jack dougherty, jeffrey harrelson, laura maloney, drew murphy, michael snow, russell smith, and...

Jack Dougherty, Jeffrey Harrelson,

Laura Maloney, Drew Murphy,

Michael Snow, Russell Smith, and Diane Zannoni

Cities, Suburbs, and Schools Research Project

Trinity College, Hartford CT

http://www.trincoll.edu/depts/educ/CSS

AERA meeting, April 2007

School Choice in Suburbia:Public School Testing

andPrivate Real Estate Markets



Question: How much more do homebuyers pay to choose a house on the higher-scoring side of a school boundary?

East School Attendance

Area

Public School Attendance Boundary

Study uses econometric analysis

West School Attendance

Area

A B



Area


Study uses econometric analysis to control for- house characteristics


Area

A B



Area


Study uses econometric analysis to control for- house characteristics- school quality


Area

A BTest Scores


Test Scores


Area


Study uses econometric analysis to control for- house characteristics- school quality- neighborhood effects


Area

A B


Test Scores

Test Scores

Context of the Study: West Hartford, CT

- one public school district with 11 elementary (K-5)

- 28 school boundaries

A boundary close-up:

A boundary close-up:

- all single-family homes sold during our study period (1996 - 2005)

A school attendance boundary close-up:

- all single-family homes sold during our study period (1996 - 2005)

- Neighborhood around a shared school attendance boundary

Our model builds on study by Sandra Black (1999):

House Price = function of (house characteristics,

school quality, neighborhood effects)

Our model builds on study by Sandra Black (1999):



- Logarithm of price of house, deflated to year 2000 dollars, using price index of average sales in West Hartford




- Number of bedrooms, bathrooms, lot size, internal footage





- Percent of 4th graders at goal on CT Mastery Test (CMT), as data appeared in newspaper graphics & internet






Hartford Courant 1999






- Set of neighborhood dummy variables (rather than imperfect census data), to account for unobservable neighborhood characteristics, and to avoid omitted variable bias






- Set of neighborhood dummy variables (rather than imperfect census data), to account for unobservable neighborhood characteristics, and to avoid omitted variable bias

Sample = 8,736 single-family home sales, 1996-2005mean home price = $198,300 (in year 2000 dollars)mean test score = 73% (standard deviation 12 pct points)

Results: 1) Geographic Restriction & Variable Distance Analysis

2) Time Period Analysis (1996-2000 vs. 2001-2005)

3) Neighborhood Progression Analysis


What was test-price relationship when we used increasingly restrictive geography?

- Gradually eliminated school boundaries that followed rivers, parks, and major 4-lane roads, leaving behind only those drawn through residential areas (Set D)


What was test-price relationship when we varied the sample by distance to the school boundary?

Results: 1) Geographic Restriction & Variable Distance AnalysisRegression Results for Most Restrictive Geography (Set D),Variable Distance of 0.15 miles, for all time periods (1996-05)(Heteroskedastic-adjusted standard errors; t-statistics in parentheses)Dependent Variable = ln (house price)

House distance from attendance area

boundary

.15 miles

Test score .0022 (4.862)

Bedrooms .01307 (1.596)

Bathrooms .2439 (7.464)

Bathrooms2 -.0349(-5.183)

Lot size (sq ft) .000006 (4.976)

Internal size (sq ft) .0003 (15.066)

Boundary fixed effects Yes

N 1822

R2(adjusted) .7619

Interpretation:

A 12 percentage point increase in test scores* is associated with a $5,065 increase in average home price***One standard deviation

**In year 2000 dollars

Results: 2) Time Period Analysis (1996 - 2005)

Expanded on S. Black’s analysis by using a 10-year sample, which allowed us to ask:

How did test-price relationship change from pre-2000 to post-2000 period?

Pre-2000: Test data availability limited; reported annually in local newspaper

Post-2000: Test data more widely and instantly available on various websites

Results: 2) Time Period Analysis (1996 - 2005)

Regression Results for most restrictive geography (Set D), for houses located within 0.15 mile from boundary(Heteroskedastic-adjusted standard errors; t-statistics in parentheses)Dependent Variable = ln (house price)

Time Period (1)All Periods(1996-2005)

(2)First Period(1996-2000)

(3)Second Period(2001-2005)

Test score .0022 (4.862)

.0010(1.748)

.0035(3.844)

Bedrooms .01307 (1.596)

.0072(.565)

.0175(1.707)

Bathrooms .2439 (7.464)

.2657(6.143)

.1998(6.906)

Bathrooms2 -.0349(-5.183)

-.0375(-4.288)

-.0273(-4.427)

Lot size (sq ft) .000006 (4.976)

.000006(3.672)

.000006(3.487)

Internal size (sq ft) .0003 (15.066)

.0003(10.969)

.0003(10.997)

Boundary fixed effects Yes Yes Yes

N 1822 850 972

R2(adjusted) .7619 .7480 .7827

Interpretation:

A 12 percentage point increase in test scores* is associated with an average increase in home price**

Pre-2000: $2,244

Post-2000: $8,060*One standard deviation

**In year 2000 dollars

Results: 3) Neighborhood Progression Analysis

What if test scores are capturing not the effect of school quality on home prices, but rather some quality change in neighborhood, from worse to better, which is captured in the prices of homes?


What if test scores are capturing not the effect of school quality on home prices, but rather some quality change in neighborhood, from worse to better, which is captured in the prices of homes?

Test by comparing actual versus artificial school attendance areas:

Actual attendance area(0.15 mile from boundary)

(1) (2)

Artificial attendance area(0.15-0.45 miles from

boundary)(3)

Test Score .0022(4.862)

Higher-scoring side dummy variable

.0307(3.342)

Artificial attendance area dummy variable

- .0559(- 4.797)

House characteristics Yes Yes Yes

Boundary Fixed Effects Yes Yes Yes

N 1822 1821 1544

Adjusted R2 .7638 .7603 .737

Regression Results for most restrictive geography (Set D), for all time periods(Heteroskedastic-adjusted standard errors; t-statistics in parentheses)Dependent Variable = ln (house price)


Interpretation

Test scores do matter at elementary school attendance boundaries

Discussion:

- In West Hartford, homebuyers grew more sensitive to test scores as data became more readily available over time

- See parallel qualitative study (Ramsay 2006), interviewed 89 homebuyers on social construction of school quality

- Further research on school racial composition, influence of middle & high school zones, and role of real estate agents

Discussion:

- In West Hartford, homebuyers grew more sensitive to test scores as data became more readily available over time

- See parallel qualitative study (Ramsay 2006), interviewed 89 homebuyers on social construction of school quality

- Further research on school racial composition, influence of middle & high school zones, and role of real estate agents

This paper and others available at

www.trincoll.edu/depts/educ/CSS

jack dougherty, jeffrey harrelson, laura maloney, drew murphy, michael snow, russell smith, and...

Documents

house price

price of house

school boundary

school choice

public school testing

public school district

west hartford slide

eliminated school boundaries