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Featured researches published by Stephen Lipscomb.


Education Finance and Policy | 2011

Funding Special Education by Capitation: Evidence from State Finance Reforms

Elizabeth Dhuey; Stephen Lipscomb

This study examines responses to state capitation policies for special education finance between 199192 and 20034. Capitation refers to distributing funds based on the entire student enrollment. We find that disability rates tended to fall following capitation reforms, primarily in subjectively diagnosed categories and in early and late grades. The association appears immediately in less severe categories but gradually in severe categories. More frequent program exiting partly accounts for falling disability rates among high school students. Capitation also is associated with a rising local share and a falling state share of funding. The evidence supports an increased use of outside school placements among severe disabilities, consistent with an incentive-based response. We find weaker evidence of a relationship between capitation and higher request rates for dispute resolution. Finally, we present evidence of differential effects based on both the pre-reform funding system and the presumed strength of the policy change.


Education Finance and Policy | 2016

Is School Value Added Indicative of Principal Quality

Hanley Chiang; Stephen Lipscomb; Brian Gill

States across the country are developing systems for evaluating school principals on the basis of student achievement growth. A common approach is to hold principals accountable for the value added of their schools—that is, schools’ contributions to student achievement growth. In theory, school value added can reflect not only principals’ effectiveness but also other school-specific influences on student achievement growth that are outside of principals’ control. In this paper, we isolate principals’ effects on student achievement growth and examine the extent to which school value added captures the effects that principals persistently demonstrate. Using longitudinal data on the math and reading outcomes of fourth- through eighth-grade students in Pennsylvania, our findings indicate that school value added provides very poor information for revealing principals’ persistent levels of effectiveness.


Journal of Research on Educational Effectiveness | 2015

Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables

Matthew Johnson; Stephen Lipscomb; Brian Gill

Abstract Teacher value-added models (VAMs) must isolate teachers’ contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they include student and peer background characteristics, and a double-lagged achievement score. We also consider two previously unexplored model variations: (a) replacing classroom peer characteristics with teacher-level averages, and (b) allowing demographics to influence the relationship between current and prior achievement. Using data from a northern state, we find that teacher effectiveness estimates are highly correlated across specifications. However, up to 26% of teachers in the bottom quintile using one specification are ranked higher using another specification. Differences between VAMs have direct implications for which estimates change. In particular, teachers in a district with a large fraction of disadvantaged students receive lower ratings when background characteristics are omitted. Other modeling choices have smaller practical consequences, and none are as important as selecting which assessment to use as the outcome measure.


Education Finance and Policy | 2013

Funding Special Education by Total District Enrollment: Advantages, Disadvantages, and Policy Considerations.

Elizabeth Dhuey; Stephen Lipscomb

Several states and the federal government distribute aid for special education programs based primarily on total district enrollment and a fixed aid amount per student, a method called census funding. In this policy brief, we address three questions to help policy makers, educators, and researchers better understand census-funding models and special education finance policies in general. The first question is, what are the key advantages and disadvantages of census-funding models? The second and third questions relate to aspects of policy implementation, in the event a state legislature should choose to adopt the approach. First, we examine what options are available to mitigate concerns about the equity of funding under a census funding model. Second, we examine what other options exist for helping states and districts to contain special education costs while maintaining a high level of quality.


Economics of Education Review | 2008

What Makes a Leader? Relative Age and High School Leadership

Elizabeth Dhuey; Stephen Lipscomb


Economics of Education Review | 2010

Disabled or Young? Relative Age and Special Education Diagnoses in Schools

Elizabeth Dhuey; Stephen Lipscomb


Mathematica Policy Research Reports | 2012

Value-Added Models for the Pittsburgh Public Schools

Matthew Johnson; Stephen Lipscomb; Brian Gill; Kevin Booker; Julie Bruch


Mathematica Policy Research Reports | 2010

Teacher and Principal Value-Added: Research Findings and Implementation Practices

Stephen Lipscomb; Bing-ru Teh; Brian Gill; Hanley Chiang; Antoniya Owens


Mathematica Policy Research Reports | 2013

Improving Post-High School Outcomes for Transition-Age Students with Disabilities: An Evidence Review

R. Brian Cobb; Stephen Lipscomb; Jennifer R. Wolgemuth; Theresa Schulte; Abigail Veliquette; Morgen Alwell; Keriu Batchelder; Robert Bernard; Paul R. Hernandez; Helen Holmquist-Johnson; Rebecca Orsi; Laura B. Sample McMeeking; Jun Wang; Andrea Welnberg


Mathematica Policy Research Reports | 2013

Classroom Observations from Phase 2 of the Pennsylvania Teacher Evaluation Pilot: Assessing Internal Consistency, Score Variation, and Relationships with Value Added

Elias Walsh; Stephen Lipscomb

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Brian Gill

Mathematica Policy Research

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Hanley Chiang

Mathematica Policy Research

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Matthew Johnson

Mathematica Policy Research

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Kevin Booker

Mathematica Policy Research

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John Burghardt

Mathematica Policy Research

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R. Brian Cobb

Colorado State University

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Duncan Chaplin

Mathematica Policy Research

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