1. Enrollment Projections Demographic Context Estimation Methodology April 16, 2008Bill Smith, Public Policy Demographics1

2. “Demographics Is Destiny” Boomers Aging: Fewer Potential Mothers Fertility Below Replacement Level Limited In-Migration Naturally Occurring Retirement Communities Smaller Households and Fewer With Children Populations Will Level Off But Not All “Experts” Agree … April 16, 2008Bill Smith, Public Policy Demographics2

3. Vermont’s Aging Population April 16, 2008Bill Smith, Public Policy Demographics3

4. Fertility Rates Vary (2004) April 16, 2008Bill Smith, Public Policy Demographics4

5. Fertility Rates Below Replacement April 16, 2008Bill Smith, Public Policy Demographics5

6. Births in Vermont Profile School Enrollment Dynamics April 16, 2008Bill Smith, Public Policy Demographics6

7. School Population Estimation Steps County Population (Total and Female) Age-Specific Fertility Rates County Births Town Percentage of County Births Town Births Birth to Kindergarten Cohort Survival Kindergarten Estimate Individual Grade Migration History Grade Estimates and Total April 16, 2008Bill Smith, Public Policy Demographics7

8. Population Projection Methodology Community: “5 Year Cohort Survival” Start with census anchor year (2000) Group by five-year age cohorts Project each cohort five years older five years later Apply state age-specific mortality rates Apply migration rate with age-specific adjustments Control migration rate to get 10 year census population change (Assumption: ten year migration rates continue) Repeat for female population age 0 to 44 Apply age-specific fertility rates for births Births in five year period become age 5 to 9 next period Iterative assignment of adjustments to achieve fit Graphical evaluation in context with historical trends April 16, 2008Bill Smith, Public Policy Demographics8

9. Chittenden County Population April 16, 2008Bill Smith, Public Policy Demographics9

10. Natural Change Dominates (Example for Chittenden County) April 16, 2008Bill Smith, Public Policy Demographics10

11. Population Projection Methodology School Age: “1 Year Cohort Survival” Start with current year enrollment grade cohorts Project each cohort in next grade following year Apply long term stable grade migration rate Estimate Kindergarten from births five years earlier Apply long term stable capture rate of births to K Births from Vermont Health Department annual stats Birth estimates from percent of county historical trend Annual update and review of population change dynamics Graphical and statistical evaluation in context with historical trends April 16, 2008Bill Smith, Public Policy Demographics11

12. Chittenden County Births (Basis for Estimation of Town Births) April 16, 2008Bill Smith, Public Policy Demographics12

13. Estimating Future Births (1) April 16, 2008Bill Smith, Public Policy Demographics13

14. Estimating Future Births (2) April 16, 2008Bill Smith, Public Policy Demographics14

15. Kindergarten Cohort Survival April 16, 2008Bill Smith, Public Policy Demographics15

16. Estimating Future Kindergarten April 16, 2008Bill Smith, Public Policy Demographics16

17. Estimating Future Migration April 16, 2008Bill Smith, Public Policy Demographics17

18. Enrollment Transition April 16, 2008Bill Smith, Public Policy Demographics18

19. Enrollment Change Components April 16, 2008Bill Smith, Public Policy Demographics19

20. Estimating Total School Enrollment April 16, 2008Bill Smith, Public Policy Demographics20

21. School Enrollment Increase & Housing Growth Driven by Housing Additions Above Critical Level TownHouseholds 2000 Census New Housing 1995 to 2000 (Percent) Percent Change K-8 1995 to 2000 Burlington15,8853.0-0.1% Essex Junction3,4095.7-5.4% Colchester6,1447.41.3% Essex with Village7,0139.8-1.1% South Burlington6,33212.54.1% Essex Town3,60413.72.4% Williston2,92124.014.6% April 16, 2008Bill Smith, Public Policy Demographics21 Refer to VHFA Issue Paper “Housing and Vermont’s School Enrollment” (http://www.vhfa.org/documents/housing_education.pdf)

22. Challenges and Cautions “Past is Prologue” ??? Conditions Change – Example: Full Day K Migration Is a (Very Noisy) Random Variable! Estimating Trend Change Timing – Example: Recovering Births? April 16, 2008Bill Smith, Public Policy Demographics22

23. Lessons Learned Things Change - Annual Update Projections Are Point Estimates Consider Error Margin When Making Decisions Kindergarten Estimate Most Uncertain Look at Change Components Separately “The Plural of Anecdote is Not Data…” April 16, 2008Bill Smith, Public Policy Demographics23