The 2019-2024 Outlook for Educational Services in India
- June 2018 •
- 197 pages •
- Report ID: 5455610 •
- Format: PDF
This study covers the latent demand outlook for educational services across the states, union territories, and cities of India. Latent demand (in millions of U.S. dollars), or potential industry earnings (P.I.E.) estimates are given across over 4,900 cities in India.
For each city in question, the percent share the city is of its state or union territory and of India as a whole is reported. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis others.
This statistical approach can prove very useful to distribution and/or sales force strategies. Using econometric models which project fundamental economic dynamics within each state, union territory, and city, latent demand estimates are created for educational services. 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 cities in India). This study gives, however, my estimates for the latent demand, or potential industry earnings (P.I.E.), for educational services in India. It also shows how the P.I.E. is divided and concentrated across the cities and regional markets of India. For each state or union territory, I also show my estimates of how the P.I.E. grows over time. In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on strategic planning at graduate schools of business.
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 geographies. Short-run distortions in the value of the dollar, therefore, do not figure into the estimates. Purchasing power parity estimates 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.
1.3 THE METHODOLOGY
In order to estimate the latent demand for educational services across the states, union territories, and cities of India, 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 union territory, 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 geographies, 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 shown as "B" 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). 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. For a general overview of this subject area, see Principles of Macroeconomics by N. Gregory Mankiw, South-Western College Publishing; ISBN: 0030340594; 2nd edition (February 2002).
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 with no income eventually have no consumption (wealth is depleted).
While the debate surrounding beliefs about how income and consumption are related is interesting, in this study a very particular school of thought is adopted. In particular, we are considering the latent demand for educational services across the states, union territories, and cities of India.
The smallest cities have few inhabitants. I assume that all of these cities fall along a "long-run" aggregate consumption function. This long-run function applies despite some of these states and union territories having wealth; current income dominates the latent demand for educational services. So, latent demand in the long-run has a zero intercept. However, I allow 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 educational services. 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 and geographic locations, not just educational services in India.
1.3.1 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, I have found that the optimal approach is to assume that certain key indicators are more likely to reflect efficiency than others.
These indicators 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 highest aggregate income and highest income-per-capita markets reflect the best standards for "efficiency".
High aggregate income alone is not sufficient (i.e. some cities have high aggregate income, but low income per capita and cannot be 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).
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 educational services 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 products and/or services that might be incorporated within educational services fall 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 states, union territories, and cities in India (without needing to know the specific parts that went into the whole in the first place).
Given this caveat, this study covers educational services as defined by the North American Industrial Classification system or NAICS (pronounced "nakes").
The NAICS code for educational services is 61. It is for this definition that aggregate latent demand estimates are derived.
Educational services is specifically defined as follows:
61 The Sector as a Whole
The Educational Services sector comprises establishments that provide instruction and training in a wide variety of subjects. This instruction and training is provided by specialized establishments, such as schools, colleges, universities, and training centers.
These establishments may be privately owned and operated for profit or not for profit, or they may be publicly owned and operated. They may also offer food and accommodation services to their students.
Educational services are usually delivered by teachers or instructors that explain, tell, demonstrate, supervise, and direct learning. Instruction is imparted in diverse settings, such as educational institutions, the workplace, or the home through correspondence, television, or other means.
It can be adapted to the particular needs of the students, for example sign language can replace verbal language for teaching students with hearing impairments. All industries in the sector share this commonality of process, namely, labor inputs of instructors with the requisite subject matter expertise and teaching ability.
611 Industries in the Educational Services subsector provide instruction and training in a wide variety of subjects. The instruction and training is provided by specialized establishments, such as schools, colleges, universities, and training centers.
The subsector is structured according to level and type of educational services. Elementary and secondary schools, junior colleges and colleges, universities, and professional schools correspond to a recognized series of formal levels of education designated by diplomas, associate degrees (including equivalent certificates), and degrees.
The remaining industry groups are based more on the type of instruction or training offered and the levels are not always as formally defined. The establishments are often highly specialized, many offering instruction in a very limited subject matter, for example ski lessons or one specific computer software package.
Within the sector, the level and types of training that are required of the instructors and teachers vary depending on the industry.
Establishments that manage schools and other educational establishments on a contractual basis are classified in this subsector if they both manage the operation and provide the operating staff. Such establishments are classified in the educational services subsector based on the type of facility managed and operated.
