2025 Update: Introducing the THIAs: Total Haig-Simons U.S. Household Income, Consumption, and Wealth Accounts, 1960–2023
Bibliographic record
Abstract
This paper presents the Total Haig-Simons U.S. Household Income Accounts (THIAs), an open-access data set providing balance-sheet-complete measures of income, saving, and wealth accumulation for U.S. households from 1960 to 2023, with prototype distributional estimates for all measures by income quintile since 2000. By integrating NIPA income and saving measures with accrued Holding Gains and Other Volume Changes from the Integrated Macroeconomic Accounts (IMAs), the THIAs construct integrated Haig-Simons income series for use by researchers. Distributional analysis reveals that 86% of Total saving over the past quarter century accrued to the top 20% of households, driven by disproportionate exposure to asset-price appreciation and significantly lower propensities to consume. The data set enables researchers to examine inequality dynamics through a fully integrated income-consumption-wealth lens, addressing researchers’ methodological calls for integrated “3D” national accounts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".