Emcor (EME) Operating Expenses (2009 - 2026)
Emcor's Operating Expenses was $475.04 million in Q2 2026, up 13.5% from $418.56 million a year earlier and up 3.2% from the prior quarter.
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Analysis
Emcor (EME) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Emcor's Operating Expenses was $1.83 billion through Jun 30, 2026, up 17.0% year-over-year; for FY2025, it came in at $1.71 billion, up 20.7% from FY2024.
- Operating Expenses has now increased for 15 consecutive years, with a five-year compound annual growth rate of 13.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.42 billion in FY2024 (+17.3%), $1.21 billion in FY2023 (+16.6%), $1.04 billion in FY2022 (+7.0%) and $970.94 million in FY2021 (+7.2%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2009.
- Compared with a year earlier, Operating Expenses has increased for 21 straight quarters, with growth averaging 17.9% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 1.0% (Q2 2022) and 25.5% (Q4 2025) over the last five years.
- Per Business Quant data, EME's Operating Expenses in the three quarters before Q2 2026 was $460.11 million (Q1 2026), $462.31 million (Q4 2025) and $429.62 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 101.70 Bn | 99.89 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 38.65 Bn | 19.25 Bn | - | - |
| 3 | Emcor | 34.80 Bn | 31.19 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Mastec | 17.34 Bn | 16.24 Bn | 556.28 Mn | 292.57 Mn |
| 5 | Sterling Infrastructure | 16.37 Bn | 14.73 Bn | 289.96 Mn | 65.66 Mn |
| 6 | Jacobs Solutions | 16.17 Bn | 10.82 Bn | 810.70 Mn | 524.00 Mn |
| 7 | IES Holdings | 13.52 Bn | 12.39 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Dycom Industries | 8.20 Bn | 7.33 Bn | - | - |
| 9 | Stantec | 7.70 Bn | 7.70 Bn | - | 972.05 Mn |
| 10 | Aecom | 7.68 Bn | 3.00 Bn | -34.04 Mn | 46.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 475.04 Mn |
| Mar 31, 2026 | 460.11 Mn |
| Dec 31, 2025 | 462.31 Mn |
| Sep 30, 2025 | 429.62 Mn |
| Jun 30, 2025 | 418.56 Mn |
| Mar 31, 2025 | 403.96 Mn |
| Dec 31, 2024 | 368.45 Mn |
| Sep 30, 2024 | 371.19 Mn |
| Jun 30, 2024 | 351.19 Mn |
| Mar 31, 2024 | 329.36 Mn |
| Dec 31, 2023 | 328.55 Mn |
| Sep 30, 2023 | 308.14 Mn |
| Jun 30, 2023 | 293.39 Mn |
| Mar 31, 2023 | 281.15 Mn |
| Dec 31, 2022 | 277.62 Mn |
| Sep 30, 2022 | 263.14 Mn |
| Jun 30, 2022 | 245.36 Mn |
| Mar 31, 2022 | 252.60 Mn |
| Dec 31, 2021 | 260.03 Mn |
| Sep 30, 2021 | 243.92 Mn |
API Access
Emcor Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=EME&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EME", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=EME&period=max&api_key=YOUR_API_KEY");
const data = await res.json();