Generated with sparks and insights from 3 sources








  • LaLonde (1986) is a seminal paper by Robert J. LaLonde that critically evaluated the effectiveness of nonexperimental methods in estimating the impact of employment training programs.

  • The study compared nonexperimental estimates to experimental benchmarks and found that nonexperimental methods at the time could not reliably replicate the results of randomized experiments.

  • This paper has had a significant impact on the field of econometrics, leading to methodological advancements and a greater emphasis on the credibility of nonexperimental methods.

  • Key lessons from LaLonde (1986) include the importance of unconfoundedness, covariate overlap, and validation exercises in nonexperimental studies.

  • Modern methods, such as propensity score matching and doubly robust estimators, have been developed to address the issues highlighted by LaLonde.

Background [1]

  • Author: Robert J. LaLonde

  • Publication Year: 1986

  • Journal: American Economic Review

  • Focus: Evaluating the effectiveness of nonexperimental methods in estimating the impact of employment training programs.

  • Method: Comparison of nonexperimental estimates to experimental benchmarks.


Key Findings [2]

  • Nonexperimental methods could not reliably replicate experimental results.

  • Highlighted the limitations of nonexperimental methods in causal inference.

  • Emphasized the need for more robust methods to estimate treatment effects.

  • Found significant discrepancies between nonexperimental and experimental estimates.

  • Called for greater scrutiny and validation of nonexperimental methods.

Methodological Advances [2]

  • Introduction of propensity score-based methods.

  • Development of doubly robust estimators.

  • Emphasis on unconfoundedness and covariate overlap.

  • Greater focus on validation exercises to ensure credibility.

  • Methods for estimating and exploiting treatment effect heterogeneity.

Impact on Econometrics [2]

  • LaLonde (1986) has been highly influential in the field of econometrics.

  • It has led to a reevaluation of nonexperimental methods.

  • The paper has spurred the development of more reliable methods for causal inference.

  • It has highlighted the importance of experimental benchmarks in validating nonexperimental estimates.

  • The study is frequently cited in econometric literature and has shaped subsequent research.

Modern Applications [2]

  • Modern methods have been applied to reexamine LaLonde's data.

  • Propensity score matching and doubly robust estimators are now commonly used.

  • Validation exercises, such as placebo tests, are essential for assessing credibility.

  • Modern methods yield robust estimates when there is sufficient covariate overlap.

  • The lessons from LaLonde (1986) continue to inform current econometric practices.