6111 Elementary and Secondary Schools
61111 See industry description for 611110.
611110 This industry comprises establishments primarily engaged in furnishing academic courses and associated course work that comprise a basic preparatory education. A basic preparatory education ordinarily constitutes kindergarten through 12th grade. This industry includes school boards and school districts.
6112 Junior Colleges
61121 See industry description for 611210.
611210 This industry comprises establishments primarily engaged in furnishing academic, or academic and technical, courses and granting associate degrees, certificates, or diplomas below the baccalaureate level. The requirement for admission to an associate or equivalent degree program is at least a high school diploma or equivalent general academic training. Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
6113 Colleges, Universities, and Professional Schools
61131 See industry description for 611310.
611310 This industry comprises establishments primarily engaged in furnishing academic courses and granting degrees at baccalaureate or graduate levels. The requirement for admission is at least a high school diploma or equivalent general academic training. Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
6114 Business Schools and Computer and Management Training
61141 See industry description for 611410.
611410 This industry comprises establishments primarily engaged in offering courses in office procedures and secretarial and stenographic skills and may offer courses in basic office skills, such as word processing. In addition, these establishments may offer such classes as office machine operation, reception, communications, and other skills designed for individuals pursuing a clerical or secretarial career. Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
61142 See industry description for 611420.
611420 This industry comprises establishments primarily engaged in conducting computer training (except computer repair), such as computer programming, software packages, computerized business systems, computer electronics technology, computer operations, and local area network management. Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
61143 See industry description for 611430.
611430 This industry comprises establishments primarily engaged in offering an array of short duration courses and seminars for management and professional development. Training for career development may be provided directly to individuals or through employers’ training programs; and courses may be customized or modified to meet the special needs of customers. Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
6115 Technical and Trade Schools
61151 This industry comprises establishments primarily engaged in offering vocational and technical training in a variety of technical subjects and trades. The training often leads to job-specific certification. Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
611511 This U.S. industry comprises establishments primarily engaged in offering training in barbering, hair styling, or the cosmetic arts, such as makeup or skin care. These schools provide job-specific certification.
611512 This U.S. industry comprises establishments primarily engaged in offering aviation and flight training. These establishments may offer vocational training, recreational training, or both.
611513 This U.S. industry comprises establishments primarily engaged in offering apprenticeship training programs. These programs involve applied training as well as course work.
611519 This U.S. industry comprises establishments primarily engaged in offering job or career vocational or technical courses (except cosmetology and barber training, aviation and flight training, and apprenticeship training). The curriculums offered by these schools are highly structured and specialized and lead to job-specific certification.
6116 This industry group comprises establishments primarily engaged in offering or providing instruction (except academic schools, colleges, and universities; and business, computer, management, technical, or trade instruction). Instruction may be provided in diverse settings, such as the establishment’s or client’s training facilities, educational institutions, the workplace, or the home, and through correspondence, television, Internet, or other means.
61161 See industry description for 611610.
611610 This industry comprises establishments primarily engaged in offering instruction in the arts, including dance, art, drama, and music.
6116101 Establishments primarily engaged in teaching dance to children and adults.
6116102 Establishments primarily engaged in offering instruction in the arts, including art, drama, and music.
61162 See industry description for 611620.
611620 This industry comprises establishments, such as camps and schools, primarily engaged in offering instruction in athletic activities to groups of individuals. Overnight and day sports instruction camps are included in this industry.
61163 See industry description for 611630.
611630 This industry comprises establishments primarily engaged in offering foreign language instruction (including sign language). These establishments are designed to offer language instruction ranging from conversational skills for personal enrichment to intensive training courses for career or educational opportunities.
61169 This industry comprises establishments primarily engaged in offering instruction (except business, computer, management, technical, trade, fine arts, athletic, and language instruction). Also excluded from this industry are academic schools, colleges, and universities.
611691 This U.S. industry comprises establishments primarily engaged in offering preparation for standardized examinations and/or academic tutoring services.
611692 This U.S. industry comprises establishments primarily engaged in offering automobile driving instruction.
611699 This U.S. industry comprises establishments primarily engaged in offering instruction (except business, computer, management, technical, trade, fine arts, athletic, language instruction, tutoring, and automobile driving instruction). Also excluded from this industry are academic schools, colleges, and universities.
