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Zoned-In and Zoned-Out:
Changes in School Attendance Zones over Time



Magdalena Bennett   
McCombs School of Business, The University of Texas at Austin   


AEFP Conference
March 24th, 2023

Attendance zones, new schools, and segregation

  • Schools can either attract or push away residents depending on socioeconomic characteristics (Hasan & Kumar, 2019; Gibbons, Machin, & Silva 2013; Figlio & Lucas, 2004)

Attendance zones, new schools, and segregation

  • Schools can either attract or push away residents depending on socioeconomic characteristics (Hasan & Kumar, 2019; Gibbons, Machin, & Silva 2013; Figlio & Lucas, 2004)

  • Neighborhoods have important effects on long-term outcomes (Chetty et al. 2020)

Attendance zones, new schools, and segregation

  • Schools can either attract or push away residents depending on socioeconomic characteristics (Hasan & Kumar, 2019; Gibbons, Machin, & Silva 2013; Figlio & Lucas, 2004)

  • Neighborhoods have important effects on long-term outcomes (Chetty et al. 2020)

  • Racial and socioeconomic disparities in the school system also have long-term effects on students (Reardon, 2016; Billings et al., 2014)

Attendance zones, new schools, and segregation

  • Schools can either attract or push away residents depending on socioeconomic characteristics (Hasan & Kumar, 2019; Gibbons, Machin, & Silva 2013; Figlio & Lucas, 2004)

  • Neighborhoods have important effects on long-term outcomes (Chetty et al. 2020)

  • Racial and socioeconomic disparities in the school system also have long-term effects on students (Reardon, 2016; Billings et al., 2014)

New public schools opening → Changes in attendance zones

This paper

  • How do changes in attendance zones (AZ) affect:

    • Zoned-in areas (i.e. neighborhoods)?

    • Zoned-out areas (i.e. neighborhoods and schools)?

This paper

  • How do changes in attendance zones (AZ) affect:

    • Zoned-in areas (i.e. neighborhoods)?

    • Zoned-out areas (i.e. neighborhoods and schools)?

  • New high schools in Texas that changed AZ → mostly gentrified areas

This paper

  • How do changes in attendance zones (AZ) affect:

    • Zoned-in areas (i.e. neighborhoods)?

    • Zoned-out areas (i.e. neighborhoods and schools)?

  • New high schools in Texas that changed AZ → mostly gentrified areas

  • Outcomes of interest:

    • Differences in scores and score gaps between race/ethnicity

    • Differences in school composition

    • Differences in neighborhood composition

What do we mean by zoned-in and zoned-out areas?

What do we mean by zoned-in and zoned-out areas?

Zoned-in area: Attendance zone for a new school S'

What do we mean by zoned-in and zoned-out areas?

Zoned-in area: Attendance zone for a new school S'

Zoned-out area: New attendance zone for school S after the opening of schools S'.

What do we mean by zoned-in and zoned-out areas?

Zoned-in area: Attendance zone for a new school S'

Spillover school: School which had a part of their catchment area zoned-in to S'.

Data

  • Common Core Data (CCD) [2005-2019]: Administrative data from NCES, including demographic and socioeconomic characteristics of schools.

Data

  • Common Core Data (CCD) [2005-2019]: Administrative data from NCES, including demographic and socioeconomic characteristics of schools.

  • Texas Educacion Agency (TEA) data [2005-2019]: Performance data for schools over time.

Data

  • Common Core Data (CCD) [2005-2019]: Administrative data from NCES, including demographic and socioeconomic characteristics of schools.

  • Texas Educacion Agency (TEA) data [2005-2019]: Performance data for schools over time.

  • Attendance zones maps [2009-2017]: Geographic data for school boundaries over time from SABS, SABINS, and Maponics.

Data

  • Common Core Data (CCD) [2005-2019]: Administrative data from NCES, including demographic and socioeconomic characteristics of schools.

  • Texas Educacion Agency (TEA) data [2005-2019]: Performance data for schools over time.

  • Attendance zones maps [2009-2017]: Geographic data for school boundaries over time from SABS, SABINS, and Maponics.

  • Census and American Community Survey (ACS) data [2010-2019]: Demographic information at the census tract level

Data

  • Common Core Data (CCD) [2005-2019]: Administrative data from NCES, including demographic and socioeconomic characteristics of schools.

  • Texas Educacion Agency (TEA) data [2005-2019]: Performance data for schools over time.

