The Separation of Real Estate Value From Business Value, in Hotel Buildings Valuation. An Exploratory Work
Building valuation aims at stating a real estate value, which is the value of land and built premises. Hotel building valuation seems to have departed from the value statement for land and built premises and evolved to the mingling with hotel operating business. This evolution might require hotel building valuation to be performed by hotel business analysts more than by real estate valuers. Though, hotel buildings may be envisaged as income assets and hotel's underlying real estate appraised accordingly. The integration of real estate value on a casuistic business model raises the risk of inaccuracy in the valuation of land and built premises, if taken per se. From this perspective, we considered a simple multiple regression model, in which a set of variables that are easily and directly obtainable from hotel owners and that bear the closest possible connection to real estate value (e.g., age of building and type of tourist location), the dependent variable being the property value per room. Also, normal business variables (e.g. average daily rate multiplied with the occupancy rate) were included in the model as well. The purpose of the model was the comparison of the role of each category of variables (i.e., "real estate" and "business") in the formation of the property value per room (which is the standard benchmark in hotel building valuation) by analyzing a sample of previously valued hotel buildings. The model allows for the explanation of the stated property value to a significant extent, therefore hinting to the relevance of the chosen variables. It also provides for a benchmark of the proportion "real estate" variables should be expected to bear in the stated property value, with the need for deviations to be investigated through further valuation refinement. This outcome could therefore provide hotel real estate valuers with a tool to assess the accuracy of their valuation.
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Volume (Year): 6 (2011)
Issue (Month): 1 ()
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