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\begin{document}

\title{\textsc{Momentum traders in the housing market:\linebreak\ survey
evidence and a search model}}
\author{Monika Piazzesi \\
%EndAName
Stanford \&\ NBER \and Martin Schneider \\
%EndAName
Stanford \&\ NBER}
\date{Macro lunch Jan 6, 2009\\
}
\maketitle

\newpage

\begin{center}
{\large Motivation}

\bigskip
\end{center}

\begin{itemize}
\item House price boom in the early 2000s

\item What were they thinking?

\newpage
\end{itemize}

\begin{center}
{\large Motivation}

\bigskip
\end{center}

\begin{itemize}
\item House price boom in the early 2000s

\item What were they thinking?

\item How do beliefs affect prices in the housing market?
\end{itemize}

\newpage

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\newpage

\begin{center}
{\large Survey evidence}
\end{center}

2 phases in the boom:

\begin{enumerate}
\item early (2002\ \& 2003): \textbf{enthusiasm about housing \&\ credit}

most say "\emph{good time to buy a house}"

why?\ most say\ "\emph{good credit conditions}"

\item later (2004 \& 2005): \textbf{disagreement \&\ momentum}

fewer say "good time to buy a house"

more say "\emph{house prices are going up}" and "\emph{capital appreciation}"
\end{enumerate}

\newpage

\begin{center}
{\large Cluster analysis}
\end{center}

\begin{itemize}
\item a small number of views of the world?

\item consider survey responses on housing, growth, inflation, interest rates

\item estimate mixture density model

\item three clusters emerge:\ \ gloomy, good credit conditions, momentum
\end{itemize}

\pagebreak

\begin{center}
{\large Price impact}
\end{center}

\begin{itemize}
\item \emph{standard finance story}:\ stock market

no short sales but otherwise frictionless

$\Longrightarrow $ few wealthy optimists drive up prices by buying up all
assets

\item \emph{This paper}:\ housing market?

transaction costs, search, non-standardized asset, indivisible

$\Longrightarrow $ standard argument does not apply

but:\ recorded price = transaction price

$\Longrightarrow $ few (not wealthy) optimists can drive up prices with
small increase in volume
\end{itemize}

\newpage

\begin{center}
{\large Data }
\end{center}

Michigan Survey of Consumers (monthly, about 500 repondants)

Q:\ "\emph{Generally speaking, do you think now is a good time \newline
or a bad time to buy a house?}"

A:\ "good", "pro-con", "bad, "don't know"

\bigskip

Q:\ "\emph{Why do you say so?}"

A:\ respondents can give up to two reasons

e.g., \ good credit conditions ("interest rates are low", interest rates
won't get any lower", "credit is easy to get"), good investment ("house
prices are going up", "capital appreciation"), current prices are low, high
quality of the houses on the market\newpage

\begin{center}
{\large Michigan Survey of Consumers}\FRAME{dtbpF}{8.4596in}{6.7724in}{0pt}{%
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\end{center}

\newpage

\begin{center}
{\large Michigan Survey of Consumers }\FRAME{dtbpF}{8.4596in}{6.7715in}{0pt}{%
}{}{talk3.eps}{\special{language "Scientific Word";type
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{\large Michigan Survey of Consumers}\FRAME{dtbpF}{8.4596in}{6.7715in}{0pt}{%
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{\large Michigan Survey of Consumers}\FRAME{dtbpF}{8.4596in}{6.7715in}{0pt}{%
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\end{center}

\newpage

\begin{center}
{\large Michigan Survey of Consumers}\FRAME{dtbpF}{8.4596in}{6.7715in}{0pt}{%
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{\large Michigan Survey of Consumers}\FRAME{dtbpF}{8.4596in}{6.7715in}{0pt}{%
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\end{center}

\newpage

\begin{center}
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{\large Summary of stylized facts}
\end{center}

2 phases in the boom:

\begin{enumerate}
\item early (2002\ \& 2003): \textbf{enthusiasm about housing \&\ credit}

85\%\ most say "\emph{good time to buy a house}"

\qquad peaks earlier than house prices, enthusiasm not particularly high

why?\ 73\%\ say\ "\emph{good credit}"

\qquad which is always main reason for overall view of housing

\item later (2004 \& 2005): \textbf{disagreement \&\ momentum}

fewer say "good time to buy a house", 60\% in 2006

20\% say "\emph{house prices are going up}" and "\emph{capital appreciation}"

\qquad peaks with house prices, \underline{momentum at an all time high}
\end{enumerate}

\begin{center}
\newpage

{\large Cluster analysis}
\end{center}

\begin{itemize}
\item clusters characterize "views about the world"

housing, future business conditions, inflation \& interest rates,

\item statistical mixture model

within each cluster, survey responses to individual questions are independent

same probabilities within each cluster, different between clusters

mixture probability measures size of each cluster

\item probability that household $n$ answers question $i$ in cluster $c$:\
"good/higher" $\mu _{i,1}\left( c\right) $, "same/no mention" $\mu
_{i,2}\left( c\right) $, "bad/lower" $1-\mu _{i,1}\left( c\right) -\mu
_{i,2}\left( c\right) $

