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+version https://git-lfs.github.com/spec/v1
+oid sha256:c30991c973eca15183b5ff245fc6adeb4c145059af922126a47612dd895a8821
+size 630868

25/replication_package/AJPS_2021_Kim_Appendix.R

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+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# ------------------------------------------- -------------------------------------------------------------------------------------
+# Entertaining Beliefs in Economic Mobility 
+# Eunji Kim, 2021
+# American Journal of Political Science
+# APPENDIX  # 
+# --------------------------------------------------------------------------------------------------------------------------------
+# --------------------------------------------------------------------------------------------------------------------------------
+
+#list.of.packages <- c("foreign", "ggplot2", "readstata13", "dplyr", "haven", "xtable", "stargazer", "tidytext", "stringr", "tidyr", "wordcloud", "scales", "tables", "ggpubr", "lubridate", "DescTools", "ggeffects", "tidyverse", "egg") 
+#new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
+#if(length(new.packages)) install.packages(new.packages)
+
+#setwd("[path to where replication archive was downloaded]")
+
+
+library(foreign)
+library(ggplot2)
+library(readstata13)
+library(dplyr)
+library(haven)
+library(xtable)
+library(stargazer)
+library(tidytext)
+library(stringr) 
+library(tidyr)
+library(wordcloud)
+library(scales)
+library(tables)
+library(ggpubr)
+library(lubridate)
+library(scales)
+library(DescTools)
+library(ggeffects)
+library(tidyverse)
+library(egg)
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# APPENDIX A
+
+## Figure A1. Content analysis results of reality/game programs aired 2015-2017.
+
+
+load("contentanalysis.rdata")
+
+ca$ordinary <- as.factor(ca$ordinary)
+ca$economicbenefit <- as.factor(ca$economicbenefit)
+ca$hardwork <- as.factor(ca$hardwork)
+
+ca$ordinary <- factor(ca$ordinary,
+                      levels = c(0,1,2),
+                      labels = c("Celebrity", "Professional", "Everyman"))
+
+
+ca$economicbenefit <- factor(ca$economicbenefit, 
+                             levels = c(0,1,2),
+                             labels = c("None/trivial", "Modest", "Significant"))
+
+ca$hardwork <- factor(ca$hardwork, 
+                      levels = c(0,1,2),
+                      labels = c("Not much effort", "Some effort", "A lot of effort"))
+
+
+ordinary.pct = ca %>% group_by(ordinary) %>% 
+  dplyr::summarise(count = n())  %>%
+  mutate(pct=count/sum(count)) 
+
+econ.pct = ca %>% group_by(economicbenefit) %>% 
+  dplyr::summarise(count = n())  %>%
+  mutate(pct=count/sum(count)) 
+hardwork.pct = ca %>% group_by(hardwork) %>% 
+  dplyr::summarise(count = n())  %>%
+  mutate(pct=count/sum(count)) 
+
+ordinary.pct$ordinary <- factor(ordinary.pct$ordinary , levels=c("Celebrity", "Professional", "Everyman"))
+
+
+p1 <- ggplot(ordinary.pct, aes(x=ordinary, y=pct*100, fill=ordinary)) +
+  geom_bar(stat="identity", width = 0.4,  position=position_dodge(0.1)) + 
+  theme(aspect.ratio = 1) +
+  scale_fill_manual(values = c("Celebrity" = "#214D72", "Professional" = "#2C7695", "Everyman"="#50BFC3")) +
+  scale_y_continuous(limits=c(0,100)) +  
+  geom_text(data=ordinary.pct, aes(label=paste0(round(pct*100,1),"%"), y=pct*100+3), size=4) +
+  ylab("Percent") + xlab("") + 
+  ggtitle("Type of People") + theme_minimal() + theme(legend.position="none")  +
+  theme(legend.title = element_blank()) + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_text(color= "black", size=12),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+ordinary.pct$ordinary <- factor(ordinary.pct$ordinary , levels=c("Celebrity", "Professional", "Everyman"))
+
+econ.pct$economicbenefit <- factor(econ.pct$economicbenefit, levels=c("None/trivial", "Modest", "Significant"))
+
+p2 <- ggplot(econ.pct, aes(x=economicbenefit, y=pct*100, fill=economicbenefit)) +
+  geom_bar(stat="identity", width = 0.4,  position=position_dodge(0.1)) + theme(aspect.ratio = 1) +
+  scale_fill_manual(values = c("None/trivial" = "#214D72", "Modest" = "#2C7695", "Significant"="#50BFC3" )) +
+  scale_y_continuous(limits=c(0,100)) +
+  geom_text(data=econ.pct, aes(label=paste0(round(pct*100,1),"%"), y=pct*100+3), size=4) +
+  ylab("") + xlab("") + 
+  ggtitle("Degree of Economic Benefit") + theme_minimal() + theme(legend.position="none") +
+  theme(legend.title = element_blank()) + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_blank(),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+hardwork.pct$hardwork <- factor(hardwork.pct$hardwork, levels=c("Not much effort", "Some effort", "A lot of effort"))
+
+p3 <- ggplot(hardwork.pct, aes(x=hardwork, y=pct*100, fill=hardwork)) +
+  geom_bar(stat="identity", width = 0.4,  position=position_dodge(0.1)) + theme(aspect.ratio = 1) +
+  scale_fill_manual(values = c("Not much effort" = "#214D72", "Some effort" = "#2C7695", "A lot of effort"="#50BFC3")) +
+  scale_y_continuous(limits=c(0,100)) +  
+  geom_text(data=hardwork.pct, aes(label=paste0(round(pct*100,1),"%"), y=pct*100+3), size=4) +
+  ylab("") + xlab("") + 
+  ggtitle("Amount of Hard Work/Effort") + theme_minimal() + theme(legend.position="none") +
+  theme(legend.title = element_blank()) + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_blank(),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+#jpeg("contentanalysis.jpeg", units="in", width=12, height=4.5, res=300)
+
+egg::ggarrange(p1, p2, p3,nrow = 1)
+
+#dev.off()
+
+
+
+## Table A1.  Full Coding Results for a Random Subset of Competitive Reality/Game Shows
+
+load("tvcoding.rdata")
+
+first <- CohenKappa(tvcoding$ordinary1,  tvcoding$ordinary2, weights = c("Unweighted"))
+second <- CohenKappa(tvcoding$benefit1,  tvcoding$benefit2, weights = c("Unweighted"))
+third <- CohenKappa(tvcoding$hardwork1,  tvcoding$hardwork2, weights = c("Unweighted"))
+          
+# Cohen's Kappa (unweighted) for the first category 
+round(first, digits=3)
+           
+# Cohen's Kappa (unweighted) for the second category  
+round(second, digits=3)
+
+# Cohen's Kappa (unweighted) for the third category  
+round(third, digits=3)
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX B
+
+## Figure B1. Relative Share of news shows and reality/game shows over time (1960-2017)
+
+load("imdb.rdata")
+
+p <- ggplot(imdb, aes(x = year, y = value,fill = variable),
+            scale_fill_manual(breaks = c("news", "realitygame"), values =c("#24345A", "#2B8D9C"))) +
+  scale_x_continuous(breaks=seq(1960,2018,4)) +
+  scale_y_continuous(breaks=seq(0,0.7,0.05)) +
+  xlab("Year") + ylab("% of TV Shows by Genre") + 
+  geom_jitter(size=2, aes(colour=variable), alpha=1) + 
+  scale_color_manual(breaks = c("news", "realitygame"), values =c("#24345A", "#2B8D9C")) + 
+  geom_smooth(aes(x=year, y=value, color=as.factor(variable)))  +
+  scale_fill_manual(breaks = c("news", "realitygame"), values =c("#24345A", "#2B8D9C")) +
+  theme_minimal() + 
+  theme(legend.title = element_blank(), legend.position = "none") + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_text(color= "black", size=12),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+p <- p +   theme(legend.position = "none") + 
+  ggplot2::annotate("text", x = 1995, y = 0.13, fontface=2, size=4, 
+                    label = "REALITY/GAME", color="#2B8D9C") +
+  ggplot2::annotate("text", x = 2012, y = 0.05, fontface=2, size=4, 
+                    label = "NEWS", color= "#24345A") +
+  theme(panel.grid.minor = element_blank(), 
+        panel.grid.major = element_line(color = "gray50", size = 0.1),
+        panel.grid.major.x = element_blank(),
+        panel.background = element_blank(),
+        axis.line.x = element_line(size = 0.1, linetype = "solid", colour = "gray50"))
+
+
+
+#jpeg("imdbplot.jpeg", units="in", width=10, height=6, res=300)
+
+p
+
+#dev.off()
+
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# APPENDIX E
+
+## Table E1. Program-Level Entertainment Media Consumption Patterns
+
+
+load("ssi.rdata")
+
+tv <- ssi %>% 
+  dplyr::summarise( tv1=mean(tv_americagottalent)*100, 
+                    tv2=mean(tv_nflcbs)*100,
+                    tv3=mean(tv_sundayfootball)*100,
+                    tv4=mean(tv_foxnfl)*100,
+                    tv5=mean(tv_sharktank)*100,
+                    tv6 = mean(tv_hellkitchen)*100,
+                    tv7 = mean(tv_voice)*100, 
+                    tv8 = mean(tv_idol)*100,
+                    tv9 = mean(tv_ninja)*100,
+                    tv10 = mean(tv_masterchef)*100,
+                    tv11 = mean(tv_celebrityfamily)*100,
+                    tv12 = mean(tv_survivor)*100,
+                    tv13 = mean(tv_mlbfox)*100,
+                    tv14 = mean(tv_collegefootball)*100,
+                    tv15 = mean(tv_youcandance)*100,
+                    tv16 = mean(tv_amazingrace)*100,
+                    tv17 = mean(tv_collegebasketball)*100,
+                    tv18 = mean(tv_nbaprimetime)*100,
+                    tv19 = mean(tv_kardashians)*100,
+                    tv20 = mean(tv_nascar)*100,
+                    tv21 = mean(tv_bachelor)*100,
+                    tv22 = mean(tv_bachelorette)*100,
+                    tv23 = mean(tv_jerseyshore)*100,
+                    tv24 = mean(tv_housewives)*100,
+                    tv25 = mean(tv_ufc)*100,
+                    tv26 = mean(tv_worldofdance)*100,
+                    tv27 = mean(tv_lovehiphop)*100,
+                    tv28 = mean(tv_cbssports)*100,
+                    tv29 = mean(tv_battlebots)*100,
+                    tv30 = mean(tv_loveconnection)*100 ) 
+
+m <- as.data.frame(t(tv))
+
+colnames(m) <- c('prop')
+
+m$prop<- round(m$prop, digits=1)
+m$tv <- c("America's Got Talent", "NFL on CBS", "Sunday Night Football", 
+         "Fox NFL Sunday", "Shark Tank", "Hell's Kichen", "Voice", "American Idol",
+         "American Ninja Warrior", "MasterChef", "Celebrity Family Feud", "Survivor",
+         "MLB on Fox", "Colege Football Today", "So You Think You Can Dance", "Amazing Race",
+         "College Bastketball on CBS", "NBA Saturday Primetime", "Keeping Up with Kardashians",
+         "NASCAR on Fox", "Bachelor", "Bachelorette", "Jersey Shore", "The Real Housewives", "UFC Fight Night",
+         "World of Dance", "Love and Hip Hop: Hollywood", "CBS Sports Spectaular", "BattleBots", "Love Connection")
+
+m
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# APPENDIX F 
+
+## Table F1. 
