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Semiparametric Estimation of Long-Term Treatment Effects

Jiafeng Chen, David M. Ritzwoller

arXiv 30 Jul 2021 · Econometrics · publishedJournal of Econometrics (2023) · 9 citations (OpenAlex)

arXiv:2107.14405 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Long-term outcomes of experimental evaluations are necessarily observed after long delays. We develop semiparametric methods for combining the short-term outcomes of experiments with observational measurements of short-term and long-term outcomes, in order to estimate long-term treatment effects. We characterize semiparametric efficiency bounds for various instances of this problem. These calculations facilitate the construction of several estimators. We analyze the finite-sample performance of these estimators with a simulation calibrated to data from an evaluation of the long-term effects of a poverty alleviation program.

Citation extraction

84
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182
in-text mentions
84
distinct cited
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appendix boundary found by appendix_titled_section at “Simulation\label{sec:appendix simulation}” · 92% of the source is main text. Read the extracted text to check this.

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
1Athey, S., Chetty, R., Imbens, G., and Kang, H (2020) Estimating treatment effects using multiple surrogates: The role of the surrogate score and the surrogate index1.000165100%
2Athey, S., Chetty, R., and Imbens, G (2020) Combining experimental and observational data to estimate treatment effects on long term outcomes1.000155100%
3Chen, X. and Liao, Z (2015) Sieve semiparametric two-step gmm under weak dependence1.000113100%
4Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C… (2018) Double/debiased machine learning for treatment and structural parameters0.97413592%
5Dynarski, S., Libassi, C., Michelmore, K., and Owen, S (2021) Closing the gap: The effect of reducing complexity and uncertainty in college pricing on the choices of low-income students0.92843100%
6Hahn, J (1998) On the role of the propensity score in efficient semiparametric estimation of average treatment effects0.92843100%
7Bickel, P. J., Klaassen, C. A., Ritov, Y., and Wellner, J. A (1993) Efficient and adaptive estimation for semiparametric models, volume 40.84333100%
8Chen, X., Liao, Z., and Sun, Y (2014) Sieve inference on possibly misspecified semi-nonparametric time series models0.81142100%
9Chen, X. and Santos, A (2018) Overidentification in regular models0.81142100%
10Imbens, G. W (2004) Nonparametric estimation of average treatment effects under exogeneity: A review0.81142100%

Showing the top 10 of 84 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
1The Surrogate Index: Combining Short-Term Proxies to Estimate Long-Term Treatment Effects More Rapidly and Precisely1.00063
2A Sensitivity Analysis of the Surrogate Index Approach for Estimating Long-Term Treatment Effects0.965103
3Identification of Long-Term Treatment Effects via Temporal Links, Observational, and Experimental Data0.92843
4Simultaneous Inference for Local Structural Parameters with Random Forests$^*$0.64422
5Kernel methods for long term dose response curves0.40511
6Long-term Causal Inference Under Persistent Confounding via Data Combination0.40511
7On Local Overidentification and Efficiency Gains in Modern Causal Inference and Data Combination0.40511
8Balancing Weights for Causal Mediation Analysis0.40511
9Long-term Causal Inference with Many Noisy Proxies0.40511
10The Proximal Surrogate Index: Long-Term Treatment Effects under Unobserved Confounding0.40511