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Initial Results Using the age-specific death, retirement, and field migration rates, the model described earlier and its associated life tables were used to estimate the average annual flow of personnel into and out of the biomedical and behavioral sciences workforces and, based on these, to calculate the annual number of new entrants. A defined growth rate was applied to calculate a target workforce, and a comparison of the estimated workforce (after all relevant inflows and outflows had been computed) with the target workforce provided the number of new entrants needed to sustain that growth rate. Recall, however, that the model assumes zero immigration (of doctorates with degrees from foreign institutions) and zero emigration and does not include flows to or from the "out of workforce" state. These assumptions bias downward the estimated workforce and its rate of growth.28 Accuracy of the Model The accuracy of the model in projecting the number of new entrants needed was assessed by applying it to biennial data for the period 1980-1981 to 1988-1989. The model was used to produce biennial "forecasts" of the number of new entrants, the total workforce, and the median age of the workforce. The base period used to generate these forecasts was 1978-1979. Due to the omission of immigration data and of data on flows in and out of the workforce, as well as the assumption of constancy for transition rates, the committee did not expect to achieve especially accurate results. Rather, the assessment presented in this section is shown as an exemplar of ways in which a model could be assessed were it to include the omitted data and were the transition rates to be modeled more richly. The average annual growth rate used to forecast new entrants for the biomedical sciences workforce was 4.2 percent, while the growth rate used to forecast the behavioral sciences was 4.0 percent. These rates are based on actual SDR growth rates for these workforces between 1980 and 1989. Observed average retirement and field migration rates for the three biennial periods covering 1973-1979 and the observed average age distribution of new entrants for the two biennial periods covering 1975-1979 were used as model parameters.29 28 For a more detailed discussion of this issue, see Xie, p. 9, and Appendix A. 29 While using data from the 1977-1979 survey cycle pair would have produced estimates based on experience closest to the forecasting period, an average of several pairs of survey cycles was used to increase the sample size.
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The forecast data were then compared with the actual data for each two-year period from 1980-1981 through 1988-1989. Given the use of actual growth rates for the period 1979-1989, it is not surprising to find that forecasts of the workforce derived from the model closely track the observed data for both the biomedical and behavioral science workforces. The model forecasts an increase of roughly 25 thousand, from 63 thousand to 88 thousand, for the biomedical workforce. The actual increase was 23 thousand. Similarly, for the behavioral science workforce the model predicts a growth of 19 thousand, and the actual increase was 17 thousand. The findings are not as impressive for the forecasts of required new entrants. The model vastly underestimated the number needed for the biomedical workforce in 1980-1981, but it tracked reasonably well for the remainder of the period. The average absolute value of the relative forecast error is slightly less than 10 percent. In the behavioral sciences, the observed number of new entrants increased between 1980 and 1985 and then decreased between 1986 and 1989, while the forecast number increased steadily over the entire period. This resulted in a strong trend in the forecast error, which understates needs by about 10 percent in 1980-1981 and eventually overstates needs by 27 percent in 1988-1989. The average absolute value of the relative forecast error was almost 13 percent. The discrepancy reflects, in part, a difference between the actual and forecast workforce growth rates. The model used the average workforce growth rate for the entire 1980-1989 period. The actual growth rate within the 1980-1989 period varied: it was higher in the first half of the decade than it was in the second half. The strong trend in forecast errors for new entrants to the behavioral science workforce generated a similar trend in forecast errors for the median age of that workforce. The model consistently understates this age, and the gap between actual and forecast values grows over time. For the biomedical science workforce, the forecasts of median age were very similar to the observed median ages. The relatively poor performance of the model for the behavioral sciences for a period of slowing growth is instructive. These models are useful in estimating demand that is inherent in the demographic structure of the system (for example, demand changes caused by an uneven distribution of ages that results in variation in retirements). They cannot, however, accurately forecast changes that result from factors not included in the model. Since such factors (e.g., economic conditions) can never be completely taken into account, these models provide, at best, a baseline from which to project the demand for new entrants, given assumptions about changes in overall demand. Where these models are useful is in exploring the sensitivity of demand for new entrants, given assumptions about workforce demand and the mobility characteristics of the workforce.
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