Urban Institute analysis of longitudinal data in education research
A program of research by the Urban Institute with Duke University, Stanford University, University of Florida, University of Missouri-Columbia, University of Texas at Dallas, and University of WashingtonUrban Institute



2007 Conference Presentations

From IES Director Russ Whitehurst's opening remarks at the CALDER Conference:

"The availability to the education research community of large administrative datasets containing longitudinal data on individual students linked to characteristics of their teachers, schools, and communities is relatively recent and very important. The wide availability of public heath data has allowed epidemiologists to relate the occurrence of diseases to environmental and personal characteristics that vary by place, time, and subgroup and in so doing spur appreciable advances in the health of the nation. Likewise, longitudinal datasets in education are allowing education researchers to uncover relationships between characteristics of schooling and student outcomes that promise both to enhance the effectiveness of education policies and to inform a new generation of research studies. CALDER is leading the way in this effort. I am very pleased that IES has funded CALDER as well as many of the statewide longitudinal data systems on which the work of CALDER depends. I am honored to be here to welcome you to the first CALDER conference."

The Narrowing Gap in New York City Qualifications and Its Implications for Student Achievement
Susanna Loeb

Teacher Credentials and Student Achievement in High School: A Cross Subject Analysis with Student Fixed Effects
Helen (Sunny) Ladd

Teacher Training, Teacher Quality and Student Achievement
Tim Sass

Estimating Teacher Quality with Administrative Data
Eric Hanushek

Teacher Pensions and Labor Market Behavior: A Descriptive Analysis
Michael Podgursky

Special Data Opportunities in Florida
David Figlio

Strategies for Estimating the Effects of Teacher Credentials
Helen (Sunny) Ladd

The Determinants of Student Achievement: Different Estimates for Different Measures
Tim Sass