Distribution of Demand for School Quality: Evidence from Quantile Regression

Wada, Roy and Herbert, Zahirovic-Herbert (2009): Distribution of Demand for School Quality: Evidence from Quantile Regression.

Abstract

Our results show that high-income families place significantly higher value on academic achievement than low-income families. High-income families are also more likely to penalize house price for non-desirable non-academic school quality. This paper uses quantile regression to examine the distribution of demand for school quality. For academic achievement, the average effects as estimated by OLS are biased toward zero due to “aggregation” of families’ willingness to pay. We take advantage of a court-ordered redistricting as a quasi-random assignment of school quality. Subdivision and school fixed-effects are used to control for unobserved characteristics.

• Item Type: MPRA Paper
• Language: English
• Keywords: school quality, demand, house price, quantile regression, hedonic equation
• Subjects: I - Health, Education, and Welfare > I2 - Education and Research Institutions; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis; D - Microeconomics > D1 - Household Behavior and Family Economics; D - Microeconomics > D4 - Market Structure, Pricing, and Design; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R5 - Regional Government Analysis

References

Annual Financial and Statistical Report. Baton Rouge: Louisiana Department of Education, 1982-2004.

Bayer P., F. Ferreira and R. McMillan (2005) “Tiebout Sorting, Social Multipliers and the Demand for School Quality,” NBER Working Paper 11087.

Black, S. (1999).”Do better schools matter? Parental valuation of elementary education.” Quarterly Journal of Economics 114(2), 579-599.

Brasington, D. M., and D. R. Haurin. 2006. “Educational outcomes and house values: A test of the value added approach.” Journal of Regional Science 46 (2), 245–268.

Buchinsky, M. (1994) “Changes in the U.S.Wage Structure 1963-1987: Application of Quantile Regression” Econometrica 62, 405-458.

Carnegie Foundation. (1992). School choice. Menlo Park, CA: Carnegie Foundation for the Advancement of Teaching.

Davis, Jr., et al. v. E. Baton Rouge Parish School Bd., et al. (D La., Baton Rouge Div., Civ. #1662.) 1956.

Davis, Jr., et al. v. East Baton Rouge Parish School Bd., 514 F. Supp. 869 (1981), p. 877.

Downes, T. A., and J. E. Zabel. 2002. “The impact of school characteristics on housing price: Chicago 1987-1991.” Journal of Urban Economics, 52, 1-25.

Emerson, F.C. (1972). “Valuation of residential amenities: an econometric approach.” The Appraisal Journal 40(2), 268–78.

Figlio, D.N. (1999). “Functional form and the estimated effects of school resources.”

Economics of Education Review, 18(2), 241-252.

Figlio D. N., and M. E. Lucas. (2004). “What's in a grade? School report cards and housing price.” American Economic Review, 94(3), 591-604.

Gould, W.W. (1992). “Quantile Regression with Bootstrapped Standard Errors.” Stata Technical Bulletin, 9, 19-21.

Gould, W.W. (1997). “Interquantile and Simultaneous-Quantile Regression.” Stata Technical Bulletin, 38, 14-22.

Hastings, J. S., T. J. Kane, and D. O. Staiger, (2005). “Parental Preferences and School Competition: Evidence from a Public School Choice Program.” National Bureau of Economic Research Working Paper No. 11805.

Haurin, D. R. and D. Brasington. 1996. “School quality and real housing price: inter- and intrametropolitan effects.” Journal of Housing Economics, 5(4): 351-68.

Hayes, K. J. and L. L. Taylor. 1996. “Neighborhood school characteristics: What signals quality to homebuyers?” Economic Review – Federal Reserve Bank of Dallas 4th Quarter: 2-9.

Jacob, B. A. and L. Lefgren (2007). “What Do Parents Value in Education? An Empirical Investigation of Parents' Revealed Preferences for Teachers.” Quarterly Journal of Economics 122(4): 1603-1637.

Kane, T., D. O. Staiger and G. Samms. 2003. “School Accountability Ratings and Housing Values.” Brookings-Wharton Papers on Urban Affairs, Brookings Institution Press, Washington DC.

Koenker, R. and Bassett, G. (1978). “Regression Quantiles.” Econometrica, 46, 33-50.

Koenker, R., and K.F. Hallock. 2001. “Quantile Regression.” Journal of Economic Perspectives 15 (4), 143-156.

Mata, J., and J.A.F. Machado. 1996. “Firm Start-up Size: A Conditional Quantile Approach.” European Economic Review 40, 1305-1323.

Lacombe, D. 2004. “Does econometric methodology matter? An Analysis of public policy using spatial econometric techniques,” Geographical Analysis, 36, 105-118.

Ries, J. and T. Somerville. 2004. “School Quality and Residential Property Values: Evidence from Vancouver Rezoning,” Working Paper, Department of Economics, University of British Columbia.

Rossell, C. 2000. “Report on Proposed Modifications to the Consent Decree,” a report to the Court in the case of Davis et al., v. East Baton Rouge Parish School Board.

Schneider, M. and J. Buckley. (2002) “What Do Parents Want from Schools? Evidence from the Internet.” Educational Evaluation and Policy Analysis, 24:2, 133–144.

Sirmans, G. S., Macpherson, D. A. and Zietz, E. N. (2005). “The Composition of Hedonic Pricing Models.” Journal of Real Estate Literature, 13:1, 3-46.

Turnbull, G.K. and J. Dombrow. 2006. “Spatial competition and shopping externalities: Evidence from the housing market.” Journal of Real Estate Finance and Economics, 32(4):391-408.

Weiher, Gregory R., and Kent L. Tedin. (2002). “Does Choice Lead to Racially Distinctive Schools? Charter Schools and Household Preferences.” Journal of Policy Analysis and Management, 21(3) 79–92.