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Allied Health Services: Avoiding Crises (1989)

Chapter: Appendix E: Projections of Demand and Supply in Occupations

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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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Suggested Citation:"Appendix E: Projections of Demand and Supply in Occupations." Institute of Medicine. 1989. Allied Health Services: Avoiding Crises. Washington, DC: The National Academies Press. doi: 10.17226/769.
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APPENDIX E 303 Appendix E Projections of Demand and Supply in Occupations This appendix describes the purposes to which projections of worker demand and supply are put and the characteristics these projections must have if they are to serve these purposes. The various methods that have been used for making projections are summarized, and the limitations of each are discussed. The accuracy and limitations of the methods used by BLS are also considered. A final section points to needed research and suggests how the projections can best be understood and used. Purposes of Projections Economic history amply demonstrates the rise and fall of industries and of occupations. Fluctuations in supply are most likely in those occupations that require long training periods; this pattern occurs because the supply of workers in a particular field that develops in response to market signals may take years to get through the educational pipeline. Workers investing time and money in education, employers concerned about the availability of skilled workers, and a public interested in stability of wages and prices and in getting services when they need them all have an interest in our ability to anticipate changes in employment at least a few years in the future. Projections may be made for a variety of purposes, among which are the following: • evaluating the adequacy of training or education programs in light of the potential need for workers;

APPENDIX E 304 • estimating the feasibility of major proposed programs for government expenditure (such as defense, public works, or facilities) in terms of the availability of skilled workers to accomplish or staff them; and • providing information on future employment opportunities for the guidance of individuals choosing courses of education or training. Examples of the first of these purposes include the insistence of Congress that federally supported programs of vocational education and training of the unemployed or the disadvantaged be planned with future employment opportunities in mind. Similarly, the congressional consideration of such programs as highway construction, community mental health facilities, and the Strategic Defense Initiative ("Star Wars") programs—to name a few—included an inquiry into the availability of the highly skilled personnel that are required for these projects. BLS launched its occupational outlook research program in 1940 in response to the concern of guidance professionals that young people have adequate information with which to choose among careers. The same motivation lies behind the efforts of state governments to provide local projections of employment growth by occupation. The rationale and assumptions underlying the projections may differ depending on the purposes these projections must serve. Both vocational guidance and evaluations of the adequacy of training programs to meet future needs for skilled workers call for a realistic estimate of future economic demand in the occupation. Estimating the feasibility of proposed human resources programs, on the other hand, calls for the translation of program goals— whether or not they are realistic—into personnel, and adding to these requirements a realistic estimate of the demand for the same types of workers in the rest of the economy. On the supply side, vocational guidance purposes require projections of the most probable worker supply in comparison with the economic demand. These types of projections give the best picture of future employment opportunities and the competitive situation in each field. For evaluating the feasibility of a proposed program a forecast of the most probable supply is also desirable; such a forecast would show whether the program can be accomplished without special measures to attract more workers to the field. For appraisals of the adequacy of present training programs, however, a major element of the estimate of future supply—the number of trainees—is the quantity for which the exercise is undertaken, the unknown in the equation, and there is no need to estimate it independently. One way to look at the supply is to treat the losses to the occupation resulting from death, retirements, and net mobility to other occupations as components of "replacement needs." These replacement needs should be added to the estimated growth of the occupation to get the total demand that has to be satisfied by the flow of trainees.

