Do Sydney tenants pay energy efficient office premiums?

Jeremy Gabe & Michael Rehm July 2013

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

A dominant narrative is that energy efficient buildings increase rents relative to uncertified property

Model Mkt. Value Rents Occupancy NOI Cap RatePivo & Fisher (2010) +8.5 %

(appraised value)+5.2 % +1.3 % +2.7 % -52 basis pts

Eicholtz et al. (2008/2010)

+19.1 % +3.3 %

Fuerst and McAllister (2011)

+26 % +4 %

Premiums observed in US Energy Star properties(controlling for key hedonic characteristics, e.g. location, size, age, market trends)

All of these studies worked at the building (asset) scale

Rent discounts for poor NABERS-rated properties observed in Australian properties(relative to uncertified properties; Newell et al. 2011)

𝑟𝑎𝑠𝑘= 𝑓 (𝑜𝑐𝑐𝑢𝑝𝑎𝑛𝑐𝑦𝑟𝑎𝑡𝑒 ,𝑠𝑡𝑜𝑟𝑒𝑦 ,𝑐𝑢𝑟𝑟𝑒𝑛𝑡𝑚𝑎𝑟𝑘𝑒𝑡 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛𝑠)1. Asking Rent

2. Average Rent

𝑟𝑎𝑣𝑔= 𝑓 (𝑜𝑐𝑐𝑢𝑝𝑎𝑛𝑐𝑦 𝑝𝑟𝑜𝑓𝑖𝑙𝑒 ,𝑚𝑎𝑟𝑘𝑒𝑡 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛𝑠𝑎𝑡 𝑙𝑒𝑎𝑠𝑒)

Rent premiums at the asset scale could arise because of higher income, occupancy, or market timing

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

The lease transaction scale can isolate whether higher income is a cause – do green office tenants pay more?

• Chegut, Eichholtz, and Kok (2012)– 24-30% annual face rent premium for BREEAM buildings– Premium includes unmeasured quality characteristics

(omitted variable bias)

• Kok and Jennen (2012) – 6.5-7.5% face rent discounts for low energy rating– C-grade (not A- or B-grade) had highest rents– Possibility of multicollinearity of target variable with

building age

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

Using Sydney as a case study overcomes some limitations of the first green lease studies

• All major office buildings are rated

• Rating based on audited performance

• Rating reviewed annually• Market consensus on

building quality grading• Face vs. Effective rent• Single market, with well-

defined submarkets

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

Australia has a comprehensive system of environmental performance reporting for commercial office buildings

NABERS Energy

12-month site energy consumption

audit

Converted tosource

GHG emissions

GHG emissions compared with city

median to determine star

rating

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

0-stars Very Poor

6 Market Leader

Evidence of Private Investment in Environmental Performance

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

Why do Sydney owners invest in energy efficiency?

• Government Interventions– Supply

• AusIndustry Green Building Fund grants (2008-2011)• Energy Upgrade Agreements (cheap loans to owners repaid by future tenants

via property taxes)– Demand

• Mandatory rating advertisement before sale/lease• State/Federal government accommodation rating floors (4/4.5 star NABERS

Energy)

• Corporate Social Responsibility Arms Race– Australian property funds ranked top in the world

• Operating Expense Savings – Gross lease (full service) contracts only

• Rent Income Premiums?

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

Tenants face weak financial/legal incentives to rent green office space at a premium; owners face stronger incentives to invest

EnergyCarbon Tax

Space (Net Rent)Labour $4,700 per m2

$542 per m2

$17 per m2

$2 per m2

TENANTS (Net Lease)

CSR and other intangible benefits remain as possible drivers

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

OWNER (Full-Service Lease)

EnergyCarbon Tax

Management Property Taxes $50 per m2

$70 per m2

$17 per m2

$2 per m2

• Hedonic Price Analysis– Unit of Analysis: Lease– Net rents converted to Gross – Dependent Variables:

