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Executive Report on Strategies in Puerto RicoProduct Type: Market Research ReportPublished by: Icon Group International, Inc. Published: June 2007 Product Code: R307-25667 Description How to Strategically Evaluate Puerto RicoPerhaps the most efficient way of evaluating Puerto Rico is to consider key dimensions which themselves are composites of multiple factors. Composite portfolio approaches have long been used by strategic planners. The biggest challenge in this approach is to choose the appropriate factors that are the most relevant to international planning. The two measures of greatest relevance are "latent demand" and "market accessibility". The figure below summarizes the key dimensions and recommendations of such an approach. Using these two composites, one can prioritize all countries of the world. Countries of high latent demand and high relative accessibility (e.g. easier entry for one firm compared to other firms) are given highest priority. The figure below shows two different scenarios. Accessibility is defined as a firm’s ease of entering or supplying from or to a market (the "supply side"), and latent demand is an indicator of the potential in serving from or to the market (the "demand side"). Framework for Prioritizing Countries Demand/Market Potential Driven Firm Relative Accessibility Accessibility/Supply Averse Firm Relative Accessibility In the top figure, the firm is driven by market potential, whereas the bottom figure represents a firm that is driven by costs or by an aversion to difficult markets. This report treats the reader as coming from a "generic firm" approaching the global market - neither a market-driven nor a cost-driven company. Planners must therefore augment this report with their own company-specific factors that might change the priorities. This report provides an overview of factors driving latent demand in Puerto Rico. Latent demand is largely driven by economic fundamentals. In Chapter 2, I summarize the economic potential for Puerto Rico over the next five years for hundreds of industries, categories, and products. The goal of this chapter is to report my findings on the real economic potential, or latent demand, represented by Puerto Rico when defined as an area of dominant influence. The data presented are the result of various spatial econometric and time-series forecasting models which, for each category presented, are applied to forecast and allocate latent demand across all countries of the world and major distribution centers or centers of dominant influence within each country. This is accomplished knowing that economic fundamentals (e.g. income) generally vary from one country to another within a given country over time. In this chapter, I report the allocation for each category for Puerto Rico as an area of dominant influence in North America & the Caribbean and, potentially, the world. ECONOMIC AND PRODUCT MARKETS IN PUERTO RICO Introduction & Methodology Overview & Methodology In performing various economic analyses for clients, I have occasionally been asked to investigate the market potential for various products and services in Puerto Rico. The purpose of the studies is to understand the density of demand within Puerto Rico and the extent to which Puerto Rico might be used as a point of distribution within North America & the Caribbean. From an economic perspective, however, Puerto Rico does not represent a population within rigid geographical boundaries, rather, it represents an area of dominant influence over markets in adjacent areas. This influence varies from one industry to another, but also from one period of time to another. In what follows, I summarize the economic potential for Puerto Rico over the next five years for hundreds of industries, categories, and products. The goal of this chapter is to report my findings on the real economic potential, or what an economist calls the latent demand, represented by Puerto Rico when defined as an area of dominant influence. The reader needs to realize that latent demand may or may not represent real sales. For many items, latent demand is clearly observable in sales, as in the case for food or housing items. Consider, however, the category ""satellite launch vehicles"". Clearly, there are no launch pads in Puerto Rico used by the space industry to launch satellites. However, the core benefit of the vehicles (e.g. telecommunications, etc.) is ""consumed"" by the area served by Puerto Rico. Without Puerto Rico, in other words, the market for satellite launch vehicles would be lower for the population in Puerto Rico, North America & the Caribbean, or the world in general. One needs to allocate, therefore, a portion of the worldwide economic demand for launch vehicles to both North America & the Caribbean and Puerto Rico. The data presented are the result of various spatial econometric and time-series forecasting models which, for each category presented, are applied to forecast and allocate latent demand across all countries of the world and major distribution centers or centers of dominant influence within each country. This is accomplished knowing that economic fundamentals (e.g. income) generally vary from one country to another within a given country over time. In this chapter, I report the allocation for each category for Puerto Rico as an area of dominant influence in North America & the Caribbean and, potentially, the world. Market Potential Estimation Methodology Overview This chapter covers the outlook for products in Puerto Rico. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for Puerto Rico (in millions of U.S. dollars). Comparative benchmarks allow the reader to quickly gauge Puerto Rico vis-à-vis regional and global totals. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This chapter does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The chapter does not consider short-term cyclicalities that might affect realized sales. The chapter, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. This chapter does not report actual sales data, but gives, however, my estimates for the latent demand for products and services in Puerto Rico. For each category, I also show my estimates of how the P.I.E. grows over time (positive or negative growth). 