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Automatic Inference for Value-Added Regressions

Tian Xie

arXiv 24 Mar 2025 · Econometrics

arXiv:2503.19178 · PDF · DOI · OpenAlex · Extracted main text

Abstract

It is common to use shrinkage methods such as empirical Bayes to improve estimates of teacher value-added. However, when the goal is to perform inference on coefficients in the regression of long-term outcomes on value-added, it's unclear whether shrinking the value-added estimators can help or hurt. In this paper, we consider a general class of value-added estimators and the properties of their corresponding regression coefficients. Our main finding is that regressing long-term outcomes on shrinkage estimates of value-added performs an automatic bias correction: the associated regression estimator is asymptotically unbiased, asymptotically normal, and efficient in the sense that it is asymptotically equivalent to regressing on the true (latent) value-added. Further, OLS standard errors from regressing on shrinkage estimates are consistent. As such, efficient inference is easy for practitioners to implement: simply regress outcomes on shrinkage estimates of value added.

Citation extraction

39
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Andrabi, T., N. Bau, J. Das, and A. I. Khwaja (2025) Heterogeneity in school value added and the private premium1.000113100%
2Kline, P., E. K. Rose, and C. R. Walters (2022) Systemic discrimination among large us employers1.00073100%
3Kane, T. J. and D. O. Staiger (2008) Estimating teacher impacts on student achievement: An experimental evaluation1.00053100%
4Chetty, R., J. N. Friedman, and J. E. Rockoff (2014) Measuring the impacts of teachers ii: Teacher value-added and student outcomes in adulthood0.87462100%
5Chetty, R., J. N. Friedman, and J. E. Rockoff (2014) Measuring the impacts of teachers i: Evaluating bias in teacher value-added estimates0.87452100%
6Kline, P., R. Saggio, and M. Slvsten (2020) Leave-out estimation of variance components0.84333100%
7Jacob, B. A. and L. Lefgren (2007) What do parents value in education? an empirical investigation of parents' revealed preferences for teachers0.81142100%
8Walters, C (2024) Empirical bayes methods in labor economics0.73732100%
9Bau, N. and J. Das (2020) Teacher value added in a low-income country0.64422100%
10Deeb, A (2021) A framework for using value-added in regressions0.64422100%

Showing the top 10 of 39 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Empirical Bayes shrinkage (mostly) does not correct the measurement error in regression0.40511