\item likelihood of answers in the survey \newline
{\normalsize L $=\tprod\nolimits_{n=1}^{N}\omega _{n}\sum_{c=1}^{C}p\left(
c\right) \tprod\nolimits_{i=1}^{I}\mu _{i,1}\left( c\right)
^{a_{i,1}^{n}}\mu _{i,2}\left( c\right) ^{a_{i,2}^{n}}\left( 1-\mu
_{i,1}\left( c\right) -\mu _{i,2}\left( c\right) \right) ^{a_{i,3}^{n}}$ }%
\newline
mixture probabilities $p\left( c\right) $, $I${\normalsize $=6$, }$%
{\normalsize C}$ varies, $\omega _{n}$ survey weight
\end{itemize}

\newpage

\begin{center}
{\large Cluster analysis ctd.}

\bigskip 
\end{center}

\begin{tabular}{cccccccccccc}
\multicolumn{12}{c}{\tiny late boom phase (2004, 2005)} \\ 
& \multicolumn{3}{c}{\tiny cluster 1} &  & \multicolumn{3}{c}{\tiny cluster 2%
} &  &  & {\tiny cluster 3} &  \\ 
{\tiny cluster prob} &  & {\tiny 0.27} &  &  &  & {\tiny 0.57} &  &  &  & 
{\tiny 0.16} &  \\ 
{\tiny next-year forecasts:} & {\tiny hi/better} & {\tiny same} & {\tiny %
lo/worse} &  & {\tiny hi/better} & {\tiny same} & {\tiny lo/worse} &  & 
{\tiny hi/better} & {\tiny same} & {\tiny lo/worse} \\ 
{\tiny bus. condition} & {\tiny 0.20} & {\tiny 0.52} & {\tiny 0.28} &  & 
{\tiny 0.35} & {\tiny 0.49} & {\tiny 0.16} &  & {\tiny 0.34} & {\tiny 0.47}
& {\tiny 0.19} \\ 
{\tiny interest rates} & {\tiny 0.75} & {\tiny 0.19} & {\tiny 0.06} &  & 
{\tiny 0.74} & {\tiny 0.22} & {\tiny 0.04} &  & {\tiny 0.78} & {\tiny 0.19}
& {\tiny 0.03} \\ 
{\tiny inflation} & {\tiny 0.36} & {\tiny 0.38} & {\tiny 0.26} &  & {\tiny %
0.33} & {\tiny 0.38} & {\tiny 0.29} &  & {\tiny 0.32} & {\tiny 0.40} & 
{\tiny 0.38} \\ 
\multicolumn{1}{l}{\tiny view about housing:} & {\tiny pos} & {\tiny --} & 
{\tiny neg} &  & {\tiny pos} & {\tiny --} & {\tiny neg} &  & {\tiny pos} & 
{\tiny --} & {\tiny neg} \\ 
{\tiny credit} & {\tiny 0} & {\tiny 0.78} & {\tiny 0.21} &  & {\tiny 0.92} & 
{\tiny 0.08} & {\tiny 0} &  & {\tiny 0.52} & {\tiny 0.48} & {\tiny 0} \\ 
{\tiny current house prices} & {\tiny 0.09} & {\tiny 0.46} & {\tiny 0.45} & 
& {\tiny 0.13} & {\tiny 0.84} & {\tiny 0.04} &  & {\tiny 0.03} & {\tiny 0.97}
& {\tiny 0} \\ 
{\tiny future house prices} & {\tiny 0} & {\tiny 0.90} & {\tiny 0.10} &  & 
{\tiny 0} & {\tiny 1} & {\tiny 0} &  & {\tiny 1} & {\tiny 0} & {\tiny 0} \\ 
{\tiny (1/N) log L} & \multicolumn{3}{c}{\tiny -4.8191} &  &  &  &  &  &  & 
&  \\ 
{\tiny mean, max s.e.} & \multicolumn{3}{c}{\tiny 0.0076, 0.015} &  & 
\multicolumn{3}{c}{\tiny 0.0064, 0.019} &  & \multicolumn{3}{c}{\tiny %
0.0069, 0.012}%
\end{tabular}

\newpage 

\begin{itemize}
\item summary -- three clusters:

\begin{enumerate}
\item gloomy

\begin{itemize}
\item (relatively)\ low growth, high inflation

\item bad time to buy a house\ 

credit conditions bad, prices too high and likely to fall
\end{itemize}

\item good credit conditions

\begin{itemize}
\item good time to buy a house because good credit and low prices

