Toshiki Tsuda, Yanchun Jin, Ryo Okui
arXiv 29 Jan 2025 · Econometrics
arXiv:2501.17455 · PDF · DOI · OpenAlex · Extracted main text
This paper presents a method for constructing uniform confidence bands for the marginal treatment effect (MTE) function. The shape of the MTE function offers insight into how the unobserved propensity to receive treatment is related to the treatment effect. Our approach visualizes the statistical uncertainty of an estimated function, facilitating inferences about the function's shape. The proposed method is computationally inexpensive and requires only minimal information: sample size, standard errors, kernel function, and bandwidth. This minimal data requirement enables applications to both new analyses and published results without access to original data. We derive a Gaussian approximation for a local quadratic estimator and consider the approximation of the distribution of its supremum in polynomial order. Monte Carlo simulations demonstrate that our bands provide the desired coverage and are less conservative than those based on the Gumbel approximation. An empirical illustration regarding the returns to education is included.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Carneiro, Pedro, Lee, Sokbae (2009) Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enro… | 0.961 | 9 | 5 | 89% |
| 2 | Piterbarg, Vladimir Il'ich (1996) Asymptotic methods in the theory of Gaussian processes and fields | 0.928 | 5 | 3 | 80% |
| 3 | Heckman, James J., Vytlacil, Edward J (2005) Structural equations, treatment effects, and econometric policy evaluation 1 | 0.874 | 5 | 2 | 100% |
| 4 | Brinch, Christian N, Mogstad, Magne, Wiswall, Matthew (2017) Beyond LATE with a discrete instrument | 0.843 | 3 | 3 | 100% |
| 5 | Heckman, James J., Urzua, Sergio, Vytlacil, Edward J (2006) Understanding instrumental variables in models with essential heterogeneity | 0.811 | 4 | 2 | 100% |
| 6 | Card, David, Christofides, L., Grant, E., Swidinsky, R (1995) Using geographic variation in college proximity to estimate the return to schooling in Louis Christofides, Kenneth E. Grant and… | 0.644 | 2 | 2 | 100% |
| 7 | Carneiro, Pedro, Heckman, James J., Vytlacil, Edward J (2011) Estimating marginal returns to education | 0.644 | 2 | 2 | 100% |
| 8 | Fan, J., Gijbels, I (1996) Local polynomial modelling and its applications | 0.644 | 2 | 2 | 100% |
| 9 | Lee, Sokbae, Okui, Ryo, Whang, Yoon-Jae (2017) Doubly robust uniform confidence band for the conditional average treatment effect function self | 0.585 | 3 | 1 | 100% |
| 10 | Chernozhukov, Victor, Chetverikov, Denis, Kato, Kengo (2014) Gaussian approximation of suprema of empirical processes | 0.567 | 11 | 4 | 18% |
Showing the top 10 of 40 scored citations.