Synthetic Control and Inference

By Jinyong Hahn, Ruoyao Shi. 2017

88 citations recorded by the source corpus.

We examine properties of permutation tests in the context of synthetic control. Permutation tests are frequently used methods of inference for synthetic control when the number of potential control units is small. We analyze the permutation tests from a repeated sampling perspective and show that the size of permutation tests may be distorted. Several alternative methods are discussed.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bf48eb31a4dde96e8050bb97996ca02a488a1124

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Manuel Funke
2. Alberto Abadie
3. M. D. Cattaneo
4. M. Schularick
5. Christoph Trebesch

In Statistics and Probability

1. M. D. Cattaneo
2. Alberto Abadie
3. M. Schularick
4. Christoph Trebesch
5. Manuel Funke
6. Max H. Farrell
7. R. Titiunik
8. Guido W. Imbens

Citations in the corpus

• Econometric Methods for Program Evaluation (2018, background): “, 2017) and propose sampling-base inferential methods (Hahn and Shi, 2017).”
• Populist Leaders and the Economy (2020, methodology): “Simulation-based confidence intervals following Cattaneo, Feng, and Titiunik (2021) and Cattaneo, Feng, Palomba, and Titiunik (2022), time and country placebo tests, and end-of-sample instability tests (Hahn and Shi, 2017) a causal interpretation of the measured effects.”
• Synthetic Difference In Differences (2018, unknown): “, Chernozhukov, Escanciano, Ichimura, Newey, and Robins, 2018b, Hirshberg and Wager, 2018, Imbens and Rubin, 2015, Newey, Hsieh, and Robins, 2004, Scharfstein, Rotnitzky, and Robins, 1999], and most of the currently recommended estimators in that literature combine them. An attraction of our regress”