Appraisal of Beach Land in Bahia, Brasil

This assignment was to value an L-shaped beach parcel, with the wide end of the parcel situated more than 1 km from the beach. 

The subject parcel had already been approved by the local small town for a 900-lot residential development, and about 200 lots were sold before sales dried up 2 years ago.  One problem in selling lots was competition from other projects. This town, which had grand growth ambitions, had already approved 16 such projects, and the adjacent project had sold only 150 lots out of 735 before pulling the plug on development. If every approved home had been built, this small town would have expanded several times in size.

To re-energize sales, this developer was planning to reconfigure the project at a lower density and include a luxury hotel with amenities.  This new plan had not yet been submitted to the city for approval, nor had there been pre-sales activity.

Despite all the “planning approvals” dispensed by the town, there did not seem to be a concomitant plan to improve the transportation infrastructure in this area.  The approved projects consisted of vacation residences and hotel rooms, and tourists would generally be coming from the airport and large cities to the south.  However, this town can only be reached via a two-lane highway divided by an estuary that can only be crossed by ferry.  The ferry seems to run at full capacity already.  Imagine the strain on the ferry service when several thousand more people have relocated to this town.

 

   Main highway separated by ferry crossing

 

Debate about beach land valuation methods

 There is more than one way to value beach land. Some appraisers use “price per hectare” while others use “price per lineal meter of beach”.  I am in the latter camp for the following reason:

An appraiser or valuer takes raw sales data and tries to make order out of chaos.  This is often done with adjustment grids or calculation of price-per-unit indicators, such as price per hectare, price per meter, or price per room. The object of this process is to adjust comparable sales data into as narrow a range as possible so that a definitive estimate of value can be made with little room for doubt.

 In valuing beach properties, I have found that price per lineal meter of beach to be anywhere from slightly more correlated to significantly more correlated with sales prices than price per hectare.  The greater the variety of shapes, the less valid is the use of “price per hectare” as a unit of value.  This is intuitive, as a parcel with 400 meters of beach front and 100 meters of depth will be much more desirable than a parcel with just 100 meters of beach front but 400 meters of depth.

My use of “price per lineal meter” was contested by the mortgage broker, who thought that I should rely exclusively on “price per hectare”, which can be a valid technique under certain circumstances, namely that the size and shape of the parcels should be similar.  In this particular case, the subject property had only about 350 meters of beach front, while most of its lots were situated more than 1 km from the beach.  In other words, most potential residents in this project would be living far from the beach, and level terrain precluded having beach views. All of the 9 comps I found had better ratios of beach front to total area.

When I have doubts about which unit of comparison to consider, I calculate a coefficient of variation for each unit of comparison.  The "coefficient of variation" is simply the ratio of the standard deviation of the sample to the mean of the sample.  A low coefficient of variation means little variation and a narrow range of indicated values.

 In the case of price per hectare, the coefficient of variation was 1.68. Whenever the standard deviation is so much larger than the mean, you have a statistically meaningless relationship.

I then applied the same analysis to "price per lineal meter of beach". In this case, the coefficient of variation was .48, signifying a much higher correlation between price and lineal meters of beach front. When I removed the two most geographically distant parcels from my sample, the coefficient of variation fell to a remarkable .133 for price per lineal meter.

The point of this post is that differences in shape and beach frontage can cause significant variations in the value per hectare for beach properties. Value per lineal meter of beach front is the more reliable indicator of value.