Data source explanation
What is the Federal Reserve DFA?
The Federal Reserve Distributional Financial Accounts, or DFA, are a public data source that helps show how wealth is distributed across different groups of households.
This kind of data is important because the Wealth Reform Project is not only concerned with income. It is also concerned with ownership: who owns assets, who carries debts, and how wealth changes over time.
Why it matters
Wealth affects economic security. A household with savings, home equity, retirement assets, or business ownership has more options than a household living paycheck to paycheck.
DFA data can help the project ask questions such as:
- How much wealth is held by the top 1 percent?
- How much wealth is held by the bottom 50 percent?
- How has wealth concentration changed over time?
- Which types of assets are most concentrated?
- How much household debt is carried by different groups?
Useful categories
The most useful parts of the DFA for this project will likely include household net worth, assets, liabilities, real estate, corporate equities, retirement assets, and consumer debt.
| Category | Why It Matters |
|---|---|
| Net worth | Shows total household wealth after subtracting debts. |
| Real estate | Shows the role of housing and home equity in wealth building. |
| Corporate equities | Shows who benefits most from stock ownership and market growth. |
| Retirement assets | Shows long-term security and uneven access to retirement wealth. |
| Liabilities | Shows how debt affects household financial position. |
How this source will be used
The first use of this source should be a simple chart showing wealth shares over time. For example, the project could compare the top 1 percent, the next 9 percent, the middle 40 percent, and the bottom 50 percent.
Later, this data can support research articles and proposal analysis. For example, it may help evaluate whether a reform actually broadens ownership or merely changes income temporarily.
Current project status
This source has been identified as a priority data source. The next step is to download a sample file, inspect the fields, and decide which series should be used for the first chart.