Posts Tagged ‘neighborhoods’

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2008 Neighborhood Rankings – Part I

December 15, 2008

We went through all 85 neighborhoods in San Francisco (as determined by the MLS), calculating the median sales prices for 2008 (January 1 through December 13).  Included in the medians are single family homes, condominiums, stock cooperatives, lofts, and TIC property types.

Where is your neighborhood on the totem pole?

Where is your neighborhood on the totem pole?

The rankings were, shall we say, quite interesting, and we’ve decided to take a look at this list periodically to see how it’s changing.  We also have another ranking of all 86 neighborhoods coming out, so stay tuned.

Rank Neighborhood Median SP
1. Sea Cliff $3,150,000
2. Presidio Heights $2,210,000
3. Clarendon Heights $1,995,000
4. St. Francis Wood $1,995,000
5. Sherwood Forest $1,690,000
6. Jordan Park/Laurel Heights $1,650,000
7. Balboa Terrace $1,500,000
8. Monterey Heights $1,487,500
9. Cow Hollow $1,450,000
10. Forest Hill $1,400,000

To see the remainder of the list, continue reading –> Read the rest of this entry ?

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In Search of Truth : The Method

December 1, 2008

We learned a lot about the Case-Shiller Index last week.  Admittedly, we have not placed much faith in this particular index for the following reasons.  First, it analyzes metropolitan area statistics.  If you haven’t figured it out by now, we’re much more into neighborhood-level data, as we have found that neighborhoods truly are their own micro-markets, each behaving in their own way.  Another reason we did not give Case-Shiller much credit is because they leave out condos, TIC’s, stock cooperatives, and lofts.  The index is based upon single family home sales only.  This is a big drawback.

Don't worry, your detective has arrived.
Your detective has arrived.

Despite these shortcomings, we read through the 40 page document describing the Case-Shiller methodology.  There is certainly value in what they are attempting to do.

In short, they look at the sales price of a recently sold home and compare it to the previous sale of that same home.  This allows them to see whether the home appreciated or depreciated, and at what rate.  Comparing the home to itself controls for factors that can dirty data when comparing homes against other homes.  When a particular home has a previous sale to which it can be compared, this called a “matched pair“.  Case-Shiller takes thousands of matched pairs to come up with their overall metropolitan area (MSA) trend.  The other brilliant thing about Case-Shiller is that they discard sales of homes that took place off-market, that were flipped (two sales too close together), and that had gains from major renovation projects or significant added square footage.  Do they go through each listing manually to verify this?  This answer is no.  There is an algorithm that decides which matched pairs to keep and which ones to discard.

Case-Shiller does offer zip-code level based data.  We called the provider (Fiserv) to purchase it so we could report on it and give it to you.  However, only institutions can purchase the data and furthermore, they cannot reproduce or share the data with anyone else (per the user license).

SO – what we’ve done is come up with our own methodology, drawing from the positive aspects of the Case-Shiller Index and applying it to our micro-markets here in San Francisco.  We’ll be reporting on each neighborhood as we go through them one by one.  Is this painstaking?  You bet.  But we are in search of truth.  And that’s what the series will be called… “In Search of Truth”.

Here’s a look at our methodology: Read the rest of this entry ?

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