Econometric EquationsIn the case of real estate, a system of equations, some of which are statistical/econometric and some identities, is often used to describe the behavior of crucial real estate market variables, such as demand, supply, prices, rents, etc. For example, an econometric equation for the demand for office space (in which case the demand for office space would be referred to as the dependent variable) will describe the factors that affect it (the independent variables) and how they affect it (in a linear or non-linear fashion), as reflected in the form of the mathematical equation describing their effect. Caution is needed when selecting the independent variables to include in an econometric equation in order to avoid problems of collinearity. Collinearity refers to the case where two variables are highly correlated (move together). For example, in a national office space demand equation one may be inclined to use as independent variables, among others, GDP growth and office employment growth. However, this will in most likelihood create collinearity problems in the sense that these two variables are highly correlated, in the sense that when GDP growth is high office employment growth is high, and when GDP growth is low office employment is low as well. Collinearity is a problem because results in biased parameter estimates. These equations are estimated through various statistical methods, with the Ordinary Least Squares (OLS)technique being the most commonly used. This technique though refers to linear relationship between the dependent and independent variables. Furthermore, its use implies that some other assumptions are valid regarding the behavior of the dependent variable. If the analyst believes that the independent variables affect the dependent variable in a non-linear fashion then other statistical estimation techniques need to be used. Econometric analysis of real estate markets is the most advanced methodology for quantifying the effect of different demand and supply variables on property prices and rents. As such, it provides the most appropriate means for forecasting the movements of real estate prices and rents under a particular economic and employment growth scenario. However, it should be emphasized, that all forecasts, including the econometric ones, have a prediction error. For this reason, any econometric forecast should not be adopted blindly by the analyst before examined carefully for its reasonableness and whether it makes sense.
|
