US state business conditions, biweekly (Census BTOS)

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Biweekly business-conditions intelligence for the 50 US states, DC, Puerto Rico and the BTOS multi-unit national grouping, from the Census Bureau Business Trends and Outlook Survey (~1.2M employer businesses): the 15 published BTOS diffusion indexes (current performance, revenues, demand, employees, hours, input/output prices, delivery time, plus 6-month outlooks) as idx_* columns, one row per (state, biweekly cycle), cycles 202319 to latest (Sep 2023 -> Sep 2026), each joined to its survey reference-period dates. Disclosure-suppressed cells are explicit nulls (never imputed; cycles 202521-202523 were hit by the Oct-Nov 2025 federal funding lapse). Adds three documented composite scores (current-conditions, outlook, business-health), their cycle-over-cycle momentum, per-cycle health ranks and tiers, trailing-year z-scores and expansion/contraction flags — a (date, state) demand driver for retail forecasting, churn models and territory planning. BTOS is the fastest official read on Main-Street conditions, biweekly where monthly series lag by weeks.

Source: U.S. Census Bureau Business Trends and Outlook Survey (BTOS) — state business-conditions intelligence
Rows: 4,187
Columns: 34
Source cadence: Weekly
Last refreshed: Oct 1, 2026
Theme: economy

Column	Type	Description
state_code	string	BTOS state code: 50 states + DC + PR + XX.
state_name	string	State / grouping name.
geo_type	string	'state' \| 'district' (DC) \| 'territory' (PR) \| 'multiunit_national' (XX: BTOS multi-unit companies national grouping, not a geography).
country_code	string	ISO alpha-3: USA (PRI for Puerto Rico).
cycle	string	BTOS biweekly cycle label YYYYPP (PP = 01..26 biweekly periods per year).
ref_period_start	date	Reference-period start: the survey's prior-two-week reference window.
ref_period_end	date	Reference-period end (join key for demand).
idx_current_performance	float	BTOS diffusion index 'Current performance' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_delivery_time	float	BTOS diffusion index 'Delivery time' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_demand	float	BTOS diffusion index 'Demand' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_employees	float	BTOS diffusion index 'Employees' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_delivery_time	float	BTOS diffusion index 'Future delivery time' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_demand	float	BTOS diffusion index 'Future demand' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_employees	float	BTOS diffusion index 'Future employees' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_hours	float	BTOS diffusion index 'Future hours' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_input_prices	float	BTOS diffusion index 'Future input prices' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_output_prices	float	BTOS diffusion index 'Future output prices' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_future_performance	float	BTOS diffusion index 'Future performance' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_hours	float	BTOS diffusion index 'Hours' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_input_prices	float	BTOS diffusion index 'Input prices' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_output_prices	float	BTOS diffusion index 'Output prices' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
idx_revenues	float	BTOS diffusion index 'Revenues' (0-100; 50 = neutral; 100(1p_increase + 0.5*p_same)). Null = disclosure-suppressed upstream.
current_conditions_score	float	Documented composite: mean(idx_current_performance, idx_revenues, idx_demand, idx_employees, idx_hours). Null unless all five components are non-null.
outlook_score	float	Documented composite: mean of the four future idx_* columns. Null unless all four are non-null.
business_health_score	float	Documented composite: mean(current_conditions_score, outlook_score). Null unless both are non-null.
current_mom_pp	float	Cycle-over-cycle change (points) of current_conditions_score per state; null on the base cycle.
outlook_mom_pp	float	Cycle-over-cycle change (points) of outlook_score per state; null on the base cycle.
health_mom_pp	float	Cycle-over-cycle change (points) of business_health_score per state; null on the base cycle.
health_rank	integer	Per-cycle competition rank of business_health_score across geos (1 = healthiest).
health_tier	integer	Fixed-cut tier on business_health_score: 4 strong (>= 55), 3 firm (>= 52), 2 soft (>= 50), 1 weak (< 50).
health_zscore_1y	float	business_health_score vs trailing-26-cycle mean/std per state (min 8 obs); null during warmup.
expanding_flag	boolean	True when business_health_score >= 52; null when the composite is null.
contracting_flag	boolean	True when business_health_score < 48; null when the composite is null.
row_hash	string	Deterministic 16-hex sha256 over 'BTOS\|<state_code>\|<cycle>'.

