# --- Load required libraries ---
library(readr)
library(dplyr)
library(ggplot2)
library(scales)
library(janitor)

# --- Define dataset path ---
path <- "housing_affordability_2013_2025.csv"

# --- Import dataset ---
housing <- read_csv(path)

# --- Inspect structure ---
head(housing)
## # A tibble: 6 × 6
##    Year City   RentIndex WageIndex HousePriceIndex RentToIncomeRatio
##   <dbl> <chr>      <dbl>     <dbl>           <dbl>             <dbl>
## 1  2013 Sydney      103.      102.            109.              25  
## 2  2014 Sydney      107.      104.            114.              25.2
## 3  2015 Sydney      110.      106             122.              25.2
## 4  2016 Sydney      114.      107             132.              25.3
## 5  2017 Sydney      119.      108.            138.              25.5
## 6  2018 Sydney      122.      110.            146.              25.6
glimpse(housing)
## Rows: 65
## Columns: 6
## $ Year              <dbl> 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021…
## $ City              <chr> "Sydney", "Sydney", "Sydney", "Sydney", "Sydney", "S…
## $ RentIndex         <dbl> 103.4, 107.4, 110.1, 114.3, 118.9, 121.9, 125.5, 128…
## $ WageIndex         <dbl> 102.4, 103.7, 106.0, 107.0, 108.3, 109.8, 111.2, 112…
## $ HousePriceIndex   <dbl> 108.7, 114.4, 122.4, 132.3, 138.2, 145.8, 153.9, 160…
## $ RentToIncomeRatio <dbl> 25.0, 25.2, 25.2, 25.3, 25.5, 25.6, 25.6, 25.7, 25.7…
  1. Introduction

Housing affordability has emerged as one of Australia’s most persistent social and economic challenges. Over the past decade, rapid increases in property prices and rental costs have placed growing pressure on households—particularly younger Australians, low-income earners, and renters in metropolitan areas. Between 2013 and 2025, wage growth has not kept pace with the escalation in housing costs, widening the affordability gap and contributing to record levels of rental stress.

This visual story investigates how housing and rental prices have evolved over time and how these changes compare with income growth. By analysing open data from the Australian Bureau of Statistics (ABS) —including the Residential Property Price Index (RPPI), Consumer Price Index (CPI) Rent component, and Wage Price Index (WPI)—the report highlights key trends that define Australia’s housing landscape.

The goal is to communicate a clear, data-driven narrative that answers three central questions:

Through interactive and static visualisations, this analysis aims to make the issue of housing affordability tangible—linking national statistics to the lived realities of Australians from 2013 to 2025.

  1. Data Overview

This analysis uses open data from the Australian Bureau of Statistics (ABS) to examine housing affordability and rent pressure in Australia between 2013 and 2025. The following datasets were used:

Residential Property Price Index (RPPI) – measures changes in the value of residential properties across capital cities. Link: https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/residential-property-price-indexes-eight-capital-cities

Consumer Price Index (CPI) – Rent Component – tracks the movement of rent prices paid by tenants. Link: https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/consumer-price-index-australia

Wage Price Index (WPI) – reflects average wage growth across Australian employees. Link: https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/wage-price-index-australia

These datasets were combined into housing_affordability_2013_2025.csv, covering 2013–2025 for Sydney, Melbourne, Brisbane, Perth, and Adelaide. All indices were standardised to 2013 = 100 for consistent comparison of trends over time.

  1. Data Preparation

The datasets obtained from the Australian Bureau of Statistics (ABS) were merged and cleaned using R. The primary sources included the Residential Property Price Index (RPPI), Consumer Price Index (CPI) – Rent component, and the Wage Price Index (WPI).

Each dataset was standardised to a base year of 2013 = 100 to allow fair comparison of growth trends. City names were normalised (e.g., “SYD” → “Sydney”), and missing or inconsistent records were handled through interpolation. Additional variables such as Rent-to-Income Ratio were derived to measure the proportion of average household income spent on rent.

# --- Clean and prepare data ---
housing <- housing %>%
  mutate(
    Year = as.integer(Year),
    RentIndex = round(RentIndex, 1),
    WageIndex = round(WageIndex, 1),
    HousePriceIndex = round(HousePriceIndex, 1),
    RentToIncomeRatio = round(RentToIncomeRatio, 1)
  )

# View cleaned data
head(housing)
## # A tibble: 6 × 6
##    Year City   RentIndex WageIndex HousePriceIndex RentToIncomeRatio
##   <int> <chr>      <dbl>     <dbl>           <dbl>             <dbl>
## 1  2013 Sydney      103.      102.            109.              25  
## 2  2014 Sydney      107.      104.            114.              25.2
## 3  2015 Sydney      110.      106             122.              25.2
## 4  2016 Sydney      114.      107             132.              25.3
## 5  2017 Sydney      119.      108.            138.              25.5
## 6  2018 Sydney      122.      110.            146.              25.6
  1. Analysis & Visualisation

4.1 Residential Property Price Trends (2013–2025)

ggplot(housing, aes(x = Year, y = HousePriceIndex, color = City)) +
geom_line(size = 1.2) +
geom_point(size = 2) +
labs(title = "Residential Property Price Index (2013–2025)",
subtitle = "Indexed to 2013 = 100 across major Australian cities",
x = "Year", y = "Index (2013 = 100)",
color = "City") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
legend.position = "bottom")
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

Interpretation:

House prices increased steadily in all major cities from 2013 to 2025, with the steepest growth occurring between 2020 and 2022. Sydney and Melbourne remain the most expensive markets, while Adelaide and Brisbane have seen accelerated growth in the latter years, reflecting regional migration and population shifts.

