+
+
+
+
+
+
+AJPS_2021_Kim_Appendix_Markdown
+Entertaining Beliefs in Economic Mobility
+Eunji Kim
+8/15/2021
+ +# 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)[1] 0.936
+# Cohen's Kappa (unweighted) for the second category
+round(second, digits=3)[1] 0.91
+# Cohen's Kappa (unweighted) for the third category
+round(third, digits=3)[1] 0.835
+# --------------------------------------------------------------------------------------------------------------------------------
+# 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 prop tvtv1 39.6 America’s Got Talent tv2 34.8 NFL on CBS tv3 34.0 Sunday Night Football tv4 32.9 Fox NFL Sunday tv5 30.8 Shark Tank tv6 26.7 Hell’s Kichen tv7 26.4 Voice tv8 25.9 American Idol tv9 25.2 American Ninja Warrior tv10 24.8 MasterChef tv11 22.9 Celebrity Family Feud tv12 21.3 Survivor tv13 21.0 MLB on Fox tv14 17.9 Colege Football Today tv15 17.2 So You Think You Can Dance tv16 16.7 Amazing Race tv17 16.1 College Bastketball on CBS tv18 15.1 NBA Saturday Primetime tv19 14.8 Keeping Up with Kardashians tv20 14.4 NASCAR on Fox tv21 14.2 Bachelor tv22 13.5 Bachelorette tv23 13.1 Jersey Shore tv24 12.5 The Real Housewives tv25 11.5 UFC Fight Night tv26 11.4 World of Dance tv27 11.1 Love and Hip Hop: Hollywood tv28 10.7 CBS Sports Spectaular tv29 8.9 BattleBots tv30 7.6 Love Connection
+# --------------------------------------------------------------------------------------------------------------------------------
+
+# 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) | + | +||||||
| + | ++mindex_rsc + | ++internalatt_rsc + | ++externalatt_rsc + | +|||
| + | ++(1) + | ++(2) + | ++(3) + | ++(4) + | ++(5) + | ++(6) + | +
| + | +||||||
| +occasionalviewer + | ++0.019 + | ++0.013 + | ++0.006 + | ++0.013 + | ++-0.004 + | ++-0.007 + | +
| + | ++(0.012) + | ++(0.011) + | ++(0.010) + | ++(0.010) + | ++(0.009) + | ++(0.009) + | +
| +frequentviewer + | ++0.047*** + | ++0.032** + | ++0.008 + | ++0.017+ + | ++0.009 + | ++0.005 + | +
| + | ++(0.012) + | ++(0.011) + | ++(0.010) + | ++(0.010) + | ++(0.009) + | ++(0.010) + | +
| +heavyviewer + | ++0.076*** + | ++0.040* + | ++0.052*** + | ++0.052*** + | ++0.039*** + | ++0.014 + | +
| + | ++(0.013) + | ++(0.016) + | ++(0.011) + | ++(0.014) + | ++(0.011) + | ++(0.013) + | +
| +othertv + | ++ | ++0.001 + | ++ | ++-0.002 + | ++ | ++0.0003 + | +
| + | ++ | ++(0.003) + | ++ | ++(0.003) + | ++ | ++(0.003) + | +
| +sportstv + | ++ | ++0.007** + | ++ | ++0.006** + | ++ | ++0.006*** + | +
| + | ++ | ++(0.002) + | ++ | ++(0.002) + | ++ | ++(0.002) + | +
| +rep + | ++ | ++0.117*** + | ++ | ++0.026* + | ++ | ++-0.029** + | +
| + | ++ | ++(0.013) + | ++ | ++(0.011) + | ++ | ++(0.011) + | +
| +dem + | ++ | ++-0.003 + | ++ | ++-0.019+ + | ++ | ++0.027** + | +
| + | ++ | ++(0.012) + | ++ | ++(0.010) + | ++ | ++(0.010) + | +
| +education_n + | ++ | ++-0.022*** + | ++ | ++-0.003 + | ++ | ++0.010** + | +
| + | ++ | ++(0.004) + | ++ | ++(0.003) + | ++ | ++(0.003) + | +
| +income_n + | ++ | ++-0.002 + | ++ | ++-0.001 + | ++ | ++-0.002 + | +
| + | ++ | ++(0.003) + | ++ | ++(0.003) + | ++ | ++(0.002) + | +
