Đang chuẩn bị liên kết để tải về tài liệu:
Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_3

Tham khảo tài liệu 'real estate modelling and forecasting by chris brooks and sotiris tsolacos_3', tài chính - ngân hàng, đầu tư bất động sản phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | An overview of regression analysis 75 Figure 4.1 Scatter plot of two variables J and x y 100 - 80 - 60 - 40 - 20 - 0 1 1 1 I 1 k x 10 20 30 40 50 to get the line that best fits the data. The researcher would then be seeking to find the values of the parameters or coefficients a and p that would place the line as close as possible to all the data points taken together. This equation y a fix is an exact one however. Assuming that this equation is appropriate if the values of a and p had been calculated then given a value of x it would be possible to determine with certainty what the value of y would be. Imagine - a model that says with complete certainty what the value of one variable will be given any value of the other. Clearly this model is not realistic. Statistically it would correspond to the case in which the model fitted the data perfectly - that is all the data points lay exactly on a straight line. To make the model more realistic a random disturbance term denoted by u is added to the equation thus yt a pxt Ut 4.2 where the subscript t 1 2 3 . denotes the observation number. The disturbance term can capture a number of features see box 4.2 . Box 4.2 Reasons for the inclusion of the disturbance term Even in the general case when there is more than one explanatory variable some determinants of yt will always in practice be omitted from the model. This might for example arise because the number of influences on y is too large to place in a single model or because some determinants of y are unobservable or not measurable. There may be errors in the way that y is measured that cannot be modelled. 76 Real Estate Modelling and Forecasting There are bound to be random outside influences on y that again cannot be modelled. For example natural disasters could affect real estate performance in a way that cannot be captured in a model and cannot be forecast reliably. Similarly many researchers would argue that human behaviour has an inherent randomness and .