To examine whether Australia’s wage growth (WPI) has kept up with the country’s inflation (CPI) during the last 20 years and to evaluate the effects of this disparity on Australians’ financial security.
The purpose of this piece is to examine if Australian wages are keeping pace with growing expenses. Comparing the CPI and WPI trends between 2000 and 2023 allows me to evaluate the potential impact of inflation on household income.
ggplot(long_data, aes(x = Year, y = Value, color = Index)) +
geom_line(linewidth = 1.2) +
geom_point(data = subset(long_data, Year %% 5 == 0), size = 2) +
labs(title = "CPI vs WPI (Indexed to 2010 = 100)",
x = "Year", y = "Index Value",
caption = "Source: ABS 6401.0 and 6345.0") +
theme_minimal()yoy_data <- merged_data %>%
mutate(`CPI YoY %` = (CPI_index / lag(CPI_index) - 1) * 100,
`WPI YoY %` = (WPI_index / lag(WPI_index) - 1) * 100) %>%
filter(!is.na(`CPI YoY %`))
ggplot(yoy_data, aes(x = Year)) +
geom_col(aes(y = `CPI YoY %`), fill = "tomato", alpha = 0.8) +
geom_line(aes(y = `WPI YoY %`), color = "steelblue", linewidth = 1) +
geom_hline(yintercept = 0, linetype = "dashed") +
labs(title = "Year-on-Year % Change in CPI and WPI",
y = "Percentage Change (%)",
caption = "Source: ABS 6401.0 and 6345.0") +
theme_minimal()gap_data <- merged_data %>%
mutate(Gap = CPI_index - WPI_index)
ggplot(gap_data, aes(x = Year, y = Gap)) +
geom_area(fill = "lightblue", alpha = 0.6) +
geom_hline(yintercept = 0, linetype = "dashed") +
labs(title = "Gap Between CPI and WPI Over Time",
y = "CPI - WPI",
caption = "Source: ABS 6401.0 and 6345.0") +
theme_minimal()