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WHAT IS LATENT DEMAND AND THE P.I.E.?

The idea of latent demand is quite subtle. The term latent typically describes something is dormant, not observable, you aren't yet realized. Demand is the notion of the economic quantity that the 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 your market when that market becomes accessible and attractive for everyone by competing firms. It is often a measure, therefore, of potential industry earnings (P.I.E.) or total revenues (not profit) if Japan is served within an efficient manner. It is normally expressed since the total revenues potentially extracted by firms. The "market" is scheduled with a given level within the value chain. There may be latent demand with the retail level, with the wholesale level, the manufacturing level, and the raw materials level (the P.I.E. of upper levels with the value chain being always smaller as opposed to P.I.E. of levels at lower levels in the same value chain, assuming all levels maintain minimum profitability).

The latent interest in bicycles and bicycle accessories in Japan just isn't actual or historic sales. Nor is latent demand future sales. In fact, latent demand could be either lower or higher than actual sales if a companies are inefficient (i.e., not representative of relatively competitive levels). Inefficiencies arise from the number of factors, like the insufficient international openness, cultural barriers to consumption, regulations, and cartel-like behavior on the section of firms. In general, however, latent demand is usually bigger than actual sales inside a 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 quantity is rarely made, though one is implied). The units used within this report are U.S. dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends). If inflation rates vary in the substantial way compared to recent experience, actually sales may also exceed latent demand (not adjusted for inflation). On the other hand, latent demand might be typically greater than actual sales because there in many cases are distribution inefficiencies that reduce actual sales below the level of latent demand.

As mentioned in the introduction, this study is strategic in nature, taking an aggregate and long-run view, irrespective in the players or products involved. In fact, all the current products or services around the market can cease to exist in their present form (i.e., in a brand-, R&D specification, or corporate-image level) and all players might be replaced by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there'll nevertheless be latent need for bicycles and bicycle accessories with the aggregate level. Product and service offerings, as well as the actual identity in the players involved, while important for certain issues, are relatively unimportant for estimates of latent demand.

THE METHODOLOGY

In order to estimate the latent interest in bicycles and bicycle accessories across the prefectures and cites of Japan, I used a multi-stage approach. Before using the approach, one needs a basic theory from which such estimates are created. In this case, I heavily rely for the utilization of certain basic economic assumptions. In particular, there is certainly an assumption governing the shape and form of aggregate latent demand functions. Latent demand functions relate the income of an prefecture, city, household, or individual to realized consumption. Latent demand (often realized as consumption when an marketplace is efficient), at any level in the value chain, occurs if an equilibrium is realized. For firms to serve a market, they need to perceive a latent demand and stay in a posture to serve that demand in a minimal return. The only most significant variable determining consumption, assuming latent demand exists, is income (or other financial resources at higher levels of the value chain). Other factors that may pivot or shape demand curves include external or exogenous shocks (i.e., business cycles), as well as modifications in utility for your product in question.

Ignoring, for your moment, exogenous shocks and variations in utility across geographies, the aggregate relation between income and consumption may be a central theme in economics. The figure below concisely summarizes one part of problem. In the 1930s, John Meynard Keynes conjectured that as incomes rise, the typical propensity to eat would fall. The common propensity to use may be the level of consumption divided through the level of income, or the slope in the line through the origin for the consumption function. He estimated this relationship empirically determined it to become true within the short-run (mostly based on cross-sectional data). The larger the income, the lower the average propensity to consume. This sort of consumption function is labeled "A" inside 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 this marginal propensity to consume was rather constant (using time series data). This kind of consumption function is shown as "B" inside figure below (note the higher slope and zero-zero intercept). The common propensity to take is constant.





Is it declining or possibly it constant? A number of other economists, notably Franco Modigliani and Milton Friedman, inside the 1950s (and Irving Fisher earlier), explained why the 2 functions were different using various assumptions on intertemporal budget constraints, savings, and wealth. The shorter enough time horizon, the harder consumption can depend on wealth (earned in previous years) and business cycles. In the long-run, however, the propensity to take is more constant. Similarly, inside long run, households without income eventually have no consumption (wealth is depleted). As the debate surrounding beliefs about how precisely income and consumption are related is interesting, within this study a really particular school of thought is adopted. In particular, we have been taking under consideration the latent interest in bicycles and bicycle accessories through the prefectures and cities of Japan. The smallest cities have few inhabitants. I assume that all of those cities fall along a "long-run" aggregate consumption function. This long-run function applies despite some of these prefectures having wealth; current income dominates the latent interest in bicycles and bicycle accessories. So, latent demand within the long-run has a zero intercept. However, I allow different propensities to use (including being on consumption functions with differing slopes, which may be the reason of differences in industrial organization, and end-user preferences).

Given this overriding philosophy, I am going to now describe the methodology utilized to produce the latent demand estimates for bicycles and bicycle accessories in Japan. Since ICON Group has asked me to apply this methodology to some large variety of categories, the rather academic discussion below is general and can be applied to a wide variety of categories and geographic locations, not just bicycles and bicycle accessories in Japan.

Step 1. Product Definition and Data Collection

Any study of latent demand requires that some standard be established to define "efficiently served". Having implemented various alternatives and matched these with market outcomes, We've found that this optimal approach would be to believe that certain key indicators are more probable to reflect efficiency than others. These indicators are given greater weight than others inside the estimation of latent demand compared to others that no known data are available. Of the numerous alternatives, We have found the assumption how the highest aggregate income and highest income-per-capita markets reflect the best standards for "efficiency". High aggregate income alone isn't sufficient (i.e. some cities have high aggregate income, but low income per capita and can not assumed being efficient). Aggregate income can be operationalized in a very variety of ways, including gross domestic product (for industrial categories), or total disposable income (for household categories; population times average income per capita, or amount of households times average household income).

Latent demand is therefore estimated using data collected for relatively efficient markets from independent data sources (e.g. Official Chinese Agencies, the World Resources Institute, the Organization for Economic Cooperation and Development, various agencies from... --This text refers to the Digital edition.

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