| +married + | ++ | ++0.016+ + | ++ | ++0.007 + | ++ | ++-0.003 + | +
| + | ++ | ++(0.009) + | ++ | ++(0.008) + | ++ | ++(0.007) + | +
| +female + | ++ | ++0.011 + | ++ | ++0.010 + | ++ | ++0.001 + | +
| + | ++ | ++(0.009) + | ++ | ++(0.008) + | ++ | ++(0.008) + | +
| +age + | ++ | ++0.001*** + | ++ | ++0.002*** + | ++ | ++0.001*** + | +
| + | ++ | ++(0.0003) + | ++ | ++(0.0002) + | ++ | ++(0.0002) + | +
| +white + | ++ | ++0.017+ + | ++ | ++0.022* + | ++ | ++-0.003 + | +
| + | ++ | ++(0.010) + | ++ | ++(0.009) + | ++ | ++(0.008) + | +
| +unemployed + | ++ | ++-0.032* + | ++ | ++-0.011 + | ++ | ++0.011 + | +
| + | ++ | ++(0.014) + | ++ | ++(0.012) + | ++ | ++(0.011) + | +
| +polinterst + | ++ | ++-0.007 + | ++ | ++0.013** + | ++ | ++0.020*** + | +
| + | ++ | ++(0.005) + | ++ | ++(0.004) + | ++ | ++(0.004) + | +
| +religion_attend + | ++ | ++0.005+ + | ++ | ++-0.001 + | ++ | ++-0.005* + | +
| + | ++ | ++(0.003) + | ++ | ++(0.002) + | ++ | ++(0.002) + | +
| +protestant + | ++ | ++0.010 + | ++ | ++0.018* + | ++ | ++-0.002 + | +
| + | ++ | ++(0.010) + | ++ | ++(0.009) + | ++ | ++(0.008) + | +
| +optimismindex + | ++ | ++0.057*** + | ++ | ++0.032*** + | ++ | ++0.009* + | +
| + | ++ | ++(0.005) + | ++ | ++(0.005) + | ++ | ++(0.004) + | +
| +insecurity + | ++ | ++0.002 + | ++ | ++0.019*** + | ++ | ++0.045*** + | +
| + | ++ | ++(0.005) + | ++ | ++(0.005) + | ++ | ++(0.005) + | +
| +intergenmobility + | ++ | ++0.036*** + | ++ | ++0.015*** + | ++ | ++-0.001 + | +
| + | ++ | ++(0.004) + | ++ | ++(0.003) + | ++ | ++(0.003) + | +
| +parentsimmigrant + | ++ | ++0.045*** + | ++ | ++0.022* + | ++ | ++-0.002 + | +
| + | ++ | ++(0.011) + | ++ | ++(0.010) + | ++ | ++(0.010) + | +
| +absolutemobility + | ++ | ++0.001 + | ++ | ++-0.0001 + | ++ | ++0.001 + | +
| + | ++ | ++(0.001) + | ++ | ++(0.001) + | ++ | ++(0.001) + | +
| +gini + | ++ | ++-0.016 + | ++ | ++-0.025 + | ++ | ++0.006 + | +
| + | ++ | ++(0.046) + | ++ | ++(0.040) + | ++ | ++(0.039) + | +
| +Constant + | ++0.649*** + | ++0.267** + | ++0.756*** + | ++0.431*** + | ++0.709*** + | ++0.401*** + | +
| + | ++(0.008) + | ++(0.085) + | ++(0.007) + | ++(0.075) + | ++(0.006) + | ++(0.072) + | +
| + | +||||||
| +Observations + | ++3,004 + | ++2,998 + | ++3,004 + | ++2,998 + | ++3,004 + | ++2,998 + | +
| +R2 + | ++0.013 + | ++0.239 + | ++0.008 + | ++0.143 + | ++0.006 + | ++0.110 + | +
| + | +||||||
| +Note: + | +
+
|
+|||||
## 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) | + | +|
| + | ++mindex_rsc + | +
| + | +|
| +realitytv + | ++0.006** + | +
| + | ++(0.002) + | +
| +othertv + | ++-0.001 + | +
| + | ++(0.003) + | +
| +sportstv + | ++0.006** + | +
| + | ++(0.002) + | +
| +rep + | ++0.118*** + | +
| + | ++(0.012) + | +
| +dem + | ++-0.003 + | +
| + | ++(0.012) + | +
| +education_n + | ++-0.022*** + | +
| + | ++(0.004) + | +
| +income_n + | ++-0.002 + | +
| + | ++(0.003) + | +
| +married + | ++0.017+ + | +
| + | ++(0.009) + | +
| +female + | ++0.011 + | +
| + | ++(0.009) + | +
| +age + | ++0.001*** + | +
| + | ++(0.0003) + | +
| +white + | ++0.017+ + | +
| + | ++(0.010) + | +
