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

Presented by Ekaterina Chernobai page 2

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)

ERES Conference 2010 (6/26/2010)

Motivation


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)?


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


2 CLASSES OF HOUSEHOLDS

UNCERTAINTY


The Model

2 TYPES OF HOUSES

2 CLASSES OF HOUSEHOLDS


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

?

?

?

?

Search-and-match model



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)


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


The Model


■ 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


The Model


simultaneously Buyer & Seller simultaneously Buyer & Seller



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 !




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




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




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




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


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


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



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



The Model: Nash Equilibrium

Solve system of equations to compute equilibrium

● 22 equations, 22 unknowns● Compute equilibrium values numerically● Unique solution is attained



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


<

Dominated by Short-term buyers, & Bad houses


Results

Characteristics of Long-term buyers:



>



<

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


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

page 20

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

Results


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”.


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

page 22


pG , pB

TOMG , TOMBGood

Bad

Good

Bad

Good

Bad

Good

Bad

Results


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)



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


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


consumption of real assets and the clientele effect

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