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 AERA meeting, April 2007 School Choice in Suburbia: Public School Testing and Private 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 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 to control for - house characteristics West School Attendance Area A B 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 to control for - house characteristics - school quality West School Attendance Area A BTest Scores Question: How much more do homebuyers pay to choose a house on the higher-scoring side of a school boundary? Test Scores

East School Attendance Area Public School Attendance Boundary Study uses econometric analysis to control for - house characteristics - school quality - neighborhood effects West School Attendance Area A B Question: How much more do homebuyers pay to choose a house on the higher-scoring side of a school boundary? 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:

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

A school attendance boundary close-up: - all single-family homes sold during our study period ( ) - 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):

House Price = function of (house characteristics, school quality, neighborhood effects) -Logarithm of price of house, deflated to year 2000 dollars, using price index of average sales in West Hartford

House Price = function of (house characteristics, school quality, neighborhood effects) -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

House Price = function of (house characteristics, school quality, neighborhood effects) -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

House Price = function of (house characteristics, school quality, neighborhood effects) -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

House Price = function of (house characteristics, school quality, neighborhood effects) -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 -Set of neighborhood dummy variables (rather than imperfect census data), to account for unobservable neighborhood characteristics, and to avoid omitted variable bias

House Price = function of (house characteristics, school quality, neighborhood effects) -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 -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, mean 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 ( vs ) 3) Neighborhood Progression Analysis

Results: 1) Geographic Restriction & Variable Distance 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)

Results: 1) Geographic Restriction & Variable Distance Analysis What was test-price relationship when we varied the sample by distance to the school boundary?

Results: 1) Geographic Restriction & Variable Distance Analysis What was test-price relationship when we varied the sample by distance to the school boundary?

Results: 1) Geographic Restriction & Variable Distance Analysis What was test-price relationship when we varied the sample by distance to the school boundary?

Results: 1) Geographic Restriction & Variable Distance Analysis Regression Results for Most Restrictive Geography (Set D), Variable Distance of 0.15 miles, for all time periods ( ) (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 (1.596) Bathrooms.2439 (7.464) Bathrooms (-5.183) Lot size (sq ft) (4.976) Internal size (sq ft).0003 (15.066) Boundary fixed effectsYes N1822 R 2 (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 ( ) Expanded on S. Blacks 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 ( ) 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 ( ) (2) First Period ( ) (3) Second Period ( ) Test score.0022 (4.862).0010 (1.748).0035 (3.844) Bedrooms (1.596).0072 (.565).0175 (1.707) Bathrooms.2439 (7.464).2657 (6.143).1998 (6.906) Bathrooms (-5.183) (-4.288) (-4.427) Lot size (sq ft) (4.976) (3.672) (3.487) Internal size (sq ft).0003 (15.066).0003 (10.969).0003 (10.997) Boundary fixed effectsYes N R 2 (adjusted) 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?

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? Test by comparing actual versus artificial school attendance areas:

Actual attendance area (0.15 mile from boundary) (1) (2) Artificial attendance area ( miles from boundary) (3) Test Score.0022 (4.862) Higher-scoring side dummy variable.0307 (3.342) Artificial attendance area dummy variable ( ) House characteristicsYes Boundary Fixed EffectsYes N Adjusted R 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) Results: 3) Neighborhood Progression Analysis 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