## Data Visualization #16—Canadian Federal Equalization Payments per capita

My most recent post in this series analyzed data related to the federal equalization program in Canada using a lollipop plot made with ggplot2 in R. The data that I chose to visualize—annual nominal dollar receipts by province—give the reader the impression that over the last five-plus decades the province of Quebec (QC) is the main recipient (by far) of these federal transfer funds. While this may be true, the plot also misrepresents the nature of these financial flows from the federal government to the provinces. The data does not take into account the wide variation in populations amongst the 10 provinces. For example, Prince Edward Island (PEI) as of 2019 has a population of about 156,000 residents, while Quebec has a population of approximately 8.5 million, or about 55 times as much as PEI. That is to say a better way of representing the provincial receipt of equalization funds is to calculate the annual per capita (i.e., for every resident) value, rather than a provincial total.

For the lollipop chart below, I’ve not only calculated an annual per-capita measure of the amount of money received by province, I’ve also controlled for inflation, understanding that a dollar in 1960 was worth a lot more (and could be used to buy many more resources) in 1960 than today. Using Canadian GDP deflator data compiled by the St. Louis Federal Reserve, I’ve created plotting variable—annual real per-capita federal equalization receipts by province, with a base year of 2014. Here, we see that the message of the plot is no longer Quebec’s dominance but a story in which Canadians (regardless of where they live) are treated relatively equally. Of course, every year, Canadian in some provinces receive no equalization receipts.

Here’s the plot, and the R code below it:

```require(ggplot2)
require(gganimate)

gg.anim.lol3 <- ggplot(eq.pop.df[eq.pop.df\$Year!="2019-20",], aes(x=province, y=real.value.per.cap, label=real.value.per.cap.amt)) +
geom_point(stat='identity', size=14, aes(col=as.factor(zero.dummy))) +  #, fill="white"
scale_color_manual(name="zero.dummy",
#      labels = c("Above", "Below"),
values = c("0"="#000000", "1"="red")) +
labs(title="Per Capita Federal Equalization Entitlements (by Province): {closest_state}",
x=" ", y="\$ CAD (Real—2014 Base Year)") +
geom_segment(aes(y = 0,
x = province,
yend = real.value.per.cap,
xend = province),
color = "red",
size=1.5) +
scale_y_continuous(breaks=seq(0,3000,500)) +
theme(legend.position="none",
plot.title =element_text(hjust = 0.5, size=23),
plot.subtitle =element_text(hjust = 0.5, size=19),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.y =element_text(size = 14),
axis.text.x=element_text(vjust=0.5,size=16, colour="black")) +
geom_text(color="white", size=4) +
transition_states(
Year,
transition_length = 1,
state_length = 9
) +