APPENDIX E 305 In all of the above, we have discussed demand and supply as though they were independent of each other; in fact, they are interdependent. An increase in demand, by raising wage rates, elicits an increase in supply, and supply also affects demand through its effects on wages and costs. Only when there are constraints on demand, such as those imposed by the technology of an industry (a steel mill cannot employ pastry cooks to roll steel), or constraints on supply, such as limited educational facilities or licensure, is the adjustment of worker demand and supply impeded. Yet in those occupations that require long periods of education or training, it may take several years for the signal of an increase in demand to fill the educational pipeline and produce an increase in graduates; it is for these occupations that projections are particularly useful in facilitating the adjustment of demand and supply. In the absence of projections, young people have only the current market situation to guide them. If they react strongly to a current shortage of graduates and high salary offers, they may find that when they graduate, 4 years later, the field has become overcrowded and salaries are dropping, conditions that may cause the current year's entrants to avoid the field and precipitate a shortage 4 years later. (The operation of "cobweb" patterns in the labor markets for highly trained workers is demonstrated in a number of papers by Richard Freeman.) Projection Methods A variety of methods have been used to project demand and supply. The simplest has been to ask employers how many workers they expect to employ in the future. This method appeals to many people as a straightforward way to tap the expert knowledge of the people who will make the decisions. Yet it has produced such poor results that, after years of use, it was abandoned early in the 1970s. Researchers found that few employers could make the necessary projections of their sales and of technological changes in their industries to develop good estimates of their future occupational requirements. (Indeed, most employers do not reply to the surveys or give casual, off-the-cuff answers.) There is some tendency for each firm to assume it will gain a larger market share; and an offsetting tendency for companies to report that their personnel requirements 5 years in the future will be the same as they are now. Finally, this method makes no allowance for employment in new firms, which, according to some research, are and will be a major provider of additional employment. A second method that has been used to project demand and supply is to extrapolate past employment trends in the occupation. This method is based on the assumption that, whatever factors have operated in the past will continue to operate. Unfortunately, history is full of instances in which

APPENDIX E 306 the employment situation changed radically—as any buggy whip manufacturer will attest. Another deficiency of this method is its tendency to treat the occupation as if it were in a vacuum and unrelated to other events in the economy and in society. This limitation is illustrated by the attempt in the early 1950s to extrapolate the growth of the engineering profession by assuming that the exponential growth it had shown would continue. With such growth, engineers would have exceeded the total labor force in a short time, leaving no draftsmen to prepare drawings, no bookkeepers to pay salaries, and no trash collectors to haul away their refuse. A more sophisticated approach of late has been to associate the growth of an occupation with causative variables that can themselves be projected independently. For example, projections of the population by age have been used to project the demand for teachers: the pupils in elementary grades 6 years hence have already been born, as have those who will be high school students 14 years hence. Changes in pupil-teacher ratios or other strategic variables can be used to modify the results of these projections. Similar methods have been used to project the demand for physicians (Graduate Medical Education National Advisory Committee) and nurses (Western Interstate Committee on Higher Education). In some cases, regression analysis has been used to measure the relative effects of the variables on the result: the projection of employment. This method may be used to yield estimates of the need for workers in the occupation rather than estimates of the economic demand. If the relevant ratios (e.g., the pupil-teacher ratio in the projection of employment for teachers) are set at an ideal level that is nevertheless in line with what experts in the field consider optimum, the resultant projections can be viewed as projections of need. To the extent that they are based on current ratios, which in turn reflect the current market situation, or are adjusted for the future to reflect expected changes in the market situation, the resultant estimate will be closer to an estimate of demand. Each approach serves a different purpose. The advantages of this approach over the simple extrapolation of past trends are obvious. This method attempts to take into account some of the strategic factors affecting employment. This is not an easy task, however; demand in an occupation may be affected by technological changes; market changes; the way consumers spend their money and the amount of income they have to spend; government expenditures on education, health, highways, and military material; and the capital expenditures of industry. Even more important than these factors are the context of the growth of related occupations and industries and the entire interwoven structure of the economy and of society. When we consider the combination of factors that affect employment in health occupations—for example, the importance of population trends, social trends, income and expenditure patterns, the

