| Excerpt. © Reprinted by permission. All rights reserved.WHAT IS LATENT DEMAND AND THE P.I.E.?
The conception of latent demand is rather subtle. The term latent specifically refers to something that is dormant, not observable or not yet realized. Demand is the notion of an economic amount that a target population or market requires under dissimilar assumptions of price, quality, and distribution, among other factors. Latent demand, therefore, is normally specified by economists as the industry net income of a market when that market becomes accessible and beautiful 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 effective manner. It is quintessentially conveyed as the total revenues potentially extracted by firms. The “market” is specified at a given level in the value chain. There may be latent demand at the retail level, at the wholesale level, the developing level, and the raw materials level (the P.I.E. of higher levels of the value chain being always littler 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 operating scheme (os) software is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand may be lower or higher than actual sales if a market is inefficient (i.e. not representative of comparatively competitory levels). Inefficiencies arise from a number of factors, including the lack of international openness, cultural barriers to consumption, regulations, and cartel-like conduct on the percentage of firms. In general, however, latent demand is quintessentially larger than actual sales in a country market.
For reasons discussed later, this report does not consider the notion of “unit quantities”, only total latent revenues (i.e. a calculation of price times amount is never made, even though one is implied). The units applied 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 interchange rates. If inflation rates or interchange rates vary in a significant way equated to recent experience, actually sales may also exceed latent demand (when conveyed in U.S. dollars, not adjusted for inflation). On the other hand, latent demand may be specifically higher than actual sales as there are often times distribution inefficiencies that reduce actual sales beneath the level of latent demand.
As noted in the introduction, this study is strategic in nature, taking an aggregate and long-run view, disregarding of the players or merchandise involved. If fact, all the current productions or services on the market may discontinue to subsist in their present form (i.e. at a brand-, R&D specification, or corporate-image level) and all the players may be substituted by other firms (i.e. thru exits, entries, mergers, bankruptcies, etc.), and there will still be latent demand for operating system (os) software in North America & the Caribbean at the aggregate level. Product and service providing details, and the actual identity of the players involved, while indispensable for sure issues, are comparatively not significant for estimates of latent demand.
THE METHODOLOGY
In order to estimate the latent demand for operating scheme (os) software in North America & the Caribbean, I applied a multi-stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In this case, I to a considerable degree rely on the use of sure 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 person 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 is realized. For firms to serve a market, they must grasp a latent demand and be capable to serve that demand at a minimal return. The single most crucial variable determining consumption, assuming latent demand exists, is income (or other financial resources at higher levels of the value chain). Other elements that may 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 all over countries, the aggregate relation amongst income and consumption has been a central theme in economics. The figure beneath concisely surmise one aspect of problem. In the 1930s, John Meynard Keynes conjectured that as incomes rise, the intermediate propensity to consume would fall. The intermediate propensity to consume is the level of consumption separated by the level of income, or the slope of the line from the origin to the consumption function. He approximated this kinship empirically and found it to be true in the short-run (mostly based on cross-sectional data). The higher the income, the lower the intermediate propensity to consume. This type of consumption function is labeled “A” in the figure underneath (note the rather flat slope of the curve). In the 1940s, another macroeconomist, Simon Kuznets, approximated long-run consumption functions which indicated that the marginal propensity to consume was rather continuous (using time series info all over countries). This type of consumption function is show as “B” in the figure beneath (note the higher slope and zero-zero intercept). The intermediate 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 dissimilar using respective assumptions on intertemporal budget constraints, savings, and wealth. The shorter the time horizon, the more consumption may depend on wealth (earned in former 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 finally have no consumption (wealth is depleted). While the debate surrounding beliefs when it comes to how income and consumption are related and interesting, in this study a very queer school of thought is adopted. In particular, we are giving careful consideration to the latent demand for operating scheme (os) software all over all the countries in North America & the Caribbean. The smallest have less than 10,000 inhabitants. I assume that all of these regions fall along a “long-run” aggregate consumption function. This long-run function applies in spite of a great deal of of these countries having wealth, current income dominates the latent demand for operating system (os) software in North America & the Caribbean. So, latent demand in the long-run has a zero intercept. However, I concede firms to have dissimilar propensities to consume (including being on consumption functions with differing slopes, which may account for divergences in industrial organization, and end-user preferences).
Given this overriding philosophy, I will now describe the methodology used to give rise to the latent demand estimates for operating system (os) software in North America & the Caribbean. Since ICON Group has asked me to implement this methodology to a big number of categories, the rather academic discussion beneath is ordinary and may be applied to a wide potpourri of categories, not just operating scheme (os) software.
Step 1. Product Definition and Data Collection
Any study of latent demand throughout countries requires that some ordinary be established to define “efficiently served”. Having imposed respective number of things from which only one can be chosen and matched these with market outcomes, I have found that the optimal approach is to assume that sure key countries are more likely to be at or near efficacy than others. These countries are given more outstanding weight than others in the estimation of latent demand equated to other countries for which no known data are available. Of the numerous alternatives, I have found the assumption that the world’s most eminent aggregate income and most eminent 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 may not assumed to be efficient). Aggregate income may be operationalized in a number of ways, including gross domestic product (for industrial categories), or total disposable income (for household categories; population times intermediate income per…
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