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Housing Prices: Demand
and Supply
Some readers were misled by the term "inflation adjusted."
It means that I am trying to explain increases in housing
prices that exceed the general level of inflation. For
example, the price of the median owner occupied home in Seattle
was $137,000
in 1989. In
2006, the US Census reports this price to be $447000. The total price increase
from 1989 to 2006 was therefore $310,000. We have to keep in
mind, however, the increase in the general price level from 1989
to 2006. Adjusting the data for
inflation, housing prices in Seattle rose about $226000, which represents the increase in housing prices
above and
beyond the rise in the general price level. It is this
increase in the "inflation adjusted" housing prices that I
examine.
The
interpretation is not that 80 percent of Seattle's housing price
is due to regulations; instead, I estimate that 44 percent of
the 2006 price of a median owner occupied home in Seattle (or
$200,000) is due to a price change since 1989 that can be
associated with land use regulations.
Another point of confusion can be the housing price data. Did
housing prices really increase "that much" in Seattle? Some
claim the increase in Seattle's housing price is not unusual,
and perhaps even below the rate of growth experienced by other large cities.
Although this
question is not directly related to the study (or the question I
set out to examine), the claim is well worth investigating. I
examine alterative housing data in "Have Housing Prices Really
Risen that Much? A Discussion of Alternative Housing Price Data for
Seattle and 15 Major Metropolitan Areas"
and cannot find support for the claim in the data.
In my attempts to
examine the drivers of housing prices, I relied on data collected by the
Samuel Zell and Robert Lurie Real Estate
Center by the
Wharton School of Business at the
University of Pennsylvania. All the relevant data on housing
regulations was obtained from
A New Measure of the Local Regulatory
Environment for Housing Markets: The Wharton Residential Land Use Regulatory
Index (March, 2007), which
was written by
Joseph Gyourko (Martin
Bucksbaum Professor of Real Estate and Finance, Acting Chairperson, Real Estate
Department Director, Samuel Zell and Robert
Lurie Real Estate Center),
Albert Saiz (Assistant
Professor of Real Estate, Wharton), and
Anita Summers (Professor
Emeritus of Public Policy, Management, Real Estate and Education).
The paper documenting the data is forthcoming in a journal called
Urban Studies.
The data was kindly made available to me by
Joseph Gyourko from his
website.
The
Wharton data is the only large scale (2730 cities) land use data that is
objective and comparable that I have located. By "comparable" I mean that the
land use restrictions across cities are identically defined and collected, and
by "objective" I mean that the data has not been created by a
particular researcher for a particular study
in a particular city. The only other national large scale study that I am aware of was
conducted by Stephen Malpezzi's “Housing
Prices, Externalities, and. Regulations in U.S. Metropolitan Areas,”
Journal of Housing Research, 7:2, 1996, 209–241, which contained data on
about 50 cities (no cities from Washington State are included in that study).
The
study that establishes the regulation data is
well documented
(follow this link!) and all questions regarding the data collection
must be directed to the
Joseph Gyourko (Martin
Bucksbaum Professor of Real Estate and Finance, Acting Chairperson, Real Estate
Department Director, Samuel Zell and Robert
Lurie Real Estate Center),
Albert Saiz (Assistant
Professor of Real Estate, Wharton), and
Anita Summers (Professor
Emeritus of Public Policy, Management, Real Estate and Education).
If a
city is not included in the 2007 Wharton data, it is either because a particular
jurisdiction (a) is not part of the
ICMA list that Wharton used as a
base for their sample; or (b) the jurisdiction did not respond to Wharton's
survey requests. Wharton sent out three requests to each jurisdiction.
If you
want to look up how a particular city in the sample ranks, you can find a
ranking of the cities for each land use criterion in this
Ranking Spreadsheet (note that
this MSExcel spreadsheet contains several worksheets). This is again, not my data,
but the data from the Wharton study.
Note that my analysis is not
confined to Seattle. Quite to the contrary: I used all available data for 250 major cities
included in the Wharton data to find the variables that explain variation in
housing prices across US cities. I could not use more cities since the intersection
between the 2006 Census data (which provided income, population, land area, and the
median price of an owner occupied house) and the Wharton data limited the sample
to those 250 cities. Based on the estimates obtained from regression
analysis, a researcher is then able to examine how each individual city is
affected by each individual regressor.
My thoughts about the results of the data
analysis are summarized in
Washington's
Housing Prices which is
forthcoming in the Northwest Journal of Business and Economics.
This paper cites my working paper
Municipal and Statewide Land Use Regulations and
Housing Prices Across 250
Major US Cities
which reports on the
regression analysis
for the entire sample. Those who find the numbers in the study
preposterous, may find it helpful to read
Glaeser and
Gyourko (2002) which is also discussed in the
Atlantic Monthly by Virginia Postrel (2007), as well as
Malpezzi (1996). The Glaeser and Gyourko study includes
Seattle, while the Malpezzi study is the other study of major US cities, housing
prices and regulations.
My
personal impression is that the literature on housing price and regulations is highly fragmented.
You may find this
reference list of academic studies
a helpful start.
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