APPENDIX E 307 science and technology of medical practice, the financing of medical care, training and licensure, and the growth and attractiveness of alternative occupations—it becomes apparent that a comprehensive approach is called for. BLS, which began its research in this area in 1940 and issued its first occupational projection 5 years later, at first tried the approach of studying individual occupations but concluded that a comprehensive analysis was needed. With support from the Veterans Administration (which wanted information to help in the vocational choices of the millions who studied under the World War I G.I. Bill), BLS published outlook information on hundreds of occupations beginning with the first Occupational Outlook Handbook in 1949. The handbook has been a biennial publication since the mid-1950s. The broad occupational coverage, frequent publication, and wide use of the projections (150,000 copies of each edition of the handbook are bought by high schools, colleges, libraries, and community agencies) have had important implications for the research program. Spreading research costs over so many occupations has allowed a more comprehensive approach than could be supported if interest were focused only on a few occupations. The continuing research effort has led to accumulating experience, deepening knowledge of each occupation, and ongoing contacts with industry, professional organizations, unions, and research institutes that are familiar with each field. It has also permitted regular appraisals of the accuracy of the projections and analyses of the possible reasons for errors. As a result of this experience, new research programs and data collection systems have been instituted, an example of which is the occupational employment statistics program begun in the early 1970s. Research is also being conducted on tables of working life and on how people move from one occupation to another, one purpose of which is to develop insight into some of the elements of supply. Over nearly five decades of experience, occupational research methods have changed and improved. The wide publication of the results of such research has ensured that industry and professional groups in each occupation have cooperated with the bureau in giving information and carefully reviewing drafts. The use of research results in schools and in vocational guidance undoubtedly influences the perceptions of students about employment opportunities and the occupational choices they make. The basic approach followed by BLS is to estimate the employment in each occupation that will be generated by economic demand. This estimate is based on the demand for the goods or services the occupation provides, which in turn is affected by the total spendable income available to consumers and governments and by the changing patterns of what they spend it on. These patterns are influenced by a wide variety of social and economic

APPENDIX E 308 factors, including changing tastes and styles, scientific discoveries and technological change affecting both what is produced and how it is produced, the growth and changing composition of the population, taxation and government expenditure policies (''guns or butter"), and what other countries are buying from and selling to us. Producing such estimates is a formidable task, and predicting what will happen in the future on so many different fronts is hazardous. Natural disasters, social cataclysms, and business cycles are hard to predict. Yet some of the changing factors move relatively slowly: there are lags between scientific discoveries and the commercial exploitation of new technology, between the initiation of a new style and its widespread adoption, between the first Japanese automobile sold in the United States and Japan's subsequent market success. These lags mean that useful projections can be produced, provided certain conditions are met: (1) projections are confined to a relatively short time horizon (about 10 years is enough to guide educational policy and the career choices of individuals); (2) sets of alternative projections are made to show the effect, for example, of alternative assumptions as to the state of the economy or the business cycle; (3) events are constantly monitored; (4) the projections are revised at frequent intervals; and (5) continuous research is carried out on the accuracy of the projections and on the adequacy of the methods. BLS projections begin with the population projections made by Census Bureau demographers. The census data give the number of consumers and are a basis for BLS's projections of the labor force, which are based on the trends in labor force participation by each age, sex, and race group. From the total human resources thus projected, BLS estimates the gross national product (GNP) that will be generated by making assumptions about the growth of output per worker, changing hours of work, and the level of unemployment that must be taken into account. To provide for the uncertainties of the business cycle and to suggest the range of error to users of the projections, three sets of projections are usually made: a "high," "moderate," and "low" forecast. The BLS assumptions about productivity, hours, and unemployment are adjusted to yield an estimate of GNP growth under these three conditions. This somewhat simplified recital of an elaborate process may give the impression of a mechanical juggernaut that rides roughshod over the entire economy of 110 million people with all its complexity, nuances, and infinite variety, mashing up the professions in which we are interested with masses of coal miners, factory workers, and fast-food slingers. What has not been said is that, at each step of the BLS process, special knowledge is introduced whenever it is available, and the factors that enter into the calculations are adjusted on the basis of information on developing and newly emerging trends in the industry. In the most recent projections, for example, forecasts for the mining industries took into account the latest petroleum import

