Working Paper: NBER ID: w14666
Authors: Jesse Rothstein
Abstract: Non-random assignment of students to teachers can bias value added estimates of teachers' causal effects. Rothstein (2008a, b) shows that typical value added models indicate large counter-factual effects of 5th grade teachers on students' 4th grade learning, indicating that classroom assignments are far from random. This paper quantifies the resulting biases in estimates of 5th grade teachers' causal effects from several value added models, under varying assumptions about the assignment process. If assignments are assumed to depend only on observables, the most commonly used specifications are subject to important bias but other feasible specifications are nearly free of bias. I also consider the case where assignments depend on unobserved variables. I use the across-classroom variance of observables to calibrate several models of the sorting process. Results indicate that even the best feasible value added models may be substantially biased, with the magnitude of the bias depending on the amount of information available for use in classroom assignments.
Keywords: Value Added Models; Teacher Effectiveness; Student Sorting; Causal Inference
JEL Codes: C12; C52; I21; J33; J45
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| nonrandom assignment (C90) | biased estimates of teachers' causal effects (C21) |
| observable characteristics (C90) | significant biases in value-added models (C52) |
| prior test scores (C52) | misestimated effectiveness of 5th grade teachers (A21) |
| amount of information (D83) | substantial biases in value-added models (C52) |
| high prior gains assigned (C78) | teacher appears less effective (A21) |