Average Weekly Earnings (AWE) August 2025 & Wage Price Index (WPI) March 2025

Understanding the drivers of inflation requires a close examination of wage dynamics across industries. This analysis draws on open source datasets from the Australian Bureau of Statistics (ABS), specifically the Average Weekly Earnings (AWE) by state and industry, and the Wage Price Index (WPI) by industry, to identify sectors contributing most to wage growth and assess their impact on inflationary pressures.

The AWE dataset, conducted twice annually, provides a snapshot of earnings levels across regions and sectors. While it does not measure wage movements directly, it captures compositional shifts in the workforce and informs wage and salary benchmarks. It focuses on full-time adult ordinary time earnings, excluding overtime and bonuses, offering a consistent view of nominal earnings.

In contrast, the quarterly WPI isolates pure wage changes, removing the influence of workforce composition. This makes it a more precise tool for tracking wage inflation. By integrating AWE and WPI, this analysis offers a comprehensive view of wage trends highlighting industries with both high earnings and strong wage momentum and explores how these trends may be contributing to broader inflationary outcomes.

The intention of an AWE data visual is to clearly and effectively communicate patterns in average weekly earnings across states by gender, enabling audiences to quickly grasp key insights such as income disparities, gender pay gaps, and regional trends.(Press auto scale for better view)

The Average Weekly Earnings data for full-time adults by state highlights notable income disparities across Australia. WA and ACT report the highest earnings, while Tasmania ranks lowest across all categories. In every state and territory, males earn more than females, with the gender pay gap most pronounced in WA and ACT. National average earnings sit just below NSW’s total, and both Victoria and SA fall behind most other mainland states.

This data is valuable to a wide range of audiences. Government agencies use it to inform wage policy, economic planning, and social services. Economists and researchers rely on it to track wage trends and inflation. Businesses and HR professionals apply it for salary benchmarking and workforce strategy. Unions and advocacy groups assess equity and negotiate fair pay, while the general public uses it to understand income patterns and cost-of-living pressures.

The Average weekly earnings data by industry and gender simplifies complex wage information, allowing viewers to quickly identify which sectors pay the most or least, how earnings differ by gender, and where the largest pay gaps exist. Mining stands out as the highest-paid industry with a significant gender disparity, while retail and hospitality rank lowest with narrower gaps. High-paying sectors like finance and professional services elevate the national average. This visual storytelling supports policymakers, researchers, and the public in spotting wage inequalities, tracking trends, and making informed decisions.

Most industries show very low quarterly contribution (Y = 0), indicating minimal impact on overall wage pressure. These sectors may have stable or stagnant wage growth (eg:Public administration and safety).Some show minimal quarterly wage contribution, clustering near the bottom of the plot, indicating limited impact on overall wage pressure. A few sectors, those with both high Average Weekly Earnings (AWE) and elevated quarterly contributions, stand out as key drivers of wage growth, typically positioned in the top-right quadrant. These industries, such as mining and finance, exert greater influence on national wage trends due to their higher earnings and stronger wage momentum.

When wages rise in key sectors without matching productivity improvements, businesses face higher labour costs that often translate into increased prices for goods and services, this is known as cost push inflation. At the same time,higher household incomes can boost consumer demand, driving demand-pull inflation if supply doesn’t keep pace.These twin pressures elevate overall inflation, prompting central banks to raise interest rates to cool spending and borrowing. For households, this policy response increases financial strain on households by raising everyday costs and debt repayments, shrinking disposable income and weakening purchasing power..