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The 2009 Report on Non-Metallic Mineral Mining and Quarrying: World Market Segmentation by City
ICON Group International, May 2009, Pages: 340
Market Potential Estimation Methodology
Overview
This study covers the world outlook for non-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying. 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-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying. 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-metallic mineral mining and quarrying. 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-metallic mineral mining and quarrying.
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-metallic mineral mining and quarrying” 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-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). For a complete definition of non-metallic mineral mining and quarrying, please refer to the Web site at http://www.icongrouponline.com/codes/NAICS.html. The NAICS code for non-metallic mineral mining and quarrying is 2123. It is for this definition of non-metallic mineral mining and quarrying that the aggregate latent demand estimates are derived. “Non-metallic mineral mining and quarrying” is specifically defined as follows:
2123
This industry group comprises establishments primarily engaged in developing mine sites, or in mining or quarrying nonmetallic minerals (except fuels). Also included are certain well and brine operations, and preparation plants primarily engaged in beneficiating (e.g., crushing, grinding, washing, and concentrating) nonmetallic minerals.
Beneficiation is the process whereby the extracted material is reduced to particles which can be separated into mineral and waste, the former suitable for further processing or direct use. The operations that take place in beneficiation are primarily mechanical, such as grinding, washing, magnetic separation, and centrifugal separation. In contrast, manufacturing operations primarily use chemical and electrochemical processes, such as electrolysis and distillation. However, some treatments, such as heat treatments, take place in both the beneficiation and the manufacturing (i.e., smelting/refining) stages. The range of preparation activities varies by mineral and the purity of any given ore deposit. While some minerals, such as petroleum and natural gas, require little or no preparation, others are washed and screened, while yet others, such as gold and silver, can be transformed into bullion before leaving the mine site.
21231
This industry comprises (1) establishments primarily engaged in developing the mine site, mining or quarrying dimension stone (i.e., rough blocks and/or slabs of stone), or mining and quarrying crushed and broken stone and/or (2) preparation plants primarily engaged in beneficiating stone (e.g., crushing, grinding, washing, screening, pulverizing, and sizing).
212311
This U.S. industry comprises establishments primarily engaged in developing the mine site and/or mining or quarrying dimension stone (i.e., rough blocks and/or slabs of stone).
2123110
DIMENSION STONE
21231101
Rough dimension limestone
2123110111
Rough dimension limestone
21231102
Rough dimension granite
2123110221
Rough dimension granite
21231103
Other rough dimension stone (slate, marble, trap rock, sandstone, and miscellaneous stone)
2123110391
Other rough dimension stone (slate, marble, trap rock, sandstone, and miscellaneous stone)
2123112
Dimension stone mining and quarrying
212311M
Miscellaneous receipts
212311P
Primary products
212311S
Secondary products
212311SM
Secondary products and miscellaneous receipts
212312
This U.S. industry comprises (1) establishments primarily engaged in developing the mine site, mining or quarrying crushed and broken limestone (including related rocks, such as dolomite, cement rock, marl, travertine, and calcareous tufa); and (2) preparation plants primarily engaged in beneficiating limestone (e.g., grinding or pulverizing).
2123120
CRUSHED AND BROKEN LIMESTONE
21231201
Crushed and broken limestone
2123120100
Crushed and broken limestone
2123123
Crushed and broken limestone mining and quarrying
212312M
Miscellaneous receipts
212312P
Primary products
212312S
Secondary products
212312SM
Secondary products and miscellaneous receipts
212313
This U.S. industry comprises: (1) establishments primarily engaged in developing the mine site, and/or mining or quarrying crushed and broken granite (including related rocks, such as gneiss, syenite, and diorite); and (2) preparation plants primarily engaged in beneficiating granite (e.g., grinding or pulverizing).
2123130
CRUSHED AND BROKEN GRANITE
21231301
Crushed and broken granite
2123130100
Crushed and broken granite
2123132
Crushed and broken granite mining and quarrying
212313M
Miscellaneous receipts
212313P
Primary products
212313S
Secondary products
212313SM
Secondary products and miscellaneous receipts
212319
This U.S. industry comprises: (1) establishments primarily engaged in developing the mine site and/or mining or quarrying crushed and broken stone (except limestone and granite); (2) preparation plants primarily engaged in beneficiating (e.g., grinding and pulverizing) stone (except limestone and granite); and (3) establishments primarily engaged in mining or quarrying bituminous limestone and bituminous sandstone.
2123190
BITUMINOUS LIMESTONE, BITUMINOUS SANDSTONE, AND OTHER CRUSHED AND BROKEN STONE
21231901
Bituminous limestone, bituminous sandstone, and other crushed and broken stone
2123190111
Bituminous limestone and bituminous sandstone
2123190121
Other crushed and broken stone
2123191
Other crushed and broken stone mining and quarrying
212319M
Miscellaneous receipts
212319P
Primary products
212319S
Secondary products
212319SM
Secondary products and miscellaneous receipts
21232
This industry comprises (1) establishments primarily engaged in developing the mine site and/or mining, quarrying, dredging for sand and gravel, or mining clay, (e.g., china clay, paper clay and slip clay) and (2) preparation plants primarily engaged in beneficiating (e.g., washing, screening, and grinding) sand and gravel, clay, and ceramic and refractory minerals.
