Amenity Valuation in Simultaneous Hedonic Property Markets: An Exploration of Rental and Sales Markets in the Coastal Zone

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Amenity Valuation in Simultaneous Hedonic Property Markets: An Exploration of Rental and Sales Markets in the Coastal Zone

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n personal consumption of vacation property. m rental supply of vacation property ... 425 observations on properties in Dare and Brunswick counties, NC ... – PowerPoint PPT presentation

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Title: Amenity Valuation in Simultaneous Hedonic Property Markets: An Exploration of Rental and Sales Markets in the Coastal Zone


1
Amenity Valuation in Simultaneous Hedonic
Property Markets An Exploration of Rental and
Sales Markets in the Coastal Zone
  • Craig E. Landry
  • East Carolina University

2
Hedonic Property Price Method
  • Revealed preference method of non-market
    valuation
  • Use property transaction prices as signal of
    economic value of environmental goods and
    services P P(a)
  • Rosen (JPE 1974) showed how we can relate
    marginal implicit prices to homebuyer preferences
  • Pa Ua/Uq

3
Applications of Hedonic Price Method
  • Environmental values in exotic locations
  • Ski chalets, Lake retreats, Alpine villas
  • Beach homes
  • Beach erosion and beach quality
  • Flood wind hazards
  • Coastal amenities
  • View
  • Proximity to beach
  • Open space
  • Water quality

4
Land Markets in Exotic Locations
  • Limited land supply
  • Competitive bidding for land
  • Sales prices adjust to reflect heterogeneity of
    parcels and structures
  • Some properties also traded in rental market
  • Rental prices will reflect heterogeneity
  • Rental income can be important source of funds
    for mortgage, taxes, insurance

5
Second Homes in Exotic Locations
  • Owner often does not occupy house year-round
  • May see same property traded in 2 markets
  • Sales market capital asset
  • Rental market pure consumption
  • Implications for theory of hedonic prices,
    statistical estimation, and welfare analysis?

6
Preview of Results
  • Simultaneous markets alter hedonic theory and
    interpretation of marginal implicit prices
  • Implications depend upon purpose of
    analysis/analytical approach utilized
  • Estimation of a simultaneous system of hedonic
    price equations improves efficiency

7
Agents in Simultaneous Markets
  • Suppliershomebuilders and redevelopers
  • Homeowners buyers in the sales market and
    suppliers in the rental market
  • Vacationersbuyers in the rental market

8
Assumptions
  • All agents take hedonic price schedules as given
  • Ignore seasonal variation in rental price
  • Asset risk factors (forest fire, avalanche,
    flood, erosion) will not affect rental rates
  • Buyers consider rental market when forming
    property bids
  • Usage for any period of time is a reasonable
    representation of usage patterns

9
Homeowners
  • Max Ui(a,n,m,q)
  • a vector of housing attributes
  • n personal consumption of vacation property
  • m rental supply of vacation property
  • q numeraire
  • subject to y r(a)m P(a) a(m) t(n) q
  • y annual income
  • r(a) weekly hedonic rental price function
  • P(a) annualized hedonic sales price function
  • a(m) rental cost function (increasing and
    convex)
  • t(n) consumption cost function (e.g. travel
    cost)
  • subject to T m n

10
Optimization
  • First-order conditions
  • Uq µ 1
  • Ua µ(Pa ram) 2
  • Un µt'(n) p 0, n 0, 3
  • Un µt' (n) pn 0
  • Um µr(a) a'(m) p 0, m 0, 4
  • Um µr(a) a'(m) pm 0
  • y r(a)m P(a) a(m) t(n) q 5
  • T m n p 0, 6
  • p T m n 0

11
Optimal Housing Attributes 2
  • Conventional hedonic model ? marginal price
    equals marginal rate of substitution
  • Pa Ua/µ Ua/Uq
  • Maintained result if m 0
  • If 0 lt m lt T
  • PaUa/µ ram Ua/Uq ram
  • If m T
  • Pa raT

12
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13
Optimal Consumption 3
  • Consumption depends upon the balance of marginal
    benefits and costs
  • MB Un
  • MC(n) µt'(n) p
  • For n 0 MC(1) gt MB
  • For 0 lt n lt T MC(n) MB
  • For n T MC(T) lt MB

14
Optimal Rental Supply 4
  • Supply depends upon the balance of marginal
    benefits and costs
  • MB r(a)
  • MC(m) am Um /µ p/ µ
  • For m 0 MC(1) gt MB
  • For 0 lt m lt T MC(m) MB
  • For m T MC(T) lt MB

15
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16
Vacationers
  • Max subject to y r(a)v q
  • where v is number of rental weeks
  • First-order conditions imply
  • ra /(µv)
  • Interpretation for vacationers marginal WTP
  • /µ rav

17
Hedonic Price Equations
  • P P(a,?) 5
  • rr(a) 6
  • Homeowners preferences play a role in both price
    schedules
  • Selection of rental supply (m) induces
    differences across the two markets
  • Distribution of property characteristics
  • Distribution of homeowners preferences