+
+load("ssi.rdata")
+
+m1 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+m3 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m4 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+m5 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m6 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+
+table <- capture.output({stargazer(m1, m2, m3, m4, m5, m6, 
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+## Table F2. 
+
+m2_conti <- lm(mindex_rsc ~ realitytv + othertv  + sportstv + rep + dem +
+                 education_n + income_n + married + female + age + 
+                 white + unemployed + polinterst + religion_attend +
+                 protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+                 +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+table <- capture.output({stargazer(m2_conti,  
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+## Table F3. The Impact of Watching Rags-to-Riches Programs By Level of Political Interest
+
+load("ssi.rdata")
+
+plow <- lm(mindex_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+             education_n + income_n + married + female + age + 
+             white + unemployed  + religion_attend +
+             protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+             absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==0,])
+
+
+phigh <- lm(mindex_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+              education_n + income_n + married + female + age + 
+              white + unemployed  + religion_attend +
+              protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+              absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==1,])
+
+
+plow_i <- lm(internalatt_rsc~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+               education_n + income_n + married + female + age + 
+               white + unemployed  + religion_attend +
+               protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+               absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==0,])
+
+
+phigh_i <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+                education_n + income_n + married + female + age + 
+                white + unemployed  + religion_attend +
+                protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+                absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==1,])
+
+plow_e <- lm(externalatt_rsc~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+               education_n + income_n + married + female + age + 
+               white + unemployed  + religion_attend +
+               protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+               absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==0,])
+
+
+phigh_e <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+                education_n + income_n + married + female + age + 
+                white + unemployed  + religion_attend +
+                protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+                absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==1,])
+
+
+table <- capture.output({stargazer(plow, phigh, plow_i, phigh_i, plow_e, phigh_e,   
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENIDX G  
+
+
+## Table G1, Columns (1) to (3) 
+
+
+load("anes2016.rdata")
+
+# ANES 2016 
+
+aw <- lm(mobilityindex_rsc ~ realitynew + rep  + dem  + ideo_conserv + white + educat3 +
+           female + income + agecat13 + married + bornagain + outofwork +
+           wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger , 
+         data=anes2016, weights=V160102)
+
+awr <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$rep==1,], weights=V160102)
+
+awd <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$dem==1,], weights=V160102)
+
+
+table <- capture.output({stargazer(aw, awr, awd,    
+                                   column.labels = c('All', 'Rep','Dem'),
+                                   column.separate = c(1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('PPSTATEN_11', 'ideo_conserv', "white", "educat3", "female", "income", "agecat13",
+                                            "married", "bornagain", "outofwork", "wrongdirection", "econbetterthanlastyear",
+                                            "unemployment_worse", "incomegap_larger", "rep", "dem", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="text") 
+})
+#table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+## Table G1, Columns (4) to (6) 
+
+# iscap 
+
+load("iscap.rdata")
+
+ia <- lm(mobility_rsc ~ combined + 
+           newscount_w8_new + 
+           rep_11 + dem_11 +  
+           ideo_11_rsc +  age + 
+           female_11 +  income +  
+           married_11 + white_11 + 
+           educ_11 +  protestant +  
+           unemployed_11 +  socio_11_rsc + 
+           PPMSACAT_11 + sjs_mean_rsc, 
+         data=iscap, weights=weight1_11) 
+
+
+
+iar  <- lm(mobility_rsc ~ combined +  newscount_w8_new  +  
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 + white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$rep_11==1,], weights=weight1_11) 
+
+
+iad  <- lm(mobility_rsc ~ combined +  newscount_w8_new  + 
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 +  white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$dem_11==1,], weights=weight1_11) 
+
+
+table <- capture.output({stargazer( ia, iar, iad,  
+                                   column.labels = c( 'All', 'Rep','Dem'),
+                                   column.separate = c( 1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('newscount_w8_new', 'rep_11', "dem_11", "ideo_11_rsc", "age",
+                                             'female_11', "income", "married_11", "white_11",
+                                            'educ_11', "protestant", "unemployed_11", "socio_11_rsc", 
+                                            "PPMSACAT_11", "sjs_mean_rsc", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENIDX H 
+
+# Table H1. Columns (1) to (4) 
+
+load("anes2016.rdata")
+
+
+aw <- lm(mobilityindex_rsc ~ realitynew + rep  + dem  + ideo_conserv + white + educat3 +
+           female + income + agecat13 + married + bornagain + outofwork +
+           wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger , 
+         data=anes2016, weights=V160102)
+
+awr <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$rep==1,], weights=V160102)
+
+awd <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$dem==1,], weights=V160102)
+
+
+awi <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$ind==1,], weights=V160102)
+
+table <- capture.output({stargazer(aw, awr, awd, awi,     
+                                   column.labels = c('All', 'Rep','Dem', "Ind"),
+                                   column.separate = c(1, 1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('PPSTATEN_11', 'ideo_conserv', "white", "educat3", "female", "income", "agecat13",
+                                            "married", "bornagain", "outofwork", "wrongdirection", "econbetterthanlastyear",
+                                            "unemployment_worse", "incomegap_larger", "rep", "dem", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="text") 
+})
+#table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# Table H1. Columns (5) to (8) 
+
+
+load("iscap.rdata")
+
+
+ia <- lm(mobility_rsc ~ combined +  newscount_w8_new + 
+           rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 + white_11 + 
+           educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 + sjs_mean_rsc, 
+         data=iscap, weights=weight1_11) 
+
+iar  <- lm(mobility_rsc ~ combined +  newscount_w8_new  +  
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 + white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$rep_11==1,], weights=weight1_11) 
+
+
+iad  <- lm(mobility_rsc ~ combined +  newscount_w8_new  + 
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 + income +  married_11 +  white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$dem_11==1,], weights=weight1_11) 
+
+
+iai  <- lm(mobility_rsc ~ combined +  newscount_w8_new  + 
+              ideo_11_rsc +  age +  female_11 +  income +  married_11 +  white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$ind_11==1,], weights=weight1_11) 
+
+
+table <- capture.output({stargazer( ia, iar, iad,  iai, 
+                                    column.labels = c( 'All', 'Rep','Dem', "Ind"),
+                                    column.separate = c( 1, 1, 1),
+                                    dep.var.caption = "",
+                                    omit.stat=c("adj.rsq","LL","ser","f"),
