$0.02
per call · USD Coin on Base
Building permits (Census, monthly): latest print, revisions, surprise — Latest Building permits print from the Census via FRED/ALFRED: first-release vs latest value with a revised flag (revisions never pose as print-day numbers), surprise vs a labeled expectation (market-implied when a matching prediction market exists, else trend-model), next monthly release date, and a 12-observation mini-series. Same shape as /v1/econ/:series bound to building-permits.
Endpoint
GET https://x402-factory.com/v1/econ/building-permits3
Calls / 30d
1
Unique payers / 30d
Sep 1
Last called
exact
Payment scheme
Call this service
import { wrapFetchWithPayment } from "@x402/fetch";
import { privateKeyToAccount } from "viem/accounts";
const account = privateKeyToAccount(process.env.PRIVATE_KEY);
const fetchWithPay = wrapFetchWithPayment(fetch, account);
const res = await fetchWithPay("https://x402-factory.com/v1/econ/building-permits", {
method: "GET",
});
const data = await res.json();curl -X GET \
"https://x402-factory.com/v1/econ/building-permits" \
-H "X-PAYMENT: <signed x402 payment>"Example response
{
"data": {
"fred_id": "PERMIT",
"frequency": "Monthly",
"latest_print": {
"first_release_value": 1367,
"first_released_on": "2026-07-17",
"headline": 1367,
"headline_basis": "first release level",
"headline_units": "thousands",
"latest_value": 1374,
"obs_date": "2026-06-01",
"revised": true
},
"next_release_date": "2026-08-18",
"recent": [
{
"obs_date": "2025-07-01",
"value": 1400
},
{
"obs_date": "2025-08-01",
"value": 1347
},
{
"obs_date": "2025-09-01",
"value": 1444
},
{
"obs_date": "2025-10-01",
"value": 1418
},
{
"obs_date": "2025-11-01",
"value": 1414
},
{
"obs_date": "2025-12-01",
"value": 1482
},
{
"obs_date": "2026-01-01",
"value": 1393
},
{
"obs_date": "2026-02-01",
"value": 1540
},
{
"obs_date": "2026-03-01",
"value": 1363
},
{
"obs_date": "2026-04-01",
"value": 1423
},
{
"obs_date": "2026-05-01",
"value": 1410
},
{
"obs_date": "2026-06-01",
"value": 1374
}
],
"release_name": "New Residential Construction",
"revisions": [
{
"first_value": 1367,
"latest_value": 1374,
"obs_date": "2026-06-01"
},
{
"first_value": 1413,
"latest_value": 1410,
"obs_date": "2026-05-01"
},
{
"first_value": 1442,
"latest_value": 1423,
"obs_date": "2026-04-01"
}
],
"series": "building-permits",
"source_agency": "U.S. Census Bureau",
"surprise": {
"actual": 1367,
"expectation_detail": "trend-model: mean of prior 3 levels",
"expectation_source": "trend-model",
"expected": 1398.7,
"surprise": -31.7
},
"title": "Building Permits (SAAR)",
"units": "Thousands of Units"
},
"meta": {
"data_mode": "live",
"docs": "https://x402-factory.com/docs/econ.series.building-permits",
"endpoint": "/v1/econ/building-permits",
"freshness": "daily",
"generated_at": "2026-09-01T09:36:54.287Z",
"request_id": "req_00000000",
"sources": [
"fred"
],
"version": "1.0.0"
}
}Payment details
0xcc42ed39a06b6cf3f484307ef76b88bf56fb305fUSD Coin · 0x833589fcd6edb6e08f4c7c32d4f71b54bda02913Is this your API?
Pin it to the top of Developer Tools and the homepage with a featured placement.
More from x402-factory & similar services
x402-factory · Evergreen Presidential Election Winner Party
x402-factory.com
Live probability: Which party wins the next US presidential election? — Stable evergreen URL for a recurring question: Which party wins the next US presidential election? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.
x402-factory · Ping
x402-factory.com
Cheapest endpoint: liveness plus x402 payment pipeline check — Returns ok with the server time and whether this call was paid. Use it to verify your x402 client end to end before spending on data endpoints.
x402-factory · Edge Backtest
x402-factory.com
Historical performance of the edge signal: hit rate, calibration, by hazard — Aggregates stored edge signals whose markets have resolved: how often the model beat the market (hit rate), average absolute-error improvement (edge captured), a model calibration curve, and per-hazard breakdowns. model_label is explicit about which model produced the signals.