Projections of Education Statistics to 2008 / Appendix A4
Numbers of public elementary and secondary classroom teachers were projected using a model similar to that used in Projections of Education Statistics to 2007, but the coefficients were re-estimated. The number of public school teachers was projected separately for the elementary and secondary levels. The elementary teachers were modeled as a function of disposable income per capita, local education revenue receipts from state sources per capita, and elementary enrollment. Secondary teachers were modeled as a function of disposable income per capita, education revenue receipts from state sources per capita (lagged 3 years), and secondary enrollment. Both disposable income per capita and local education revenue receipts from state sources were in constant 1986-87 dollars.
The equations in this section should be viewed as forecasting rather than structural equations, as the limitations of time and available data precluded the building of a large-scale, structural teacher model. The particular equations shown were selected on the basis of their statistical properties, such as coefficients of determination (R2s), the t-statistics of the coefficients, the Durbin-Watson statistic, and residual plots.
The multiple regression technique will yield good forecasting results only if the relationships that existed among the variables in the past continue throughout the projection period.
The public elementary classroom teacher model is:
ELTCH = b0 + b1PCI87 + b2SGRANT + b3ELENR
where:
ELTCH is the number of public elementary classroom teachers.
PCI87 is disposable income per capita in 1986-87 dollars;
SGRANT is the level of education revenue receipts from state sources per capita in 1986-87 dollars; and
ELENR is the number of students enrolled in public elementary schools.
Each variable affects the number of teachers in the expected way. As people receive more income, as the state spends more money on education, and as enrollment increases, the number of elementary teachers hired increases.
The public secondary classroom teacher model is:
SCTCH = b0 + b1PCI87+ b2SGRANT3 + b3SCENR
where:
SCTCH is the number of public secondary classroom teachers;
PCI87 is disposable income per capita in 1986-87 dollars;
SGRANT3 is the level of education revenue receipts from state sources per capita in 1986-87 dollars, lagged 3 years, and;
SCENR is the number of students enrolled in public secondary schools.
Each variable affects the number of teachers in the expected way. As people receive more income, as the state spends more money on education, and as enrollment increases, the number of secondary teachers hired increases.
Table A4.1 summarizes the results for the elementary and secondary public teacher models.
Enrollment is by organizational level, not by grade level. Thus, secondary enrollment is not the same as grade 9-12 enrollment because some states count some grade 7 and 8 enrollment as secondary. Therefore, the distribution of the number of teachers is also by organizational level, not by grade span.
Projections of private classroom teachers were derived in the following manner. For 1960 to 1994, the ratio of private school teachers to public school teachers was calculated by organizational level. These ratios were projected using single exponential smoothing, yielding a constant value over the projection period. This constant value was then applied to projections of public school teachers by organizational level to yield projections of private school teachers. This method assumes that the future pattern in the trend of private school teachers will be the same as that for public school teachers. The reader is cautioned that a number of factors could alter the assumption of constant ratios over the projection period.
The total number of public school teachers, enrollment by organizational level, and education revenue receipts from state sources used in these projections were from the Common Core of Data (CCD) survey conducted by NCES. The proportion of public school teachers by organizational level was taken from the National Education Association and then applied to the total number of teachers from CCD to produce the number of teachers by organizational level.
Disposable income was obtained from the WEFA Group and population data, used for per capita calculations, were from the Bureau of the Census.
An analysis of projection errors from the past 14 editions of Projections of Education Statistics indicated that the mean absolute percentage errors (MAPEs) for projections of classroom teachers in public elementary and secondary schools were 0.9 percent for 1 year out, 1.2 percent for 2 years out, 2.3 percent for 5 years out, and 3.4 percent for 10 years out. For the 2-year-ahead prediction, this means that one would expect the projection to be within 1.2 percent of the actual value, on the average.