| +unemployed + | ++-0.032* + | +
| + | ++(0.014) + | +
| +polinterst + | ++-0.006 + | +
| + | ++(0.005) + | +
| +religion_attend + | ++0.005+ + | +
| + | ++(0.003) + | +
| +protestant + | ++0.010 + | +
| + | ++(0.010) + | +
| +optimismindex + | ++0.057*** + | +
| + | ++(0.005) + | +
| +insecurity + | ++0.002 + | +
| + | ++(0.005) + | +
| +intergenmobility + | ++0.036*** + | +
| + | ++(0.004) + | +
| +parentsimmigrant + | ++0.045*** + | +
| + | ++(0.011) + | +
| +absolutemobility + | ++0.001 + | +
| + | ++(0.001) + | +
| +gini + | ++-0.014 + | +
| + | ++(0.046) + | +
| +Constant + | ++0.275** + | +
| + | ++(0.085) + | +
| + | +|
| +Observations + | ++2,998 + | +
| +R2 + | ++0.239 + | +
| + | +|
| +Note: + | +
+
|
+
## 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) | + | +||||||
| + | ++mindex_rsc + | ++internalatt_rsc + | ++externalatt_rsc + | +|||
| + | ++(1) + | ++(2) + | ++(3) + | ++(4) + | ++(5) + | ++(6) + | +
| + | +||||||
| +occasionalviewer + | ++0.012 + | ++0.015 + | ++0.013 + | ++0.015 + | ++-0.002 + | ++-0.004 + | +
| + | ++(0.021) + | ++(0.013) + | ++(0.019) + | ++(0.011) + | ++(0.018) + | ++(0.011) + | +
| +frequentviewer + | ++0.013 + | ++0.036** + | ++0.047* + | ++0.010 + | ++0.037+ + | ++0.0004 + | +
| + | ++(0.024) + | ++(0.013) + | ++(0.022) + | ++(0.012) + | ++(0.020) + | ++(0.011) + | +
| +heavyviewer + | ++0.105** + | ++0.032+ + | ++0.101** + | ++0.044** + | ++0.064* + | ++0.007 + | +
| + | ++(0.036) + | ++(0.018) + | ++(0.033) + | ++(0.015) + | ++(0.030) + | ++(0.015) + | +
| +othertv + | ++-0.004 + | ++0.003 + | ++0.0002 + | ++-0.002 + | ++-0.010 + | ++0.002 + | +
| + | ++(0.008) + | ++(0.004) + | ++(0.007) + | ++(0.003) + | ++(0.006) + | ++(0.003) + | +
| +sportstv + | ++0.010* + | ++0.006** + | ++0.003 + | ++0.007*** + | ++0.010* + | ++0.006*** + | +
| + | ++(0.005) + | ++(0.002) + | ++(0.005) + | ++(0.002) + | ++(0.004) + | ++(0.002) + | +
| +rep + | ++0.092*** + | ++0.119*** + | ++0.004 + | ++0.039** + | ++-0.025 + | ++-0.020 + | +
| + | ++(0.023) + | ++(0.016) + | ++(0.021) + | ++(0.014) + | ++(0.019) + | ++(0.014) + | +
| +dem + | ++0.012 + | ++-0.008 + | ++-0.014 + | ++-0.013 + | ++0.024 + | ++0.037** + | +
| + | ++(0.020) + | ++(0.015) + | ++(0.018) + | ++(0.013) + | ++(0.017) + | ++(0.013) + | +
| +education_n + | ++-0.035*** + | ++-0.018*** + | ++-0.012 + | ++0.001 + | ++-0.001 + | ++0.015*** + | +
| + | ++(0.009) + | ++(0.004) + | ++(0.008) + | ++(0.004) + | ++(0.007) + | ++(0.004) + | +
| +income_n + | ++-0.006 + | ++-0.002 + | ++-0.003 + | ++-0.001 + | ++-0.001 + | ++-0.003 + | +
| + | ++(0.007) + | ++(0.003) + | ++(0.006) + | ++(0.003) + | ++(0.005) + | ++(0.003) + | +
| +married + | ++0.014 + | ++0.013 + | ++0.016 + | ++0.007 + | ++-0.030* + | ++0.004 + | +
| + | ++(0.019) + | ++(0.010) + | ++(0.017) + | ++(0.009) + | ++(0.015) + | ++(0.009) + | +
| +female + | ++-0.006 + | ++0.011 + | ++0.028 + | ++0.001 + | ++0.027 + | ++-0.011 + | +
| + | ++(0.021) + | ++(0.011) + | ++(0.019) + | ++(0.009) + | ++(0.017) + | ++(0.009) + | +
| +age + | ++0.002** + | ++0.001*** + | ++0.003*** + | ++0.002*** + | ++0.002** + | ++0.001*** + | +
