arXiv 17 Aug 2024 · Econometrics
arXiv:2408.09271 · PDF · DOI · OpenAlex · Extracted main text
In this paper, we propose a novel method for causal inference within the framework of counterfactual and synthetic control. Matching forward the generalized synthetic control method, our instrumented principal component analysis method instruments factor loadings with predictive covariates rather than including them as regressors. These instrumented factor loadings exhibit time-varying dynamics, offering a better economic interpretation. Covariates are instrumented through a transformation matrix, $\Gamma$, when we have a large number of covariates it can be easily reduced in accordance with a small number of latent factors helping us to effectively handle high-dimensional datasets and making the model parsimonious. Moreover, the novel way of handling covariates is less exposed to model misspecification and achieved better prediction accuracy. Our simulations show that this method is less biased in the presence of unobserved covariates compared to other mainstream approaches. In the empirical application, we use the proposed method to evaluate the effect of Brexit on foreign direct investment to the UK.
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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 | Yiqing Xu (2017) Generalized synthetic control method: Causal inference with interactive fixed effects models | 0.920 | 9 | 7 | 78% |
| 2 | Bryan T Kelly, Seth Pruitt, and Yinan Su (2020) Instrumented principal component analysis | 0.874 | 6 | 5 | 67% |
| 3 | Jushan Bai (2009) Panel data models with interactive fixed effects | 0.843 | 4 | 3 | 75% |
| 4 | Marc Chan, Simon Kwok, et al (2016) Policy evaluation with interactive fixed effects | 0.843 | 3 | 3 | 100% |
| 5 | Jushan Bai and Pierre Perron (2003) Computation and analysis of multiple structural change models | 0.737 | 3 | 2 | 100% |
| 6 | James H Stock and Mark W Watson (2002) Forecasting using principal components from a large number of predictors | 0.737 | 3 | 2 | 100% |
| 7 | Alberto Abadie, Alexis Diamond, and Jens Hainmueller (2010) Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program | 0.644 | 2 | 2 | 100% |
| 8 | Eli Ben-Michael, Avi Feller, and Jesse Rothstein (2021) The augmented synthetic control method | 0.644 | 2 | 2 | 100% |
| 9 | Victor Chernozhukov, Kaspar Wüthrich, and Yinchu Zhu (2021) An exact and robust conformal inference method for counterfactual and synthetic controls | 0.644 | 2 | 2 | 100% |
| 10 | Laurent Gobillon and Thierry Magnac (2016) Regional policy evaluation: Interactive fixed effects and synthetic controls | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 41 scored citations.