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 is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand can be 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 country market. It should be noted that the estimates are "culture blind" and "climate blind", meaning that sales may in fact be lower than the latent demand due to cultural or exogenous factors, such as religion or climate (e.g. the presence of certain religions can effect the actual sales of certain food and beverage products, in the same way that climatic conditions can affect the actual sales of clothing and/or heating products). The estimates of latent demand do not explicitly control for either these long-run exogenous factors or shot-run exogenous factors that may be present from year to year (e.g. the effects of war, SARS, terrorist activities, civil wars, natural disasters, elections, or similar events). For reasons discussed later, this chapter 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 chapter 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 chapter 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 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 Puerto Rico, 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 is 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 chapter a very particular school of thought is adopted. In particular, we are considering the latent demand 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. 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 Puerto Rico. Since ICON Group has asked me to apply this methodology to a large number of categories and countries, the rather academic discussion below is general and can be applied to a wide variety of categories and countries, not just Puerto Rico. Step 1. Product Definition and Data Collection Any study of latent demand across countries and within Puerto Rico 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 are more likely to be at or near efficiency than others. These countries are given greater weight than others in the estimation of latent demand compared to other countries 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 cannot 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 for Puerto Rico 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 a category is established. In the case of this chapter, 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 a category falls under the broadest definition of the 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 chapter only relies on public data at the aggregate level without reliance on the summation of various category components. In other words, this chapter does not aggregate a number of components to arrive at the "whole". Rather, it starts with the "whole", and estimates the whole for all countries and the world at large (without needing to know the specific parts that went into the whole in the first place). All figures in this chapter are for sales resulting from retail channels. Step 2. Filtering and Smoothing Based on the aggregate view of categories as defined above, data were then collected for as many similar countries as possible for that same definition, at the same level of the value chain. This generates a convenience sample of countries 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 on a sporadic basis. In other cases, data from a country 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), countries 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 in additional countries 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 countries 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 countries along the aggregate consumption function, but also over time (i.e., not all countries are perceived to have the same income growth prospects over time and this effect can vary from country to country as well). Another way of looking at this is to say that latent demand is more likely to be similar across countries that have similar characteristics in terms of economic development (i.e., African countries will have similar latent demand structures controlling for the income variation across the pool of African countries). This approach is useful across countries for which some notion of non-linearity exists in the aggregate cross-country consumption function. For some categories, however, the reader must realize that the numbers will reflect the contribution of Puerto Rico to global latent demand and may never be realized in the form of local sales. For certain country-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 "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 countries 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 Non-linearities are assumed in cases where filtered data exist along the aggregate consumption function. Because the world consists of more than 200 countries, there will always be those countries, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible. For these countries, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a country’s stock of income), but a function of current income (a country’s flow of income). In the long run, if a country has no current income, the latent demand is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., countries which earn low levels of income will not use their savings, in the long run, to demand). In a graphical sense, for low income countries, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, low-income countries are assumed to have a latent demand proportional to their income, based on the country 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 countries of the world, for Puerto Rico and 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 figures are presented. Figures are rounded, so minor inconsistencies may exist across tables. Table of Contents
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