Read Me
This version, November 2020

“Mediating Conflict in the Lab” - Alessandra Casella, Evan Friedman, Manuel Perez Archila
For questions email mfp2122@columbia.edu

This folder contains the files to replicate the empirical analysis figures and regressions from the main 
paper as well as its appendix. 

Throughout the code and folders, the names Parameter 1 and Parameter 0 are used to refer to the 
cases where q = 1/2 and q = 1/3 respectively. 

The main script which replicates the majority of figures and regressions from the data analysis is the 
R Markdown file Replication File.Rmd, which when compiled and knitted outputs the file 
Replication File.pdf. The functions used to calculate the average and confidence intervals to construct 
figures are defined and used in the order they are presented in the paper (Honesty in Figure 2, Peace 
in Figure 3, Causes of War in Figure 5, and the Appendix figures 14-16). A sample of regressions are 
run, including those presented in Table 1 (sincerity.linear.model.1 and silence.linear.model.1), Table 2 
(peace.linear.model.1 and peace.linear.model.2), Table 6 (peace.linear.model.3) and Table 7 
(peace.linear.model.1_UC, peace.linear.model.1_HM and peace.linear.model.1_CM). 

This script uses the raw data from the experiments which is saved in the file Mediation_Data.RData. 
The file contains two data frames, the main one called mediation.data for which each row is one 
observation of a game in the experiment. The values in the table can be read using the names of the 
variables included in the loaded data. For instance, a High Player/Message is coded as a 1, while a 
Low Player/Message is coded as a 2. Unmediated Communication treatment is coded as a 1, Human 
Mediation as a 2, Computer Mediation as a 3 and No Communication as a 4. The data frame 
session.parameters summarizes the parameters and orders of each session. 

The calculations related to Best Responses are in the folder Best Response. The Mathematica Notebook 
Best Response.nb constructs expected payouts and optimizes best responses which are later plotted 
(Figs 9 and 10). It also constructs the CDFs and comparisons to random behavior presented in Fig 11. 
The file reads the accompanying excel files, which are the average values of tau and alpha/beta for 
each individual. The first line in each of the files corresponds to values of tau, while the second one 
corresponds to values of alpha/beta. In the case of the files named Param 1/0 - Tau_H/L Alpha/Beta 
the third line is the number of identical observations, which is used to determine the area of the 
circles in the best response plots. The file Random xlsx has random numbers to construct the CDF 
comparisons.   

The Matlab files CM_silence_adjust.m and HM_silence_adjust.m calculate the empirical silence-adjusted 
strategies used in creating Figure 12 and Table 4. Figure 12 is created by the Stata program 
HM_CM_recommendations.do. 


