---
license: mit
---
# 💸 U.S. Federal Outlays Dataset – Budget Execution in Action


**Maintainer**: [Terry Eppler](https://gravatar.com/terryepplerphd)  
**Source**: Office of Management and Budget (OMB), U.S. Department of the Treasury  
**Standards**: OMB Circular A-11, DATA Act (Pub. L. 113–101), Treasury GTAS

---

## 🧾 What Are Federal Outlays?

**Federal outlays** are the **actual disbursements of funds** by the U.S. federal government. They occur when the Treasury **issues a payment** to satisfy obligations — such as:
- Social Security checks 💰
- Grant disbursements to states and localities 🏛️
- Contractor payments for defense, construction, and services ⚙️
- Interest on the national debt 📉

They are the most definitive reflection of **what money actually leaves the Treasury**.

---

## 🎯 Purpose of This Dataset

This dataset provides **federal outlays by agency, account, program, and function** to support:

- 📊 Budget execution tracking
- 🧠 Economic forecasting and modeling
- 🔍 Transparency and accountability
- 🧪 Machine learning and AI research in public finance
- 🏗️ Infrastructure and stimulus tracking

---

## 📦 Dataset Structure

| Column Name | Description |
|-------------|-------------|
| `fiscal_year` | Fiscal year (e.g., 2023) |
| `period` | Month or quarter (e.g., 12 = year-end) |
| `agency_code` | Treasury 3-digit agency ID |
| `main_account_code` | 4-digit Treasury account code |
| `tas` | Treasury Appropriation Fund Symbol |
| `gross_outlay_amount` | Cumulative amount paid from account |
| `object_class` | Type of expenditure (e.g., personnel, contracts) |
| `program_activity` | Linked to budget function and purpose |
| `recipient_type` | (if award-linked) e.g., business, nonprofit |
| `geo_location` | State or region of outlay (if known) |

---

## 🔍 Why Outlays Matter

Federal outlays are:

| Use Case | Description |
|----------|-------------|
| 🧮 **Budget Enforcement** | Key metric for scoring legislation and tracking actual spending |
| 📉 **Deficit Analysis** | Outlays – Receipts = Deficit |
| 🌎 **Macroeconomic Modeling** | Impact of federal spending on GDP, employment, inflation |
| 🛠️ **Policy Evaluation** | See if programs are delivering on their funding levels |
| 📊 **Transparency** | Public insight via [USAspending.gov](https://www.usaspending.gov) |

---

## 🛠 Example: Visualizing Outlay Trends

```python
from datasets import load_dataset
import matplotlib.pyplot as plt

ds = load_dataset("your-org/federal-outlays")

# Filter for Department of Health and Human Services
hhs = ds.filter(lambda x: x["agency_code"] == "075")

# Sum outlays by fiscal year
import pandas as pd
df = pd.DataFrame(hhs)
summary = df.groupby("fiscal_year")["gross_outlay_amount"].sum()

# Plot it
summary.plot(kind="bar", title="HHS Outlays by Fiscal Year")
plt.ylabel("USD ($ Billions)")
plt.show()