| + | ++(0.001) + | ++(0.0003) + | ++(0.001) + | ++(0.0003) + | ++(0.001) + | ++(0.0003) + | +
| +white + | ++-0.015 + | ++0.025* + | ++0.017 + | ++0.023* + | ++0.001 + | ++-0.004 + | +
| + | ++(0.023) + | ++(0.011) + | ++(0.021) + | ++(0.010) + | ++(0.019) + | ++(0.010) + | +
| +unemployed + | ++-0.022 + | ++-0.041* + | ++-0.025 + | ++-0.005 + | ++-0.010 + | ++0.015 + | +
| + | ++(0.023) + | ++(0.017) + | ++(0.021) + | ++(0.015) + | ++(0.019) + | ++(0.015) + | +
| +religion_attend + | ++0.005 + | ++0.005+ + | ++-0.003 + | ++-0.001 + | ++-0.004 + | ++-0.004 + | +
| + | ++(0.006) + | ++(0.003) + | ++(0.006) + | ++(0.003) + | ++(0.005) + | ++(0.003) + | +
| +protestant + | ++0.036 + | ++0.006 + | ++0.045* + | ++0.012 + | ++0.029 + | ++-0.007 + | +
| + | ++(0.023) + | ++(0.011) + | ++(0.020) + | ++(0.009) + | ++(0.019) + | ++(0.009) + | +
| +optimismindex + | ++0.074*** + | ++0.055*** + | ++0.032** + | ++0.035*** + | ++0.001 + | ++0.014** + | +
| + | ++(0.012) + | ++(0.006) + | ++(0.010) + | ++(0.005) + | ++(0.010) + | ++(0.005) + | +
| +insecurity + | ++0.018 + | ++-0.001 + | ++0.027** + | ++0.017** + | ++0.045*** + | ++0.047*** + | +
| + | ++(0.011) + | ++(0.006) + | ++(0.010) + | ++(0.005) + | ++(0.009) + | ++(0.005) + | +
| +intergenmobility + | ++0.022** + | ++0.039*** + | ++0.015* + | ++0.014*** + | ++0.005 + | ++-0.002 + | +
| + | ++(0.007) + | ++(0.004) + | ++(0.007) + | ++(0.004) + | ++(0.006) + | ++(0.004) + | +
| +parentsimmigrant + | ++0.025 + | ++0.051*** + | ++0.012 + | ++0.025* + | ++0.005 + | ++-0.004 + | +
| + | ++(0.024) + | ++(0.013) + | ++(0.022) + | ++(0.011) + | ++(0.020) + | ++(0.011) + | +
| +absolutemobility + | ++0.004 + | ++-0.0002 + | ++-0.0005 + | ++-0.0002 + | ++0.0004 + | ++0.001 + | +
| + | ++(0.003) + | ++(0.002) + | ++(0.003) + | ++(0.001) + | ++(0.003) + | ++(0.001) + | +
| +gini + | ++0.123 + | ++-0.054 + | ++0.104 + | ++-0.064 + | ++0.081 + | ++-0.020 + | +
| + | ++(0.092) + | ++(0.053) + | ++(0.084) + | ++(0.047) + | ++(0.076) + | ++(0.046) + | +
| +Constant + | ++0.018 + | ++0.313** + | ++0.386* + | ++0.487*** + | ++0.400** + | ++0.445*** + | +
| + | ++(0.172) + | ++(0.099) + | ++(0.157) + | ++(0.087) + | ++(0.142) + | ++(0.085) + | +
| + | +||||||
| +Observations + | ++690 + | ++2,308 + | ++690 + | ++2,308 + | ++690 + | ++2,308 + | +
| +R2 + | ++0.263 + | ++0.257 + | ++0.187 + | ++0.145 + | ++0.178 + | ++0.108 + | +
| + | +||||||
| +Note: + | +
+
|
+|||||
# --------------------------------------------------------------------------------------------------------------------------------
+
+# 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$dem==1,], weights=V160102)
+
+
+table <- capture.output({stargazer(aw, awr, awd,
+ column.labels = c('All', 'Rep','Dem'),
+ column.separate = c(1, 1, 1),
+ dep.var.caption = "",
+ omit.stat=c("adj.rsq","LL","ser","f"),
+ omit = c('PPSTATEN_11', 'ideo_conserv', "white", "educat3", "female", "income", "agecat13",
+ "married", "bornagain", "outofwork", "wrongdirection", "econbetterthanlastyear",
