miamidata

The Miami Data Indices

Monthly and annual indices that track changes in resale and inventory of condo, single-family homes, and rental properties for Miami, Miami Beach, Brickell, Downtown Miami, Edgewater/Midtown, Aventura, Sunny Isles Beach, Bar Harbour/Surfside, Coral Cables, and Coconut Grove.

We parse down the data for some of the most in demand neighborhoods in Miami going as far back as January 2008 for all condos and single family homes and 2010 for all rental properties.

Waterfront versus Non-Waterfront properties:

This is one of the most important data points on miamidata.com. According to the United States Census Bureau, Miami Beach has a total area of 18.7 square miles (48.5 km2), of which 7.0 square miles (18.2 km2) is land and 11.7 square miles (30.2 km2) (62.37%) is water. Miami Beach has a lot of waterfront and these properties have a premium value attached to them. The vast majority of new development and retrofits over the last 20 years in Miami Beach are properties abutting to the waterfront including the Atlantic Ocean, Biscayne Bay, and the many canals, waterways and lakes. It’s extremely important when doing a pricing study that we differentiate the difference. As surprising as it may seem, there are very few new developments in Miami Beach that are not directly on the water. In South Beach you have projects such as Artecity, which is comprised of six properties making this a large community of Art Deco low-rises, villas, and two new construction towers built in 2012. 2001 Meridian, 6000 Collins Ave, 1700 Meridian Ave, 6080 Collins Ave, and a few others are among part of a collection on non-waterfront luxury condos built in recent years.

The difference between properties built before 1996 and after 1997:

Older properties account for the majority of Miami's lower rise structures, Art Deco architecture, beach style condos, and smaller houses, the vast majority of which were built in the 1970's and earlier. There was a period of very little residential development in Miami throughout the 1980's and most of the 1990’s. In 1996 a Florida building code commission was formed. The purpose being to create a single minimum building standard and enforce compliance. This is the direct result of the damage from Hurricane Andrew in 1992. Here and here. Legislation was first introduced in 1997 with the recommendations adopted in 1998 by the state. By 2002, the first edition of the new building codes superseded all other local codes and maintained by the Florida Building Commission. It's also now the standard used by other cites in Florida. Miami's luxury condos along the waterfront feature some of the best engineering and build quality in the world. After legislation adopted the new building codes, including local incentives to build, luxury condos started to dot the skyline in the late 1990’s. They trade at a significant premium to their pre 1996 residential predecessors. We chose to use 1996/1997 as the cut-off to determine value considering the official designation in the revision of building codes and also when factoring a handful of luxury properties in the late 1990’s that show current values more in line with their younger counterpart than properties built much earlier.

Furnished versus Unfurnished:

Miami’s ownership profile can vary from primary residents to part-time residents, seasonal guests to investment groups. The truth is, much of the investment made in Miami are independent owners - individuals who own real estate on the beach where this is their 2nd or 3rd home. Perhaps some live here for more than 6 months a year, but many of our residents own other real estate elsewhere when coming to Miami. Because of this and factoring in our large tourism industry, Miami has a large market for short-term rentals including furnished rentals. You also need to consider having the proper business designation and tax status. This is an excellent article on short- term rentals. Zoning restricts most single family areas from operating as short-term rentals. Unfurnished rentals vary from neighborhood to neighborhood, but account for the majority of rentals overall in Miami.

Listing Price (average for condo or median for single family):

We have developed formulas that process all data for a specific area and analyze the relationship between original listing price, last listing price to sold price. The difference in using average for condo and median for single family general comes down to the sample used for each study. Median is the middle point of all properties entered in a data set and is usually better representative of markets with lower inventory or larger gaps in pricing ex. It’s quite common to have a house on the water in Miami Beach sell for $10M, $15M, $20M and the house directly across the street sell for $1.5M, $2M, $3M which is not on the water. Ex: using Median when analyzing five house sales. Five houses sell for $850k, $1.4M, $2.2M, $4.8M and $11M. The median in that data set is $2.2M. This tells you exactly that two houses sold for less than $2.2M and two houses sold for more. While the sales prices are relevant, this is a great indicator about values in a particular neighborhood or block. If we used average and the same data set above, the result would be $4,050,000. If you’re a buyer looking for a house for $1M or $2M and have an impression that average values for houses in that neighborhood are $4M, you’ll think you’re priced out. Usually most data aggregators use Median the same, but don’t highlight the reason as to why this is important. We use average specifically for condominiums and rentals. Average tends to be more representative of value with larger data sets, which is why it is the most widely used method for analyzing real estate transaction data. The purpose is to summarize large amounts of data into a single value. Within buildings or neighborhoods where values are clustered, the average of all data used will often be much more in line with most properties used in the data set. Average is typically weighed higher than median values in larger data sets.

Price Per Square Foot (average for condo or median for single family):

We like using P/PSF to establish a macro view of neighborhood value. You can arrive at the "average" per-square-foot cost of a home by adding the square foot cost of each home in a data set and then dividing that by the number of homes that sold. For example:

Property A sold at $200 per square foot.
Property B sold at $167 per square foot.
Property C sold at $167 per square foot.
Property D sold at $150 per square foot.
Property E sold at $278 per square foot.