Post on 07-May-2018
transcript
How Rents and Expenditures Depreciate: A Case of Tokyo Office Properties
JIRO YOSHIDA (PENN STATE & UNIV. OF TOKYO)KOHEI KAWAI (XYMAX REAL ESTATE INSTITUTE)DAVID GELTNER (MIT)CHIHIRO SHIMIZU (NIHON UNIVERSITY)
(DAVID GELTNER PRESENTING TODAY)
March 27, 2018Hitotsubashi-RIETI Workshop on Real Estate and the Macro Economy
MotivationRents (& resulting net income) measure the productivity of the physical capital represented by built commercial propertiesSuch productivity is fundamental economic reason why buildings are builtRents reflect value of the structure plus value of the location, for existing users (in existing building)Depreciation is important economic phenomenon, major impact on use of vital resources (construction), as depreciation ultimately leads to demolition & redevelopmentRent depreciation is rarely studied (worldwide). (Most studies are of structure value depreciation.)Unique, great database available from Xymax Corp in JapanCase of Tokyo office properties has global interest as an example of extremely high land value real estateFrom urban economics perspective, interesting comparisons possible with “land rich” country (relatively low land values) such as USA where recent depreciation studies of commercial properties have been made.
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The “big picture”…Property value (including land) depreciates only down to 60% of starting value. ==> Land Value Fraction @Dvlpt = 60%.
How does this compare to low land value USA case?
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Age profile of commercial property value in Tokyo (Yoshida, 2017)
Depreciation Rates: 5.3%/y for 1-5 years, 2.1%/y for 21-25 years, 0.9%/y for 41-45 years
The “big picture”…Property Value/Age Profile flattening at 30 years age ==> Building fully-depreciated at 30 yrs age (land does not depreciate). ==> Short avg building economic life.
How does this compare to low land value USA case?
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Depreciation Rates: 5.3%/y for 1-5 years, 2.1%/y for 21-25 years, 0.9%/y for 41-45 years
The “big picture”…Here is corresponding USA case for commercial property. Value/Age Profile does not flatten until 100 yrs age, at 30% Land Value Fraction
This is for commercial property, national average.
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Property Value/Age Profile (including land): Non-Parametric & Geometric/Linear Fit(Based on hedonic price model of 80,431 transaction prices in property asset market)
Commercial Properties:
Net Depreciation (non-parametric) Net Depreciation (geometric fit) Land Value
3.1%/yr of remaining structvalue (1st 50 yrs)
LVF = 47% @median age
(23yrs)
LVF @ Redvlpt= 100% of old
30% of new
Geltner-Bokhari (2015), First study with sufficient data to construct empirical based survival probability curve for commercial buildings in U.S. (life expectancy = 100 yrs). Corresponds to Value/Age Profile flattening.
50% ProbSurv
105 yrs
Mean lifetime = 100 yrs; Median lifetime = 105 yrs.
How do we know relevant land value fractions (30% commercial, 20% apartments)? Two ways…1) Direct evidence from transaction prices of properties bought as “development sites” subsequently sold developed, Ratio of prices:
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Estimated Non-parametric Property Value/Age Profiles:Commercial & Apartment
2) Survival analysis (ages of buildings @ demolition) life expectancy (100 yrs) combined with remaining property value fraction (30%, 20%) at age where non-parametric (flexible) value/age profile flattens out (80-110 yrs), indicating no further depreciation (just land value):
Mean NDLVF N Apartment 0.18 139 Commercial 0.32 691 Total 0.30 830
The “big picture”…Here is picture for three different USA metros, with three different levels of land value… (Bokhari-Geltner, REE 2016)
New York flattens at 60% at 75 yrs age. Dallas at < 10% over 120 yrs.