+ "unemployment_worse", "incomegap_larger", "rep", "dem", "Constant") ,
+ star.cutoffs = c(0.1, .05,.01,.001),
+ no.space=TRUE,
+ star.char = c("+", "*", "**", "***"),
+ notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"),
+ notes.append = F,
+ notes.align="l",
+ digits=3,
+ align = TRUE,
+ type="html")
+})
+#table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+#table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table) | + | +|||
| + | ++mobilityindex_rsc + | +||
| + | ++All + | ++Rep + | ++Dem + | +
| + | ++(1) + | ++(2) + | ++(3) + | +
| + | +|||
| +realitynew + | ++0.012* + | ++0.019** + | ++0.006 + | +
| + | ++(0.005) + | ++(0.007) + | ++(0.007) + | +
| + | +|||
| +Observations + | ++3,291 + | ++1,342 + | ++1,530 + | +
| +R2 + | ++0.126 + | ++0.131 + | ++0.127 + | +
| + | +|||
| +Note: + | +
+
|
+||
## Table G1, Columns (4) to (6)
+
+# iscap
+
+load("iscap.rdata")
+
+ia <- lm(mobility_rsc ~ combined +
+ newscount_w8_new +
+ rep_11 + dem_11 +
+ ideo_11_rsc + age +
+ female_11 + income +
+ married_11 + white_11 +
+ educ_11 + protestant +
+ unemployed_11 + socio_11_rsc +
+ PPMSACAT_11 + sjs_mean_rsc,
+ data=iscap, weights=weight1_11)
+
+
+
+iar <- lm(mobility_rsc ~ combined + newscount_w8_new +
+ rep_11 + dem_11 + ideo_11_rsc + age + female_11 + income + married_11 + white_11 +
+ educ_11 + protestant + unemployed_11 + socio_11_rsc + PPMSACAT_11 + sjs_mean_rsc, data=iscap[iscap$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$dem_11==1,], weights=weight1_11)
+
+
+table <- capture.output({stargazer( ia, iar, iad,
+ column.labels = c( 'All', 'Rep','Dem'),
+ column.separate = c( 1, 1, 1),
+ dep.var.caption = "",
+ omit.stat=c("adj.rsq","LL","ser","f"),
+ omit = c('newscount_w8_new', 'rep_11', "dem_11", "ideo_11_rsc", "age",
+ 'female_11', "income", "married_11", "white_11",
+ 'educ_11', "protestant", "unemployed_11", "socio_11_rsc",
+ "PPMSACAT_11", "sjs_mean_rsc", "Constant") ,
+ star.cutoffs = c(0.1, .05,.01,.001),
+ no.space=TRUE,
+ star.char = c("+", "*", "**", "***"),
+ notes = c("+ p< 0.1, * p<0.05; ** p<0.01; *** p<0.001"),
+ notes.append = F,
+ notes.align="l",
+ digits=3,
+ align = TRUE,
+ type="html")
+})
+table <- gsub("\\begin{tabular}","\\resizebox{0.8\\textwidth}{!}{\\begin{tabular}", table,fixed=T)
+table <- gsub("\\end{tabular}","\\end{tabular}}", table,fixed=T)
+cat(table) | + | +|||
| + | ++mobility_rsc + | +||
| + | ++All + | ++Rep + | ++Dem + | +
| + | ++(1) + | ++(2) + | ++(3) + | +
| + | +|||
| +combined + | ++0.041* + | ++0.023 + | ++0.017 + | +
| + | ++(0.017) + | ++(0.033) + | ++(0.023) + | +
| + | +|||
| +Observations + | ++1,156 + | ++340 + | ++581 + | +
| +R2 + | ++0.180 + | ++0.221 + | ++0.212 + | +
| + | +|||
| +Note: + | +
+
|
+||
# --------------------------------------------------------------------------------------------------------------------------------
+# Table H1. Columns (1) to (4)
+
+load("anes2016.rdata")
+
+
+aw <- lm(mobilityindex_rsc ~ realitynew + rep + dem + ideo_conserv + white + educat3 +
+ female + income + agecat13 + married + bornagain + outofwork +
+ wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger ,
