US state retail-demand panel (52 geographies x 12 sectors)
Monthly US state retail-demand panel, 2019-01 onward, for 52 geographies (50 states + District of Columbia + the USA national aggregate) x 12 retail measures (Total retail sales excluding nonstore retailers + the 11 NAICS 3-digit retail subsectors): the Census Monthly State Retail Sales year-over-year percent change (not seasonally adjusted), redistributed by FRED as MSRS<STATE><SECTOR> series, with YoY acceleration, 3-month trend, deviation from the national sector, a documented 0-100 demand-pressure score, per-month-x-sector demand ranks, d1..d4 demand tiers, and contraction/soft/steady/strong/booming demand regimes. MSRS is an experimental modeled Census product (Monthly Retail Trade Survey + administrative + third-party data) released with a ~4-month lag; series are complete by construction except one documented upstream gap — 2020-05 for the clothing sector (blank on FRED, the COVID retail shutdown), kept as honest nulls — and small-state niche sectors have genuine interior gaps (e.g. Alaska sporting-goods blank 2025-05..2025-09) and genuine discontinuations (Alabama sporting-goods ends 2026-01), also kept as honest nulls. The fail-loud gates guard the FEED's liveness (global latest month within 200 days) and structure (closed 624-series world, no duplicates, implausible-value bound), not per-series recency or interior completeness. One row per state x sector x month; join keys: state_code, sector_code, year_month, country_code=USA. Who joins this: Shopify shops join demand_pressure_score on month + state + sector to forecast category demand and time promos; subscription businesses use state retail demand as a consumer-strain churn feature; sales teams rank territories by retail vitality.
- Rows
- 55,531
- Columns
- 17
- Source cadence
- Monthly
- Last refreshed
- Sep 30, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| month | date | First day of the calendar month. (unit: date) |
| year_month | string | Calendar month as YYYY-MM (panel join key). (unit: string) |
| state_code | string | 2-letter postal state code (panel join key); 'USA' is the national aggregate, which serves as the benchmark and is excluded from the peer group. (unit: string) |
| state_name | string | State / District / national name. (unit: string) |
| country | string | Country name (shared normalization layer). (unit: string) |
| country_code | string | ISO 3166-1 alpha-3 country code (USA). (unit: string) |
| sector_code | string | Retail sector code (panel join key): 'TOTAL' for total retail sales excluding nonstore retailers, otherwise the NAICS 3-digit subsector code (441, 442, 443, 444, 445, 446, 447, 448, 451, 452, 453). (unit: string) |
| sector_name | string | NAICS retail subsector name (Census MSRS). (unit: string) |
| yoy_pct | float | Published Census MSRS year-over-year percent change of retail sales, not seasonally adjusted (percent). MSRS is an experimental modeled product (Monthly Retail Trade Survey + administrative + third-party data); released with a ~4-month lag. One genuine upstream gap is kept as null, never imputed: 2020-05 for the clothing sector (blank on FRED — the COVID retail shutdown). Extreme values are genuine upstream observations, never winsorized (e.g. +7848.4% for Alaska general merchandise in 2021-04 — a near-zero COVID base, verified on FRED). (unit: percent) |
| yoy_accel_pp | float | Change of the YoY rate versus the same month a year earlier (percentage points): positive = demand accelerating, negative = decelerating. Null until a 12-months-ago observation exists. (unit: percentage points) |
| yoy_trend_3m | float | Trailing 3-month mean of yoy_pct (minimum 2 observations; percent). (unit: percent) |
| yoy_vs_national_pp | float | State-sector YoY minus the USA-sector YoY for the same month (percentage points). Null for USA rows — the national aggregate is the benchmark, not a peer. (unit: percentage points) |
| demand_pressure_score | float | 0-100 min-max rescaling of yoy_pct within the (month x sector) peer group across the 51 states + DC (100 = strongest YoY demand that month in that sector; degenerate month -> 50). Null for USA rows. (unit: score 0-100) |
| demand_rank | integer | Rank of yoy_pct within the (month x sector) peer group across the 51 states + DC (1 = strongest demand; dense ranking — ties share a rank). Null for USA rows and when fewer than 2 states report that month. (unit: rank) |
| demand_tier | string | Within-(month x sector) demand quartile from demand_rank: d1 (weakest) to d4 (strongest). Null for USA rows. (unit: string) |
| demand_regime | string | Fixed YoY demand bands: contraction (<0%), soft (0-2%), steady (2-5%), strong (5-10%), booming (>=10%). (unit: string) |
| row_hash | string | Deterministic 16-hex sha256 of state_code + sector_code + year_month + yoy_pct (idempotency key). (unit: string) |
First 10 sample rows — a preview, not the complete dataset.
