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Enrollment Projections

Demographic ContextEstimation Methodology

April 16, 2008 Bill Smith, Public Policy Demographics 1

“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, 2008 Bill Smith, Public Policy Demographics 2

Vermont’s Aging Population

April 16, 2008 Bill Smith, Public Policy Demographics 3

Fertility Rates Vary (2004)

April 16, 2008 Bill Smith, Public Policy Demographics 4

Fertility Rates Below Replacement

April 16, 2008 Bill Smith, Public Policy Demographics 5

Births in VermontProfile School Enrollment Dynamics

April 16, 2008 Bill Smith, Public Policy Demographics 6

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, 2008 Bill Smith, Public Policy Demographics 7

Population Projection MethodologyCommunity: “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, 2008 Bill Smith, Public Policy Demographics 8

Chittenden County Population

April 16, 2008 Bill Smith, Public Policy Demographics 9

Natural Change Dominates(Example for Chittenden County)

April 16, 2008 Bill Smith, Public Policy Demographics 10

Population Projection MethodologySchool 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, 2008 Bill Smith, Public Policy Demographics 11

Chittenden County Births(Basis for Estimation of Town Births)

April 16, 2008 Bill Smith, Public Policy Demographics 12

Estimating Future Births (1)

April 16, 2008 Bill Smith, Public Policy Demographics 13

Estimating Future Births (2)

April 16, 2008 Bill Smith, Public Policy Demographics 14

Kindergarten Cohort Survival

April 16, 2008 Bill Smith, Public Policy Demographics 15

Estimating Future Kindergarten

April 16, 2008 Bill Smith, Public Policy Demographics 16

Estimating Future Migration

April 16, 2008 Bill Smith, Public Policy Demographics 17

Enrollment Transition

April 16, 2008 Bill Smith, Public Policy Demographics 18

Enrollment Change Components

April 16, 2008 Bill Smith, Public Policy Demographics 19

Estimating Total School Enrollment

April 16, 2008 Bill Smith, Public Policy Demographics 20

School Enrollment Increase & Housing

Growth Driven by Housing Additions Above Critical LevelTown Households 2000

CensusNew Housing 1995 to 2000 (Percent)

Percent Change K-8 1995 to 2000

Burlington 15,885 3.0 -0.1%

Essex Junction 3,409 5.7 -5.4%

Colchester 6,144 7.4 1.3%

Essex with Village 7,013 9.8 -1.1%

South Burlington 6,332 12.5 4.1%

Essex Town 3,604 13.7 2.4%

Williston 2,921 24.0 14.6%

April 16, 2008 Bill Smith, Public Policy Demographics 21

Refer to VHFA Issue Paper “Housing and Vermont’s School Enrollment” (http://www.vhfa.org/documents/housing_education.pdf)

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, 2008 Bill Smith, Public Policy Demographics 22

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, 2008 Bill Smith, Public Policy Demographics 23

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