+                                    omit = c('newscount_w8_new', 'rep_11', "dem_11", "ideo_11_rsc", "age",
+                                             'female_11', "income", "married_11", "white_11",
+                                             'educ_11', "protestant", "unemployed_11", "socio_11_rsc", 
+                                             "PPMSACAT_11", "sjs_mean_rsc", "Constant") , 
+                                    star.cutoffs = c(0.1, .05,.01,.001),
+                                    no.space=TRUE,
+                                    star.char = c("+", "*", "**", "***"), 
+                                    notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                    notes.append = F,
+                                    notes.align="l",
+                                    digits=3,
+                                    align = TRUE, 
+                                    type="text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+
+
+
+## Table H2 2018 Media and Culture Survey Results by Party ID
+
+load("ssi.rdata")
+
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem + 
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+
+m2r <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv +
+            education_n + income_n + married + female + age + 
+            white + unemployed + polinterst + religion_attend +
+            protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+            +absolutemobility + gini + as.factor(state_n) , data=ssi[ssi$rep==1,]) 
+
+m2d <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv +
+            education_n + income_n + married + female + age + 
+            white + unemployed + polinterst + religion_attend +
+            protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+            +absolutemobility + gini + as.factor(state_n) , data=ssi[ssi$dem==1,]) 
+
+
+m2i <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv +
+            education_n + income_n + married + female + age + 
+            white + unemployed + polinterst + religion_attend +
+            protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+            +absolutemobility + gini + as.factor(state_n) , data=ssi[ssi$ind==1,]) 
+
+
+
+table <- capture.output({stargazer(m2, m2r, m2d, m2i,  
+                                   column.labels = c('All', 'Rep','Dem', 'Ind'), 
+                                   column.separate = c(1, 1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n', "othertv", "sportstv", "education_n", "income_n", "married", "female", "age",
+                                   "white", "unemployed", "polinterst", "religion_attend", "protestant", "optimismindex", "insecurity",
+                                   "intergenmobility", "parentsimmigrant", "absolutemobility", "gini", "Constant", "rep", "dem") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "ssi2018",
+                                   title = "ssi2018", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX K 
+
+
+load("combined.rdata")
+
+# manipulation check
+
+# person featured on the show profitted a lot financially
+t.test(combined$m1_rsc ~ combined$condition2)
+# likely to have a higher income from now 
+t.test(combined$m2_rsc ~ combined$condition2)
+# has a good work ethic
+t.test(combined$m3_rsc ~ combined$condition2)
+# showed that people can succeed when they are willing to work hard 
+t.test(combined$m4_rsc ~ combined$condition2)
+# liked the program 
+t.test(combined$like ~ combined$condition2)
+# thought the program was entertaining
+t.test(combined$entertaining ~ combined$condition2)
+
+
+## Table K1. Heterogeneous Treatment Effects by System Justification Tendency
+
+
+j <-  lm(mperception_combined ~ condition2*sjs_high + pid + optimism_index + date + as.factor(surveymode_n), 
+           data=combined)
+
+table <- capture.output({stargazer(j, 
+                                   covariate.labels = c('Rags-to-Riches TV Treatment', "System Justification Scale - High", "Party ID",
+                                                        "Optimism Index", "Treatment x System Justification Scale"),
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('surveymode_n', 'date') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "experiment",
+                                   title = "Heterogeneous Treatment Effects by SJS", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX L 
+
+# Table L1. The impact of merit-based rags-to-riches TV on redistribution-related attitudes
+
+load("merit.rdata")
+
+m1 <- lm( dv3_rich_rcd ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+m2 <- lm( dv3_poor_rcd ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+m3 <- lm( dv4_inequality_rsc ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+m4 <- lm( antigov2 ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+
+table <- capture.output({stargazer(m1, m2,  m3,  m4,   
+                                   dep.var.labels= c('The rich works hard',
+                                                     'The poor lacks efforts',
+                                                     'Inequality is desirable',
+                                                     'Anti-redistribution'),
+                                   covariate.labels = c('Meritocracy Treatment'),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('surveymode_n', 'date_n', 'durationinseconds', 'rep', 'dem', 'Constant') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "main",
+                                   title = "The Casual Effect of Merit-Based Rags-to-Riches TV", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type = "text") 
+})
+
+#%table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX M
+# Figure M1
+
+load("gss.rdata")
+
+
+fit <- lm(getahead_new~ tv_dummy*as.factor(year) + news + polviews + pid3 + 
+            age + income + as.factor(race) + educ + sex, data = gss, weights=gss$wtssall)
+
+dat <- ggpredict(fit, terms = c("year", "tv_dummy"))
+dat$year <- as.Date(as.character(dat$x), format = "%Y")
+dat$year <- year(dat$year)
+
+
+p1 <- ggplot(dat, aes(x=year, y=predicted, color=group, shape=group)) +
+  geom_smooth(span=1.2, se=T, alpha=0.2, aes(fill=group)) + scale_fill_manual(name='group', values=c("black", "#00A7A3"))+ geom_point() +    scale_shape_manual(values = c(4, 11)) + 
+  theme_minimal()  +  theme(legend.position="top") +  guides(shape = FALSE, fill=F) + 
+  xlab("Year") + 
+  ylab("people can get ahead by working hard")  + scale_x_continuous(breaks=seq(1970,2020,4)) +
+  scale_y_continuous(breaks=scales::pretty_breaks(n=4)) + 
+  scale_color_manual(values=c("#214455", "#00A7A3", "grey40"), name="Overall TV Consumption", labels=c("Low", "High")) +
+  theme(axis.text.x = element_text(colour = "black", size=15), 
+        axis.title.x = element_text(size=15), 
+        axis.text.y=element_text(colour = "black", size=15), 
+        legend.text=element_text(size=16, face="bold"), legend.title=element_text(size=16, face="bold"),
+        axis.title.y = element_text(size=18), panel.grid.minor.x = element_blank(), panel.grid.minor.y=element_blank()) 
+p1 
+
+#pdf('gss_timetrend_new.pdf',height=6,width=8)
+#p1
+#dev.off()
+

25/replication_package/AJPS_2021_Kim_Appendix_RMarkdown.Rmd

@@ -0,0 +1,777 @@
+---
+title: "AJPS_2021_Kim_Appendix_Markdown"
+subtitle: "Entertaining Beliefs in Economic Mobility"
+author: "Eunji Kim"
+date: "8/15/2021"
+output: html_document
+---
+
+```{r, message=F, warning=F, echo=F}
+# Load libraries
+rm(list=ls())  
+library(foreign)
+library(ggplot2)
+library(readstata13)
+library(dplyr)
+library(haven)
+library(xtable)
+library(stargazer)
+library(tidytext)
+library(stringr) 
+library(tidyr)
+library(wordcloud)
+library(scales)
+library(tables)
+library(ggpubr)
+library(lubridate)
+library(scales)
+library(DescTools)
+library(ggeffects)
+library(tidyverse)
+library(egg)
+
+```
+
+
+
+```{r,  warning=F, message=F, results="asis"}
+
+
+# APPENDIX A
+
+## Figure A1. Content analysis results of reality/game programs aired 2015-2017.
+
+
+load("contentanalysis.rdata")
+
+ca$ordinary <- as.factor(ca$ordinary)
+ca$economicbenefit <- as.factor(ca$economicbenefit)
+ca$hardwork <- as.factor(ca$hardwork)
+
+ca$ordinary <- factor(ca$ordinary,
+                      levels = c(0,1,2),
+                      labels = c("Celebrity", "Professional", "Everyman"))
+
+
+ca$economicbenefit <- factor(ca$economicbenefit, 
+                             levels = c(0,1,2),
+                             labels = c("None/trivial", "Modest", "Significant"))
+
+ca$hardwork <- factor(ca$hardwork, 
+                      levels = c(0,1,2),
+                      labels = c("Not much effort", "Some effort", "A lot of effort"))
