The Surrogate Index: Combining Short-Term Proxies to Estimate Long-Term Treatment Effects More Rapidly and Precisely / Susan Athey, Raj Chetty, Guido W. Imbens, Hyunseung Kang.

Format:

Book

Author/Creator:

Athey, Susan.

Contributor:

National Bureau of Economic Research.

Chetty, Raj.

Imbens, Guido W.

Kang, Hyunseung.

Series:

Working Paper Series (National Bureau of Economic Research) no. w26463.

NBER working paper series no. w26463

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Other Title:

Surrogate Index

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2019.

Summary:

A common challenge in estimating the long-term impacts of treatments (e.g., job training programs) is that the outcomes of interest (e.g., lifetime earnings) are observed with a long delay. We address this problem by combining several short-term outcomes (e.g., short-run earnings) into a "surrogate index," the predicted value of the long-term outcome given the short-term outcomes. We show that the average treatment effect on the surrogate index equals the treatment effect on the long-term outcome under the assumption that the long-term outcome is independent of the treatment conditional on the surrogate index. We then characterize the bias that arises from violations of this assumption, deriving feasible bounds on the degree of bias and providing simple methods to validate the key assumption using additional outcomes. Finally, we develop efficient estimators for the surrogate index and show that even in settings where the long-term outcome is observed, using a surrogate index can increase precision. We apply our method to analyze the long-term impacts of a multi-site job training experiment in California. Using short-term employment rates as surrogates, one could have estimated the program's impacts on mean employment rates over a 9 year horizon within 1.5 years, with a 35% reduction in standard errors. Our empirical results suggest that the long-term impacts of programs on labor market outcomes can be predicted accurately by combining their short-term treatment effects into a surrogate index.

Notes:

Print version record

November 2019.