STAG Industrial (STAG) Property Operating Expenses (2010 - 2026)
STAG Industrial's Property Operating Expenses was $46.24 million in Q3 2026, up 9.6% from $42.17 million a year earlier and up 2.7% from the prior quarter.
STAG Industrial (STAG) Property Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, STAG Industrial's Property Operating Expenses was $184.16 million through Sep 30, 2026, up 10.6% year-over-year; for FY2025, it was $171.83 million, up 11.0% from FY2024.
- Property Operating Expenses has now increased for 13 consecutive years, with a five-year compound annual growth rate of 14.0% (FY2020 to FY2025).
- In earlier years, Property Operating Expenses was $154.83 million in FY2024 (+10.9%), $139.6 million in FY2023 (+11.1%), $125.7 million in FY2022 (+16.4%) and $107.99 million in FY2021 (+20.8%).
- Quarterly Property Operating Expenses has moved between $28.87 million (Q2 2022) and $47.32 million (Q1 2026) over five years.
- Compared with a year earlier, Property Operating Expenses has increased for 51 straight quarters, with growth averaging 10.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Property Operating Expenses ran from 4.7% in Q4 2023 to 21.0% in Q4 2022.
- Per Business Quant data, STAG's Property Operating Expenses in the three quarters before Q3 2026 was $45.03 million (Q2 2026), $47.32 million (Q1 2026) and $45.58 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Property Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 181.70 Bn | 168.77 Bn | 1.47 Bn | 2.25 Bn |
| 2 | Prologis | 123.65 Bn | 122.03 Bn | - | 511.72 Mn |
| 3 | Simon Property | 80.48 Bn | 78.58 Bn | - | 180.83 Mn |
| 4 | Public Storage | 62.76 Bn | 62.20 Bn | 112.08 Mn | 333.19 Mn |
| 5 | Realty Income | 56.61 Bn | 57.99 Bn | - | 122.39 Mn |
| 6 | Ryman Hospitality Properties | 47.80 Bn | 46.64 Bn | 266.41 Mn | 158.13 Mn |
| 7 | Ventas | 47.78 Bn | 46.95 Bn | -3.39 Bn | 1.10 Bn |
| 8 | Vivmark Residential | 38.23 Bn | 37.98 Bn | - | 245.28 Mn |
| 9 | Extra Space Storage | 33.20 Bn | 32.98 Bn | 650.96 Mn | 238.84 Mn |
| 10 | STAG Industrial | 7.21 Bn | 7.18 Bn | - | 46.24 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 46.24 Mn |
| Jun 30, 2026 | 45.03 Mn |
| Mar 31, 2026 | 47.32 Mn |
| Dec 31, 2025 | 45.58 Mn |
| Sep 30, 2025 | 42.17 Mn |
| Jun 30, 2025 | 40.40 Mn |
| Mar 31, 2025 | 43.68 Mn |
| Dec 31, 2024 | 40.26 Mn |
| Sep 30, 2024 | 38.02 Mn |
| Jun 30, 2024 | 37.48 Mn |
| Mar 31, 2024 | 39.07 Mn |
| Dec 31, 2023 | 36.61 Mn |
| Sep 30, 2023 | 34.43 Mn |
| Jun 30, 2023 | 32.68 Mn |
| Mar 31, 2023 | 35.88 Mn |
| Dec 31, 2022 | 34.97 Mn |
| Sep 30, 2022 | 30.09 Mn |
| Jun 30, 2022 | 28.87 Mn |
| Mar 31, 2022 | 31.78 Mn |
| Dec 31, 2021 | 28.89 Mn |
STAG Industrial Property 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=property-operating-expenses&ticker=STAG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-operating-expenses", "ticker": "STAG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=property-operating-expenses&ticker=STAG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();