+
+
+ordinary.pct = ca %>% group_by(ordinary) %>% 
+  dplyr::summarise(count = n())  %>%
+  mutate(pct=count/sum(count)) 
+
+econ.pct = ca %>% group_by(economicbenefit) %>% 
+  dplyr::summarise(count = n())  %>%
+  mutate(pct=count/sum(count)) 
+hardwork.pct = ca %>% group_by(hardwork) %>% 
+  dplyr::summarise(count = n())  %>%
+  mutate(pct=count/sum(count)) 
+
+ordinary.pct$ordinary <- factor(ordinary.pct$ordinary , levels=c("Celebrity", "Professional", "Everyman"))
+
+
+p1 <- ggplot(ordinary.pct, aes(x=ordinary, y=pct*100, fill=ordinary)) +
+  geom_bar(stat="identity", width = 0.4,  position=position_dodge(0.1)) + 
+  theme(aspect.ratio = 1) +
+  scale_fill_manual(values = c("Celebrity" = "#214D72", "Professional" = "#2C7695", "Everyman"="#50BFC3")) +
+  scale_y_continuous(limits=c(0,100)) +  
+  geom_text(data=ordinary.pct, aes(label=paste0(round(pct*100,1),"%"), y=pct*100+3), size=4) +
+  ylab("Percent") + xlab("") + 
+  ggtitle("Type of People") + theme_minimal() + theme(legend.position="none")  +
+  theme(legend.title = element_blank()) + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_text(color= "black", size=12),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+ordinary.pct$ordinary <- factor(ordinary.pct$ordinary , levels=c("Celebrity", "Professional", "Everyman"))
+
+econ.pct$economicbenefit <- factor(econ.pct$economicbenefit, levels=c("None/trivial", "Modest", "Significant"))
+
+p2 <- ggplot(econ.pct, aes(x=economicbenefit, y=pct*100, fill=economicbenefit)) +
+  geom_bar(stat="identity", width = 0.4,  position=position_dodge(0.1)) + theme(aspect.ratio = 1) +
+  scale_fill_manual(values = c("None/trivial" = "#214D72", "Modest" = "#2C7695", "Significant"="#50BFC3" )) +
+  scale_y_continuous(limits=c(0,100)) +
+  geom_text(data=econ.pct, aes(label=paste0(round(pct*100,1),"%"), y=pct*100+3), size=4) +
+  ylab("") + xlab("") + 
+  ggtitle("Degree of Economic Benefit") + theme_minimal() + theme(legend.position="none") +
+  theme(legend.title = element_blank()) + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_blank(),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+hardwork.pct$hardwork <- factor(hardwork.pct$hardwork, levels=c("Not much effort", "Some effort", "A lot of effort"))
+
+p3 <- ggplot(hardwork.pct, aes(x=hardwork, y=pct*100, fill=hardwork)) +
+  geom_bar(stat="identity", width = 0.4,  position=position_dodge(0.1)) + theme(aspect.ratio = 1) +
+  scale_fill_manual(values = c("Not much effort" = "#214D72", "Some effort" = "#2C7695", "A lot of effort"="#50BFC3")) +
+  scale_y_continuous(limits=c(0,100)) +  
+  geom_text(data=hardwork.pct, aes(label=paste0(round(pct*100,1),"%"), y=pct*100+3), size=4) +
+  ylab("") + xlab("") + 
+  ggtitle("Amount of Hard Work/Effort") + theme_minimal() + theme(legend.position="none") +
+  theme(legend.title = element_blank()) + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_blank(),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+#jpeg("contentanalysis.jpeg", units="in", width=12, height=4.5, res=300)
+
+egg::ggarrange(p1, p2, p3,nrow = 1)
+
+#dev.off()
+
+
+
+
+## Table A1.  Full Coding Results for a Random Subset of Competitive Reality/Game Shows
+
+load("tvcoding.rdata")
+
+first <- CohenKappa(tvcoding$ordinary1,  tvcoding$ordinary2, weights = c("Unweighted"))
+second <- CohenKappa(tvcoding$benefit1,  tvcoding$benefit2, weights = c("Unweighted"))
+third <- CohenKappa(tvcoding$hardwork1,  tvcoding$hardwork2, weights = c("Unweighted"))
+          
+# Cohen's Kappa (unweighted) for the first category 
+round(first, digits=3)
+           
+# Cohen's Kappa (unweighted) for the second category  
+round(second, digits=3)
+
+# Cohen's Kappa (unweighted) for the third category  
+round(third, digits=3)
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX B
+
+## Figure B1. Relative Share of news shows and reality/game shows over time (1960-2017)
+
+load("imdb.rdata")
+
+p <- ggplot(imdb, aes(x = year, y = value,fill = variable),
+            scale_fill_manual(breaks = c("news", "realitygame"), values =c("#24345A", "#2B8D9C"))) +
+  scale_x_continuous(breaks=seq(1960,2018,4)) +
+  scale_y_continuous(breaks=seq(0,0.7,0.05)) +
+  xlab("Year") + ylab("% of TV Shows by Genre") + 
+  geom_jitter(size=2, aes(colour=variable), alpha=1) + 
+  scale_color_manual(breaks = c("news", "realitygame"), values =c("#24345A", "#2B8D9C")) + 
+  geom_smooth(aes(x=year, y=value, color=as.factor(variable)))  +
+  scale_fill_manual(breaks = c("news", "realitygame"), values =c("#24345A", "#2B8D9C")) +
+  theme_minimal() + 
+  theme(legend.title = element_blank(), legend.position = "none") + 
+  theme(axis.title.x = element_text(color="black", size=14, face="bold"),
+        axis.text.y = element_text(color= "black", size=12),
+        axis.text.x = element_text(color= "black", size=12),
+        axis.title.y = element_text(color="black", size=14, face="bold"),
+        plot.title = element_text(size = 14, face="bold"))
+
+p <- p +   theme(legend.position = "none") + 
+  ggplot2::annotate("text", x = 1995, y = 0.13, fontface=2, size=4, 
+                    label = "REALITY/GAME", color="#2B8D9C") +
+  ggplot2::annotate("text", x = 2012, y = 0.05, fontface=2, size=4, 
+                    label = "NEWS", color= "#24345A") +
+  theme(panel.grid.minor = element_blank(), 
+        panel.grid.major = element_line(color = "gray50", size = 0.1),
+        panel.grid.major.x = element_blank(),
+        panel.background = element_blank(),
+        axis.line.x = element_line(size = 0.1, linetype = "solid", colour = "gray50"))
+
+
+
+#jpeg("imdbplot.jpeg", units="in", width=10, height=6, res=300)
+
+p
+
+#dev.off()
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX E
+
+## Table E1. Program-Level Entertainment Media Consumption Patterns
+
+
+load("ssi.rdata")
+
+tv <- ssi %>% 
+  dplyr::summarise( tv1=mean(tv_americagottalent)*100, 
+                    tv2=mean(tv_nflcbs)*100,
+                    tv3=mean(tv_sundayfootball)*100,
+                    tv4=mean(tv_foxnfl)*100,
+                    tv5=mean(tv_sharktank)*100,
+                    tv6 = mean(tv_hellkitchen)*100,
+                    tv7 = mean(tv_voice)*100, 
+                    tv8 = mean(tv_idol)*100,
+                    tv9 = mean(tv_ninja)*100,
+                    tv10 = mean(tv_masterchef)*100,
+                    tv11 = mean(tv_celebrityfamily)*100,
+                    tv12 = mean(tv_survivor)*100,
+                    tv13 = mean(tv_mlbfox)*100,
+                    tv14 = mean(tv_collegefootball)*100,
+                    tv15 = mean(tv_youcandance)*100,
+                    tv16 = mean(tv_amazingrace)*100,
+                    tv17 = mean(tv_collegebasketball)*100,
+                    tv18 = mean(tv_nbaprimetime)*100,
+                    tv19 = mean(tv_kardashians)*100,
+                    tv20 = mean(tv_nascar)*100,
+                    tv21 = mean(tv_bachelor)*100,
+                    tv22 = mean(tv_bachelorette)*100,
+                    tv23 = mean(tv_jerseyshore)*100,
+                    tv24 = mean(tv_housewives)*100,
+                    tv25 = mean(tv_ufc)*100,
+                    tv26 = mean(tv_worldofdance)*100,
+                    tv27 = mean(tv_lovehiphop)*100,
+                    tv28 = mean(tv_cbssports)*100,
+                    tv29 = mean(tv_battlebots)*100,
+                    tv30 = mean(tv_loveconnection)*100 ) 
+
+m <- as.data.frame(t(tv))
+
+colnames(m) <- c('prop')
+
+m$prop<- round(m$prop, digits=1)
+m$tv <- c("America's Got Talent", "NFL on CBS", "Sunday Night Football", 
+         "Fox NFL Sunday", "Shark Tank", "Hell's Kichen", "Voice", "American Idol",
+         "American Ninja Warrior", "MasterChef", "Celebrity Family Feud", "Survivor",
+         "MLB on Fox", "Colege Football Today", "So You Think You Can Dance", "Amazing Race",
+         "College Bastketball on CBS", "NBA Saturday Primetime", "Keeping Up with Kardashians",
+         "NASCAR on Fox", "Bachelor", "Bachelorette", "Jersey Shore", "The Real Housewives", "UFC Fight Night",
+         "World of Dance", "Love and Hip Hop: Hollywood", "CBS Sports Spectaular", "BattleBots", "Love Connection")
+
+m
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# APPENDIX F 
+
+## Table F1. 
+
+load("ssi.rdata")
+
+m1 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+m3 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m4 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+m5 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m6 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+
+table <- capture.output({stargazer(m1, m2, m3, m4, m5, m6, 
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+## Table F2. 