APPENDIX E 309 analyses for the target year from the Department of Energy. Projections for the machinery and computer manufacturing industries incorporated analyses of the market situation and foreign competition. Projections for health services considered such developments as cost containment policies, the shift of many surgical procedures to physicians' offices and outpatient facilities, the growth of new group practices and nursing and personal care facilities, and the aging of the population. The bureau's extensive research program on productivity and technological development yields insights about the growth of overall productivity and of productivity in each industry, and the technological developments that affect the numbers and kinds of occupations that are employed. The advantage of the comprehensive interactive approach is that special information or analyses on any aspect of our complex economy can be inserted and implications drawn—not only for a particular occupation or industry but for all of the others as well. In contrast, there is no unifying and systematic method for projections on the supply side. The supply of workers in an occupation is affected by two factors: (1) the inflow of trainees and of persons who acquire the necessary skills by experience or work in related occupations or by the study of related subjects and (2) the outflow of persons retiring, dropping out of the labor force temporarily, dying, or transferring to other occupations. Supply, of course, is also affected by the relative wages in this and other occupations available to workers. Projections of the number of college graduates in each field have been published by the Department of Education; they were based on the projected population of the appropriate age and on mathematical extrapolation of trends in the proportion of the population completing college. The total degrees awarded were distributed by field (college majors) using mathematical extrapolation of past trends. Because there was no attempt to take into account the effects of social and market factors on the decisions of young people (except insofar as these factors were embodied in projected past trends), these projections cannot be considered realistic. They do, however, serve a useful purpose: they can be used to illustrate what would happen to the outflow of graduates, an important component of the supply of workers, if nothing happened to change the choices people make about future careers. If such estimates are compared to independent estimates of future demand or the requirements for attaining some national goal such as a proposed community mental health program, a disparity between the projected demand and the projected supply could point to policy measures that might be required to attain the goals (e.g., scholarships or other inducements to undertake training for the occupations). To determine the outflows and inflows that affect occupational supply, BLS has pursued a number of avenues of research. For example, the bureau has developed tables of working life (similar to life tables), showing

APPENDIX E 310 the annual attrition to a population at each age, to estimate losses resulting from deaths and retirements. These age-specific rates were then applied to the age composition of each occupation to estimate annual losses. The tables take no account of differences in work life patterns among occupations, however, nor of losses resulting from transfers to other occupations. More recently, studies have been made of transfers into and out of occupations (Eck, 1984), and more complete attrition rates for each occupation have been estimated, including shifts into unemployment and withdrawal from the labor force (either retirement or temporary withdrawal). BLS does not make projections of worker supply in occupations. It does publish estimates of annual attrition or replacement rates. This information is offered, together with the projected rate of growth in each occupation and information on the unemployment rate, as clues to the employment opportunities in the occupation. The inclusion of information on replacement rates makes clear the point that projected growth alone does not tell the whole story about employment opportunities. Projections of employment demand for more than 300 occupations are published in technical articles and bulletins. (The most recent projections of general economic growth, industrial growth, and occupations were published in the September 1987 issue of Monthly Labor Review). Brief articles on each of about 200 occupations involving relatively long periods of training are published in the Occupational Outlook Handbook ; profiles of the basic numbers —employment, projected employment growth, unemployment rates, replacement rates, and number of people completing training in a recent year— for about the same number of occupations are published in a series of bulletins called Occupational Projections and Training Data, of which the most recent (BLS Bulletin 2206) was issued in 1984. State and Local Projections In most states, employment projections for the state and major geographic areas within the state are made by state agencies, most commonly employment security agencies, but sometimes universities or other economic analysis organizations. Until a few years ago, there was a cooperative federal—state relationship in this work, with BLS providing technical con-suiting and sometimes tabulation work, but this cooperation has been discontinued as a result of budget cuts. The states are continuing their work, however. The National Occupational Information Coordinating Committee, which is composed of representatives of the Departments of Labor and Education, and its affiliated state occupational information coordinating committees give leadership to these efforts. The states use varying methods, but they all have a few elements in common. The national projections of the growth of industries are generally

