Student Yields Through the Life Course

1. Student Yield Differentials by Housing Tenure: Examples from Selected U.S. School DistrictsJerome McKibbenMcKibben Demographic ResearchMatthew CropperCropper GIS2014Applied Demography ConferenceSan Antonio TexasJanuary 9 ,2014

2. Student Yields Through the Life Course • It has long been noted that the number of school age children per household varies greatly over the life course of both households and housing units. • The variables that have been most often correlated to the student yield levels are housing cost (socio-economic) and age of householder.

3. Using Housing Tenure as a Predictive Variable • By identifying the differentials in student yield characteristics by housing tenure and age of housing units, forecasters can more accurately predict future enrollment trends. • One of the reasons these factors have been difficult to quantify in the past was the lack of data at the micro level on both student ages and housing unit characteristics.

4. Geo-coding students with Census Housing Data • With the ability to now geo-code students by grade at the address level, forecasters can now examine the association between housing unit characteristics and student distribution by age. • Further, by developing these data over time, researchers can now examine the dynamics of student yield as the occupants age in their housing units.

5. Typologies • We have constructed five typologies of the most common student yield characteristics by housing tenure/householder age . • Type A - Multi-family rental- area that feature steady elementary enrollment and high pre-school age counts. Enrollment tends to decline in middle school grades as households migrate to single family housing..

6. Typologies • Type B - Single family, new development – areas that feature single family detached home built in the last 10 year. Enrollment tends to be elementary moving towards muddle school. Preschool population declines over time. • Type C – Single family, established – development that is older than 10 years but less than 20. Enrollment tends to be middle school/high school with declining elementary over time

7. Typologies • Type D – Single family empty nest – Housing stock is between 20 and 40 years old where most of the children of the homeowners have moved away. Very low student yield. • Type E – Single family Turnover – housing stock is more than 40 years old. A significant number of original home owners have moved away and have been replaced with new young families. An even distribution of students across the ages.

8. Case Studies – Type A: Lakota OhioMulti -Family Rental Student Yield (2012-13) = .94

9. Case Studies – Type B: Lakota OhioSingle Family New Development Student Yield (2012-13) = .86

10. Case Studies – Type C: Lakota OhioSingle Family Established Development Student Yield (2012-13) = .69

11. Case Studies – Type D: Lakota OhioSingle Family Empty Nest Development Student Yield (2012-13) = .39

12. Case Studies – Type E: Billings MTSingle Family Turnover Student Yield (2012-13) = .44

13. Implications and Applications • This procedure enables the forecaster to account for future changes in student yields by age of householder, age of housing stock and tenure. • With a growing number of housing units “turning over” in the next 10 to 20 years, the ability to account these dynamics in student yields will help produce more accurate micro area forecasts.

14. Implications and Applications • Further, since 6 existing housing units are bought and sold each year for every new unit built, this procedure allows forecasters to account for a greater proportion of housing dynamics in their enrollment forecasts.