
3371228311
Wood bedroom chests of drawers (except custom sold directly to the customer at retail)
33712284
Other nonupholstered wood bedroom furniture (except custom sold directly to the customer at retail)
3371228411
Wood bedroom armoires, chifforobes, wardrobes, and wardrobe_type cabinets (except custom sold directly to the customer at retail)
3371228421
Wood bedroom cedar chests (except custom sold directly to the customer at retail)
3371228431
Wood bedroom night tables and stands (except custom sold directly to the customer at retail)
3371228481
Other nonupholstered wood bedroom furniture (except custom sold directly to the customer at retail), including bed rails, chairs, commodes, and valet stands
337122A
INFANTS’ AND CHILDREN’S WOOD FURNITURE (EXCEPT CUSTOM SOLD DIRECTLY TO THE CUSTOMER AT RETAIL)
337122A1
Infants’ and children’s wood furniture (except custom sold directly to the customer at retail)
337122A111
Infants’ and children’s wood cribs (except custom sold directly to the customer at retail), including springs sold as part of the crib
337122A121
Infants’ and children’s wood seating (chairs, nursery seats, high chairs, etc.)
337122A131
Other infants’ and children’s wood bedroom furniture (except custom sold directly to the customer at retail), including youth beds
337122A141
Other infants’ and children’s nonupholstered wood furniture
337122A151
Other infants’ and children’s nonupholstered wood furniture (except custom sold directly to the customer at retail), including wood seating, such as chairs, high chairs, and nursery seats
337122E
WOOD OUTDOOR FURNITURE, UNPAINTED WOOD FURNITURE, AND READY_TO_ASSEMBLE WOOD FURNITURE (EXCEPT CUSTOM SOLD DIRECTLY TO THE CUSTOMER AT RETAIL)
337122E1
Wood outdoor furniture, unpainted wood furniture, and ready_to_assemble wood furniture (except custom sold directly to the customer at retail)
337122E111
Wood outdoor furniture (except custom sold directly to the customer at retail) , assembled and ready_to_assemble, including beach, lawn, and porch furniture
337122E121
Unpainted wood furniture, assembled (furniture_in_the_white) (except custom sold directly to the customer at retail), including bookcases, chairs, chests of drawers, desks, tables, and vanities
337122E131
Ready_to_assemble wood household seating (except custom sold directly to the customer at retail), unpainted and finished, sold in kits
337122E141
Ready_to_assemble wood kitchen furniture (except custom sold directly to the customer at retail), unpainted and finished, sold in kits
337122E151
Ready_to_assemble wood bedroom furniture (except custom sold directly to the customer at retail), unpainted and finished, sold in kits
337122E161
Ready_to_assemble wood home entertainment centers (except custom sold directly to the customer at retail), unpainted and finished, sold in kits
337122E171
Ready_to_assemble wood shelving (except custom sold directly to the customer at retail), unpainted and finished, sold in kits
337122E181
Ready_to_assemble wood home_office computer furniture (except custom sold directly to the customer at retail), unpainted and finished, sold in kits
337122E191
Other ready_to_assemble wood furniture, unpainted and finished, sold in kits (except custom sold directly to the customer at retail)
337122H
CUSTOM NONUPHOLSTERED WOOD HOUSEHOLD FURNITURE SOLD DIRECTLY TO THE CUSTOMER AT RETAIL (EXCEPT KITCHEN CABINETS, BATHROOM VANITIES, AND RELATED CABINETWORK)
337122H1
Custom nonupholstered wood household furniture sold directly to the customer at retail (except kitchen cabinets, bathroom vanities, and related cabinetwork)
337122H100
Custom nonupholstered wood household furniture sold directly to the customer at retail (except kitchen cabinets, bathroom vanities, and related cabinetwork)
337122M
Miscellaneous receipts
337122P
Primary products
337122S
Secondary products
337122SM
Secondary products and miscellaneous receipts
Furthermore, the definition of NAICS code 337122 includes the following:
Bed frames, wood household-type, manufacturing
Bedroom furniture (except upholstered), wood household-type, manufacturing
Beds (except hospital), wood household-type, manufacturing
Beds, wood dormitory-type, manufacturing
Beds, wood hotel-type, manufacturing
Bookcases, wood household-type, manufacturing
Buffets (furniture), wood, manufacturing
Cabinets, wood household-type, freestanding, manufacturing
Camp furniture, wood, manufacturing
Card table sets (furniture), wood, manufacturing
Cedar chests manufacturing
Chairs (except upholstered), wood household-type, manufacturing
China closets, wood, manufacturing
Coffee tables, wood, manufacturing
Computer furniture, wood household-type, manufacturing
Cots, wood household-type, manufacturing
Cradles, wood, manufacturing
Cribs (i.e., baby beds), wood, manufacturing
Desks, wood household-type, manufacturing
Dining room chairs (including upholstered), wood, manufacturing
Dining room furniture, wood household-type, manufacturing
Dressers, wood, manufacturing
Dressing tables, wood, manufacturing
End tables, wood, manufacturing
Furniture, outdoor wood household-type (e.g., beach, garden, lawn, porch), manufa
Furniture, unassembled or knock-down wood household-type, manufacturing
Furniture, unfinished wood household-type, manufacturing
Furniture, wood household-type, not upholstered (except TV and radio housings, an
Futon frames manufacturing
Garden furniture, wood, manufacturing
Hammocks, wood framed, manufacturing
Headboards, wood, manufacturing
High chairs, wood, children's, manufacturing
Home entertainment centers, wood, manufacturing
Household-type furniture, wood, not upholstered (except TV and radio housings and
Juvenile furniture (except upholstered), wood, manufacturing
Kitchen chairs (e.g., upholstered), wood, manufacturing
Kitchen furniture, wood household-type, manufacturing
Knickknack shelves, wood, manufacturing
Lawn furniture, wood, manufacturing
Living room furniture (except upholstered), wood, manufacturing
Magazine racks, wood, manufacturing
Night stands, wood, manufacturing
Nonupholstered, household-type, custom wood furniture, manufacturing
Nursery furniture (except upholstered), wood, manufacturing
Playpens, children's wood, manufacturing
Porch furniture (except upholstered), wood, manufacturing
Rockers (except upholstered), wood, manufacturing
Room dividers, wood household-type, manufacturing
Serving carts, wood household-type, manufacturing
Stools, wood household-type (except upholstered), manufacturing
Tables, wood household-type, manufacturing
TV stands and similar stands for consumer electronics, wood, manufacturing
Vanities, freestanding, wood, manufacturing
Wardrobes, wood household-type, manufacturing
Water bed frames, wood, manufacturing.
Step 2. Filtering and Smoothing
Based on the aggregate view of non-upholstered wood household furniture 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-upholstered wood household furniture 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 con
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