Replication Data for: Agenda Setting and Attention to Precedent in the U.S. Federal Courts
收藏DataONE2021-02-17 更新2024-06-08 收录
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资源简介:
• attn-to-prec.Rproj -- you can safely ignore this file; it is helpful for people who use RStudio, but not necessary for replication • README.md -- this file explains how to replicate results and lists and explains the content of the archive • bapvar/ -- this is a directory that contains an R extension package necessary to replicate the results • code/ -- this is a directory that contains all the replication code o 00-util.R -- additional R functions we use in the remaining files o 01-sampling.R -- code to do the sampling for each precedent's BaP-VAR model o 02-frequency-of-effects.R -- ensures any precedents sampled for in the previous file replicate our results and reproduces Tables 1 and 2 and Figure 1 o 03-examples.R -- replicates the results for the example cases presented in the paper, Smith and Watts, replicating Tables 3 and 4 and Figures 2 and 3 o 04-magnitude-of-effects.R -- reproduces Figures 4, 5, 6, and 7 • data/ -- this is a directory that contains all the replication data o citation-data.csv -- contains the precedent-year-level data on citations to U.S. Supreme Court precedents decided between 1946 and 1985 o coef-signs.csv -- contains the \"sign\" for lag coefficients in all optimal-lag models run for the paper o coef-summaries.csv -- contains summary data on the posterior draws for lag coefficients in all one-lag models run for the paper o dynamic-summaries.csv -- contains summary data on impulse responses and forecast error variance decomposition calculated from the posterior draws for all one-lag models run for the paper o codebook.pdf -- contains information on how the data for the paper were gathered, and documenting the contents of \"citation-data.csv\", \"coef-summaries.csv\", and \"dynamic-summaries.csv\"
创建时间:
2023-11-19