| month | year_month | state_code | state_name | country | country_code | sector_code | sector_name | yoy_pct | yoy_accel_pp | yoy_trend_3m | yoy_vs_national_pp | demand_pressure_score | demand_rank | demand_tier | demand_regime | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-01-01 | 2019-01 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -1.7 | — | — | -1.6 | 21.311 | 25 | d3 | contraction | edd17b215ea4e619 |
| 2019-02-01 | 2019-02 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | 2.4 | — | 0.35 | 2.1 | 35.165 | 7 | d4 | steady | ca0caa511e35c842 |
| 2019-03-01 | 2019-03 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -4.8 | — | -1.367 | -5.5 | 2.857 | 34 | d2 | contraction | bb396b83ab06a94f |
| 2019-04-01 | 2019-04 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | 3.5 | — | 0.367 | -0.6 | 22.174 | 20 | d3 | steady | ff0f31bef3133a60 |
| 2019-05-01 | 2019-05 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -1.2 | — | -0.833 | -3.6 | 6.18 | 35 | d2 | contraction | cea56a4a10baff19 |
| 2019-06-01 | 2019-06 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -4 | — | -0.567 | -3.8 | 16.749 | 37 | d2 | contraction | 7882035f8a727552 |
| 2019-07-01 | 2019-07 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -4.5 | — | -3.233 | -9.7 | 0 | 35 | d2 | contraction | 7ac14400001d1461 |
| 2019-08-01 | 2019-08 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -4.1 | — | -4.2 | -9.5 | 0 | 35 | d2 | contraction | 03301e2c59977d6d |
| 2019-09-01 | 2019-09 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -5.9 | — | -4.833 | -9.1 | 0 | 36 | d2 | contraction | 809025400290c520 |
| 2019-10-01 | 2019-10 | AK | Alaska | United States | USA | 441 | Motor vehicle and parts dealers | -0.3 | — | -3.433 | -4.2 | 30.909 | 37 | d2 | contraction | a45cc460fd210b2b |
- Current
20260930T014815Z-5ab7bcba340e · sha256 5ab7bcba340e…
55,531 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/census_msrs_retail_demand_intel/us_state_retail_demand_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/census_msrs_retail_demand_intel/us_state_retail_demand_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/census_msrs_retail_demand_intel/us_state_retail_demand_monthly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260930T014815Z-5ab7bcba340e and its content hash, so readers get exactly the data you used.
US State Retail Demand (Census MSRS via FRED, keyless). (2026). US state retail-demand panel (52 geographies x 12 sectors) [Data set, snapshot 20260930T014815Z-5ab7bcba340e, sha256 5ab7bcba340e]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/en/datasets/census_msrs_retail_demand_intel/us_state_retail_demand_monthly?snapshot=20260930T014815Z-5ab7bcba340e
@misc{dz_census_msrs_retail_demand_intel_us_state_5ab7bcba,
title = {{US state retail-demand panel (52 geographies x 12 sectors)}},
author = {{US State Retail Demand (Census MSRS via FRED, keyless)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/census_msrs_retail_demand_intel/us_state_retail_demand_monthly?snapshot=20260930T014815Z-5ab7bcba340e}},
note = {Snapshot 20260930T014815Z-5ab7bcba340e, sha256 5ab7bcba340e97bf9601f4ea49d7505d61ce79a307027906e267fe8527df8753; accessed 2026-09-30}
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<iframe src="https://datazimuts.com/embed/chart?dataset=census_msrs_retail_demand_intel%2Fus_state_retail_demand_monthly&lang=en&theme=auto&snapshot=20260930T014815Z-5ab7bcba340e&x=year_month&y=yoy_pct&agg=avg" title="US state retail-demand panel (52 geographies x 12 sectors)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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