• Natural log of initial gross face rent per m2

• Natural log of effective gross rent per m2

Research Scope & MethodologyINTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

ln ( )= ( , , , )𝑅𝑒𝑛𝑡 𝑓 𝛼 𝛽 𝛾 𝑢 𝛼 = Vector of market characteristics 𝛽 = Vector of lease characteristics 𝛾 = NABERS Energy characteristics

u = Stochastic term

Data• Lease Transactions

– 708 unique lease agreements with face rent – 339 unique lease agreements disclose full signing incentives– January 2007 to September 2011

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

DESCRIPTIVESTATISTICS

Mean(Std. Dev.)

Results – Effective Gross Rent

*Significant at 95% Level **Significant at 99% Level

Independent Variable 1 2 3 4

NABERS Energy Rating at Commencement

0, 1, or 1.5 -2.94x10-3

2 or 2.5 0.052

3 or 3.5 -0.012

4 Reference

4.5 and up 7.58x10-3

Poor Rating (2 and below) 0.014

Average Rating (2.5 to 3.5) Reference

High Rating (4 and above) 2.80x10-3

Natural Log of Energy Intensity 0.026

Lowest Floor Leased

Level 9 or lower Reference Reference Reference Reference

Level 10 to 19 0.061** 0.061** 0.064** 0.060**

Level 20 to 29 0.115** 0.115** 0.106** 0.115**

Level 30 to 39 0.203** 0.205** 0.211** 0.202**

Level 40 and above 0.291** 0.294** 0.294** 0.293**

Operating Expenses Liability

Net Lease 0.141** 0.140** 0.140** 0.144**

Gross Lease Reference Reference Reference Reference

Independent Variable 1 2 3 4

Lease Term

Short (4 years or less) -0.083** -0.084** -0.079** -0.084**

Average (5 years) Reference Reference Reference Reference

Long (6 years or more) 0.026 0.025 0.033 0.026

Building Quality Rating (PCA)

Premium 0.216** 0.213** 0.207** 0.208**

A-Grade Reference Reference Reference Reference

“Secondary” (B-Grade and C-Grade) -0.116** -0.114** -0.117** -0.114**

Type of Negotiation

New Lease 0.077** 0.075** 0.067** 0.078**

Renewal/Expansion (Tenant already in building) Reference Reference Reference Reference

Leased Area (m2) -2.96x10-5 -3.01x10-5 -2.70x10-5 -2.99x10-5 *

Leased Area Squared 2.65x10-9 2.68x10-9 2.57x10-9 2.63x10-9

Size of Entire Building (natural log) 0.081** 0.083** 0.087** 0.084**

Walking Distance to Train (natural log) -1.70x10-3 -2.68x10-3 -4.29x10-3 -9.10x10-4

Building Age at Commencement (years) -4.75x10-3 * -5.11x10-3 * -4.85x10-3 * -4.96x10-3 *

Building Age Squared 7.49x10-5 ** 7.87x10-5 ** 7.18x10-5 ** 7.67x10-5 **

Constant 5.482** 5.468** 5.425** 5.278**

Locational Variable (4 Submarkets) Included Included Included Included

Time Dummy Variables (Semi-annual periods) Included Included Included Included

Adjusted R-Squared 0.813 0.812 0.818 0.812

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

Conclusions

• No evidence of a premium/discount based on energy attributes– Tenants respond as expected to financial and legal incentives– CSR initiative not strong enough to pay space premiums– Cannot reject an alternative hypothesis that rent premiums in building-

scale studies caused by method used to calculate a single rental price

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS

Conclusions

• Split incentive between owner/tenant not a clear barrier– Tenants have an incentive to negotiate a full-service lease:

Net Rent + Outgoings > Gross (Full-Service) Rent

– Energy Upgrade Agreements: Are tenants funding capital appreciation?

INTRODUCTION – RESEARCH QUESTION – CASE STUDY CONTEXT – DATA & METHOD - RESULTS