library(pacman); p_load(ggplot2, tidyr, dplyr, ggrepel, ggthemes)
data
bounds <- as_tibble(data) %>%
pivot_wider(names_from = Character, values_from = Value) %>%
mutate(
ymax = pmax(Manufacturing, CarbonDioxide),
ymin = pmin(Manufacturing, CarbonDioxide),
fill = Manufacturing >= CarbonDioxide); bounds
bounds$Difference <- bounds$Manufacturing - bounds$CarbonDioxide
data_ends <- data %>%
group_by(Character) %>%
top_n(1, Year)
data_ends
Emissions and productivity growth have become decoupled in many first world countries (see Ritchie, 2021). This is a world-historical development, as it marks the end of Jevon’s Paradox and suggests a clean and materially abundant future is possible. The U.S. is an excellent example of this happening. However, some people believe that this development has resulted from first world countries shipping their emissions-producing industries and their production overseas, but this is not a justified belief, as first world countries’ domestic production has also grown. Consequently, everyone must concede that even if first world countries do ship their polluting production overseas, the decoupling of growth and emissions cannot be fully explained in that way. Given the magnitudes of productivity increases and emissions’ failure to grow, that explanation is only possible for far below even a quarter of the observed decoupling. Below, I have plotted total U.S. manufacturing productivity versus total carbon dioxide emissions for the United States to showcase this point. As a further and very important point, Ritchie showed in her plot that consumption has become less carbon intensive in the United Kingdom by about 34% since 1990, and production has become even less carbon intensive, by almost 50% in the same time.
My data comes from FRED and is linked at the bottom of this page.
ggplot(data) +
geom_line(aes(Year, Value, linetype = Character, color = Character), size = 1.5) +
geom_ribbon(data = bounds, aes(Year, ymin = ymin, ymax = ymax, fill = fill), alpha = .4) +
guides(linetype = "none", fill = "none") +
labs(x = NULL, y = "Scaled Manufacturing and CO2 Levels", title = "Manufacturing and Emissions in the United States",
caption = "Sources: U.S. Energy Information Administration, Board of Governors of the Federal Reserve System") +
theme_economist() +
theme(
text = element_text(family = "serif"),
plot.title = element_text(hjust = .5),
legend.position = c(.1, .96),
legend.background = element_blank(),
legend.title = element_blank(),
plot.caption = element_text(hjust = 0, vjust = -1),
axis.title.y = element_text(vjust = 3)) +
scale_color_manual(values = c("steelblue", "orangered"),
labels = c("Total Carbon Dioxide Emissions", "Total Manufacturing Productivity")) +
scale_fill_manual(name = "fill", values = c("steelblue")) #+
#geom_text_repel(mapping = aes(label = Value, x = Year, y = Value), position = "dodge", force = 1, data = data_ends, size = 3)
ggplot(bounds, aes(Year, Difference)) +
geom_line(size = .9, linetype = 7) +
geom_area(fill = "#800020", alpha = .4) +
geom_hline(aes(yintercept = 0), linetype = "dashed") +
theme_economist() +
labs(y = "Manufacturing Growth over Emissions Growth", x = NULL, title = "The Growing Gap between Emissions and Production",
caption = "Sources: U.S. Energy Information Administration, Board of Governors of the Federal Reserve System") +
theme(
text = element_text(family = "serif"),
plot.title = element_text(hjust = .5),
axis.title.y = element_text(vjust = 3),
plot.caption = element_text(hjust = 0, vjust = -1))
https://ourworldindata.org/co2-gdp-decoupling, i.e., Ritchie (2021).
Industrial Production, Manufacturing, U.S., 1980-2018, averaged annually, scale-year = 1980: https://fred.stlouisfed.org/series/IPMAN
Total Carbon Dioxide Emissions from All Sectors, All Fuels for the United States, 1980-2018, averaged annually, scale-year = 1980: https://fred.stlouisfed.org/series/EMISSCO2TOTVTTTOUSA