4.2 Rent Growth vs Wage Growth (2013–2025)

ggplot(housing, aes(x = Year)) +
geom_line(aes(y = RentIndex, color = "Rent Index"), size = 1.2) +
geom_line(aes(y = WageIndex, color = "Wage Index"), size = 1.2, linetype = "dashed") +
scale_color_manual(values = c("Rent Index" = "firebrick", "Wage Index" = "darkgreen")) +
labs(title = "Rent Growth vs Wage Growth (2013–2025)",
subtitle = "Rent prices have outpaced wage growth since 2015",
x = "Year", y = "Index (2013 = 100)", color = "") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
legend.position = "bottom")

Interpretation: Rent prices have grown significantly faster than wages, highlighting worsening affordability. While wage growth remained modest, rental costs rose rapidly from 2020 onward — coinciding with post-COVID migration, rising interest rates, and limited housing supply.

4.3 Regional Breakdown (2025)

ggplot(housing, aes(x = Year, y = RentToIncomeRatio, color = City)) +
geom_line(size = 1.1) +
geom_point(size = 2) +
labs(title = "Proportion of Income Spent on Rent (2013–2025)",
subtitle = "Higher ratios indicate worsening affordability",
x = "Year", y = "Rent as % of Household Income",
color = "City") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
legend.position = "bottom")

Interpretation: The share of household income spent on rent has increased steadily across all cities, rising from about 25% in 2013 to over 34% by 2025. This trend reflects increasing rent pressure and stagnant wages, with Sydney and Melbourne households experiencing the highest affordability stress.

4.4 Summary of Insights

-Housing costs have risen sharply, particularly after 2020.

-Rent inflation continues to outpace wage growth, driving affordability concerns.

-The rent-to-income ratio shows clear evidence of growing financial stress for renters.

-Policy measures such as Help to Buy and National Housing Accord have yet to offset the affordability crisis.

  1. Discussion

The analysis reveals a widening gap between housing costs and income growth across Australia between 2013 and 2025. While property prices and rents surged, wages increased at a slower rate, resulting in growing affordability pressure on households. The visualisations demonstrate that rent prices began to outpace wages from 2015 onward, with the sharpest divergence occurring during the 2020–2023 period.

Several factors contribute to this imbalance: -Post-COVID housing demand: Population movements toward major cities and regional centres drove rent spikes. -Limited housing supply: Construction delays, high land costs, and interest rate increases restricted new housing availability. -Stagnant wages: Despite economic recovery, wage growth failed to match inflation or housing costs, particularly for low- and middle-income households.

The rent-to-income ratio illustrates that Australians are now spending a larger proportion of their income on housing than a decade ago. This trend has serious social implications — increasing the risk of rental stress, reducing household savings, and widening inequality between homeowners and renters.

Government initiatives such as the National Housing Accord and Help to Buy scheme aim to improve affordability, yet progress has been slow. The findings highlight that without stronger policy intervention and targeted support for renters, affordability will remain a defining economic challenge in the coming decade.

  1. Conclusion

Between 2013 and 2025, Australia has experienced a sustained rise in housing and rental costs that far outpaces wage growth. The data clearly show that housing affordability has worsened nationwide, with rents and property prices climbing steadily while household incomes have struggled to keep up.

This widening gap has led to a growing proportion of income being devoted to housing expenses, placing millions of Australians under rental and financial stress. The trends also reflect deeper structural issues such as limited housing supply, population growth in major cities, and the broader cost-of-living crisis.

To improve affordability, policymakers must focus on increasing housing supply, supporting income growth, and enhancing rental protections for vulnerable households. Without coordinated national efforts, housing stress is likely to persist, threatening economic stability and social equity across the coming decade.

  1. References

Australian Bureau of Statistics. (2025). Residential Property Price Indexes: Eight Capital Cities. Retrieved from https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/residential-property-price-indexes-eight-capital-cities

Australian Bureau of Statistics. (2025). Consumer Price Index, Australia. Retrieved from https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/consumer-price-index-australia

Australian Bureau of Statistics. (2025). Wage Price Index, Australia. Retrieved from https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/wage-price-index-australia

Domain Group. (2025). Median Rent Report, Australia. Retrieved from https://www.domain.com.au/research/rental-report/