First 10 sample rows — a preview, not the complete dataset.

state_code	state_name	geo_type	country_code	cycle	ref_period_start	ref_period_end	idx_current_performance	idx_delivery_time	idx_demand	idx_employees	idx_future_delivery_time	idx_future_demand	idx_future_employees	idx_future_hours	idx_future_input_prices	idx_future_output_prices	idx_future_performance	idx_hours	idx_input_prices	idx_output_prices	idx_revenues	current_conditions_score	outlook_score	business_health_score	current_mom_pp	outlook_mom_pp	health_mom_pp	health_rank	health_tier	health_zscore_1y	expanding_flag	contracting_flag	row_hash
AK	Alaska	state	USA	202319	2023-08-28	2023-09-10	62	55.2	40.8	39.4	59.3	52.8	47.7	44.4	82.1	66.2	59.1	39.6	74.2	54.1	34.5	43.26	51	47.13	—	—	—	53	1	—	false	true	e4043a94349b9751
AK	Alaska	state	USA	202320	2023-09-11	2023-09-24	55.3	50.7	43	45	53.4	52.6	52.3	42.9	82.1	68	52.2	42.6	71.2	52.1	37.6	44.7	50	47.35	1.44	-1	0.22	53	1	—	false	true	3321eb0c5be21f9c
AK	Alaska	state	USA	202321	2023-09-25	2023-10-08	62.8	53.5	50.1	48	56.1	53.7	53.8	48.4	78.3	66.1	57.5	46.4	65.4	50.9	48.4	51.14	53.35	52.245	6.44	3.35	4.895	6	3	—	true	false	171b7097696bebd6
AK	Alaska	state	USA	202322	2023-10-09	2023-10-22	57.4	54.4	43.3	47.2	57.8	56	53.4	52.3	78.3	68	55.1	45	60.2	54.9	46.1	47.8	54.2	51	-3.34	0.85	-1.245	26	2	—	false	false	30158299a1cd943b
AK	Alaska	state	USA	202323	2023-10-23	2023-11-05	59.4	57.2	41.6	45.9	56.4	56.2	53.7	53	82.3	66.6	53	43.4	69.4	57.2	35	45.06	53.975	49.518	-2.74	-0.225	-1.483	42	1	—	false	false	75c6c05bad48c0ac
AK	Alaska	state	USA	202324	2023-11-06	2023-11-19	58	55	43.2	46.7	55.4	62.5	57.3	59.5	78	68.6	54	42.7	68.8	55.7	40.9	46.3	58.325	52.313	1.24	4.35	2.795	5	3	—	true	false	21aa7f22d8150b06
AK	Alaska	state	USA	202325	2023-11-20	2023-12-03	59.8	61.2	44.9	45.9	51.7	59.1	58.5	56.3	76.4	68.4	59.9	43.5	66.1	54.1	42.3	47.28	58.45	52.865	0.98	0.125	0.553	3	3	—	true	false	d04dc58ccd3d8e9d
AK	Alaska	state	USA	202326	2023-12-04	2023-12-17	56.3	56.3	46.6	48.7	49.5	66	59.7	62.6	80.2	65.6	59.2	47.7	65.1	56	47.8	49.42	61.875	55.647	2.14	3.425	2.782	2	4	1.6	true	false	4a399aa6a6941528
AK	Alaska	state	USA	202401	2023-12-18	2023-12-31	59.2	61.6	45.8	46.1	58.8	62.3	57.5	60.9	69.6	64.7	58.4	38.5	63.8	53	40.2	45.96	59.775	52.867	-3.46	-2.1	-2.78	4	3	0.594	true	false	80344da108d637bf
AK	Alaska	state	USA	202402	2024-01-01	2024-01-14	55.5	53.9	42.2	44.7	42.6	53.8	58.8	57.8	76.1	66	53.7	43.6	71.1	56.9	38.1	44.82	56.025	50.423	-1.14	-3.75	-2.445	26	2	-0.271	false	false	392cbe724b2fd8b9

