Real Estate State of San Diego Real Estate

Health of Real Estate – Downtown/Coronado – November

Two very different real estate markets have emerged in Coronado (defined for the purpose of this analysis as all attached and detached residential properties listed with the San Diego Multiple Listing Service for the 92118 zip code). One is struggling and has challenges ahead. The other remains resilient and much better positioned.


Two very different real estate markets have emerged in Coronado (defined for the purpose of this analysis as all attached and detached residential properties listed with the San Diego Multiple Listing Service for the 92118 zip code). One is struggling and has challenges ahead. The other remains resilient and much better positioned.

To see this dichotomy, we segmented Coronado real estate into 3 groups by original listing price: 1) Properties less than $1.5 million; 2) Properties greater than or equal to $1.5 million and less than $2.4 million; and 3) Properties greater than or equal to $2.4 million. For each of these price groups, we compared their performance in the first 8 months of 2007 to the same period of 2008. Interestingly, their behaviors differed markedly between those properties below $1.5 million and those above $1.5 million. The contrast is significant enough to merit as two distinct markets.

The first market consists of properties with an original listing price less than $1.5 million (or price Group 1 from our segmentation list above). Of all the groups, this group is struggling the most under the current real estate environment. When comparing the first 8 months of 2007 to 2008, this group has experienced the greatest reduction in sales volume, the largest increase in existing inventory, and the largest median price decline. Most worrisome is the dramatic growth of inventory or properties available for sale within this price group. Even though the number of sales has declined almost 50% from last year, inventory has grown almost 20%, despite longer marketing timelines and falling prices. At some point, inventory will correct itself. Most likely, given waning demand, this will be due to: A) price reductions to attract demand and/or, B) reductions in new listings.

The second and stronger positioned market consists of properties with an original listing price greater than or equal to $1.5 million (or price Groups 2 and 3 from our segmentation list above). Even though there are behavior differences between Groups 2 and 3, they are slight, when contrasted as a whole to Group 1. It is this distinct contrast that differentiates them as a separate market. For example, while properties with an original listing price less than $1.5 million have dramatically grown inventory, those above have reduced average daily inventory levels. Much of this inventory reduction has come from a reduction in new listings and a stronger relative demand level than those properties below $1.5 million. Not surprisingly, median prices have either been maintained or increased slightly, since 2007. However, equally important, this “second market” is much better positioned going forward, since it will not be wrestling with excess supply.

This market dichotomy within Coronado highlights the importance of establishing buy/sell strategies. Those who have followed this editorial throughout 2008 understand that not only do areas behave differently, but so do subpopulations within those areas. Some of these subpopulations experienced different appreciations on the way up. What we are witnessing now is how differently many of these subpopulations behave on the way down. Some will fare better than others, but incorporating those anticipated dynamics into a buy/sell strategy is critical. No one can precisely predict how a subpopulation will decide to correct itself. Will it take its properties off the market and ride out the environment? Will it sell off? And then, in what proportion and degree? This is determined in part by demographic behavior, economics, and personal financial positions. None of which are known comprehensively. However, some scenarios do present readily apparent inferences. It is these conclusions that should at least be considered when selecting an investment direction.

Downtown San Diego

Of all the areas that we analyze, downtown San Diego (defined for the purpose of this analysis as all residential properties in the 92101 zip code) has been under the greatest degree of transformation, adding several spectacular condominium buildings with literally world class views. However, it is exactly this vertical growth or dramatic increase of new supply that makes downtown a challenge to analyze. Like other areas, it is bounded by its zip code, but unlike other areas, downtown has been growing toward the sky. Essentially, this is equivalent to an expanding zip code boundary.

To better appreciate how new construction can distort statistics, we created two geospatial representations of all sale activity for downtown San Diego from January 2006 to July 2008. The first representation (Chart C) shows the number of residential sales plotted against downtown parcels. We call it a geospatial representation, because the number of sales are represented as a cluster cloud lying over the downtown area. This cloud represents 81% of all downtown sales with the other 19% not shown but broadly dispersed over the remaining zip code. In Chart C, there are four clusters representing the areas of highest sale activity. The second representation (Chart D) shows the same cluster cloud, but plotted over the districts of downtown. As we will see, portions of the sale activity, represented by the cluster cloud, are due to new construction while other portions are due to existing repeat sales. Separating the two and understanding their influence upon one another is critical for assessing market dynamics.

If we look at the second geospatial representation (Chart C), showing the sale activity against downtown districts, it is clear that the majority of the activity happens along the waterfront. This occurs because the larger condominium buildings border the waterfront while most commercial parcels occupy downtown’s center. When comparing the first half of 2007 to 2008, we see very different statistics coming from each cluster, largely skewed by the presence or absence of new construction. For example, Cluster 1 had 124 sales for the first half of 2007 and 86 sales for the same period in 2008. Average sale price remained unchanged at approximately $460K. This activity represents the dynamics of no new construction within this area for the time period under consideration. However, when we look at Cluster 3, we see a clear aberration emerge. Sales increase from 50 in 2007 to 183 in 2008 with average sale price also increasing 11% from $812K in 2007 to $903K in 2008.

When analyzing the data points that make up Cluster 3, it quickly becomes apparent that Cluster 3 is primarily made up from the sale activity of a single, large new luxury condominium building. This is why we see sales go from 50 to 183 when comparing the first half of 2007 and 2008. It is also why we see the average sale price jump 11%. Cluster 3 represents apples and oranges; new and existing inventory. The introduction of this new building into the downtown real estate market skews existing sale statistics, especially for its localized sale cluster area. Compounding the issue, there are many of these new large buildings that were introduced and are still being introduced to the downtown market. The key to assessing the downtown market dynamics is price-per-square foot. The challenge there is normalizing the square footage by multiple categories. Floor height is a category. View direction is a category. Downtown location is a category. Construction quality is a category. Building amenities is a category. New construction or building age is a category, etc. Here we showed how the latter can skew statistics when not properly segmented out from existing inventory. In articles to come, we will show the influence of some of these other categories when not properly accounted for.

What’s next?

When reviewing the data that we put together for Coronado and Downtown San Diego, it is important to remember that these areas are comprised of sub-populations, some behaving much differently than others. For example, properties that are on the beach in Coronado can behave differently than other areas of Coronado. Likewise, condominiums in one area of downtown can behave differently than another area. There are even sub-populations within areas. What we have presented here is a partial sub-population analysis. A complete analysis would identify the subpopulation of the property in question and then assess that particular subpopulation’s behavior. In next month’s edition, we will revisit Rancho Santa Fe and Del Mar for an update of their year-to-date performance.

Written by Linda and Tom Sansone

Willis Allen Real Estate

(858) 775 – 6356

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