Consumption of real assets and the clientele effect
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Transcript of Consumption of real assets and the clientele effect
Presented by Ekaterina Chernobai page 1ERES Conference 2010 (6/26/2010) 1
Ekaterina Chernobai
California State Polytechnic University, Pomona, USACollege of Business Administration
Department of Finance, Real Estate, and Law
University of Nürtingen, GermanyDepartment of Real Estate Management
Consumption of real assets and the clientele effect
Anna Chernobai
Syracuse University, USAWhitman School of Management
Department of Finance
Motivation
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Financial assets Stocks, bonds
• Monetary benefits to holders
• “Clientele effect”:
Long-horizon investors buy illiquid assets; bid price down to compensate for future transaction costs; high returns(Vice versa for short-horizon investors)
Long- & short-horizon investors
Liquid & illiquid assets
Real estate assets Residential real estate
• Monetary & non-monetary benefits (=utility from consumption) to holders
• “Clientele effect”:
Long- & short-horizon house buyers
Different liquidity houses
Illiquid house: bidding the price down is not the only compensation for illiquidity. Can also compensate with higher utility given the right amount of search
Amihud & Mendelson (1986, 1991)Also: Miller-Modigliani (1961)
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Motivation
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Does Clientele Effect exist for real assets, which are characterized by
heterogeneous valuations,
utility from consumption,
and have no investment motive ?
Which type of houses is purchased by which type of buyers (by holding period)?
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The Model■ Theoretical model of illiquidity in residential housing markets Krainer & LeRoy (ET 2002)
■ Key features in our model:
selling pricetime on the marketproportions of houses by typeproportions of households by class
GENERAL EQUILIBRIUM: BUYERS & SELLERS
2 TYPES OF HOUSES
COMPETITION
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2 CLASSES OF HOUSEHOLDS
UNCERTAINTY
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The Model
2 TYPES OF HOUSES
2 CLASSES OF HOUSEHOLDS
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Short-tenure (S)e.g., Expect to moveout in 1-5 years
Long-tenure (L)e.g., Expect to moveout in 20-25 years
Good (HG)Higher potential utility
Bad (HB)Lower potential utility
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Search-and-match model
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The Model■ Agents differ in their expected housing tenure
Short-tenure agents ( S ) Long-tenure agents ( L )
Probability (preserve match with housing services during a given period):
πS
Probability (preserve match with housing services during a given period):
πL<ERES Conference 2010 (6/26/2010)
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The Model■ Houses differ in max amount of services they can provide
Distribution of ε reflects heterogeneity
Good houses ( HG ) Bad houses ( HB )
Prospective buyer’s drawn “fit:” ε1 ~ Uniform [ 0, 1 ]
Prospective buyer’s drawn “fit:” ε2 ~ Uniform [ 0, θ ]
0 < θ < 1
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The Model
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■ Key assumptions:
● Houses have only consumption value, no investment value
● Can buy or sell only 1 house per period
● Home choice problem, not a homeownership problem
● Buyers ex ante do not observe level of services of houses- Do NOT know if a house is Good or Bad
- Only know that in the economy, P(HG) = P(HB) = 0.5
● Sellers do not observe the type of buyers- Do NOT know if a buyer is Short-tenure or Long-tenure
- Only know that in the economy, P(S) = P(L) = 0.5
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The Model
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simultaneously Buyer & Seller simultaneously Buyer & Seller
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The Model: Buyer’s Side
Visit 2 houses randomly:
Good + Bad? Good + Good? Bad + Bad?
Buy 1 house
■ In every period t of house-searching process:
Don’t buy either; Keep searching in next
period t+1
or
Search option has value !