Profiled Oct 1, 2026 from snapshot 20261001T230958Z-b14a7a65f768

Measured

Completeness: 96.6%
Rows: 4,187
Columns: 34
Columns with gaps: 26

Rows per yearref_period_start · 2023–2026 · 4 years

20232026

Column	Missing	Distinct	Range	Distribution
state_codevarchar	0%	58	—	AK79 AL79 AR79
state_namevarchar	0%	60	—	Alabama79 Alaska79 Arizona79
geo_typevarchar	0%	3	—	state3,950 district79 multiunit_national79
country_codevarchar	0%	2	—	USA4,108 PRI79
cyclevarchar	0%	77	—	20231953 20232053 20232153
ref_period_startdate	0%	100	Aug 28, 2023 → Aug 24, 2026	—
ref_period_enddate	0%	91	Sep 10, 2023 → Sep 6, 2026	—
idx_current_performancedouble	3.8%	243	44 → 69median 55.4	82 outside 1st–99th percentile
idx_delivery_timedouble	3.8%	167	36.7 → 65.7median 52.7	81 outside 1st–99th percentile
idx_demanddouble	3.8%	217	32.5 → 59.4median 44.8	81 outside 1st–99th percentile
idx_employeesdouble	3.8%	146	38 → 58median 47.9	77 outside 1st–99th percentile
idx_future_delivery_timedouble	3.8%	184	39 → 69.8median 53	78 outside 1st–99th percentile
idx_future_demanddouble	3.8%	304	35.8 → 70.2median 54	81 outside 1st–99th percentile
idx_future_employeesdouble	3.8%	217	39.4 → 67.1median 52.4	81 outside 1st–99th percentile
idx_future_hoursdouble	3.8%	250	36.6 → 66.9median 51.75	79 outside 1st–99th percentile
idx_future_input_pricesdouble	3.8%	204	60.5 → 90.7median 75.2	82 outside 1st–99th percentile
idx_future_output_pricesdouble	3.8%	206	50.9 → 77.2median 64.5	79 outside 1st–99th percentile
idx_future_performancedouble	3.8%	204	45.4 → 68.6median 55.2	81 outside 1st–99th percentile
idx_hoursdouble	3.8%	214	32.4 → 57.4median 46.3	77 outside 1st–99th percentile
idx_input_pricesdouble	3.8%	213	52.8 → 87.3median 68.1	82 outside 1st–99th percentile
idx_output_pricesdouble	3.8%	148	43.4 → 68.1median 55.2	80 outside 1st–99th percentile
idx_revenuesdouble	3.8%	246	27.4 → 57.1median 42.2	80 outside 1st–99th percentile
current_conditions_scoredouble	3.8%	1,061	38.3 → 56.46median 47.32	82 outside 1st–99th percentile
outlook_scoredouble	3.8%	1,140	41.8 → 64.93median 53.35	80 outside 1st–99th percentile
business_health_scoredouble	3.8%	3,253	42.5 → 59.53median 50.43	82 outside 1st–99th percentile
current_mom_ppdouble	6.3%	1,502	-11.84 → 9.8median 0.02	80 outside 1st–99th percentile
outlook_mom_ppdouble	6.3%	1,119	-12.13 → 11.25median 0	80 outside 1st–99th percentile
health_mom_ppdouble	6.3%	2,812	-9.51 → 8.5median -0.0088	80 outside 1st–99th percentile
health_rankbigint	3.8%	47	1 → 53median 27
health_tierbigint	3.8%	4	1 → 4median 2
health_zscore_1ydouble	12.7%	3,630	-3.14 → 2.93median 0.0165	74 outside 1st–99th percentile
expanding_flagboolean	3.8%	2	—	false3,267 true761
contracting_flagboolean	3.8%	2	—	false3,610 true418
row_hashvarchar	0%	3,955	—	000555cfdfc2082f1 00074f37dc43ef761 00228215af1f13e41

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/btos_state_business_intel/us_state_business_conditions_biweekly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/btos_state_business_intel/us_state_business_conditions_biweekly").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/btos_state_business_intel/us_state_business_conditions_biweekly

Tip: fetch /llms.txt for the full machine-readable catalog.

Cite this snapshot

Pinned to snapshot 20261001T230958Z-b14a7a65f768 and its content hash, so readers get exactly the data you used.

APA

U.S. Census Bureau Business Trends and Outlook Survey (BTOS) — state business-conditions intelligence. (2026). US state business conditions, biweekly (Census BTOS) [Data set, snapshot 20261001T230958Z-b14a7a65f768, sha256 b14a7a65f768]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/en/datasets/btos_state_business_intel/us_state_business_conditions_biweekly?snapshot=20261001T230958Z-b14a7a65f768

BibTeX

@misc{dz_btos_state_business_intel_us_state_busin_b14a7a65,
  title        = {{US state business conditions, biweekly (Census BTOS)}},
  author       = {{U.S. Census Bureau Business Trends and Outlook Survey (BTOS) — state business-conditions intelligence}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/btos_state_business_intel/us_state_business_conditions_biweekly?snapshot=20261001T230958Z-b14a7a65f768}},
  note         = {Snapshot 20261001T230958Z-b14a7a65f768, sha256 b14a7a65f768e1c48bd471a0da749b809da26a29b0c5cee7872e20bebbe88369; accessed 2026-10-02}
}

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<iframe src="https://datazimuts.com/embed/chart?dataset=btos_state_business_intel%2Fus_state_business_conditions_biweekly&lang=en&theme=auto&snapshot=20261001T230958Z-b14a7a65f768&x=ref_period_start&y=idx_current_performance&agg=avg" title="US state business conditions, biweekly (Census BTOS)" width="100%" height="380" style="border:0" loading="lazy"></iframe>

US state business conditions, biweekly (Census BTOS)

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