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Cumulative Effect of Real Depreciation on Property Value (including land): Comparison of Several Metro Areas
NY Chi Dallas
New York
Chicago
Dallas
The “big picture”…We found “three stage” lifespan of USA buildings: Youth, Middle Age, Old Age…
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New York
Chicago
Dallas
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Property Value/Age Profiles: Commercial & Apartment Properties(Property Asset Value Including Land)
Commercial (80,431 obs) Apartment (27,374 obs)
Youth (0-30yrs)(Loses "Class A") Middle Age (30-65yrs)
("Class B" absorbs CapEx)
Old Age (65-100yrs)(Declines to Land Value)
The “big picture”…This seems to exist in Japanese buildings too. Rapid depreciation in “Youth”… (But youth may be shorter.)
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Age profile of commercial property value in Tokyo (Yoshida, 2017)
Depreciation Rates: 5.3%/y for 1-5 years, 2.1%/y for 21-25 years, 0.9%/y for 41-45 years
The “big picture”…Depreciation more broadly from economic perspective is “Capital Consumption”, which includes: (i) Net Depreciation, + (ii) Capital Improvement Expenditures (“Capex”)…
Depreciation rates can be measured either as fraction of total property value (including land), or as fraction just of remaining structure value (since structure is what depreciates).In the case of Rent Depreciation, we measure it as a fraction of itself (fraction of rent), but rent reflects land value (for existing bldg) as well as structure value. Rent is current productivity of the property, not Present Value of all future expected cash flows from property.
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Tokyo Office Net Depreciation Rates, Fraction of Property Value Including Land: 5.3%/y for 1-5 years, 2.1%/y for 21-25 years, 0.9%/y for 41-45 years
Percent of Value of: Property Structure Property StructureNet Depreciation 1.63% 3.14% 2.38% 3.94%Capex 1.75% 3.47% 1.96% 3.36%Gross Depreciation 3.39% 6.61% 4.34% 7.30%
USA Annual Gross Depreciation Rates for 25-year-old Building:Commercial: Apartment:
The “big picture”…Here is what we find about the Capex/Age Profile for Tokyo offices…
Capex tends to increase with building age.
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The “big picture”…Similar finding for USA commercial property capex…
Capex tends to increase with building age. (With or without including “Leasing Commissions”)
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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49Building Age (Yrs)
NCREIF Commercial (Annual Capex/Sqft)
Commercial (Capex/Sqft) Comm (Capex/Sqft) - No LCs
The “big picture”…Back to a key question… Why/How does the Value/Age Profile flatten out so early for Tokyo commercial properties? Why do Japanese buildings have such a short economic lifespan?...
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Age profile of commercial property value in Tokyo (Yoshida, 2017)
Depreciation Rates: 5.3%/y for 1-5 years, 2.1%/y for 21-25 years, 0.9%/y for 41-45 years
The “big picture”…Is it because of decline in the productivity of the buildings? If so, this would be indicated by Rent Depreciation. Or is it because of “economic obsolescence” (Redevelopment Option Value)?...
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Age profile of commercial property value in Tokyo (Yoshida, 2017)
Depreciation Rates: 5.3%/y for 1-5 years, 2.1%/y for 21-25 years, 0.9%/y for 41-45 years
Newly Contracted Rents: Building Panel
Baseline Control Cohort
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1.4%/y for ages 0-100.9%/y for ages 11-200.8%/y for ages 21-300.6%/y for ages 31-400.3%/y for ages 41-50
This is may be our single most important empirical finding. Rents in Tokyo Office Properties decline with bldg age only very little, less than decline in property value…
Baseline Control Cohort
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1.4%/y for ages 0-100.9%/y for ages 11-200.8%/y for ages 21-300.6%/y for ages 31-400.3%/y for ages 41-50
Rent/Age Profile nearly flat. Declines with bldg age only about 30% to about 70% of original value. Then rent flattens, even though rents do not reflect the redevelopment option value in the land. ==> Buildings maintain very high productivity at age where economic obsolescence occurs.
This StudyWe do more than just study rents on new leases…Estimate age profiles of complete office cash flows◦ New rents, rents for sitting tenants, average rents, operating
expenses, net operating income, capital expenditures, and net cash flow
Proprietary data from Xymax, a major property management firm in Tokyo.