APPENDIX E 311 taken as a framework, and past changes in each state's share of national employment in the industry, together with projections of the state's population and any available input from the economic development agency of the state, are used to project the industry's growth locally. Industry occupational composition data from the Occupational Employment Survey (which is conducted by the state agencies in cooperation with BLS) are used to project employment by occupation. Replacement rates provided by BLS are also published. Evaluation of BLS Projections and Methods Any evaluation of BLS's projection methods should begin with a look at the scorecard—that is, at how accurate the projections have been. The bureau has published a number of evaluations of the accuracy of its projections, comparing them to actual employment in each industry and occupation when the target year's statistics become available. The two most recent evaluations will be analyzed here: those for the 1960-1975 projections (Carey, 1980) and the 1970-1980 projections (Carey and Kasunic, 1982). (No more recent evaluations have been published, in part because changes in the classification system for occupations have made it difficult to compare earlier projections with employment data gathered since 1983.) Comparing a projection that purports to reflect demand, without regard to supply, with the actual employment in the target year is not entirely logical. It is justified only if one can assume that the supply will adjust itself to match the demand, which does not always happen. There are a number of ways to consider the accuracy of projections. One is to compare the number of workers employed in the target year with the number projected. The purpose of the projections, however, is to anticipate change, to distinguish occupations that are growing rapidly or slowly, and, especially, to perform the more difficult task of identifying occupations that shrink while the economy as a whole is growing. Our evaluation will therefore concentrate on how well the rate and direction of change in employment was projected. To begin with, we must look at the degree of variability in growth rates among occupations. If growth rates vary in a narrow range around the average, we would expect projections to be fairly accurate; if growth rates are widely dispersed, the projections may be judged by more lenient standards. Table E-1 arrays the actual changes in employment in occupations included in the two BLS evaluation studies referred to above according to broad groupings of their rates and directions of change as compared to the average change for all occupations. This little table could well have been made the preface of this paper: it powerfully demonstrates the variability of occupational change, the risk undertaken by anyone who invests in long and expensive training for an

APPENDIX E 312 occupation, and the difficulties of the forecaster. In a 10-or 15-year period when the average occupation grew by about 30 percent, between one-fifth and one- third of the occupations under study actually experienced declines in employment. The number of occupations that grew at a rate triple the average was about the same as the number that grew at a rate less than the average. There was virtually no clustering around the average. Obviously, occupations are highly volatile in their rates of employment and subject to diverse economic forces. An evaluation (Goldstein, 1983) of how well the BLS projections for these occupations succeeded in predicting the actual changes shown above concluded that, first, users of the projections had some warning of the declines: 5 of the 16 occupations that declined from 1960 to 1975 had been predicted to decline, and small increases of less than the average had been predicted for the other 11. In the 1970-1980 period, 6 of the 20 occupations that declined had been projected to decline, and small increases of less than the average had been projected for 7 more. Second, did the projections identify the occupations that were growing rapidly and that needed special attention in planning training programs? In the first period, 21 occupations grew at more than twice the average rate; 15 of them had been projected to grow that fast. In the second period, 14 occupations grew at more than twice the average rate, but in only 2 of them had such growth been projected. Taking all of the projections together, how close did they come to the actual employment changes that occurred? Going back to the class intervals shown in Table E-1, we might say that if the predicted change was in TABLE E-1 Growth Rates in Employment in Occupations with Increases and Decreases in Employment, 1960-1975 and 1970-1985 Item 1960-1975 1970-1985 Average (weighted) change (in percentage) for all 32.6 28.9 occupations Total number of occupations compared 76 64 Occupations with declines in employment 16 20 Occupations with increases in employment 60 44 Below average (more than 10 percent below the average) 11 10 About average (within 10 percent above or below the 17 9 average) Somewhat above the average (between 10 percent 11 11 above the average and twice the average) Twice to triple the average 11 5 More than triple the average 10 9 SOURCE: Carey (1980); Carey and Kasunic (1982).