6117 Educational Support Services
61171 See industry description for 611710.
611710 This industry comprises establishments primarily engaged in providing noninstructional services that support educational processes or systems.
This report was prepared from a variety of sources including excerpts from documents and official reports or databases published by the World Bank, the U.S. Department of Commerce, the U.S. State Department, various national agencies, the International Monetary Fund, the Central Intelligence Agency, various agencies from the United Nations (e.g. ILO, ITU, UNDP, etc.), and non-governmental sources, including ICON Group Ltd., Euromonitor, the World Resources Institute, Mintel, the U.S. Industrial Outlook, and various public sources cited in the trade press.
1.3.2 STEP 2. FILTERING AND SMOOTHING
Based on the aggregate view of educational services as defined above, data were then collected for as many geographic locations as possible for that same definition, at the same level of the value chain. This generates a convenience sample of indicators 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 a 2-year moving average weighting scheme (longer weighting schemes do not substantially change the results).
If data are available for a geographic region, but these reflect short-run aberrations due to exogenous shocks (such as would be the case of beef sales in a state, union territory, or city stricken with foot and mouth disease), these observations were dropped or "filtered" from the analysis.
1.3.3 STEP 3. FILLING IN MISSING VALUES
In some cases, data are available 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, state, union territory, and city-level income.
Based on the overriding philosophy of a long-run consumption function (defined earlier), states, union territories, and cities which have missing data for any given year, are estimated based on historical dynamics of aggregate income for that geographic entity.
1.3.4 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 crosssectionally pooled time series model". The interested reader can find longer discussions of this type of modeling in Studies in Global Econometrics (Advanced Studies in Theoretical and Applied Econometrics V. 30) , by Henri Theil, et al., Kluwer Academic Publishers; ISBN: 0792336607; (June 1996), and in Principles of Econometrics, by Henri Theil John Wiley & Sons; ISBN: 0471858455; (December 1971), and in Econometric Models and Economic Forecasts by Robert S. Pindyck, Daniel L. Rubinfeld McGraw Hill Text; ISBN: 0070500983; 3rd edition (December 1991). Simply stated, the effect of income on latent demand is assumed to be constant 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 states, union territories, or cities). This assumption applies along the aggregate consumption function, but also over time (i.e., not all states, union territories, or cities in India are perceived to have the same income growth prospects over time). Another way of looking at this is to say that latent demand for educational services is more likely to be similar across states, union territories, or cities that have similar characteristics in terms of economic development.
This approach is useful across geographic regions for which some notion of non-linearity exists in the aggregate cross-region consumption function. For some categories, however, the reader must realize that the numbers will reflect a state’s, union territory’s, or city’s contribution to latent demand in India and may never be realized in the form of local sales.
1.3.5 STEP 5. FIXED-PARAMETER LINEAR ESTIMATION
Nonlinearities are assumed in cases where filtered data exist along the aggregate consumption function. Because the India consists of more than 4,900 cities, there will always be those cities, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible.
For these cities, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a city’s stock of income), but a function of current income (a city’s flow of income). In the long run, if a state or union territory has no current income, the latent demand for educational services is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., cities which earn low levels of income will not use their savings, in the long run, to demand educational services). In a graphical sense, for low-income cities, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, a low-income city is assumed to have a latent demand proportional to its income, based on the cities closest to it on the aggregate consumption function.
1.3.6 STEP 6. AGGREGATION AND BENCHMARKING
Based on the models described above, latent demand figures are estimated for all major cities in India. These are then aggregated to get state or union territory totals.
This report considers a city as a part of the regional and national market. The purpose is to understand the density of demand within a state or union territory and the extent to which a city might be used as a point of distribution within its state or union territory.
From an economic perspective, however, a city does not represent a population within rigid geographical boundaries. To an economist or strategic planner, a city 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. I allocate latent demand across areas of dominant influence based on the relative economic importance of cities within its state or union territory. Not all cities (e.g. the smaller towns) are estimated within each state or union territory as demand may be allocated to adjacent areas of influence. Since some cities have higher economic wealth than others within the same state or union territory, a city’s population is not generally used to allocate latent demand. Rather, the level of economic activity of the city vis-à-vis others is used. Figures are rounded, so minor inconsistencies may exist across tables.