212321
This U.S. industry comprises establishments primarily engaged in one or more of the following: (1) operating commercial grade (i.e., construction) sand and gravel pits; (2) dredging for commercial grade sand and gravel; and (3) washing, screening, or otherwise preparing commercial grade sand and gravel.
2123211
CONSTRUCTION SAND AND GRAVEL (RUN OF PIT OR BANK)
21232111
Construction sand and gravel (run of pit or bank)
2123211111
Construction sand (run of pit or bank)
2123211121
Construction gravel (run of pit or bank)
2123213
Construction sand
21232131
Construction sand (washed, screened, or otherwise treated)
2123213111
Construction sand (washed, screened, or otherwise treated)
21232132
Construction gravel (washed, screened, or otherwise treated)
2123213221
Construction gravel (washed, screened, or otherwise treated)
21232138
Mountain
21232139
Pacific
2123213A
Northeastern Region
2123213B
North Central Region
2123213C
Southern Region
2123213D
Western Region
2123215
Construction gravel
21232158
Mountain
21232159
Pacific
2123215A
Northeastern Region
2123215B
North Central Region
2123215C
Southern Region
2123215D
Western Region
212321M
Miscellaneous receipts
212321P
Primary products
212321S
Secondary products
212321SM
Secondary products and miscellaneous receipts
212322
This U.S. industry comprises establishments primarily engaged in one or more of the following: (1) operating industrial grade sand pits; (2) dredging for industrial grade sand; and (3) washing, screening, or otherwise preparing industrial grade sand.
2123221
Industrial glass sand
21232211
Industrial glass sand
2123221100
Industrial glass sand
2123223
INDUSTRIAL MOLDING SAND
21232231
Industrial molding sand
2123223100
Industrial molding sand
2123225
Industrial molding sand
2123229
Other industrial sand
21232291
Other industrial sand
2123229100
Other industrial sand
212322M
Miscellaneous receipts
212322P
Primary products
212322S
Secondary products
212322SM
Secondary products and miscellaneous receipts
212324
This U.S. industry comprises (1) establishments primarily engaged in developing the mine site and/or mining kaolin or ball clay (e.g., china clay, paper clay, and slip clay) and (2) establishments primarily engaged in beneficiating (i.e., preparing) kaolin or ball clay.
2123240
KAOLIN AND BALL CLAY
21232401
Kaolin and ball clay
2123240111
Kaolin
2123240121
Ball clay
21232402
Kaolin and ball clay
2123240212
Kaolin
2123240222
Ball clay
2123241
Crude kaolin and ball clay
2123242
Prepared kaolin and ball clay
212324M
Miscellaneous receipts
212324P
Primary products
212324S
Secondary products
212324SM
Secondary products and miscellaneous receipts
212325
This U.S. industry comprises establishments primarily engaged in one or more of the following: (1) mining clay (except kaolin and ball), ceramic, or refractory minerals; (2) developing the mine site for clay, ceramic, or refractory minerals; and (3) beneficiating (i.e., preparing) clay (except kaolin and ball), ceramic, or refractory minerals.
2123251
Bentonite
21232511
Bentonite
2123251100
Bentonite
2123252
Fire clay
21232521
Bentonite
2123252100
Bentonite
2123253
Fullers earth
21232531
Fire clay
2123253100
Fire clay
2123254
FIRE CLAY
21232541
Fire clay
2123254100
Fire clay
2123255
FULLER’S EARTH
21232551
Fuller’s earth
2123255100
Fuller’s earth
2123256
Feldspar (crude, crushed, or ground)
21232561
Fuller’s earth
2123256100
Fuller’s earth
2123257
Common (miscellaneous) clay and shale
21232571
Feldspar (crude, crushed, or ground)
2123257100
Feldspar (crude, crushed, or ground)
2123258
COMMON (MISCELLANEOUS) CLAY AND SHALE
21232581
Common (miscellaneous) clay and shale
2123258111
Crude common (miscellaneous) clay and shale
2123258121
Prepared common (miscellaneous) clay and shale
2123259
Other clay, ceramic, and refractory materials including magnesite and brucite
21232591
Other clay, ceramic, and refractory minerals including magnesite and brucite
2123259100
Other clay, ceramic, and refractory minerals including magnesite and brucite
212325A
FELDSPAR (CRUDE, CRUSHED, OR GROUND)
212325A1
Feldspar (crude, crushed, or ground)
212325A100
Feldspar (crude, crushed, or ground)
212325B
COMMON (MISCELLANEOUS) CLAY AND SHALE
212325B1
Common (miscellaneous) clay and shale
212325B111
Crude common (miscellaneous) clay and shale
212325B122
Prepared common (miscellaneous) clay and shale
212325M
Miscellaneous receipts
212325P
Primary products
212325S
Secondary products
212325SM
Secondary products and miscellaneous receipts
21239
This industry comprises establishments primarily engaged in developing the mine site, mining, and/or milling or otherwise beneficiating (i.e., preparing) nonmetallic minerals (except coal, stone, sand, gravel, clay, ceramic, and refractory minerals).