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Main Results1. The rent depreciation rate is 0.8% for new leases, 0.4% for
sitting tenants, and 0.5% on average2. Rents depreciate at a declining rate.3. Smaller buildings experience larger rent depreciation.4. A tenant occupying a larger proportion of building
experiences larger rent depreciation.5. Operating expenses depreciate annually at 0.6%.6. Net operating income depreciates annually at 0.4%.7. Capital expenditures generally increase over time.8. Net cash flows depreciates at 0.6% per year.
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Rent and Cash Flow Data
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Unit-levelMonthlyPanel(162,559obs.)
Building-levelAnnualPanel(6159 bldgs.)
Tenants occupying
consecutive years
Average by year
& building
A chain-type index
Average by year
& building
New Rent
New Rent
AverageRent
Individual Lease Rates
Sitting TenantRent
Individual Lease Rates(sitting tenants)
OperatingExpenses
CapitalExpenses
Net Operating
Income
Net Cash Flow
Descriptive Statistics: Entire building panel (bldg. & year)
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Variable n mean sd median min maxBLDG_ID 21,415 7,143.753 7,250.650 4,629.000 1.000 36,294.000 YEAR 21,415 2,011.268 3.323 2,011.000 2,005.000 2,016.000 NEW_RENT 19,993 64,177.906 22,696.630 58,080.002 22,143.001 254,100.010 AVG_RENT 1,930 63,350.561 17,225.231 60,169.777 32,514.430 165,010.293 SIT_RENT 1,930 67,934.411 17,599.644 65,066.088 32,670.001 157,894.326 CAPEX 1,965 4,151.942 9,280.731 1,767.917 2.264 222,806.522 OPEX 897 18,443.338 12,426.174 16,637.749 295.432 164,039.653 Net Operating Income 816 46,647.814 20,518.152 45,775.612 -118,565.427 141,168.308 Net Cash Flows 680 42,760.880 21,948.160 41,369.957 -127,933.144 141,015.083 GFA 21,415 12,374.030 27,971.174 4,196.562 285.289 379,447.920 NRA 21,415 7,326.374 14,760.149 2,911.008 115.008 182,443.993 HEIGHT 21,345 10.310 6.154 9.000 2.000 60.000 DISTANCE 21,415 288.529 156.170 267.375 1.764 1,177.446 MINUTES 21,415 4.960 2.442 4.633 0.000 23.683 AGE 21,415 22.725 10.704 22.000 1.000 50.000 COMPLETION_YEAR 21,415 1,988.543 10.448 1,990.000 1,956.000 2,015.000 RENEWAL 21,415 0.164 0.371 0.000 0.000 1.000 RENEWAL_YEAR 4,266 2,005.124 7.414 2,006.000 1,964.000 2,017.000 DEMOLITION 21,415 0.032 0.175 0.000 0.000 1.000 DEMOLITION_YEAR 561 2,013.879 2.345 2,014.000 2,002.000 2,017.000
Empirical StrategyRents, Operating Expenses, Capital Expenditures
ln𝑉𝑉𝑖𝑖𝑖𝑖 = 𝑎𝑎0 + 𝑓𝑓 𝐴𝐴𝑖𝑖𝑖𝑖 + 𝑿𝑿𝒊𝒊𝒊𝒊𝒃𝒃 + 𝑌𝑌𝑖𝑖 + 𝐶𝐶𝑑𝑑 + 𝜖𝜖𝑖𝑖𝑖𝑖,◦ 𝑉𝑉𝑖𝑖𝑖𝑖: the variable of interest for building 𝑖𝑖 at time 𝑡𝑡, ◦ Age function 𝑓𝑓 𝐴𝐴𝑖𝑖𝑖𝑖◦ (1) the linear model, 𝑓𝑓 𝐴𝐴𝑖𝑖𝑖𝑖 = 𝑎𝑎1𝐴𝐴𝑖𝑖𝑖𝑖◦ (2) the spline function, 𝑓𝑓 𝐴𝐴𝑖𝑖𝑖𝑖 = ∑𝑛𝑛=0𝑇𝑇 𝑎𝑎1,𝑛𝑛𝐼𝐼𝑛𝑛 , where 𝐼𝐼𝑛𝑛 is the age dummy.
