Office and Industrial

Author(s):  
Grant Ian Thrall

A developer needs advice on the market for commercial space, including office and industrial properties. An owner of a commercial building needs to determine how much to charge for leased space, how much to sell the property for, or how much the property can be refinanced for. A purchaser needs to determine if market conditions support purchasing commercial space, or renting, and at what price. The real estate market analyst is responsible for the creation and assembly of information to guide such decisions. A background overview of real estate market analysis for the product categories of office and industrial projects is presented. The hedonic approach hypothesizes that a variety of phenomena contribute in one way or another to determining market rent. In a hedonic model, office or industrial property rent or occupancy rate may be the dependent variable of a regression equation, as explained in chapter 4. The phenomena that are hypothesized to cause the value of the dependent variable are the independent variables of the regression equation. Some examples of independent variables that have been hypothesized and examined in hedonic models as to their contribution to determining office market rent are listed below: . . . Terms of lease (Glascock et al. 1990). Architectural design (Hough and Kratz 1983) Building characteristics (Vandell and Lane 1989) Access to white collar employment (Clapp 1980) Local property tax rates (Wheaton 1984) Status and prestige (Archer 1981; Archer et al. 1990) Agglomeration—benefits of high geographic concentrations of specialized office establishments for specific kinds of industry (Gad 1979; Kroll 1984) Spillovers from close geographic proximity (Clapp et al. 1992). . . . Hedonic models might also include dummy variables as independent variables to represent the presence of some characteristic or phenomenon. The dummy variables have an assigned the value of 1.0 to denote the occurrence of some characteristic and 0.0 to denote its absence. An expectation must be developed by the analyst on how markets and submarkets differ in their rents, vacancy rates, and absorption rates and what their trend is expected to be.

2020 ◽  
Vol 12 (1) ◽  
pp. 144
Author(s):  
Ainur A. Akhmetzianov ◽  
Andrew Y. Sokolov

This article demonstrates the use of a financial and econometric model with dummy variables to calculate the average price in the real estate market. The average price is used in the model for calculating project effectiveness and allows you to evaluate the profitability of the project at the construction planning stage. The number of rooms, the presence of a balcony, the number of sides of the windows and the number of floors were used as independent variables. A model with these factors showed qualitative estimates and can be applied for the purpose of forecasting prices in standard projects in the Russian real estate market.


2017 ◽  
Vol 50 (3) ◽  
pp. 247-279 ◽  
Author(s):  
Pilar Gargallo ◽  
Jesús Angel Miguel ◽  
Manuel Juan Salvador

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