This Github repository contains replication files for ``Single Proxy Synthetic Control'' Park and Tchetgen Tchetgen (2023) (SPSC).
1.Simulation folder contains 0.Function_SSC_Simulation.R, 1.Simulation.R, and 2.PaperReport.R files. These files replicate the simulation study in Section 4 of the paper.
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0.Function_SSC_Simulation.R contains functions used for the simulation study.
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1.Simulation.R is used to replicate the simulation study with a parameter BATCH
$\in \{1,\ldots,6000\}$ . For each BATCH parameter,$d \in \{0,1\}$ (0 = without covariate, 1 = with covariate),$b \in \{1,2\}$ (1 = constant average treatment effect on the treated (ATT), 2 = linear ATT),$n \in \{02,05,09\}$ (number of donors),$i \in \{001,\ldots,500\}$ (simulation repetition index) is assigned, and 4 csv files with a format SSC_T$[t]$ _D$[d]$ _B$[b]$ _N$[n]$ _Iter$[i]$ .csv ($t \in \{00050,00100,00250,01000\}$ ) are generated in Result_D$[d]$ _B$[b]$ _N$[n]$ folder. It is recommended to use a parallel computing system by parallelizing the BATCH parameter. -
2.PaperReport.R is used to summarize the results into tables and figures of the paper and supplementary material.
1.Simulation_Supp folder contains 0.Function_SSC_Simulation.R, 1.Simulation.R, and 2.PaperReport.R files. These files replicate the simulation study in Section 4 of the paper.
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0.Function_SSC_Simulation2.R contains functions used for the simulation study.
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1.NoAdjustment.R and 2.NoAdjustment.R are used to replicate the simulation study in Section S1.9 of the supplementary material based on the simulation scenario given in Cattaneo et al. (2021). The two code files have similar structures except that 1.NoAdjustment.R uses time-invariant
$g$ and 2.NoAdjustment.R uses time-varying$g_t$ . These R codes involve with a parameter$i \in \{1,\ldots,500\}$ , and for each BATCH, a csv file with a format Result_BATCH$[i]$ .csv is created in Result_Raw or Result_Raw_Time folder. -
3.Summary.R is used to summarize the results into tables of the supplementary material.
The dataset used in the paper is first analyzed in Fohlin and Lu (2021), and is publicly available at the following [link].
Data folder contains the following files, which replicate the data analysis results in Section 5 of the paper.
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0.Function_SPSC_Data.R contains functions used for the data analysis.
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0.DataCleaning.R and 0.DataCleaning_Placebo.R are used to clean the dataset based on the actual treatment time and the placebo treatment time, respectively.
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1-1.ATT_SPSC.R and 1-2.ATT_Time_SPSC.R are used to estimate the ATT based on the SPSC approach with time-invariant
$g$ and time-varying$g_t$ , respectively. -
1-3.ATT_Abadie.R is used to estimate the ATT based on the approach of Abadie et al. (2010).
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1-4.ATT_Placebo_SPSC.R is used to estimate the placebo ATT based on the SPSC approach.
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2-1.Conformal_SPSC.R and 2-2.Conformal_Time_SPSC.R are used to estimate prediction intervals of the ATT based on the conformal inference approach of Chernozhukov et al. (2021) adapted to the SPSC setting.
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2-3.Conformal_SCPI.R is used to estimate prediction intervals of the ATT based on the approach of Cattaneo et al. (2021)
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2-4.Conformal_Placebo_SPSC.R is used to estimate prediction intervals of the placebo ATT based on the conformal inference approach of Chernozhukov et al. (2021) adapted to the SPSC setting.
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3-1.Table_ATT.R, 3-2.Plot_Conformal.R, and 3-3.Table_Plot_Placebo.R are used to summarize the results into tables and figures of the paper and supplementary material.
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10-1.Analysis_OverlapSelection.R, 10-2.Analysis_LassoSelection.R, and 10-3.Analysis_RegressionSelection.R provide details on how donors are selected.
Alberto Abadie, Alexis Diamond & Jens Hainmueller (2010) Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program, Journal of the American Statistical Association, 105:490, 493-505 [link]
Victor Chernozhukov, Kaspar Wüthrich & Yinchu Zhu (2021) An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls, Journal of the American Statistical Association, 116:536, 1849-1864 [link]
Matias D. Cattaneo, Yingjie Feng & Rocio Titiunik (2021) Prediction Intervals for Synthetic Control Methods, Journal of the American Statistical Association, 116:536, 1865-1880 [link]
Caroline Fohlin & Zhikun Lu (2021) How Contagious Was the Panic of 1907? New Evidence from Trust Company Stocks AEA Papers and Proceedings, 111: 514-19 [link]
Chan Park & Eric Tchetgen Tchetgen (2023) Single Proxy Synthetic Control, arXiv: [link]# myrepo