What program-level data exist to map federal taxes paid by residents of one state to federal spending received elsewhere?

1. What raw data are available and where they come from

The basic inputs for any mapping exercise are federal revenue tallies by state and federal outlays by location; gross tax collections by state are compiled and published (IRS-based tables summarized on Wikipedia) showing collections of individual, corporate, payroll, estate, gift and excise taxes by state and territory ^[1], while federal spending by recipient location can be drawn from federal outlay datasets and portals such as the Rockefeller Institute’s Balance of Payments portal and the federal spending data hosted by USAspending.gov ^{[2] [4]}.

2. How researchers construct state-level “balance of payments” maps

Analysts merge per‑state tax receipts with spending flows to estimate a balance of payments: examples include Rockefeller Institute’s portal and media visualizations that present outflows and inflows per capita or in aggregate, showing which states are net contributors or beneficiaries ^{[2] [5] [6]}. These studies typically allocate pensions, social benefits, federal wages, grants, procurement contracts and defense spending to states based on administrative records (contractor location, payroll address, recipient address), then compare those outlays to tax collections attributed to residents ^{[6] [5]}.

3. What program-level granularity exists and its limits

Program-level data exist in specific federal administrative systems—Social Security and Medicare benefit records, federal employee payroll, grants databases, and procurement records—that can be aggregated by state, and those are the building blocks used in public exercises ^{[6] [4]}. However, combining them into a deterministic “A paid, B received” trail faces conceptual and methodological limits: tax collections are tied to taxpayers’ filing addresses or employer locations while benefits and contracts may be allocated by recipient address or the physical location of a project, producing mismatches; researchers therefore use attribution rules and approximations rather than a one‑to‑one audit trail ^{[6] [1]}.

4. Common methodological choices and contentious assumptions

Choices about what counts as “received” drive different portraits: some analyses emphasize direct benefits (like SNAP, Medicare) while others include defense contracting and federal wages—two decisions that tilt results toward states with military bases or large contractor presences ^{[6] [5]}. Advocacy and commercial sites may emphasize per‑capita returns or political narratives—HowMuch and SmartAsset frame net receipts as “getting more back,” a rhetorical choice that reflects their dataset and framing rather than a single objective truth ^{[7] [8]}. The constitutional note that direct taxes historically were to be apportioned by population underlies debates about fairness, though modern federal taxation is largely indirect and regionally uneven ^[9].

5. Practical pathways for someone who wants program-level mappings

The pragmatic route is to start with IRS gross collections by state and then layer program-level outlays from agency records: Social Security/Medicare payment files, grants and loans databases, federal payroll, and procurement records accessible via USAspending or agency sites; Rockefeller Institute and academic teams have already published balance of payments compilations that can be inspected and reweighted ^{[1] [4] [2]}. Users should expect to make and document allocation assumptions—how to assign multi‑state contracts, how to treat federal tax expenditures and corporate taxes—because those choices materially alter net contributor/beneficiary lists ^{[6] [3]}.

6. Bottom line and transparency caveats

There is enough program-level and administrative data to build credible estimates showing how taxes paid by residents of State A compare to federal spending located in State B, and respected compilations exist (Rockefeller Institute, media analyses), but no single authoritative dataset traces individual tax dollars end‑to‑end; results depend on allocation rules, the selection of programs included, and sometimes the policy or editorial aims of the publisher ^{[2] [5] [7]}. Where sources disagree, they often reflect different methodological choices rather than factual errors, so transparency about those choices is the most reliable way to assess competing maps ^{[6] [3]}.