APPENDIX E 313 same interval as the actual change, it was on target. For the first period, 40 percent of the predictions were on target; for the second, 33 percent were on target. If we consider as reasonably close those predictions that were in the class intervals adjacent to the actual change, we find that 40 percent of the predictions in the first period and 27 percent of those in the second period were reasonably close. By these standards, which are perhaps somewhat lenient but whose leniency is justified by the variability of economic employment changes, we would consider 80 percent of the projections in the first period and 60 percent in the second to be either on target or reasonably close. TABLE E-2 Projected and Actual Employment Changes (percentage) for Six Health Occupations, 1960-1975 Occupation Projected Actual Nurses, professional 73.5 68.5 Dietitians and nutritionists 35.1 44.6 Optometrists 17.6 10.0 Attendants, hospital and other institutions 140.7 122.4 Dentists 43.8 23.1 Physicians, medical and osteopathic 66.7 40.2 SOURCE: Carey (1980); Carey and Kasunic (1982). Another question that must be answered is: Were the errors biased so that projections were consistently too high or too low? Of all the projections in the first period that were not on target, one-third were too low; in the second period, roughly half were too low. Thus, there is some evidence of a pessimistic bias in the second period. Our concern in this report is somewhat more narrow, however. We must thus consider how well the method predicts the growth of the the allied health occupations. It is a reasonable hypothesis that the economic, technological, social, and institutional factors that are peculiar to the health industry and its occupations may make the general projection method used by BLS inappropriate for use in these fields. The evaluation studies we have cited do not include many of the allied health professions, largely because they included only occupations for which the statistics were comparable over the 10-or 15-year spans between the original projections and the target years. The comparison data needed for the allied health professions, with their dynamic changes over recent decades, are not available. Yet we can still test the hypothesis of peculiarity with evaluations of the accuracy of the projections for other health occupations (Tables E-2 and E-3). It appears that the projections captured the general magnitude of the employment changes in these fields rather better than they did for all of the occupations evaluated earlier in this section, although one could wish

APPENDIX E 314 for more accurate projections for dentists and physicians in the first period and for nurses in the second. From these data, the hypothesis of peculiarity of the health fields is not supported. Let us turn, however, to some of the aspects of the projection method that raise questions or present problems. TABLE E-3 Projected and Actual Employment Changes (percentage) for Five Health Occupations, 1970-1980 Occupation Projected Actual Optometrists 20.0 19.4 Osteopaths 43 7 39.3 Physicians and surgeons 48.5 43.3 Registered nurses 42.7 59.9 Dentists 32.0 22.3 SOURCE: Care) (1980); Care,) and Kasunic (1982). Demand or Requirements? In traditional economic analysis, demand and supply are equated at a price or wage. Yet there is no explicit evidence of this process in the BLS projection methods. Instead, the employment estimates for future years may be seen as requirements generated by the levels of production or services that the projected economic changes will engender. Indeed, changing relative prices throughout the system could change the projected economic relationship—for example, in tracing the demand for raw materials generated by the production of finished goods. However, the adjustments made at various steps in the projection process to introduce technological change and changes in markets and foreign trade have the effect of inserting price and market changes into the system. At the end of the process, it is true that there is no systematic attempt to modify the employment estimates for each occupation by a consideration of supply. Indeed, as the forecasters lack projections of supply, this cannot be done. The projections of occupational employment will be consistent with actual employment in the target year only if the supply of trained workers (perhaps forewarned by publication of the estimates or, in the 1960s, responding to policy measures that were designed to raise supply to meet increased demand resulting from new entitlement programs) adjusts to the employer's requirements. Although the projections are not true estimates of demand in the sense of traditional economic concepts, they do come close to the goal of a realistic estimate of the number of jobs that will be offered, as distinct, for example, from an estimate of ideal needs. Occupational Composition of Industries Evaluations of the accuracy of the projections made by BLS staff have concluded that the subject industries' total employment was more accurately