+
+m2_conti <- lm(mindex_rsc ~ realitytv + othertv  + sportstv + rep + dem +
+                 education_n + income_n + married + female + age + 
+                 white + unemployed + polinterst + religion_attend +
+                 protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+                 +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+table <- capture.output({stargazer(m2_conti,  
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+## Table F3. The Impact of Watching Rags-to-Riches Programs By Level of Political Interest
+
+load("ssi.rdata")
+
+plow <- lm(mindex_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+             education_n + income_n + married + female + age + 
+             white + unemployed  + religion_attend +
+             protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+             absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==0,])
+
+
+phigh <- lm(mindex_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+              education_n + income_n + married + female + age + 
+              white + unemployed  + religion_attend +
+              protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+              absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==1,])
+
+
+plow_i <- lm(internalatt_rsc~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+               education_n + income_n + married + female + age + 
+               white + unemployed  + religion_attend +
+               protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+               absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==0,])
+
+
+phigh_i <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+                education_n + income_n + married + female + age + 
+                white + unemployed  + religion_attend +
+                protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+                absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==1,])
+
+plow_e <- lm(externalatt_rsc~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+               education_n + income_n + married + female + age + 
+               white + unemployed  + religion_attend +
+               protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+               absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==0,])
+
+
+phigh_e <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer+ heavyviewer + othertv + sportstv + rep + dem +
+                education_n + income_n + married + female + age + 
+                white + unemployed  + religion_attend +
+                protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+                absolutemobility + gini + as.factor(state_n), data=ssi[ssi$polinterest_high==1,])
+
+
+table <- capture.output({stargazer(plow, phigh, plow_i, phigh_i, plow_e, phigh_e,   
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# APPENIDX G  
+
+
+## Table G1, Columns (1) to (3) 
+
+
+load("anes2016.rdata")
+
+# ANES 2016 
+
+aw <- lm(mobilityindex_rsc ~ realitynew + rep  + dem  + ideo_conserv + white + educat3 +
+           female + income + agecat13 + married + bornagain + outofwork +
+           wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger , 
+         data=anes2016, weights=V160102)
+
+awr <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$rep==1,], weights=V160102)
+
+awd <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$dem==1,], weights=V160102)
+
+
+table <- capture.output({stargazer(aw, awr, awd,    
+                                   column.labels = c('All', 'Rep','Dem'),
+                                   column.separate = c(1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('PPSTATEN_11', 'ideo_conserv', "white", "educat3", "female", "income", "agecat13",
+                                            "married", "bornagain", "outofwork", "wrongdirection", "econbetterthanlastyear",
+                                            "unemployment_worse", "incomegap_larger", "rep", "dem", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="html") 
+})
+#table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+## Table G1, Columns (4) to (6) 
+
+# iscap 
+
+load("iscap.rdata")
+
+ia <- lm(mobility_rsc ~ combined + 
+           newscount_w8_new + 
+           rep_11 + dem_11 +  
+           ideo_11_rsc +  age + 
+           female_11 +  income +  
+           married_11 + white_11 + 
+           educ_11 +  protestant +  
+           unemployed_11 +  socio_11_rsc + 
+           PPMSACAT_11 + sjs_mean_rsc, 
+         data=iscap, weights=weight1_11) 
+
+
+
+iar  <- lm(mobility_rsc ~ combined +  newscount_w8_new  +  
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 + white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$rep_11==1,], weights=weight1_11) 
+
+
+iad  <- lm(mobility_rsc ~ combined +  newscount_w8_new  + 
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 +  white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$dem_11==1,], weights=weight1_11) 
+
+
+table <- capture.output({stargazer( ia, iar, iad,  
+                                   column.labels = c( 'All', 'Rep','Dem'),
+                                   column.separate = c( 1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('newscount_w8_new', 'rep_11', "dem_11", "ideo_11_rsc", "age",
+                                             'female_11', "income", "married_11", "white_11",
+                                            'educ_11', "protestant", "unemployed_11", "socio_11_rsc", 
+                                            "PPMSACAT_11", "sjs_mean_rsc", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# Table H1. Columns (1) to (4) 
+
+load("anes2016.rdata")
+
+
+aw <- lm(mobilityindex_rsc ~ realitynew + rep  + dem  + ideo_conserv + white + educat3 +
+           female + income + agecat13 + married + bornagain + outofwork +
+           wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger , 
+         data=anes2016, weights=V160102)
+
+awr <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$rep==1,], weights=V160102)
+
+awd <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$dem==1,], weights=V160102)
+
+
+awi <- lm(mobilityindex_rsc ~ realitynew  + ideo_conserv + white + educat3 +
+            female + income + agecat13 + married + bornagain + outofwork +
+            wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger, 
+          data=anes2016[anes2016$ind==1,], weights=V160102)
+
+table <- capture.output({stargazer(aw, awr, awd, awi,     
+                                   column.labels = c('All', 'Rep','Dem', "Ind"),
+                                   column.separate = c(1, 1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('PPSTATEN_11', 'ideo_conserv', "white", "educat3", "female", "income", "agecat13",
+                                            "married", "bornagain", "outofwork", "wrongdirection", "econbetterthanlastyear",
+                                            "unemployment_worse", "incomegap_larger", "rep", "dem", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="html") 
+})
+#table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+# Table H1. Columns (5) to (8) 
+
+
+load("iscap.rdata")
+
+
+ia <- lm(mobility_rsc ~ combined +  newscount_w8_new + 
+           rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 + white_11 + 
+           educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 + sjs_mean_rsc, 
+         data=iscap, weights=weight1_11) 
+
+iar  <- lm(mobility_rsc ~ combined +  newscount_w8_new  +  
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 + white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$rep_11==1,], weights=weight1_11) 
+
+
+iad  <- lm(mobility_rsc ~ combined +  newscount_w8_new  + 
+             rep_11 + dem_11 +  ideo_11_rsc +  age +  female_11 +  income +  married_11 +  white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$dem_11==1,], weights=weight1_11) 
+
+
+iai  <- lm(mobility_rsc ~ combined +  newscount_w8_new  + 
+               ideo_11_rsc +  age +  female_11 +  income +  married_11 +  white_11 + 
+             educ_11 +  protestant +  unemployed_11 +  socio_11_rsc +  PPMSACAT_11 +  sjs_mean_rsc, data=iscap[iscap$ind_11==1,], weights=weight1_11) 
+
+
+table <- capture.output({stargazer( ia, iar, iad,  iai, 
+                                    column.labels = c( 'All', 'Rep','Dem', "Ind"),
+                                    column.separate = c( 1, 1, 1),
+                                    dep.var.caption = "",
+                                    omit.stat=c("adj.rsq","LL","ser","f"),
+                                    omit = c('newscount_w8_new', 'rep_11', "dem_11", "ideo_11_rsc", "age",
+                                             'female_11', "income", "married_11", "white_11",
+                                             'educ_11', "protestant", "unemployed_11", "ind_11" ,"socio_11_rsc", 
+                                             "PPMSACAT_11", "sjs_mean_rsc", "Constant") , 
+                                    star.cutoffs = c(0.1, .05,.01,.001),
+                                    no.space=TRUE,
+                                    star.char = c("+", "*", "**", "***"), 
+                                    notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                    notes.append = F,
+                                    notes.align="l",
+                                    digits=3,
+                                    align = TRUE, 
+                                    type="html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+## Table H2 2018 Media and Culture Survey Results by Party ID
