Replication code and data for ‘‘Corruption information and vote share: A meta-analysis and lessons for experimental design.’’ American Political Science Review, 114.3 (2020): 761-774.

Required Software: R (3.6.1 or Above), Stata (Version 14 or Above). Additional required software packages and libraries are specified in the replication code.

Overview: These files replicate all analyses in Trevor Incerti, “Corruption information and vote share: A meta-analysis and lessons for experimental design.” To replicate all analyses and figures, download all data files to a folder entitled “/data”, create a second folder entitled “/figs” in the same directory, and run all code files in numerical order.

Replication Code

1. replications_all.R

• Replicates all survey experiments with available replication data and/or compiles data needed for subsequent analysis for all included studies.

2. meta.R

• Conducts meta-analysis, including fixed effects estimation, random effects estimation, mixed effects estimation with moderator, and heterogeneity analysis.
• Creates Online Appendix Tables A.3-A.5.

3. plot.R

• Plots meta-analysis results from "2. meta.R."
• Creates Figures 1 and 2.

4. publication_bias.R

• Conducts all analyses related to publication bias: p-curve, examination of funnel plot asymmetry, regression tests for funnel plot asymmetry, trim and fill, and PET-PEESE.
• Creates Online Appendix Tables A.10-A.14 and A.4-A.12.

5. predicted_probabilities.do

• (Requires Stata) Loads replication data for Breitenstein 2019, Franchino and Zucchini 2014, Mares and Visconti 2019, and Chauchard, Klasnja and Harish 2019, and conducts all predicted probabilities calculations.
• Creates Figure 4 and Online Appendix Figures A.14-A.15, A.18-A.21, and A.23-A.25.

6. amce.R

• Loads replication data for Breitenstein 2019, Franchino and Zucchini 2014, and Mares and Visconti 2019, and calculates Average Marginal Component Effects (AMCEs).
• Creates Figure 3 and Online Appendix Figures A.17 and A.22.

7. tree.R

• Loads replication data for Breitenstein 2019 and Chauchard, Klasnja and Harish 2019 and calculates predicted probabilities using recursive partitioning (classification trees).
• Creates Figure 5 and Online Appendix Figures A.16 and A.26.

%%%%% Results in the Online Appendix only start here %%%%%

a1. lab.R

• Conducts meta-analysis of lab experiments.
• Creates Online Appendix Figure A.1.

a2. robustness.R

• Conducts field experiment meta-analysis excluding Banerjee et al. studies. Conducts mixed effects estimation with moderator and heterogeneity analysis excluding Banerjee et al. studies. Conducts survey experiment meta-analysis including De Figueiredo, Hidalgo and Kasahara 2011.
• Creates Online Appendix Tables A.6-A.9 and Figures A.2-A.3.

a3. publication_plot.R

• Creates plot of all experiments (point estimates and 95% confidence intervals) by publication status.
• Creates Online Appendix Figure A.12.

a4. quality.R

• Replicates survey experiments that vary quality of corruption information and plots point estimates and 95% confidence intervals.
• Creates Online Appendix Figure A.13.

Data Files (relative path "~/data")

Replication data for survey experiments:

• Choosing_crook.dta (Breitenstein Research and Politics 2019 raw data)
• Choosing_crook_recode.do (cleans data for Breitenstein Research and Politics 2019 experiment)
• choosing_crook_clean.dta (Breitenstein Research and Politics 2019)
• panel_cleaned.csv (Boas, Hidalgo, and Melo: AJPS 2018)
• chauchard_klasnja_harish.dta (Chauchard, Klasnja, and Harish JOP 2019)
• experiment_data_eggers.Rds (Eggers, Vivyan, and Wagner JOP 2017)
• franchino_zucchini.dta (Franchino and Zucchini PSRM 2014)
• analysis-data.dta (Klasnja, Lupu, and Tucker Working Paper)
• mares_visconti.dta (Mares and Visconti PSRM 2019)
• WintersWeitzShapiro_2013_Replication.dta (Winters and Weitz-Shapiro Comparative Politics 2013)
• WintersWeitz-Shapiro_PRQ_Specificity_ReplicationData.dta (Winters and Weitz-Shapiro PRQ 2016)
• Weitz-ShapiroWinters_JOP_Credibility_ReplicationData.dta (Winters and Weitz-Shapiro Journal of Politics 2017)
• WintersWeitz-Shapiro_PSRM_Argentina_ReplicationData.dta (Winters and Weitz-Shapiro PSRM 2018)

Point estimates and standard errors from field experiments and survey experiments without replication data

• study_results.xlsx