APPENDIX E 315 projected than was employment by occupation. From the foregoing discussion, we might suspect that the lower accuracy of occupational projections may have resulted from the fact that demand had not yet been confronted with supply. If it had, a different level of employment would have emerged. Less accuracy could also have been the result of the quality of the occupational data; until recently the only reasonably complete source of data on the occupational composition of each industry was the decennial population census. In household surveys such as censuses, people report their occupation by whatever name they have to describe it, telling the census enumerator briefly what activities they perform. These reports are classified by census clerks into the approximately 400 occupations the census tabulates. There is potential error first in the respondent's report: some people overstate their occupational status, as is evident from independent data. Second, the census clerks do not always have enough information to classify the occupations correctly; terminology varies across the country. (The same comments apply to another source of occupational employment data, the Current Population Survey, which is conducted by the Census Bureau. The occupational estimates of this survey are based on a smaller sample than those in the population census and thus have larger sampling errors and somewhat less occupational detail; however, they are available annually.) To improve the accuracy of occupational composition data, BLS initiated an Occupational Employment Statistics (OES) survey, early in the 1970s in cooperation with state agencies. Employment by occupation is collected from employers by means of a separate questionnaire for each industry that lists the occupations found in that industry. The questionnaire contains brief definitions of the occupations that have been worked out in consultation with employers to ensure understanding and accurate reporting. The sample plants in the survey are chosen to represent all size classes in the industry and to yield accurate estimates. The survey is limited to wage and salary workers in each industry; BLS adds the self-employed in each occupation using data from the Current Population Survey. Because it is based on reports from employers, the OES counts each worker more than once if he or she has more than one job at a time. This practice introduces a small inaccuracy in the occupation employment estimates; in the series of surveys of dual job-holding that was made from 1958 to 1980, the number of persons with more than one job averaged about 5 percent of the total employed—the exact figures were 6 percent for men and 3 percent for women. The BLS estimates count workers whether they work full-time or part-time and do not distinguish between these two categories. Thus, in any occupation, there could be many part-time workers in the figures. In 1986, 18.7 percent of all persons at work were working part-time—5.3 percent

APPENDIX E 316 for economic reasons (no full-time work was available or they had been temporarily assigned to part-time work) and 13.4 percent because they preferred part-time work. There was more part-time work among women—27.5 percent of women worked part-time, 6.5 percent for economic reasons and 21 percent voluntarily. The incidence of part-time work varies among occupations, in the occupation group ''technicians and related support personnel," in which many allied health professions are included, 12.9 percent of workers were part-time (2.2 percent for economic reasons): among women technicians, 20 percent were on part-time (3.4 percent for economic reasons). (All data in this paragraph are from the Current Population Survey.) There are therefore fewer FTE (full-time equivalent) jobs than the number of people employed in an occupation implies. The definitions of each occupation worked out for the OES were, as noted above, designed in cooperation with employers to facilitate reporting. The definitions must be understood within the culture of each industry and must be consistent across industries so that the employment estimates for each occupation are additive. This qualification, however, may not always provide the nuances in definition that professional societies—concerned about qualifications, licensure, and similar matters—would like to have. Appendix C lists allied health occupations and related occupation definitions. We have suggested two reasons for the lower degree of accuracy of the occupational employment projections compared with those for industry employment: (1) the demand projections are not tested against occupational supply and (2) the basic data on the occupational composition of industries used in past projections were inaccurate. We should consider a third reason: the way in which occupational composition is changing is not well understood, and the adjustments inserted into the system to allow for the effects of technological and other changes thus are not adequate. The theory underlying the use of occupational composition data in forecasts is that the technology of each industry and the way it does its business calls for a unique mix of occupations. In a gross sense, this is certainly true: pastry cooks are not employed in steel-rolling mills. But there could be differences among plants in the same industry that result from differences in processes, in equipment, in the way the work is organized, and in the local supply of trained workers and the extent to which less-trained workers are substituted for them. For those familiar with hospitals and other health service institutions, there is no need to belabor the point that occupational composition may differ from one to another for many reasons. When the acting commissioner of the Bureau of Labor Statistics first testified before Congress on the request for funds to conduct occupational outlook research, he stated that the research would consider the occupational composition of the most technologically advanced plants in each

