Esri has made exciting improvements to its current (2025/2030) household income estimates that provide a clearer picture of income distributions across the United States. This overview highlights new income categories, new methods for calculating aggregate income, and the implications for income-related data such as disposable income, net worth, and the wealth index.
Expanded Income Categories
One of the most significant changes is the expansion of household income categories from nine to twenty intervals. This change allows for a more detailed analysis, especially for households earning over $200,000, which are now divided into five distinct categories.
Using the chart below, here’s a quick look at the changes:
New income intervals are displayed as white boxes, while summary intervals are shown in blue boxes. Summary intervals are consistent with the previous year’s income data estimates. New intervals are nested within the original intervals, enabling backwards compatibility and comparisons. Summary intervals are made available to allow users ample time to transition to the expanded income categories.
Mapping extended income data ranges
Let’s explore the concentration of households earning more than $500,000 in comparison to those earning over $200,000 in 2025. The maps below illustrate the predominant income brackets in the greater New York area.
Figure 1 shown below highlights areas in pink where households earn $200,000 or more, with large sections of Manhattan and Brooklyn noted for high-income concentrations.
Figure 1
Figure 2 shown below uses the new extended income intervals for households earning $500,000 or more in 2025. Notice how it reveals even more detail with areas shaded in purple and blue indicating very high incomes.
Figure 2
Improved Summary Statistics Calculations
As household income categories are expanded and aggregate income calculations improved, it is expected that Esri’s summary statistics will experience significant changes. Esri has recalibrated its methods for calculating median, average, and per capita income to capture detail provided by the new 20-interval income distribution. Following is a highlight of what has been improved with each summary statistic measure:
Median Income
Median Income is calculated using Pareto interpolation, which is sensitive to the number of intervals. This means the shift to twenty intervals yields different and more precise results, especially in areas with high concentrations of households at the tails of the income distribution.
Average Income
Aggregate Income, which is necessary to calculate average income, refers to the total income earned by all households in a specific area. Esri calculates this by summing incomes of all households using a midpoint approach for income intervals and a representative income value for each household within an interval. Average income is then calculated by dividing the aggregate income by the total number of households.
Esri’s Average Income calculations have three key improvements
1. Midpoint Methodology
Esri recalibrated its midpoints to align with reported small-area data rather than relying on broad socio-economic patterns and groupings. This means average income is now influenced by more localized data, enhancing accuracy.
2. Impact of Interval Changes
The increase in intervals affects average income calculations because midpoints are bound by the low and high of each interval. With more detailed intervals, average income can better reflect the full distribution of income.
3. Uppermost Intervals
For households earning over $500,000, (the uppermost interval), Esri employs modeling techniques to estimate the midpoint. The change in top-coded intervals from $200,000 to $500,000 shifts more households into bounded intervals and reduces the number of households in the last interval which improves the accuracy of average income estimates.
Per capita income
Per capita Income is calculated as the sum of aggregate household income plus the income attributed to non-household (such as dorms and nursing homes) population. New methods now align income for non-household population to reported small area estimates while smoothing inconsistencies in the source data. Improvements in the aggregate household income model are reflected in per capita income estimates.
Income Tiers and Inequality Measures
To provide a clearer understanding of income distributions, Esri has categorized households into lower, middle, and upper tiers, along with a comprehensive suite of income inequality measures. These metrics are built upon Esri Updated Demographics’ current and forecast year estimates of households by income. The 2025/2030 income tiers and inequality calculations are based on the new twenty-income intervals. With the uppermost interval at $500,000 (compared to $200,000 previously), more detail is available to inform these measures. Care should be taken when comparing these with earlier data releases, particularly in areas with high concentrations of incomes over $200,000. Share ratios are also influenced by improvements to the aggregate income estimates. These metrics are built upon Esri Updated Demographics’ current and forecast year estimates of households by income.
Implications for Other Related Tables
The enhancements to the household income model also impact related tables such as age by income, disposable income, net worth, and the wealth index.
Listed below is a highlight of what is new and improved with each related statistic measure.
Esri continues to estimate household income by age using the previous nine income intervals and seven age of householder groups. The average estimates for household income by age remain consistent with the overall household income, meaning the sum of aggregate income for each of the seven age groups adds up to total aggregate income. Improvements made to the aggregate and average income calculations for total income are therefore reflected in the breakdown by age. Differences are most apparent in age groups with concentrations of households in the highest and lowest intervals.
Esri’s disposable income estimates still use nine brackets and seven age of householder groups. Average disposable income estimates also build on midpoints developed in the household income model. Improvements to the household income midpoints are adopted in the calculation of average disposable income. Midpoints are now constructed by using local data more directly, rather than being stratified by socio-demographic grouping.
Esri age by household income data and tenure data are used as the foundation for the net worth estimates. For the 2025 dataset, the net worth estimation leverages the new household income estimates to enhance the model for high-income households. The intervals reported have not changed.
Esri’s wealth index compiles various indicators of affluence, including average household income and average net worth. With improved methodologies for average calculations, and the availability of more detailed income breaks, trends in the wealth index do show a break from the past.
Note that disposable income, net worth and wealth index are not included in Esri’s five-year forecasts.
Additional Resources
To learn more about Esri’s household income and methodologies, explore the following resources:
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