|Benefit-Cost Summary Statistics Per Participant|
|Taxpayers||$3,980||Benefits minus costs||($1,180)|
|Participants||$9,292||Benefit to cost ratio||$0.90|
|Others||$4,951||Chance the program will produce|
|Indirect||($7,778)||benefits greater than the costs||39 %|
|Net program cost||($11,625)|
|Benefits minus cost||($1,180)|
|Meta-Analysis of Program Effects|
|Outcomes measured||Treatment age||No. of effect sizes||Treatment N||Adjusted effect sizes(ES) and standard errors(SE) used in the benefit - cost analysis||Unadjusted effect size (random effects model)|
|First time ES is estimated||Second time ES is estimated|
High school graduation
On-time completion of high school with a diploma (excluding GED attainment).
Standardized, validated tests of academic achievement.
|Detailed Monetary Benefit Estimates Per Participant|
|Affected outcome:||Resulting benefits:1||Benefits accrue to:|
|High school graduation||Criminal justice system||$25||$0||$50||$12||$87|
|Test scores||Labor market earnings associated with test scores||$3,956||$9,292||$4,902||($1,978)||$16,172|
|Program cost||Adjustment for deadweight cost of program||$0||$0||$0||($5,813)||($5,813)|
|Detailed Annual Cost Estimates Per Participant|
|Annual cost||Year dollars||Summary|
|Program costs||$974||2011||Present value of net program costs (in 2018 dollars)||($11,625)|
|Comparison costs||$0||2011||Cost range (+ or -)||0 %|
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
|Benefits Minus Costs Over Time (Cumulative Discounted Dollars)|
|The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.|
Archibald, S. (2006). Narrowing in on educational resources that do affect student achievement. Peabody Journal of Education, 81(4), 23-42.
Chaudhary, L. (2009). Education inputs, student performance and school finance reform in Michigan. Economics of Education Review, 28(1), 90-98.
Dee, T.S. (2005). Expense preference and student achievement in school districts. Eastern Economic Journal, 31(1), 23-44.
Dolton, P. & Marcenaro-Gutierrez, O.D. (2011). If you pay peanuts do you get monkeys? A cross-country analysis of teacher pay and pupil performance. Economic Policy, 26(65), 5-55.
Ferguson, R.F. & Ladd, H.F. (1996). How and why money matters: An analysis of Alabama schools. In H. F. Ladd (Ed.), Holding schools accountable: Performance based reform in education (pp. 265–298). Washington, DC: Brookings Institution.
Fuchs, T. & Wößmann, L. (2007). What accounts for international differences in student performance? A re-examination using PISA data. Empirical Economics, 32(2), 433-464.
Gibbons, S., McNally, S., & Viarengo, M. (2012). Does additional spending help urban schools?: An evaluation using boundary discontinuities. Bonn: IZA.
Guryan, J. (2003). Does money matter? Estimates from education finance reform in Massachusetts (NBER Working Paper). Cambridge, MA: National Bureau of Economic Research.
Hægeland, T., Raaum, O., & Salvanes, K. G. (2012). Pennies from heaven: Using exogenous tax variation to identify effects of school resources on pupil achievement. Economics of Education Review, 31(5), 601-614.
Häkkinen, I., Kirjavainen, T., & Uusitalo, R. (2003). School resources and student achievement revisited: New evidence from panel data. Economics of Education Review, 22(3), 329-335.
Heinesen, E. & Graversen, B. K. (2005). The effect of school resources on educational attainment: Evidence from Denmark. Bulletin of Economic Research, 57(2), 109-143.
Holmlund, H., McNally, S., & Viarengo, M. (2010). Does money matter for schools?. Economics of Education Review, 29(6), 1154-1164.
Houtenville, A.J. & Conway, K.S. (2008). Parental effort, school resources, and student achievement. Journal of Human Resources 43(2), 437–453.
Hoxby, C. (2001). All school finance equalizations are not created equal. The Quarterly Journal of Economics, 116(4), 1189-1231.
Jacob, B.A. (2001). Getting tough? The impact of high school graduation exams. Educational Evaluation and Policy Analysis, 23(2), 99-121.
Ladd, H.F., Muschkin, C.G., & Dodge, K. (2012). From birth to school: Early childhood initiatives and third grade outcomes in North Carolina. Working Paper, Duke University.
Lee, J.W. & Barro, R.J. (2001). Schooling quality in a cross-section of countries. Economica, 68, 465-488.
Loeb, S. & Page, M.E. (2000). Examining the link between teacher wages and student outcomes: The importance of alternative labor market opportunities and non-pecuniary variation. The Review of Economics and Statistics, 82(3), 393-408.
Machin, S., McNally, S., & Meghir, C. (2010). Resources and standards in urban schools. Journal of Human Capital, 4(4), 365-393.
Papke, L.E. (2005). The effects of spending on test pass rates: Evidence from Michigan. Journal of Public Economics, 89(5-6), 821-839.
Papke, L.E. & Wooldridge, J.M. (2008). Panel data methods for fractional response variables with an application to test pass rates. Journal of Econometrics, 145, 121-133.
Ram, R. (2004). School expenditures and student achievement: Evidence for the United States. Education Economics, 12(2) 169- 176.
Ribich, T.I. & Murphy, J.L. (1975). The economic returns to increased educational spending. The Journal of Human Resources, 10(1), 56-77.
Sander, W. (1999). Endogenous expenditures and student achievement. Economics Letters, 64(2), 223-231.
Sherlock, M. (2011). The effects of financial resources on test pass rates: Evidence from Vermont's Equal Education Opportunity Act. Public Finance Review, 39(3), 331-364.
Steele, F., Vignoles, A., & Jenkins, A. (2007). The effect of school resources on pupil attainment: A multilevel simultaneous equation modelling approach. Journal of the Royal Statistical Society: Series A (Statistics in Society), 170(3), 801-824.
Taylor, C. (1998). Does money matter? An empirical study introducing resource costs and student needs to educational production function analysis. In W. J. Fowler, Jr. (Ed.), Developments in school finance, 1997: Fiscal proceedings from the Annual State Data Conference (pp. 75-97). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Todd, P.E. & Wolpin, K.I. (2007). The production of cognitive achievement in children: Home, school and racial test score gaps. Journal of Human Capital, 1(1), 91-136.
Waldfogel, J. & Zhai, F. (2008). Effects of public preschool expenditures on the test scores of 4th graders: Evidence from TIMSS. Educational Research and Evaluation, 14, 9-28.
Wenglinsky, H. (1997). How money matters: The effect of school district spending on academic achievement. Sociology of Education, 70(3), 221-237.
Wenglinsky, H. (1998). School district expenditures, school resources and student achievement: Modeling the production function. In W. J. Fowler, Jr. (Ed.), Developments in school finance, 1997: Fiscal proceedings from the Annual State Data Conference (pp. 99-120). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Wilson, K. (2001). The determinants of educational attainment: Modeling and estimating the human capital model and education production functions. Southern Economic Journal, 67(3), 518-551.
WSIPP study, unpublished (2012). We conducted a multi-year, state-level, fixed-effects analysis of NCES data on per pupil expenditures, student test scores, and on-time graduation rates. See the technical appendix in this report for details.