NEMA Electroindustry Statistics & Market Programs

NEMA - the National Electrical Manufacturers Association, the trade association standing behind roughly $130 billion in annual electroindustry shipments and $38 billion in exports - operates the sector's benchmark indicators through its business intelligence arm. The flagship is the Electroindustry Business Confidence Index (EBCI), a diffusion index built from a survey of senior managers at NEMA member companies across the United States and Canada. Every print carries a Current Conditions component, a Future Conditions component looking six months ahead, the share of respondents reporting better, worse or unchanged conditions, median and mean magnitude-of-change scores on a -5 to +5 scale, respondent counts and verbatim panelist comments. Because the formula is percentage-better plus half the unchanged share, anything above 50 reads as expansion - which makes the index directly comparable to the purchasing-manager barometers analysts already know.

The flagship is not alone. Around it sits a wider statistical estate: the Electroindustry Economic Outlook, a macro, industry and end-market report; the quarterly Global Economic Monitor covering trading partners; Lamp Indices; and tailored market statistics programs carrying sales and orders data for hundreds of electrical product lines plus forecasts. A separate impact track quantifies what the industry contributes - $375.82 billion in GDP contribution, 2.35 million jobs and $220.91 billion in labor income - broken down by state, congressional district and roughly 30 NAICS-based product categories.

Within Datadory's catalog this is one of 22 datasets in the Electrical Components & Equipment slice, rated 7/10 against a 7.81 average across all 1,744 records. Get a sample of this dataset scoped to the measures you actually track.

One print is one month's survey verdict, and the delivered shape keeps every documented field on one line:

# ebci print - july 2026, delivered shape
month                      : 2026-07
current_conditions_index   : 63.0      # 50+ = expansion
future_conditions_index    : 73.9      # expected conditions, six months out
pct_better                 : 39%       # share reporting better conditions
pct_worse                  : 13%       # share reporting worse conditions
pct_unchanged              : 48%       # share reporting unchanged conditions
median_magnitude_of_change : 0.0       # -5 deteriorated ... +5 improved
mean_magnitude_of_change   : 0.7
number_of_respondents      : 23
survey_window              : July 15-29, 2026

# recent current-conditions run, captured at research time
2026-02 : 63.8   2026-04 : 50.0   2026-05 : 47.7   2026-06 : 63.2   2026-07 : 63.0

Read the July line and the story arrives whole: an expanding present at 63.0 with expectations running ten points hotter at 73.9 - a panel leaning into the second half. The run underneath explains why the series repays monthly attention: April sat exactly on the 50 neutral line, May slid to 47.7, and by June the panel was back at 63.2. A twelve-point round trip in eight weeks is exactly the kind of move annual data averages away.

One honesty note: the captured run skips March, so verify month-to-month continuity against delivered rows rather than assuming a complete sequence.

Nine documented fields define every print, and three do the analytical lifting. current_conditions_index is the headline - the diffusion formula applied to this month, expansion above 50. future_conditions_index applies the identical formula to expectations six months out, which turns the gap between the two into a readable momentum signal. And the magnitude pair - median and mean change on the -5 to +5 scale - adds intensity the binary better/worse split cannot: a panel can be net-positive and shallow, or net-positive and surging.

The distribution trio - % Better, % Worse, % Unchanged - is what makes the index auditable: the composite recomputes from its own parts, so nobody has to take the headline on faith. Number of Respondents sizes the panel (23 senior managers in July 2026), and Survey collection window dates the measurement itself, typically mid-month to end-of-month. The complete dictionary:

• Geography: the EBCI panel reads North America - United States and Canada. The wider estate extends past it: the Global Economic Monitor tracks global trading partners, and the impact figures break down to every US state and congressional district.
• Temporal: a monthly observation clock. Prints captured at research time span January through July 2026, with historical depth varying by program rather than following one uniform archive.
• Granularity: one index level per month with its full response distribution underneath; impact data lands by state, congressional district and roughly 30 NAICS-derived product categories; market statistics run per product line across several hundred lines.
• Scale: one compact print per month for the flagship, hundreds of product lines across the statistics programs, and a national-to-district impact matrix.

On Datadory's 0-10 quality rubric the record rates 7/10, against a 7.81 average across the 1,744 cataloged datasets - carried by the index's methodological transparency, discounted for a short captured history and a skipped month in the observed run.

API, files, or your warehouse. Daily, weekly, or hourly.

You choose the channel and the cadence; the nine-field dictionary travels unchanged through all three. Rows land flattened and typed - indices as numbers, shares as percentages, windows as dated ranges - so a confidence print joins your shipment, backlog or billing tables on period on the first attempt instead of after a document-reading project. Cadence changes are a setting, not a migration, and a sample scoped to your measures settles the shape before anything ships.

Cycle-timing dashboards. Pair the current-conditions level with the future-conditions spread and the magnitude pair to get a three-signal leading stack for electrical-equipment demand (data scientists use cases).

Forecast features. A transparent diffusion index with a published formula is rare among sentiment series; the composite recomputes from its own parts, so it survives audit in a model review.

End-market sizing. Sales and orders statistics across hundreds of product lines give product-line-level revenue baselines with forecasts attached (market researchers use cases).

Advocacy and policy work. State and congressional-district impact figures - $375.82 billion in GDP contribution, 2.35 million jobs - turn "the industry matters" into a district-by-district table.

Benchmark positioning. The better/worse/unchanged distribution lets a company place its own month against the panel instead of against a single aggregate number (competitive intel use cases).

Market Researchers & Consultants get a directional read for electrical-sector sizings that does not wait for lagging official series (data for market researchers). Data Scientists & ML Engineers inherit typed, dated, auditable index rows ready to serve as model features (data for data scientists). Investors & Quants read the current-versus-future spread as sentiment momentum for industrial exposures. Competitive Intelligence & Product Teams track panel direction around category announcements (data for competitive intel and product teams). Journalists, Academics & Students get a citable sector barometer whose formula is published and reproducible. Developers & Data-Product Builders wire a stable nine-field schema into dashboards and alerting (data for developers and builders).

This record reads best beside the volume and compliance layers of the same industry. The BEA GDP-by-industry iTable supplies value-added and gross-output context for the electrical equipment line - the macro frame these sentiment prints move inside. The Economic Census data tables provide the shipment ground truth the panel is predicting, and ECIA electronic component sales data contributes the electronic-component counterpart: bookings, lead times and distributor rankings on a weekly-and-quarterly clock. The UL Product iQ certification database adds the safety-certification layer, and SIA semiconductor data resources extend the bill of materials upstream. Joined on period, the stack answers what the electroindustry expects, what it ships and who is certified to sell it.

Full slice ranking sits on the electrical components & equipment data hub, and the cross-industry shortlist lives at best electrical-components-equipment datasets. Two notes before requesting a sample: the captured index history is short and carries a skipped month, so depth beyond the recent window is confirmed when the sample is prepared; and program scope varies - name the measures and product lines you need and the sample arrives filtered to those rows.