Empire State Realty OP (ESBA) Operating Expenses (2012 - 2026)
Empire State Realty OP (ESBA) reported Operating Expenses of $335.61 million for Q2 2026, up 115.0% from $156.13 million a year earlier and up 108.6% from the prior quarter.
Empire State Realty OP (ESBA) Operating Expenses (2012 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Empire State Realty OP's Operating Expenses came in at $818.7 million, up 32.2% year-over-year; for FY2025, it came in at $632.62 million, up 3.8% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 2.8% (FY2020 to FY2025).
- By year, Operating Expenses came in at $609.21 million in FY2024 (+2.8%), $592.87 million in FY2023 (-1.2%), $600.01 million in FY2022 (+10.1%) and $544.96 million in FY2021 (-1.0%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q4 2014.
- Year over year, Operating Expenses has now increased in each of the last 12 quarters, with growth averaging 17.4% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2026 (growth of 115.0%); the low point was Q1 2023 (a decline of 6.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $160.87 million (Q1 2026), $163.82 million (Q4 2025) and $158.4 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 166.01 Bn | 148.52 Bn | 1.39 Bn | 3.22 Bn |
| 2 | Prologis | 121.16 Bn | 125.55 Bn | - | 1.47 Bn |
| 3 | Simon Property | 65.49 Bn | 66.75 Bn | - | 900.79 Mn |
| 4 | Realty Income | 51.38 Bn | 53.76 Bn | - | 1.19 Bn |
| 5 | Public Storage | 49.67 Bn | 48.75 Bn | - | 766.20 Mn |
| 6 | Ventas | 43.61 Bn | 42.81 Bn | - | 1.68 Bn |
| 7 | Extra Space Storage | 27.79 Bn | 27.79 Bn | 642.43 Mn | 481.97 Mn |
| 8 | Vici Properties | 25.29 Bn | 23.41 Bn | 1.05 Bn | 315.61 Mn |
| 9 | Vivmark Residential | 22.78 Bn | 22.97 Bn | - | 566.18 Mn |
| 10 | Empire State Realty OP | 1.08 Bn | 1.08 Bn | - | 335.61 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 335.61 Mn |
| Mar 31, 2026 | 160.87 Mn |
| Dec 31, 2025 | 163.82 Mn |
| Sep 30, 2025 | 158.40 Mn |
| Jun 30, 2025 | 156.13 Mn |
| Mar 31, 2025 | 154.28 Mn |
| Dec 31, 2024 | 154.66 Mn |
| Sep 30, 2024 | 154.25 Mn |
| Jun 30, 2024 | 150.18 Mn |
| Mar 31, 2024 | 150.12 Mn |
| Dec 31, 2023 | 152.11 Mn |
| Sep 30, 2023 | 149.27 Mn |
| Jun 30, 2023 | 144.35 Mn |
| Mar 31, 2023 | 147.13 Mn |
| Dec 31, 2022 | 142.32 Mn |
| Sep 30, 2022 | 148.19 Mn |
| Jun 30, 2022 | 151.52 Mn |
| Mar 31, 2022 | 157.99 Mn |
| Dec 31, 2021 | 139.24 Mn |
| Sep 30, 2021 | 151.85 Mn |
Empire State Realty OP 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=ESBA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ESBA", "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=ESBA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();