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The Model: Buyer’s Side
Household LIKES a house if:
For each class (Short-term, Long-term) and house type (Good , Bad):
● Marginal Probability (like G ) = (1 – εG ) Probability (Like G | visit G) = ● Marginal Probability (like B ) = (1 – εB/θ) Probability (Like G | visit G) = ● εG , εB each depends on household class: Short-term or Long-term ● Reservation fit is positively related to sales price
observed fit ≥ reservation fit ε ε
)#|()#(2
0#
GoodsawGoodlikePGoodsawP
)#|()#(2
0#
BadsawBadlikePBadsawP
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The Model: Buyer’s Side
Household LIKES a house does not guarantee purchase
For each class (Short-term, Long-term) and house type (Good , Bad):
● Availability factor – negatively related to competition ● Determined endogenously
Pr(BUY a house) = Pr(LIKE a house) x Availability factor
μ l a
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The Model: Buyer’s Side
Household’s search option value, s :
For each class (Short-term , Long-term):
s and s* = search option value during t, during t+1 μG and μB = per-period probability of house HG and HB
pG and pB = selling price of house HG and HB
β = discount factor v(ε) = life-time utility given fit ε ● Life-time Utility v(ε) :
v(ε) = β ε + β π v(ε) + (1 – π) (s + q) [
]
spps BGBB
BGG
G )1(22
1
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The Model: Buyer’s Side
Buyer’s dilemma:
For each class (Short-term , Long-term):
● Buyer’s F.O.C.:
Utility(ε) – price = discounted S + value of choice Net life-time utility > 0
● F.O.C. depends on: House type (Good, Bad) and buyer class (Short, Long)
Choose optimal ε1 and ε2 to maximize search option value S
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Seller’s value of house on the market, q:
For each house type (Good, Bad):
q and q* = value during t, during t+1 M = per-period selling probability p = selling price β = discount factor
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The Model: Seller’s Side
q = M p + β (1 – M) q*
Seller sets a take-it-or-leave-it price Trade-off: High price vs. longer time-on-the-market (liquidity) Sells in period t with some probability
● M is the probability that at least 1 of the visitors wants to buy the house
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The Model: Seller’s Side
Seller’s dilemma:
● Seller’s F.O.C depends on:
House type (Good, Bad) and buyer class (Short, Long)
Choose optimal price to maximize value of house on the market p q
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The Model: Nash Equilibrium
Solve system of equations to compute equilibrium
● 22 equations, 22 unknowns● Compute equilibrium values numerically● Unique solution is attained
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Research Questions Research Questions:
Are prices and liquidity (time-on-the-market) for Good and Bad houses (HG and HB) different? How?
Do short-term (S) buyers & long-term (L) buyers buy different house types (CLIENTELES)?
What is the composition of buyers & houses in the market?
Our Hypotheses:
priceG > priceB
Bad houses sell faster (liquid)
Characteristics of buyers L:
Likelihood to buy HG
Likelihood to buy HB
>
Characteristic of buyers S:Likelihood to
buy HG
Likelihood to buy HB
<
Dominated by Short-term buyers, & Bad houses
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Results
Characteristics of Long-term buyers:
Likelihood to buy HG
Likelihood to buy HB
>
Likelihood to buy HG
Likelihood to buy HB
<
Characteristics of Short-term buyers:
Presented by Ekaterina Chernobai
Myers and Pitkin (1995): frequently transacted homes are more likely to be “starter” homes owned by higher-mobility young households
McCarthy (1976), Clark and Onaka (1983), and Ermisch, Findlay and Gibb (1996): positive relation b/w housing demand & household age, and a negative relation b/w the two & mobility
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θ : Max level of services from partial-utility house μ : Per-period probability to buy this house type– , – – , --- : Expected tenure (S) is 2, 2.5, 3
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Results θ = 0.9 θ = 0.75 (very similar houses) (different houses)
μG / μB
indifferent indifferentLong
Short
Long
Short
Long
Short
E[net utility]G – E[net utility]B
Long
Short
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Results
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priceGood > priceBad
“Bad” houses sell faster (more liquid)
Past literature: Mixed results on the relationship b/w price & time-on-the-market
Haurin (1998): “house with a value of [the atypicality index] being two standard deviations above the mean is predicted to take 20% longer to sell than would the typical house”.
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θ : Max level of services from partial-utility house p ,TOM : House price, Expected time on the market – , – – , --- : Expected tenure (S) is 2, 2.5, 3
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Results θ = 0.9 θ = 0.75 (very similar houses) (different houses)
pG , pB
TOMG , TOMBGood
Bad
Good
Bad
Good
Bad
Good
Bad
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Results
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The market is dominated by:
- “Bad” houses
- Short-term buyers
Englund, Quigley and Redfearn (1999): in Sweden different types of dwellings have different price paths. Bias in repeat sales price index: track smaller, more modest homes that transact more often, rather than the aggregate housing stock.
Jansen, de Vries, Coolen, Lamain and Boelhouwer (2008): in the Netherlands, 30% of the apartments (i.e., low quality) were sold at least twice during the period of study, while the proportion of detached homes (i.e., high quality) sold was at mere 7%.
Case & Shiller (1987), Shiller (1991), Case, Pollakowski & Wachter (1991), Goetzmann (1992), Dreiman & Pennington-Cross (2004)
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Results θ = 0.9 θ = 0.75 (very similar houses) (different houses)
proportionL, proportionS
proportionG, proportionB
Long
Short
GoodBad
Long
Short
Good
Bad
0.5
0.5 0.5
0.5
θ : Max level of services from partial-utility house – , – – , --- : Expected tenure (S) is 2, 2.5, 3
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Summary of Main Results - (Theoretical) Clientele effect: Long-term buyers prefer “good” homes Short-term buyers prefer “bad” homes
Only consumption incentive
Heterogeneous valuations of houses
- Prices and liquidity: PG > PB and TOMG > TOMB
Net expected utility compensates for higher price of illiquid (=“good”) houses
As expected tenure(L) PG , PB and TOMG , TOMB
- Composition of houses & buyers on the market: Dominated by “bad” houses & Short-term buyers
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