APPENDIX E 317 industry for clues as to the way composition would be changing. Now, nearly half a century later, this kind of analysis is made possible for the first time by the OES. Not only are the occupational statistics better but the collection of reports from ;individual plants offers a potential that has never before been available except from a few industry wage surveys: The chance to analyze why the occupational composition differs among plants in the same industry and how it is affected by the size of the plant and by new technology—analyses that may lead to better projections of occupational employment. Staffing of The Projections Research The number of BLS occupational outlook research staff has been reduced over the past few years as a result of budget cuts, and the burden on individual staff members has therefore increased. With some 200 occupations to cover with articles in the Occupational Outlook Handbook , staff are spread thin. Nevertheless, when the National Academy of Sciences staff visited them to discuss their projections, it was found that no fewer than four economists were working on health occupations. They were in touch with developments in their fields and in the health care industry generally and were familiar with the issues and findings of recent studies. Use of The Projections and Further Research Needs It should be apparent that forecasting for years in advance is always hazardous and that this truism applies particularly to employment by occupation. While there is always hope that the data and methods will improve in the future, the best we can realistically expect is that the degree of error will be somewhat reduced. The user of projections must bear this in mind and take them as only rough indications of the direction and general magnitude of changes. Of the projection methods we have reviewed, that of the Bureau of Labor Statistics appears to be the best in its ability to take into account multiple factors. BLS staff have been doing such projections continuously for a long time; they have accumulated experience, knowledge, and contacts in each field; and they check their errors and are innovative in improving data collection and analysis methods. For any projections of employment in the allied health professions the Institute of Medicine committee would be well advised to build on the work BLS has done—not necessarily to accept the projections without question but to take advantage of the analysis of the framework of the U.S. economy within which the health industry operates, and to examine the assumptions and judgments made by BLS staff in the health fields, modifying them if necessary. Our discussions with BLS staff made it clear that they are ear

APPENDIX E 318 nestly searching for understanding and would welcome any insights that would improve their projections. Before we can have any assurance that occupational supply can be understood or projected, more research needs to be done on occupational mobility and the factors that determine how people shift employment among occupations. The same may be said about the factors affecting occupational choice. On the demand side, the weakest link has been in converting projections of employment by industry, which have a fair degree of accuracy, into projections by occupation. Now, however, analysis of the factors that affect the occupational composition patterns of industries can be performed because for the first time we have occupational data for individual plants. BLS practice in publishing its projections has been to issue only 10-year or longer projections (without the intermediate years). Yet intermediate-year projections are likely to be more accurate because they are closer to what we now know; in addition, they are useful for many purposes. They also lend themselves to more frequent evaluations of accuracy, a practice that, if adopted, would enable BLS to correct its more distant projections. References Carey, M. L. 1980. Evaluating the 1975 projections of occupational employment. Monthly Labor Review 103(June):10-20. Carey, M. L., and K. Kasunic. 1982. Evaluating the 1980 projections of occupational employment. Monthly Labor Review 105(July):22-30. Eck, A. 1984. New occupational separation data improve estimates of job replacement needs. Monthly Labor Review 107(March):3-10. Goldstein, H. 1983. The accuracy and utilization of occupational forecasting. In Responsiveness of Training Institutions to Changing Labor Market Demands, R. E. Taylor, H. Rosen, and F. C. Pratzner, eds. Columbus, Ohio: The National Center for Research in Vocational Education.

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With estimates of their numbers ranging from one million to almost four million people, allied health care personnel make up a large part of the health care work force. Yet, they are among the least studied elements of our health care system. This book describes the forces that drive the demand for and the supply of allied health practitioners—forces that include demographic change, health care financing policies, and career choices available to women. Exploring such areas as credentialing systems and the employment market, the study offers a broad range of recommendations for action in both the public and private sectors, so that enough trained people will be in the right place at the right time.

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