  • Attendance zones maps [2009-2017]: Geographic data for school boundaries over time from SABS, SABINS, and Maponics.

  • Census and American Community Survey (ACS) data [2010-2019]: Demographic information at the census tract level

  • Housing Prices data [2005-2019]: Information about housing prices over time from CoreLogic and Zillow (coming soon).

Identification Strategy: An Augmented Synthetic Control Method

  • Use a weighted average of similar districts/schools/AZ/neighborhoods to create a comparison group for affected areas.

Identification Strategy: An Augmented Synthetic Control Method

  • Use a weighted average of similar districts/schools/AZ/neighborhoods to create a comparison group for affected areas.

  • Under Augmented Synthetic Control Method (ASCM) (Ben-Michael et al., 2020) there is a correction for poor fit:

Y^1Taug(0)=∑Wi=0γiYiT+(m^iT(Xi)−∑Wi=0γim^iT(Xi))

  • miT: Estimator for YiT(0)
  • Extrapolation for "bias correction".
  • If ridge regression is used → penalization for extrapolation.

Identification Strategy: An Augmented Synthetic Control Method

  • Use a weighted average of similar districts/schools/AZ/neighborhoods to create a comparison group for affected areas.

  • Under Augmented Synthetic Control Method (ASCM) (Ben-Michael et al., 2020) there is a correction for poor fit:

Y^1Taug(0)=∑Wi=0γiYiT+(m^iT(Xi)−∑Wi=0γim^iT(Xi))

  • miT: Estimator for YiT(0)
  • Extrapolation for "bias correction".
  • If ridge regression is used → penalization for extrapolation.

  • Proposal of sensitivity analysis to hidden bias (Rosenbaum, 2002; Keele et al., 2019):

    • How much should an unobserved confounder affect the probability of treatment (i.e. new school opening there vs in a control area) to explain away the results we find?

Broader picture: What happens to districts?

  • Compare districts with a new school between 2012 and 2016 vs districts with no new schools.

  • ASCM for different characteristics, adjusting for other baseline covariates (e.g. number of schools, enrollment, %FRPL, % race/ethnicity)

Districts with new schools increase gap in Math


... no significant change in Reading


What happens within districts?

  • Identify 6 new high schools between 2012-2016 that change AZ.

  • Compare attendance zones within districts to create a counterfactual.

What happens within districts?

  • Identify 6 new high schools between 2012-2016 that change AZ.

  • Compare attendance zones within districts to create a counterfactual.


  • Important caveat:

    • Limited sample size → under-powered.

    • Trends are suggestive.

Zoned-in Areas: How do neighborhoods change?

  • No major changes in % white population (left) or % African American population (right)

Zoned-in Areas: How do neighborhoods change?

  • Suggestive increase in % of college educated population

Zoned-out Areas: How are schools affected?

  • Demographics: Decreasing trend in white students enrollment (left) vs increasing trend in African American enrollment (right).

Zoned-out Areas: How are schools affected?

  • Performance: Decreasing trend % of proficiency (sharper for African American students).

Zoned-out Areas: What about neighborhoods?

  • Increasing trend in % of African-American population (left) and decreasing trend in % college-educated population (right).

Wrapping up

  • Attendance zones have a huge role in shaping neighborhoods and nearby areas.

Wrapping up

  • Attendance zones have a huge role in shaping neighborhoods and nearby areas.

  • Importance of understanding the effects of new schools and their location and boundaries.

Wrapping up

  • Attendance zones have a huge role in shaping neighborhoods and nearby areas.

  • Importance of understanding the effects of new schools and their location and boundaries.

  • Effects of housing prices? Long-run outcomes?

Wrapping up

  • Attendance zones have a huge role in shaping neighborhoods and nearby areas.

  • Importance of understanding the effects of new schools and their location and boundaries.

  • Effects of housing prices? Long-run outcomes?

  • Next steps:

    • Include other states (e.g. CA)
    • Analyze housing prices over time.
    • Heterogeneity in effect for gentrified neighborhoods?




Zoned-In and Zoned-Out:
Changes in School Attendance Zones over Time



Magdalena Bennett   
McCombs School of Business, The University of Texas at Austin   


AEFP Conference
March 24th, 2023

Attendance zones, new schools, and segregation

  • Schools can either attract or push away residents depending on socioeconomic characteristics (Hasan & Kumar, 2019; Gibbons, Machin, & Silva 2013; Figlio & Lucas, 2004)
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