+load("ssi.rdata")
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem + 
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+
+m2r <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv +
+            education_n + income_n + married + female + age + 
+            white + unemployed + polinterst + religion_attend +
+            protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+            +absolutemobility + gini + as.factor(state_n) , data=ssi[ssi$rep==1,]) 
+
+m2d <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv +
+            education_n + income_n + married + female + age + 
+            white + unemployed + polinterst + religion_attend +
+            protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+            +absolutemobility + gini + as.factor(state_n) , data=ssi[ssi$dem==1,]) 
+
+
+m2i <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv +
+            education_n + income_n + married + female + age + 
+            white + unemployed + polinterst + religion_attend +
+            protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+            +absolutemobility + gini + as.factor(state_n) , data=ssi[ssi$ind==1,]) 
+
+
+
+table <- capture.output({stargazer(m2, m2r, m2d, m2i,  
+                                   column.labels = c('All', 'Rep','Dem', 'Ind'), 
+                                   column.separate = c(1, 1, 1, 1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n', "othertv", "sportstv", "education_n", 
+                                            "income_n", "married", "female", "age",
+                                            "white", "unemployed", "polinterst", "religion_attend", 
+                                            "protestant", "optimismindex", "insecurity",
+                                   "intergenmobility", "parentsimmigrant", "absolutemobility", 
+                                   "gini", "Constant", "rep", "dem") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "ssi2018",
+                                   title = "ssi2018", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+
+
+# APPENDIX K 
+
+
+load("combined.rdata")
+
+# manipulation check
+
+# person featured on the show profitted a lot financially
+t.test(combined$m1_rsc ~ combined$condition2)
+# likely to have a higher income from now 
+t.test(combined$m2_rsc ~ combined$condition2)
+# has a good work ethic
+t.test(combined$m3_rsc ~ combined$condition2)
+# showed that people can succeed when they are willing to work hard 
+t.test(combined$m4_rsc ~ combined$condition2)
+# liked the program 
+t.test(combined$like ~ combined$condition2)
+# thought the program was entertaining
+t.test(combined$entertaining ~ combined$condition2)
+
+
+## Table K1. Heterogeneous Treatment Effects by System Justification Tendency
+
+
+j <-  lm(mperception_combined ~ condition2*sjs_high + pid + optimism_index + date + as.factor(surveymode_n), 
+           data=combined)
+
+table <- capture.output({stargazer(j, 
+                                   covariate.labels = c('Rags-to-Riches TV Treatment', 
+                                                        "System Justification Scale - High", "Party ID",
+                                                        "Optimism Index", "Treatment x System Justification Scale"),
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('surveymode_n', 'date') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "experiment",
+                                   title = "Heterogeneous Treatment Effects by SJS", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX L 
+
+# Table L1. The impact of merit-based rags-to-riches TV on redistribution-related attitudes
+
+load("merit.rdata")
+
+m1 <- lm( dv3_rich_rcd ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+m2 <- lm( dv3_poor_rcd ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+m3 <- lm( dv4_inequality_rsc ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+m4 <- lm( antigov2 ~ condition2 + rep + dem  + as.factor(surveymode_n) + as.factor(date_n) + durationinseconds,data=merit)
+
+table <- capture.output({stargazer(m1, m2,  m3,  m4,   
+                                   dep.var.labels= c('The rich works hard',
+                                                     'The poor lacks efforts',
+                                                     'Inequality is desirable',
+                                                     'Anti-redistribution'),
+                                   covariate.labels = c('Meritocracy Treatment'),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('surveymode_n', 'date_n', 'durationinseconds', 'rep', 'dem', 'Constant') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "main",
+                                   title = "The Casual Effect of Merit-Based Rags-to-Riches TV", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type = "html") 
+})
+
+#%table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# APPENDIX M
+# Figure M1
+
+load("gss.rdata")
+
+
+fit <- lm(getahead_new~ tv_dummy*as.factor(year) + news + polviews + pid3 + 
+            age + income + as.factor(race) + educ + sex, data = gss, weights=gss$wtssall)
+
+dat <- ggpredict(fit, terms = c("year", "tv_dummy"))
+dat$year <- as.Date(as.character(dat$x), format = "%Y")
+dat$year <- year(dat$year)
+
+
+p1 <- ggplot(dat, aes(x=year, y=predicted, color=group, shape=group)) +
+  geom_smooth(span=1.2, se=T, alpha=0.2, aes(fill=group)) + scale_fill_manual(name='group', values=c("black", "#00A7A3"))+ geom_point() +    scale_shape_manual(values = c(4, 11)) + 
+  theme_minimal()  +  theme(legend.position="top") +  guides(shape = FALSE, fill=F) + 
+  xlab("Year") + 
+  ylab("people can get ahead by working hard")  + scale_x_continuous(breaks=seq(1970,2020,4)) +
+  scale_y_continuous(breaks=scales::pretty_breaks(n=4)) + 
+  scale_color_manual(values=c("#214455", "#00A7A3", "grey40"), name="Overall TV Consumption", labels=c("Low", "High")) +
+  theme(axis.text.x = element_text(colour = "black", size=15), 
+        axis.title.x = element_text(size=15), 
+        axis.text.y=element_text(colour = "black", size=15), 
+        legend.text=element_text(size=16, face="bold"), legend.title=element_text(size=16, face="bold"),
+        axis.title.y = element_text(size=18), panel.grid.minor.x = element_blank(), panel.grid.minor.y=element_blank()) 
+p1 
+
+
+```
+

25/replication_package/AJPS_2021_Kim_Manuscript.R

@@ -0,0 +1,330 @@
+
+# --------------------------------------------------------------------------------------------------------------------------------
+# --------------------------------------------------------------------------------------------------------------------------------
+# Entertaining Beliefs in Economic Mobility 
+# Eunji Kim, 2021
+# American Journal of Political Science
+# --------------------------------------------------------------------------------------------------------------------------------
+# --------------------------------------------------------------------------------------------------------------------------------
+
+#list.of.packages <- c("foreign", "ggplot2", "readstata13", "dplyr", "haven", "xtable", "stargazer", "tidytext", "stringr", "tidyr", "scales", "tables", "ggpubr") 
+#new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
+#if(length(new.packages)) install.packages(new.packages)
+
+#setwd("[path to where replication archive was downloaded]")
+
+library(foreign)
+library(ggplot2)
+library(readstata13)
+library(dplyr)
+library(haven)
+library(xtable)
+library(stargazer)
+library(tidytext)
+library(stringr) 
+library(tidyr)
+library(scales)
+library(tables)
+library(ggpubr)
+
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT FIGURE 1 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+load("nyt.rdata")
+
+cleaned_nyt_text %>% 
+  count(year) %>%
+  filter(year != 2020 & year != 1980) %>%
+  ggplot(aes(as.Date(paste(year, "-01", "-01", sep="")), n)) + 
+  geom_col(show.legend = F) + 
+  labs(x = "Year", y = "Number of Articles Containing Keywords",
+       title = "Articles by Year")
+
+
+search_terms <- paste(c('economic mobility', 'social ladder', 'income ladder', 'social mobility', 'economic ladder',
+                        'rags to riches', 'economic mobility', 'social ladder', 'class mobility', 'socioeconomic mobility', 
+                        'intergenerational mobility', 'upward mobility', "meritocracy", "american dream", "land of opportunity",
+                        'rugged individualism', 'horatio alger', 'self-made man', 'self-made woman', 'self-made success'), 
+                      collapse = '|') 
+
+custom_stop_words <- stop_words
+
+cleaned_nyt_text$text <- as.character(cleaned_nyt_text$text)
+
+nyt_words <- cleaned_nyt_text %>%
+  unnest_tokens(word, text) %>%
+  mutate(word = gsub("\u2019", "'", word)) %>% 
+  anti_join(custom_stop_words) 
+
+bing <- get_sentiments('bing')
+
+nyt_polarity_year <- nyt_words %>%
+  inner_join(bing) %>%
+  count(sentiment, Month_Yr) %>%
+  spread(sentiment, n) %>%
+  mutate(polarity = positive - negative,
+         percent_positive = positive / (positive + negative) * 100) %>%
+  filter(!str_detect(Month_Yr, "2020"))
+
+
+nyt_polarity_year$year<- nyt_polarity_year %>% 
+  separate(Month_Yr, into = c("year", "month")) %>% 
+  pull("year")
+
+nyt_polarity_year_2000 <-  nyt_polarity_year %>% filter(year > 1999)
+
+
+polarity_over_time <- nyt_polarity_year_2000 %>%
+  ggplot(aes(as.Date(paste(Month_Yr, "-01", sep="")), 
+             polarity, 
