State Hotel Economic Impact Data: Dataset Structure and Field Coverage

One source owns the category: the American Hotel & Lodging Association's “Economic Impacts of the Hotel Industry Across the Country” dashboard at economic-impact.ahla.com (redirected from ahla.com/statefacts). Its front page leads with three national headlines — hotels support more than 9.1 million jobs, contribute more than $894 billion to US GDP, and AHLA counts more than 30,000 members — above a state dropdown that routes to /states/{slug} pages such as /states/california.

The extractable substance sits underneath the interactive layer. Four component CSV files totalling roughly 65 KB carry the whole model: 52 state rows, 436 congressional-district rows, and separate tables splitting total industry impact from direct hotel operations. A methodology footnote states the figures cover 2024 and attributes the modelling to Oxford Economics, drawing on CoStar/STR hotel inventory and performance data plus IMPLAN, Bureau of Economic Analysis and US Census Bureau statistics, with the hotel industry defined as hotels, motels and B&Bs excluding short-term rentals.

That makes the dashboard an economic impact study in the strict sense — modelled direct, indirect and induced effects rather than surveyed receipts — which is exactly why its state tables need the federal cross-checks described further down.

Fourteen documented columns make up the snapshot files: Hotel_Guest_Spending_Dollars, Hotel_Guestrooms_Number_of_Rooms, Properties_Number_of_Hotels, Share_of_Total_Jobs_Supported_by_Hotel_Industry, Employment_Number_of_Jobs, Wages_and_Salaries_Dollars, Business_Sales_Output_Dollars, GDP_Dollars, Federal_Taxes_Dollars, State_and_Local_Taxes_Dollars, Taxes_on_Lodging_Dollars, Total_Taxes_Dollars, Total_Taxes_Per_Household_Dollars and Total_Jobs_Supported_by_Hotel_Industry_per_100_Households. Field names ship exactly as delivered — they were read straight from the files during verification.

Expect fractional values in the employment column. They reflect Oxford Economics' modelling estimates, not headcounts, so round before quoting and cite the modelled basis.

The AHLA files win on geography alone — nothing else in the slice cuts hotel economics below the state line to 435 congressional districts. Everything else trades breadth for depth, frequency or history, so pick by question:

The BEA Travel and Tourism Satellite Account supplies the benchmark layer: 27 annual Excel workbooks spanning 1998 through 2023, each roughly 50 KB with eight tables carrying an explicit Traveler accommodations line, and a demand table splitting accommodations revenue among resident households, business, government and nonresidents. Regular production ended in February 2026, so the archive is fixed — a feature for reproducible research, not a bug.

The standard combination: deflate Census nominal receipts with BEA chain-type price indexes to separate real travel demand from rate-driven growth, then read the AHLA tables for who employs and collects taxes where.

Two Datadory personas rate AHLA's tables at maximum relevance. Market Researchers & Consultants (3 of 3) anchor US hospitality market sizing on state and district impact tables built by Oxford Economics from CoStar/STR inputs. Journalists, Academics & Students (3 of 3) cite state-by-state jobs, tax and guest-spending figures precisely because the AHLA/Oxford Economics provenance is disclosed on the dashboard footer. Sales & Growth Teams (2 of 3) size territories from rooms, properties and jobs per state or district.

What nobody should do with these files is treat them as firm-level or tradable data. There is no company detail, one reference year and no time axis. Property-level operating statistics — comparable-hotel RevPAR and occupancy — live in lodging REIT filings instead, where an active issuer posts roughly 20 to 60 documents per year on EDGAR.

For the researcher workflow around those choices, see the market researchers' hotel & resort REITs page, and for the filing-side complement, the EDGAR walkthrough covers retrieval script-by-script.

To size the listed set independently, Nasdaq's stock screener filter for Real Estate returns 284 rows, from which HST, RHP, APLE, DRH, PEB, RLJ, INN, CLDT, BHR, AHT and IHT are separable as lodging names. Their audited property tables sit on SEC EDGAR, where the XBRL Company Facts API returns every tagged concept per filer in one JSON call — Host Hotels' payload runs about 3 MB across 459 us-gaap concepts.

Continue through the connected pages:

1. Hotel & Resort REITs data guide — the pillar covering all 23 catalogued datasets in the slice, from EDGAR filings to the Kaggle review corpus.
2. SEC EDGAR hotel REIT filings — the sibling cluster that pairs these state totals with property-level RevPAR and occupancy disclosures.
3. AHLA – Hospitality Economic Impact & State Facts Dashboard — the dataset record with every component URL verified in August 2026.
4. Best hotel-resort-reits datasets — the ranked shortlist when you need one source per job.