212391
This U.S. industry comprises establishments primarily engaged in developing the mine site, mining and/or milling, or otherwise beneficiating (i.e., preparing) natural potassium, sodium, or boron compounds. Drylake brine operations are included in this industry, as well as establishments engaged in producing the specified minerals from underground and open pit mines.
2123911
Crude potassium salts
21239111
Potassium salts and boron compounds
2123911100
Potassium salts and boron compounds
2123912
Processed or refined potassium salts
2123913
Natural sodium carbonates and sulfates
21239131
Sodium carbonate and sulfate
2123913111
Sodium carbonate (natural)
2123913121
Sodium sulfate (natural)
2123914
Boron compounds
212391M
Miscellaneous receipts
212391P
Primary products
212391S
Secondary products
212391SM
Secondary products and miscellaneous receipts
212392
This U.S. industry comprises establishments primarily engaged in developing the mine site, mining, milling, and/or drying or otherwise beneficiating (i.e., preparing) phosphate rock.
2123921
Crude phosphate ore or matrix
21239211
Crude phosphate rock (ore or matrix)
2123921100
Crude phosphate rock (ore or matrix)
2123922
Processed phosphate rock
212392201
Washed or concentrated phosphate rock
212392206
Dried phosphate rock
212392208
Calcined or sintered phosphate rock
2123923
PREPARED PHOSPHATE ROCK
21239231
Prepared phosphate rock
2123923111
Washed and concentrated phosphate rock
2123923131
Dried, calcined, sintered, or nodulized phosphate rock
212392M
Miscellaneous receipts
212392P
Primary products
212392S
Secondary products
212392SM
Secondary products and miscellaneous receipts
212393
This U.S. industry comprises establishments primarily engaged in developing the mine site, mining, milling, and/or drying or otherwise beneficiating (i.e., preparing) chemical or fertilizer mineral raw materials (except potash, soda, boron, and phosphate rock).
2123931
Barite
21239311
Barite
2123931100
Barite
2123932
Fluorspar
21239321
Barite
2123932100
Barite
2123933
Rock salt
21239331
Rock salt
2123933100
Rock salt
2123934
Sulfur
2123935
NATIVE SULFUR
21239351
Native sulfur
2123935100
Native sulfur
2123939
Chemical and fertilizer mineral mining, n.e.c.
21239391
Other chemical and fertilizer minerals
2123939100
Other chemical and fertilizer minerals
212393M
Miscellaneous receipts
212393P
Primary products
212393S
Secondary products
212393SM
Secondary products and miscellaneous receipts
212399
This U.S. industry comprises establishments primarily engaged in developing the mine site, mining and/or milling or otherwise beneficiating (i.e., preparing) nonmetallic minerals (except stone, sand, gravel, clay, ceramic, refractory minerals, chemical and fertilizer minerals).
2123991
DIATOMITE, CRUDE AND PREPARED
21239911
Diatomite, crude and prepared
2123991100
Diatomite, crude and prepared
2123992
DIATOMITE, CRUDE AND PREPARED
21239921
Diatomite, crude and prepared
2123992100
Diatomite, crude and prepared
2123993
GYPSUM
21239931
Gypsum
2123993100
Gypsum
2123994
GYPSUM
21239941
Gypsum
2123994100
Gypsum
2123995
TALC, SOAPSTONE, AND PYROPHYLLITE
21239951
Talc, soapstone, and pyrophyllite
2123995100
Talc, soapstone, and pyrophyllite
2123996
TALC, SOAPSTONE, AND PYROPHYLLITE
21239961
Talc, soapstone, and pyrophyllite
2123996100
Talc, soapstone, and pyrophyllite
2123998
OTHER NONMETALLIC MINERALS
21239981
Other nonmetallic minerals
2123998112
Mica
2123998121
Native asphalt and bitumens (except bituminous limestone and bituminous sandstone)
2123998132
Pumice and pumicite
2123998141
Natural abrasives, except sand
2123998151
Peat
2123998162
Perlite
2123998171
Shell, crushed or broken
2123998192
All other nonmetallic minerals
2123999
OTHER NONMETALLIC MINERALS
21239991
Other nonmetallic minerals
2123999111
Mica
2123999121
Native asphalt and bitumens (except bituminous limestone and bituminous sandstone)
2123999131
Pumice and pumicite
2123999141
Natural abrasives, except sand
2123999151
Peat
2123999161
Perlite
2123999171
Shell, crushed or broken
2123999191
All other nonmetallic minerals
212399A
All other nonmetallic mineral mining
212399M
Miscellaneous receipts
212399P
Primary products
212399S
Secondary products
212399SM
Secondary products and miscellaneous receipts
Step 2. Filtering and Smoothing
Based on the aggregate view of non-metallic mineral mining and quarrying 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-metallic mineral mining and quarrying 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 esti
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