+ data=anes2016, weights=V160102)
+
+awr <- lm(mobilityindex_rsc ~ realitynew + ideo_conserv + white + educat3 +
+ female + income + agecat13 + married + bornagain + outofwork +
+ wrongdirection + econbetterthanlastyear + unemployment_worse + incomegap_larger,
+ data=anes2016[anes2016$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) | + | +||||
| + | ++mobilityindex_rsc + | +|||
| + | ++All + | ++Rep + | ++Dem + | ++Ind + | +
| + | ++(1) + | ++(2) + | ++(3) + | ++(4) + | +
| + | +||||
| +realitynew + | ++0.012* + | ++0.019** + | ++0.006 + | ++0.010 + | +
| + | ++(0.005) + | ++(0.007) + | ++(0.007) + | ++(0.015) + | +
| + | +||||
| +Observations + | ++3,291 + | ++1,342 + | ++1,530 + | ++419 + | +
| +R2 + | ++0.126 + | ++0.131 + | ++0.127 + | ++0.162 + | +
| + | +||||
| +Note: + | +
+
|
+|||
# 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) | + | +||||
| + | ++mobility_rsc + | +|||
| + | ++All + | ++Rep + | ++Dem + | ++Ind + | +
| + | ++(1) + | ++(2) + | ++(3) + | ++(4) + | +
| + | +||||
| +combined + | ++0.041* + | ++0.023 + | ++0.017 + | ++-0.101 + | +
| + | ++(0.017) + | ++(0.033) + | ++(0.023) + | ++(0.120) + | +
| + | +||||
| +Observations + | ++1,156 + | ++340 + | ++581 + | ++34 + | +
| +R2 + | ++0.180 + | ++0.221 + | ++0.212 + | ++0.613 + | +
| + | +||||
| +Note: + | +
+
|
+|||
## 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) | + | +||||
| + | ++mindex_rsc + | +|||
| + | ++All + | ++Rep + | ++Dem + | ++Ind + | +
| + | ++(1) + | ++(2) + | ++(3) + | ++(4) + | +
| + | +||||
| +occasionalviewer + | ++0.013 + | ++-0.012 + | ++0.005 + | ++0.070* + | +
| + | ++(0.011) + | ++(0.018) + | ++(0.016) + | ++(0.028) + | +
| +frequentviewer + | ++0.032** + | ++0.013 + | ++0.018 + | ++0.091** + | +
| + | ++(0.011) + | ++(0.018) + | ++(0.017) + | ++(0.032) + | +
| +heavyviewer + | ++0.040* + | ++0.001 + | ++0.031 + | ++0.119** + | +
| + | ++(0.016) + | ++(0.027) + | ++(0.023) + | ++(0.043) + | +
| + | +||||
| +Observations + | ++2,998 + | ++1,019 + | ++1,489 + | ++490 + | +
| +R2 + | ++0.239 + | ++0.198 + | ++0.187 + | ++0.322 + | +
| + | +||||
| +Note: + | +
+
|
+|||
# --------------------------------------------------------------------------------------------------------------------------------
+
+
+# APPENDIX K
+
+
+load("combined.rdata")
+
+# manipulation check
+
+# person featured on the show profitted a lot financially
+t.test(combined$m1_rsc ~ combined$condition2)Welch Two Sample t-testdata: combined\(m1_rsc by combined\)condition2 t = -17.032, df = 921.19, p-value < 2.2e-16 alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0 95 percent confidence interval: -0.3280082 -0.2602266 sample estimates: mean in group 0 mean in group 1 0.4088115 0.7029289
+# likely to have a higher income from now
+t.test(combined$m2_rsc ~ combined$condition2)Welch Two Sample t-testdata: combined\(m2_rsc by combined\)condition2 t = -17.251, df = 951.25, p-value < 2.2e-16 alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0 95 percent confidence interval: -0.3413982 -0.2716582 sample estimates: mean in group 0 mean in group 1 0.3770492 0.6835774