+             color = ifelse(polarity >= 0,  '#86d7c1', '#0e698b'))) +
+  geom_col(position = "identity", 
+           color=ifelse(nyt_polarity_year_2000$polarity>= 0,'#86d7c1', '#0e698b'),
+           fill = ifelse(nyt_polarity_year_2000$polarity>= 0,'#86d7c1', '#0e698b'),
+           size = 0.1, show.legend = F) + 
+  #theme(plot.title = element_text(size = 11), legend.position = "none") + 
+  theme(plot.title = element_text(size = 11), legend.position = "none", 
+        panel.background = element_blank(), 
+        axis.title.x = element_text(color="black", size=10),
+        axis.title.y = element_text(color="black", size=10)) + 
+  theme(axis.text.x = element_text(color="black", size=10),
+        axis.text.y = element_text(color="black", size=10))  + 
+  xlab("Year") + ylab("Sentiment Score")  
+
+# ggtitle("NYT Word Sentiment Polarity Over Time (positive words - negative words per year)")
+
+polarity_over_time 
+
+
+#pdf('nytsentiment.pdf',height=4,width=7)
+#polarity_over_time
+#dev.off()
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT TABLE 1 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# mturk 
+
+load("mturk.rdata")
+
+m1 <-lm(mperception_combined ~ condition2 +  rep + dem  + optimism_index  + sjs_index, data=msample)
+mr <-lm(mperception_combined ~ condition2  + optimism_index  + sjs_index, data=msample[msample$rep==1,])
+md <- lm(mperception_combined ~ condition2  + optimism_index  + sjs_index, data=msample[msample$dem==1,])
+# interaction model 
+mrd <-lm(mperception_combined ~ condition2*rep1dem0new  + optimism_index + sjs_index, data=msample)
+
+# lab in the field 
+# main model 
+
+load("labinthefield.rdata")
+
+f1 <-lm(mperception_combined ~ condition2 + rep + dem + optimism_index + sjs_index +
+          as.factor(surveymode_n) + as.factor(date_n), data=fieldsample)
+fr <-lm(mperception_combined ~ condition2 + rep + dem + optimism_index + sjs_index +
+          as.factor(surveymode_n) + as.factor(date_n), data=fieldsample[fieldsample$rep==1,])
+fd <-lm(mperception_combined ~ condition2 + rep + dem + optimism_index + sjs_index +
+          as.factor(surveymode_n) + as.factor(date_n), data=fieldsample[fieldsample$dem==1,])
+frd <-lm(mperception_combined ~ condition2*rep1dem0new  + optimism_index + sjs_index +
+           as.factor(surveymode_n) + as.factor(date_n), data=fieldsample)
+
+table <- capture.output({stargazer(m1, mr, md, mrd,  f1, fr, fd, frd, 
+                                   dep.var.labels= c(
+                                     "Mturk Sample",
+                                     "Lab-in-the-Field Sample"),
+                                   covariate.labels = c('Rags-to-Riches TV Treatment'),
+                                   column.labels = c('All', 'Rep', 'Dem', 'Interaction Model','All', 'Rep', 'Dem', 'Interaction Model'), 
+                                   column.separate = c(1,1, 1, 1, 1, 1, 1,1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('surveymode_n', 'date_n' ) , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "experiment",
+                                   title = "The Casual Effect of Rags-to-Riches TV", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT TABLE 2 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+
+load("ssi.rdata")
+
+m1 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+m3 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m4 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+m5 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m6 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+
+table <- capture.output({stargazer(m1, m2, m3, m4, m5, m6, 
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n') , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "text") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{1\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT FIGURE 3 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+load("ssi.rdata")
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+
+t1 <- coef(summary(m2))
+
+
+# Combined 
+
+c3 <- numeric(length = 16)
+
+c3[16] <- t1[7,1]*sd(ssi$rep)  
+c3[15] <- t1[21,1]*sd(ssi$intergenmobility) 
+c3[14] <- t1[13,1]*sd(ssi$age)
+c3[13] <- t1[22,1]*sd(ssi$parentsimmigrant, na.rm=T)
+c3[12] <-  t1[4,1]*sd(ssi$heavyviewer)       
+c3[11] <-  t1[3,1]*sd(ssi$frequentviewer)             
+c3[10] <-  t1[2,1]*sd(ssi$occasionalviewer) 
+c3[9] <- t1[14,1]*sd(ssi$white) 
+c3[8] <- t1[18,1]*sd(ssi$protestant)   
+c3[7] <- t1[23,1]*sd(ssi$absolutemobility, na.rm=T)
+c3[6] <-  t1[20,1]*sd(ssi$insecurity, na.rm=T) 
+c3[5] <-  t1[24,1]*sd(ssi$gini, na.rm=T)
+c3[4] <-  t1[8,1]*sd(ssi$dem)   
+c3[3] <-  t1[10,1]*sd(ssi$income_n)
+c3[2] <-  t1[15,1]*sd(ssi$unemployed)
+c3[1] <- t1[9,1]*sd(ssi$education_n)      
+
+c3 <-as.data.frame((c3))
+
+c3[1,c(2)] <- "#24345A"
+c3[2,c(2)] <-"#24345A"
+c3[3,c(2)] <- "#24345A"
+c3[4,c(2)] <- "#24345A"
+c3[5,c(2)] <- "#24345A"
+c3[6,c(2)] <- "#24345A"
+c3[7,c(2)] <- "#24345A"
+c3[8,c(2)] <-"#24345A"
+c3[9,c(2)] <- "#24345A"
+c3[10,c(2)] <- "#2B8D9C"
+c3[11,c(2)] <-"#2B8D9C"
+c3[12,c(2)] <- "#2B8D9C"
+c3[13,c(2)] <- "#24345A"
+c3[14,c(2)] <- "#24345A"
+c3[15,c(2)] <- "#24345A"
+c3[16,c(2)] <- "#24345A"
+
+
+s3 <- numeric(length = 16)
+
+
+s3[16] <- t1[7,2]*sd(ssi$rep)
+s3[15] <- t1[21,2]*sd(ssi$intergenmobility)  
+s3[14] <- t1[13,2]*sd(ssi$age)      
+s3[13] <- t1[22,2]*sd(ssi$parentsimmigrant, na.rm=T) 
+s3[12] <-  t1[4,2]*sd(ssi$heavyviewer)          
+s3[11] <- t1[3,2]*sd(ssi$frequentviewer)        
+s3[10] <- t1[2,2]*sd(ssi$occasionalviewer)      
+s3[9] <- t1[14,2]*sd(ssi$white)
+s3[8] <- t1[18,2]*sd(ssi$protestant)
+s3[7] <- t1[23,2]*sd(ssi$absolutemobility, na.rm=T)    
+s3[6] <- t1[20,2]*sd(ssi$insecurity, na.rm=T)    
+s3[5] <- t1[24,2]*sd(ssi$gini, na.rm=T)
+s3[4] <- t1[8,2]*sd(ssi$dem)
+s3[3] <- t1[10,2]*sd(ssi$income_n)
+s3[2] <- t1[15,2]*sd(ssi$unemployed)
+s3[1] <- t1[9,2]*sd(ssi$education_n)
+
+yloc <- c(1, 2,  3, 4,5,6,7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
+
+
+
+# jpeg("SDfigure_AJPS.jpg", units="in", width=10, height=5, res=300)
+p <- recordPlot()
+plot.new()
+
+plot(c3$`(c3)`, yloc, pch = 23, col=c3$V2, bg=c3$V2,
+     xlim = c(-0.135, 0.14), ylim = c(0,16), xlab = "Impact of Standard Deviation Change", 
+     ylab = "", yaxt = "n",  xaxt = "n", axes=FALSE)
+abline(v = 0, col = "gray")
+grid()
+segments((c3$`(c3)` - (qnorm(0.975) * s3)), yloc, (c3$`(c3)` + (qnorm(0.975) * s3)), yloc,  col = c3$V2, 
+         lwd = 2)
+
+
+text(-0.05,16,'Republican' ,pos=2, cex=.8, col='grey30')
+text(-0.05,15,'Perceived Personal Mobility',pos=2, cex=.8, col='grey30')
+text(-0.05,14,'Age',pos=2, cex=.8, col='grey30')
+text(-0.05,13,'Have Immigrant Parents',pos=2, cex=.8, col='grey30')
+text(-0.05,12,'Rags-to-Riches TV: Heavy Viewer',pos=2, cex=.8, font=2)
+text(-0.05,11,'Rags-to-Riches TV: Frequent Viewer',pos=2, cex=.8, font=2)
+text(-0.05,10,'Rags-to-Riches TV: Occasional Viewer',pos=2, cex=.8, font=2)
+text(-0.05,9,'White',pos=2, cex=.8, col='grey30')
+text(-0.05,8,'Protestant',pos=2, cex=.8, col='grey30')
+text(-0.05,7,'County-level Intergenerational Mobility Rates' ,pos=2, cex=.8, col='grey30')
+text(-0.05,6,'Personal economic insecurity', ,pos=2, cex=.8, col='grey30')
+text(-0.05,5,'County-level Income Inequality (Gini)',pos=2, cex=.8, col='grey30')
+text(-0.05,4,'Democrat',pos=2, cex=.8, col='grey30')
+text(-0.05,3,'Income',pos=2, cex=.8, col='grey30')
+text(-0.05,2, 'Unemployed', cex=.8,pos=2, col='grey30')
+text(-0.05,1,'Education',cex=.8, pos=2, col='grey30')
+
+axis(1, at=c(-0.05, 0, 0.05, 0.1))
+
+# dev.off() 
+
+
+
+
+
+

25/replication_package/AJPS_2021_Kim_Manuscript_RMarkdown.Rmd

@@ -0,0 +1,317 @@
+---
+title: "AJPS_2021_Kim_Manuscript_Markdown"
+subtitle: "Entertaining Beliefs in Economic Mobility"
+author: "Eunji Kim"
+date: "8/15/2021"
+output: html_document
+---
+
+
+```{r, message=F, warning=F, echo=F}
+# Load libraries
+rm(list=ls())  
+library(foreign)
+library(ggplot2)
+library(readstata13)
+library(dplyr)
+library(haven)
+library(xtable)
+library(stargazer)
+library(ggplot2)
+library(dplyr)
+library(tidytext)
+library(stringr) 
+library(tidyr)
+library(scales)
+library(tables)
+
+library(ggpubr)
+
+```
+
+
+
+```{r,  warning=F, message=F, results="asis"}
+
+
+load("nyt.rdata")
+
+search_terms <- paste(c('economic mobility', 'social ladder', 'income ladder', 'social mobility', 'economic ladder',
+                        'rags to riches', 'economic mobility', 'social ladder', 'class mobility', 'socioeconomic mobility', 
+                        'intergenerational mobility', 'upward mobility', "meritocracy", "american dream", "land of opportunity",
+                        'rugged individualism', 'horatio alger', 'self-made man', 'self-made woman', 'self-made success'), 
+                      collapse = '|') 
+
+custom_stop_words <- stop_words
+
+cleaned_nyt_text$text <- as.character(cleaned_nyt_text$text)
+
+nyt_words <- cleaned_nyt_text %>%
+  unnest_tokens(word, text) %>%
+  mutate(word = gsub("\u2019", "'", word)) %>% 
+  anti_join(custom_stop_words) 
+
+bing <- get_sentiments('bing')
+
+nyt_polarity_year <- nyt_words %>%
+  inner_join(bing) %>%
+  count(sentiment, Month_Yr) %>%
+  spread(sentiment, n) %>%
+  mutate(polarity = positive - negative,
+         percent_positive = positive / (positive + negative) * 100) %>%
+  filter(!str_detect(Month_Yr, "2020"))
+
+
+nyt_polarity_year$year<- nyt_polarity_year %>% 
+  separate(Month_Yr, into = c("year", "month")) %>% 
+  pull("year")
+
+nyt_polarity_year_2000 <-  nyt_polarity_year %>% filter(year > 1999)
+
+