◦ 𝑌𝑌𝑖𝑖: year fixed effects◦ 𝐶𝐶𝑑𝑑: decennial cohort (vintage) effects◦ 𝑿𝑿𝒊𝒊𝒊𝒊: log gross floor area, walk minutes from station, city, past renovation
Cash Flows (NOI, NCF) 𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖 = 𝑎𝑎0 + 𝑓𝑓 𝐴𝐴𝑖𝑖𝑖𝑖 + 𝑿𝑿𝒊𝒊𝒊𝒊𝒃𝒃 + 𝑌𝑌𝑖𝑖 + 𝜖𝜖𝑖𝑖𝑖𝑖
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Newly Contracted Rents: Building Panel
LHS: log new rents
(1) (2) (3) (4)
GFA_LOG 0.153*** 0.145*** 0.144*** 0.144***
MINUTES -0.0235*** -0.0220*** -0.0220*** -0.0219***
RNW 0.0472*** 0.0377*** 0.0361*** 0.0356***
AGE -0.00783*** -0.00840***
_cons 10.04*** 10.19*** 10.33*** 10.32***
AgeFE(1yr) No Yes No YesCohortFE No No Yes YesYearFE Yes Yes Yes YesCityFE Yes Yes Yes YesN 19993 19993 19993 19993adj. R2 0.722 0.738 0.738 0.739
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Newly Contracted Rents: Building Panel
Baseline Control Cohort
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1.4%/y for ages 0-100.9%/y for ages 11-200.8%/y for ages 21-300.6%/y for ages 31-400.3%/y for ages 41-50
Newly Contracted Rents: Large/Small Buildings
LHS: lognew rents
(1) (2) (3) (4)Large25% Large25% Small25% Small25%
GFA_LOG 0.143*** 0.137*** 0.156*** 0.159***
MINUTES -0.0265*** -0.0238*** -0.0233*** -0.0225***
RNW 0.0571*** 0.0445*** 0.0412* 0.0335*
AGE -0.00826*** -0.00901***
_cons 10.22*** 10.34*** 10.01*** 10.03***
AgeFE(1yr) No Yes No YesYearFE Yes Yes Yes YesCityFE Yes Yes Yes YesN 7486 7486 2762 2762adj. R2 0.728 0.744 0.565 0.581
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Rents for Sitting Tenants
LHS: log sitting tenant rents
(1) (2) (3) (4)GFA_LOG 0.117*** 0.112*** 0.114*** 0.112***
MINUTES -0.0155*** -0.0104* -0.0117* -0.0108*
RNW -0.0125 -0.0140 -0.0140 -0.0136AGE -0.00421** -0.00504_cons 10.39*** 10.34*** 10.44*** 10.21***
AgeFE(1yr) No Yes No YesCohortFE No No Yes YesYearFE Yes Yes Yes YesCityFE Yes Yes Yes YesN 1930 1930 1930 1930adj. R2 0.480 0.527 0.531 0.534
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New and Sitting Tenant Rents differently respond to market conditions
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Year fixed effects(Hedonic Price Index)
New Leases
Sitting Tenants
“Stickiness” in Sitting Tenants Rents. Tenants have less “holdup threat” than landlords, less negotiating leverage? Why?... (& bldg may retain greater functionality for sitting tenants)
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Year fixed effects(Hedonic Price Index)
New Leases
Sitting Tenants
Average Rents
LHS: log average rents
(1) (2) (3) (4)GFA_LOG 0.113*** 0.110*** 0.109*** 0.108***
MINUTES -0.0197*** -0.0151*** -0.0164*** -0.0153***
RNW -0.0227 -0.0264 -0.0260 -0.0264AGE -0.00530*** -0.00422_cons 10.46*** 10.42*** 10.45*** 10.39***
AgeFE(1yr) No Yes No YesCohortFE No No Yes YesYearFE Yes Yes Yes YesCityFE Yes Yes Yes YesN 1930 1930 1930 1930adj. R2 0.520 0.550 0.555 0.554
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Average Rents: Large/Small Buildings