+# has a good work ethic
+t.test(combined$m3_rsc ~ combined$condition2)Welch Two Sample t-testdata: combined\(m3_rsc by combined\)condition2 t = -16.35, df = 956.92, p-value < 2.2e-16 alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0 95 percent confidence interval: -0.2359286 -0.1853623 sample estimates: mean in group 0 mean in group 1 0.6188525 0.8294979
+# showed that people can succeed when they are willing to work hard
+t.test(combined$m4_rsc ~ combined$condition2)Welch Two Sample t-testdata: combined\(m4_rsc by combined\)condition2 t = -11.669, df = 960.51, p-value < 2.2e-16 alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0 95 percent confidence interval: -0.2101978 -0.1496777 sample estimates: mean in group 0 mean in group 1 0.6260246 0.8059623
+# liked the program
+t.test(combined$like ~ combined$condition2)Welch Two Sample t-testdata: combined\(like by combined\)condition2 t = -0.63107, df = 961.42, p-value = 0.5281 alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0 95 percent confidence interval: -0.16025431 0.08226542 sample estimates: mean in group 0 mean in group 1 4.163934 4.202929
+# thought the program was entertaining
+t.test(combined$entertaining ~ combined$condition2)Welch Two Sample t-testdata: combined\(entertaining by combined\)condition2 t = -1.4671, df = 963.77, p-value = 0.1427 alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0 95 percent confidence interval: -0.20782287 0.03001575 sample estimates: mean in group 0 mean in group 1 4.149590 4.238494
+## 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) | + | +|
| + | ++Dependent variable: + | +
| + | ++ | +
| + | ++mperception_combined + | +
| + | +|
| +Rags-to-Riches TV Treatment + | ++-0.029* + | +
| + | ++(0.013) + | +
| +System Justification Scale - High + | ++0.032* + | +
| + | ++(0.014) + | +
| +Party ID + | ++0.033*** + | +
| + | ++(0.007) + | +
| +Optimism Index + | ++0.042*** + | +
| + | ++(0.005) + | +
| +Treatment x System Justification Scale + | ++0.181*** + | +
| + | ++(0.020) + | +
| +Constant + | ++0.311*** + | +
| + | ++(0.022) + | +
| + | +|
| +Observations + | ++966 + | +
| +R2 + | ++0.400 + | +
| + | +|
| +Note: + | +
+
|
+
# --------------------------------------------------------------------------------------------------------------------------------
+# 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) | + | +||||
| + | ++The rich works hard + | ++The poor lacks efforts + | ++Inequality is desirable + | ++Anti-redistribution + | +
| + | ++(1) + | ++(2) + | ++(3) + | ++(4) + | +
| + | +||||
| +Meritocracy Treatment + | ++0.175+ + | ++-0.090 + | ++0.098* + | ++0.079+ + | +
| + | ++(0.091) + | ++(0.092) + | ++(0.045) + | ++(0.044) + | +
| + | +||||
| +Observations + | ++119 + | ++119 + | ++119 + | ++119 + | +
| +R2 + | ++0.115 + | ++0.066 + | ++0.097 + | ++0.087 + | +
| + | +||||
| +Note: + | +
+
|
+|||
# --------------------------------------------------------------------------------------------------------------------------------
+# 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 