##########################
#### Campaign Finance Laws 
#### and Party Competition 
#### Joshua D. Potter and
#### Margit Tavits
#### April 2013
##########################


##########################
#### Codebook
##########################

# cnty \ country name
# year \ year of current election
# rulelaw \ from World Bank
# polity \ Polity IV score
# thresh \ legal vote threshold 
# postenp \ ENP after current election
# preenp \ ENP prior to current election
# fundparity4 \ Metric presented in paper
# fundparity 3 \ Alternate drops direct funding
# directelig \ Direct funding eligibility
# demin \ Year first democratic
# demyear \ Number of democratic years
# fed \ Whether or not federal
# pres \ Whether or not presidential
# avemag \ Average district magnitude
# smd \ Whether or not SMD system
# fract \ Ethnolinguistic fractionalization
# donorlimit \ Whether limits on donations
# eligmedia \ Free media eligibility
# partyspend \ Whether limits on spending


##########################
#### Replication Code
##########################

# read in data
library(foreign)
raw.data<-read.dta("potter_tavits_data.dta")

# drop statistical outliers
campaigns <- subset(raw.data, # delete 3 outliers
				counter!="Liberia2012" &
				counter!="Albania2003" &
				counter!="Brazil2003"
				)
				
# create post-1974 subset for endogeneity test
later1974<-subset(campaigns, demin>1973)

# estimate Model 1 in Table 2
library(arm)
full<-lm(postenp ~ fundparity4
	+ demyears
	+ fed 
	+ pres 
	+ log(avemag) 
	+ fract 
	+ log(avemag):fract, 
	data=campaigns)
display(full)	

# estimate Model 2 in Table 2
post1974<-lm(postenp ~ fundparity4
	+ demyears
	+ fed 
	+ pres 
	+ log(avemag) 
	+ fract 
	+ log(avemag):fract, 
	data=later1974)	
display(post1974)

# construct the endogeneity plot in Figure 1
plot(campaigns$fundparity4 
	~ campaigns$preenp, 
	pch=20, col="grey20", cex=1.5, 
	xlab="Previous ENP", 
	ylab="Current Fund Parity Value")
display(lm(fundparity4 ~ preenp, data=campaigns))
abline(a=0.82, b=-0.04, lwd=2)	

# model to ensure that all fund parity metric components are exerting similarly-signed influences (this model is mentioned in footnote 44)
components<-lm(postenp ~ directelig 
	+ partyspend
	+ donorlimit
	+ eligmedia
	+ demyears
	+ fed 
	+ pres 
	+ log(avemag) 
	+ fract 
	+ log(avemag):fract, 
	data=campaigns)
display(components)

# model to ensure that differences between legal rules and actual empirical practice in a country are not driving our results (this model is mentioned in footnote 45)
rules.practice<-lm(postenp ~ fundparity4
	+ rulelaw
	+ fundparity4*rulelaw
	+ demyears
	+ fed 
	+ pres 
	+ log(avemag) 
	+ fract 
	+ log(avemag):fract, 
	data=campaigns)
display(rules.practice)

# model to ensure that including legal threshold (which eliminates a large number of our observations due to data availability) does not undercut our results (this model is mentioned in footnote 56) 
threshold<-lm(postenp ~ fundparity4
	+ thresh
	+ demyears
	+ fed 
	+ pres 
	+ log(avemag) 
	+ fract 
	+ log(avemag):fract, 
	data=campaigns)
display(threshold)