(1) (2) (3) (4)Large25% Large25% Small25% Small25%
GFA_LOG 0.114** 0.113** -0.113 -0.315MINUTES -0.0303*** -0.0284*** -0.0115 -0.0120RNW -0.0381 -0.0275 -0.112 -0.191*
AGE -0.00537* -0.00725_cons 10.59*** 10.60*** 12.02*** 13.38***
AgeFE(1yr) No Yes No YesYearFE Yes Yes Yes YesCityFE Yes Yes Yes YesN 620 620 230 230adj. R2 0.641 0.660 0.611 0.645
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Average Rents: Tenants with Large/Small Presence
(1) (2) (3) (4)Large25% Large25% Small25% Small25%
GFA_LOG 0.0959*** 0.0892*** 0.142*** 0.140***
MINUTES -0.0186* -0.0160* -0.0209* -0.0220**
RNW 0.00434 -0.0321 -0.0597 -0.00695AGE -0.00647*** -0.000793_cons 10.64*** 10.71*** 10.19*** 10.03***
AgeFE(1yr) No Yes No YesYearFE Yes Yes Yes YesCityFE Yes Yes Yes YesN 39469 39469 39496 39496adj. R2 0.558 0.601 0.621 0.670
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Operating Expenses
LHS: logoperating expenses
(1) (2)GFA_LOG 0.0579 0.0526MINUTES -0.0110 -0.00965RNW -0.00685 -0.0184AGE -0.00635_cons 9.232*** 9.040***
AgeFE(1yr) No YesYearFE Yes YesCityFE Yes YesN 897 897adj. R2 0.086 0.090
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Net Operating Income
LHS: net operating income
(1) (2)GFA_LOG 8168.4** 7770.8**
MINUTES -1232.8* -1010.7RNW -2517.2 -1835.5AGE -182.6_cons -559.9 -1990.2AgeFE(1yr) No YesYearFE Yes YesCityFE Yes YesN 816 816adj. R2 0.383 0.401
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Rate≈0.4%/year
Capital Expenditures
LHS: log capital expenditure
(1) (2)GFA_LOG -0.0110 0.00973MINUTES -0.00158 -0.0325RNW 0.112 0.226AGE 0.0238***
_cons 6.608*** 5.424***
AgeFE(5yr) No YesYearFE Yes YesCityFE Yes YesN 1965 1965adj. R2 0.045 0.122
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Net Cash Flows
LHS: net cash flow
(1) (2)GFA_LOG 8303.1** 8035.6**
MINUTES -984.4 -670.3RNW -5452.9 -5729.7AGE -273.6*
_cons -8205.3 -3112.2AgeFE(5yr) No YesYearFE Yes YesCityFE Yes YesN 680 680adj. R2 0.327 0.365
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Rate≈0.6%/year
Net Cash Flows
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This is “bottom line” of property current productivity with existing building. Profile almost flat. Maybe even evidence rises toward end (40-50 yrs age). Suggests economic (“external”) obsolescence is major reason for demolition & redevelopment in Tokyo.
ConclusionCash Flow (Building Productivity) depreciation rate is very small (0.4%-0.6%/year)
This rate is less than property value depreciation (Yoshida 2017)
This is the first study to uncover this point. Suggests Tokyo buildings demolished (redeveloped) when building still highly productive (economic obsolescence: redevelopment option value). But why so much more so in Japan compared to USA. Can land value difference fully explain it?...
We plan to conduct additional analysis by introducing rent uncertainty, etc.
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