\item more optimistic on growth, inflation
\end{itemize}

\item momentum

\begin{itemize}
\item good time to buy because prices will raise

\item views on growth, inflation similar to 2, but higher expected interest
rates
\end{itemize}
\end{enumerate}

\newpage 
\end{itemize}

\begin{center}
{\large Observable characteristics}
\end{center}

\begin{tabular}{lccccccccc}
&  &  &  & \multicolumn{5}{c}{percent} &  \\ 
&  & age & income/yr & male & married & white & black & college & \#kids \\ 
momentum &  & 48.2 & 67403 & 48 & 57 & 77 & 5 & 46 & 0.55 \\ 
non-momentum &  & 47.3 & 60247 & 43 & 57 & 76 & 9 & 41 & 0.68%
\end{tabular}

{\footnotesize Average characteristics of households who justified their
view that now is a good time to buy (Michigan Survey of Consumers, variable
HOM)\ with \textquotedblleft house prices are going up\textquotedblright ,
\textquotedblleft house prices won't get lower\textquotedblright\ or there
will be \textquotedblleft capital appreciation\textquotedblright\ (variables
HOMRN1, HOMRN2) during the housing boom years 2004 and 2005, and those
households who did not. Averages based on survey weights.}

\bigskip 

\begin{itemize}
\item observable characteristics are significant in multinomial logit, with
zero $R^{2}$ 
\end{itemize}

\newpage 

\begin{center}
{\large Search model of the housing market}
\end{center}

\emph{setup}

\begin{itemize}
\item continuous time

\item measure 1 of infinitely lived households

\item quasilinear utility in numeraire consumption and housing consumption, 
\newline
discount future at $r$

\item indivisible housing units, fixed supply $h$ \TEXTsymbol{<}\ 1

\item one house max per person

\item preference shock:\ homeowner initially "happy" (gets services $v$ from
house)\ turns "unhappy" ($v$=0) with some probability (Poisson process with
arrival rate $\eta )$
\end{itemize}

\newpage

\begin{center}
{\large Search model of the housing market ctd.}
\end{center}

\emph{actions }

\begin{itemize}
\item homeowners (happy $\mu _{H}$ or unhappy $\mu _{U}$):\ \ \ put house on
the market? (costly!)

\item renters $\mu _{R}$:\ \ \ search for house?
\end{itemize}

\emph{matching}

\begin{itemize}
\item matching function $M\left( \mu _{B},\mu _{S}\right) =m\mu _{B}^{\alpha
}\mu _{S}^{1-\alpha }$, sellers make take-it-or-leave-it offers
\end{itemize}

\emph{equilibrium }

\begin{itemize}
\item optimal actions

\item number of home owners = fixed supply of houses = $h<1$
\end{itemize}

\newpage

\begin{center}
{\large Search model of the housing market ctd.}
\end{center}

\emph{steady state}

\begin{itemize}
\item only unhappy owners put house on market $\mu _{S}=\mu _{U}$, \newline
renters search $\mu _{B}=\mu _{R}=1-h$

\item housing price-dividend ratio%
\begin{equation*}
P=\frac{v}{r}-\frac{\eta }{r+\eta +m}\frac{v+c}{r}
\end{equation*}

discount vanishes as matching gets faster $(m\rightarrow \infty )$

\item pick parameters so that

\qquad 6\% houses traded per year, 3\% inventory outstanding, 16
price-dividend ratio,

\qquad cost incurred during sale 10\% of house value

\qquad $\Longrightarrow $ \ roughly 3\% renters

\newpage 
\end{itemize}

\begin{center}
{\large Search model of the housing market ctd.}
\end{center}

\emph{experiment}

\begin{itemize}
\item make renters optimistic

\qquad believe that house is worth price-dividend ratio of 19 (rather than
16)

\qquad once matched, they become happy owners
\end{itemize}

\newpage

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\newpage 

{\large Search model of the housing market ctd.}

\begin{itemize}
\item bottom line:\ small number of optimistic households can have large
price impact, even if each only buys one house and trading volume increases
modestly

[frictionless (stock)\ market:\ need wealthy optimistic households who buy
up all the assets, high volume]

\item key feature:\ high share of optimistic buyers in transactions, not
high market share!

\item average price \ = transaction price goes up in a market with few
transactions
\end{itemize}

\bigskip \newpage 

\begin{center}
{\large Conclusion}
\end{center}

\begin{itemize}
\item Stylized facts:\ 

in the late phase of the boom, \newline
a historically large fraction of households expected further house price
increases

\item Cluster analysis

three main views: good credit conditions, high future prices \&\ gloomy
outlook

\item Model:\ 

small number of optimists drive average prices in a search market, \newline
because average price reflects few transactions
\end{itemize}

\end{document}