18
Data
  • 425 observations on properties in Dare and
    Brunswick counties, NC
  • Sales 1979-1997 (expressed as annual expense)
  • Rental rates 1998
  • Observe rental supply
  • 29 not rented (m 0)
  • 36 rented fulltime (n 0)
  • Remaining 35 rented/consumed part of the year
  • Only 12 occupied year-round (renter or owner)
  • Observe housing and household attributes

19
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20
Econometric Model
  • Pi(a,?) xißp epi 5
  • ri (a) zißr eri 6
  • Estimate likelihood function as a Bivariate
    Normal
  • Box-Cox transformation of dependent variable
  • Model selection in first-stage probit model

21
PROBIT SELECTION EQUATION (Pr(mgt0))
  • Probit regression
    Number of obs 690

  • LR chi2(8) 63.71

  • Prob gt chi2 0.0000
  • Log likelihood -397.06653
    Pseudo R2 0.0743
  • --------------------------------------------------
    ---------------------------------
  • rental Coef. Std. Err. z
    Pgtz
  • -------------------------------------------------
    --------------------------------
  • gradsch -0.0958244 0.115899
    -0.83 0.408
  • hschool -0.2626746 0.153001
    -1.72 0.086
  • retire -0.6391054 0.1069345
    -5.98 0.000
  • incom98 -0.0002414 0.0006404
    -0.38 0.706
  • nodare -0.0632154 0.1286555
    -0.49 0.623
  • cendare 0.4560292 0.1576279
    2.89 0.004
  • sodare 0.6586108 0.351817
    1.87 0.061
  • nobrun -0.233207 0.1881866
    -1.24 0.215
  • _cons 0.7978059 0.1494016
    5.34 0.000
  • --------------------------------------------------
    ----------------------------------

22
Results for BVN Model
  • Box-Cox parameter different from zero for sales
    model (plt0.001), not for rental model
  • Use semi-log form for rent
  • Compared to independent hedonic regressions
  • Overall coefficient estimates are close
  • Standard errors are generally smaller
  • Covariance estimate is significant (p0.002)

23
Results of BVN Model
  • For significance level of 10
  • 10/14 significant coefficients in sales model
  • Lotsize, bedrooms, air, fireplace, multistory,
    age, ocean-frontage, distance from shore,
    distance from CBD, elevation
  • Yearly dummies generally statistically
    significant increasing trend
  • 11/13 significant coefficients in rental model
  • Square-footage, lotsize, bedrooms, air,
    fireplace, garage, multistory, age,
    ocean-frontage, distance from shore, distance
    from CBD
  • Risk variables have no explanatory power
  • Coefficient on Hazard Ratio not significant
    (p0.168)

24
Selected Results BVN Model
  • Number of obs 425
    LR chi2(45) 2310.85
  • Log likelihood -6268.3611
    Prob gt chi2 0.0000
  • -------------------------------------------------
    ---------------------------------------------
  • Coef. Std. Err.
    z Pgtz
  • --------------------------------------------------
    ---------------------------------------------
  • sales
  • sqft 2.28e-06 1.83e-06
    1.25 0.213
  • lotsize 1.15e-06 3.88e-07
    2.96 0.003
  • air1 0.017921 0.0074215
    2.41 0.016
  • pur_age -0.0008969 0.0003158
    -2.84 0.005
  • ocean 0.0243136 0.0085695
    2.84 0.005
  • distance -0.0000364 0.0000148
    -2.46 0.014
  • elev 0.0009411 0.0004239
    2.22 0.026
  • -------------------------------------------------
    --------------------------------------------
  • rental
  • sqft 0.0000224 0.0000128
    1.75 0.079
  • lotsize 0.000013 1.84e-06
    7.06 0.000
  • air2 0.2481065 0.081493
    3.04 0.002
  • housage -0.0108035 0.0014259 -7.58
    0.000

25
Marginal Prices
  • Need adjustment to r(a) since it only measure
    peak rent
  • Assume 50 in pre- and post-peak periods
  • Assume 37 rest of year
  • Present means for Pa and ra
  • Calculate marg WTP Ua/Uq Pa - ram for each
    household that occupies house for some portion of
    year (n gt 0)

26
Marginal Prices
Attribute Pa ra MWTP
Sqft 0.83 0.02 0.54
Lot size 0.42 0.01 0.13
Age -328.31 -11.16 -83.90
Distance to shore -13.32 -0.38 -5.11
Ocean 8,900.01 265.03 3,094.99
MWTP Ua/µ Pa - ram
27
Conclusions
  • Can improve efficiency by allowing for
    correlation of sales and rental prices
  • Interpretation of marginal sales price depends
    upon rental supply behavior
  • If household occupies and rents part-time
    marginal price reflects both homeowners and
    renters preferences and rental supply
  • Components of marginal price can be decomposed
  • Better characterization of household behavior
  • Applications in policy analysis

28
Extensions
  • Identify conditions for market equilibrium
  • Incorporate selection into simultaneous model
  • Make use of Envelope theorem result to
    incorporate rental supply
  • m(r(a),P(a),n,y) Vr/Vy
  • Recover parameters of utility
  • Account for hazards/risk in model

29
Likelihood Function
  • Ir rental indicator variable
  • lnL for ith observation

30
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