+polarity_over_time <- nyt_polarity_year_2000 %>%
+  ggplot(aes(as.Date(paste(Month_Yr, "-01", sep="")), 
+             polarity, 
+             color = ifelse(polarity >= 0,  '#86d7c1', '#0e698b'))) +
+  geom_col(position = "identity", 
+           color=ifelse(nyt_polarity_year_2000$polarity>= 0,'#86d7c1', '#0e698b'),
+           fill = ifelse(nyt_polarity_year_2000$polarity>= 0,'#86d7c1', '#0e698b'),
+           size = 0.1, show.legend = F) + 
+  #theme(plot.title = element_text(size = 11), legend.position = "none") + 
+  theme(plot.title = element_text(size = 11), legend.position = "none", 
+        panel.background = element_blank(), 
+        axis.title.x = element_text(color="black", size=10),
+        axis.title.y = element_text(color="black", size=10)) + 
+  theme(axis.text.x = element_text(color="black", size=10),
+        axis.text.y = element_text(color="black", size=10))  + 
+  xlab("Year") + ylab("Sentiment Score")  
+
+# ggtitle("NYT Word Sentiment Polarity Over Time (positive words - negative words per year)")
+
+polarity_over_time 
+
+
+#pdf('nytsentiment.pdf',height=4,width=7)
+#polarity_over_time
+#dev.off()
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT TABLE 1 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# mturk 
+
+load("mturk.rdata")
+
+m1 <-lm(mperception_combined ~ condition2 +  rep + dem  + optimism_index  + sjs_index, data=msample)
+mr <-lm(mperception_combined ~ condition2  + optimism_index  + sjs_index, data=msample[msample$rep==1,])
+md <- lm(mperception_combined ~ condition2  + optimism_index  + sjs_index, data=msample[msample$dem==1,])
+# interaction model 
+mrd <-lm(mperception_combined ~ condition2*rep1dem0new  + optimism_index + sjs_index, data=msample)
+
+# lab in the field 
+# main model 
+
+load("labinthefield.rdata")
+
+f1 <-lm(mperception_combined ~ condition2 + rep + dem + optimism_index + sjs_index +
+          as.factor(surveymode_n) + as.factor(date_n), data=fieldsample)
+fr <-lm(mperception_combined ~ condition2 + rep + dem + optimism_index + sjs_index +
+          as.factor(surveymode_n) + as.factor(date_n), data=fieldsample[fieldsample$rep==1,])
+fd <-lm(mperception_combined ~ condition2 + rep + dem + optimism_index + sjs_index +
+          as.factor(surveymode_n) + as.factor(date_n), data=fieldsample[fieldsample$dem==1,])
+frd <-lm(mperception_combined ~ condition2*rep1dem0new  + optimism_index + sjs_index +
+           as.factor(surveymode_n) + as.factor(date_n), data=fieldsample)
+
+table <- capture.output({stargazer(m1, mr, md, mrd,  f1, fr, fd, frd, 
+                                   dep.var.labels= c(
+                                     "Mturk Sample",
+                                     "Lab-in-the-Field Sample"),
+                                   covariate.labels = c('Rags-to-Riches TV Treatment'),
+                                   column.labels = c('All', 'Rep', 'Dem', 'Interaction Model','All', 'Rep', 'Dem', 'Interaction Model'), 
+                                   column.separate = c(1,1, 1, 1, 1, 1, 1,1),
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('surveymode_n', 'date_n' ) , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   label = "experiment",
+                                   title = "The Casual Effect of Rags-to-Riches TV", 
+                                   digits=3,
+                                   align = TRUE, 
+                                   type="html") 
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table)  
+
+
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT TABLE 2 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+
+load("ssi.rdata")
+
+m1 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+m3 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m4 <- lm(internalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+m5 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer, data=ssi)
+
+m6 <- lm(externalatt_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex + insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n), data=ssi)
+
+
+stargazer(m1, m2, m3, m4, m5, m6, 
+                                   dep.var.caption = "",
+                                   omit.stat=c("adj.rsq","LL","ser","f"),
+                                   omit = c('state_n', "othertv", "sportstv", "rep", "dem", "education_n",
+                                            "income_n", "married", "female", "age", "white", "unemployed", 
+                                            "polinterst", "religion_attend", "protestant", "optimismindex",
+                                            "insecurity", "intergenmobility", "parentsimmigrant", "absolutemobility", "gini", "Constant") , 
+                                   star.cutoffs = c(0.1, .05,.01,.001),
+                                   no.space=TRUE,
+                                   star.char = c("+", "*", "**", "***"), 
+                                   notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"), 
+                                   notes.append = F,
+                                   notes.align="l",
+                                   digits=3,
+                                   align = TRUE, 
+                                   type= "html") 
+# --------------------------------------------------------------------------------------------------------------------------------
+#  MAIN MANUSCRIPT FIGURE 3 # 
+# --------------------------------------------------------------------------------------------------------------------------------
+
+load("ssi.rdata")
+
+m2 <- lm(mindex_rsc ~ occasionalviewer + frequentviewer + heavyviewer + othertv  + sportstv + rep + dem +
+           education_n + income_n + married + female + age + 
+           white + unemployed + polinterst + religion_attend +
+           protestant + optimismindex +insecurity + intergenmobility + parentsimmigrant +
+           +absolutemobility + gini + as.factor(state_n) , data=ssi) 
+
+
+t1 <- coef(summary(m2))
+
+
+# Combined 
+
+c3 <- numeric(length = 16)
+
+c3[16] <- t1[7,1]*sd(ssi$rep)  
+c3[15] <- t1[21,1]*sd(ssi$intergenmobility) 
+c3[14] <- t1[13,1]*sd(ssi$age)
+c3[13] <- t1[22,1]*sd(ssi$parentsimmigrant, na.rm=T)
+c3[12] <-  t1[4,1]*sd(ssi$heavyviewer)       
+c3[11] <-  t1[3,1]*sd(ssi$frequentviewer)             
+c3[10] <-  t1[2,1]*sd(ssi$occasionalviewer) 
+c3[9] <- t1[14,1]*sd(ssi$white) 
+c3[8] <- t1[18,1]*sd(ssi$protestant)   
+c3[7] <- t1[23,1]*sd(ssi$absolutemobility, na.rm=T)
+c3[6] <-  t1[20,1]*sd(ssi$insecurity, na.rm=T) 
+c3[5] <-  t1[24,1]*sd(ssi$gini, na.rm=T)
+c3[4] <-  t1[8,1]*sd(ssi$dem)   
+c3[3] <-  t1[10,1]*sd(ssi$income_n)
+c3[2] <-  t1[15,1]*sd(ssi$unemployed)
+c3[1] <- t1[9,1]*sd(ssi$education_n)      
+
+c3 <-as.data.frame((c3))
+
+c3[1,c(2)] <- "#24345A"
+c3[2,c(2)] <-"#24345A"
+c3[3,c(2)] <- "#24345A"
+c3[4,c(2)] <- "#24345A"
+c3[5,c(2)] <- "#24345A"
+c3[6,c(2)] <- "#24345A"
+c3[7,c(2)] <- "#24345A"
+c3[8,c(2)] <-"#24345A"
+c3[9,c(2)] <- "#24345A"
+c3[10,c(2)] <- "#2B8D9C"
+c3[11,c(2)] <-"#2B8D9C"
+c3[12,c(2)] <- "#2B8D9C"
+c3[13,c(2)] <- "#24345A"
+c3[14,c(2)] <- "#24345A"
+c3[15,c(2)] <- "#24345A"
+c3[16,c(2)] <- "#24345A"
+
+
+s3 <- numeric(length = 16)
+
+
+s3[16] <- t1[7,2]*sd(ssi$rep)
+s3[15] <- t1[21,2]*sd(ssi$intergenmobility)  
+s3[14] <- t1[13,2]*sd(ssi$age)      
+s3[13] <- t1[22,2]*sd(ssi$parentsimmigrant, na.rm=T) 
+s3[12] <-  t1[4,2]*sd(ssi$heavyviewer)          
+s3[11] <- t1[3,2]*sd(ssi$frequentviewer)        
+s3[10] <- t1[2,2]*sd(ssi$occasionalviewer)      
+s3[9] <- t1[14,2]*sd(ssi$white)
+s3[8] <- t1[18,2]*sd(ssi$protestant)
+s3[7] <- t1[23,2]*sd(ssi$absolutemobility, na.rm=T)    
+s3[6] <- t1[20,2]*sd(ssi$insecurity, na.rm=T)    
+s3[5] <- t1[24,2]*sd(ssi$gini, na.rm=T)
+s3[4] <- t1[8,2]*sd(ssi$dem)
+s3[3] <- t1[10,2]*sd(ssi$income_n)
+s3[2] <- t1[15,2]*sd(ssi$unemployed)
+s3[1] <- t1[9,2]*sd(ssi$education_n)
+
+yloc <- c(1, 2,  3, 4,5,6,7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
+
+
+
+# jpeg("SDfigure_AJPS.jpg", units="in", width=10, height=5, res=300)
+p <- recordPlot()
+plot.new()
+
+plot(c3$`(c3)`, yloc, pch = 23, col=c3$V2, bg=c3$V2,
+     xlim = c(-0.135, 0.14), ylim = c(0,16), xlab = "Impact of Standard Deviation Change", 
+     ylab = "", yaxt = "n",  xaxt = "n", axes=FALSE)
+abline(v = 0, col = "gray")
+grid()
+segments((c3$`(c3)` - (qnorm(0.975) * s3)), yloc, (c3$`(c3)` + (qnorm(0.975) * s3)), yloc,  col = c3$V2, 
+         lwd = 2)
+
+
+text(-0.05,16,'Republican' ,pos=2, cex=.8, col='grey30')
+text(-0.05,15,'Perceived Personal Mobility',pos=2, cex=.8, col='grey30')
+text(-0.05,14,'Age',pos=2, cex=.8, col='grey30')
+text(-0.05,13,'Have Immigrant Parents',pos=2, cex=.8, col='grey30')
+text(-0.05,12,'Rags-to-Riches TV: Heavy Viewer',pos=2, cex=.8, font=2)
+text(-0.05,11,'Rags-to-Riches TV: Frequent Viewer',pos=2, cex=.8, font=2)
+text(-0.05,10,'Rags-to-Riches TV: Occasional Viewer',pos=2, cex=.8, font=2)
+text(-0.05,9,'White',pos=2, cex=.8, col='grey30')
+text(-0.05,8,'Protestant',pos=2, cex=.8, col='grey30')
+text(-0.05,7,'County-level Intergenerational Mobility Rates' ,pos=2, cex=.8, col='grey30')
+text(-0.05,6,'Personal economic insecurity', ,pos=2, cex=.8, col='grey30')
+text(-0.05,5,'County-level Income Inequality (Gini)',pos=2, cex=.8, col='grey30')
+text(-0.05,4,'Democrat',pos=2, cex=.8, col='grey30')
+text(-0.05,3,'Income',pos=2, cex=.8, col='grey30')
+text(-0.05,2, 'Unemployed', cex=.8,pos=2, col='grey30')
+text(-0.05,1,'Education',cex=.8, pos=2, col='grey30')
+
+axis(1, at=c(-0.05, 0, 0.05, 0.1))
+
+
+```

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