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Title: Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High-Performance Office Buildings

Abstract

Evidence has shown that owning and operating energy-efficient, high-performance, “green” properties results in multiple benefits including lower utility bills, higher rents, improved occupancy, and greater net operating income. However, it is difficult to isolate and control moderating factors to identify the specific drivers behind improved financial performance and value to investors that results from sustainability in real estate. DOE is interested in facilitating deeper investigation of the correlation between energy efficiency and financial performance, reducing data acquisition and matching challenges, and developing a stronger understanding of how sustainable design and energy efficiency impact value. DOE commissioned this pilot study to test the logistical and empirical procedures required to establish a Commercial Real Estate Data Aggregation & Trends Analysis lab, determine the potential benefits available through the lab, and contribute to the existing body of evidence in this field.

Authors:
 [1];  [1];  [1]
  1. JDM Associates, Falls Church, VA (United States)
Publication Date:
Research Org.:
JDM Associates, Falls Church, VA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)
Contributing Org.:
Building Technologies Office Corporate
OSTI Identifier:
1419623
Report Number(s):
DOE/EE-1568
7851
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 29 ENERGY PLANNING, POLICY, AND ECONOMY; Utility consumption; tenant retention/renewal rate; leasing velocity; net operating income; green certifications

Citation Formats

Cloutier, Deborah, Hosseini, Farshid, and White, Andrew. Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High-Performance Office Buildings. United States: N. p., 2017. Web. doi:10.2172/1419623.
Cloutier, Deborah, Hosseini, Farshid, & White, Andrew. Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High-Performance Office Buildings. United States. doi:10.2172/1419623.
Cloutier, Deborah, Hosseini, Farshid, and White, Andrew. Mon . "Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High-Performance Office Buildings". United States. doi:10.2172/1419623. https://www.osti.gov/servlets/purl/1419623.
@article{osti_1419623,
title = {Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High-Performance Office Buildings},
author = {Cloutier, Deborah and Hosseini, Farshid and White, Andrew},
abstractNote = {Evidence has shown that owning and operating energy-efficient, high-performance, “green” properties results in multiple benefits including lower utility bills, higher rents, improved occupancy, and greater net operating income. However, it is difficult to isolate and control moderating factors to identify the specific drivers behind improved financial performance and value to investors that results from sustainability in real estate. DOE is interested in facilitating deeper investigation of the correlation between energy efficiency and financial performance, reducing data acquisition and matching challenges, and developing a stronger understanding of how sustainable design and energy efficiency impact value. DOE commissioned this pilot study to test the logistical and empirical procedures required to establish a Commercial Real Estate Data Aggregation & Trends Analysis lab, determine the potential benefits available through the lab, and contribute to the existing body of evidence in this field.},
doi = {10.2172/1419623},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}

Technical Report:

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