Single equation regression models: -The dependent variable, Y, is expressed as a linear function of one or more explanatory variables, the Xs. Assumption the cause-and-effect relationship, if any, between Y and the Xs is unidirectional: explanatory variables are the cause; the dependent variable is the effect
14.1 Restricted Least Squares (RLS) 1. OLS and RLS ()Unrestricted least squares(ULS) When using the ordinary least square method(OLS) to estimate the parameters, we do not put any prior constraint() or restriction(s) on the parameters. So we can estimate the parameters without any restrictions. This is ULS
12.1 The Nature of Autocorrelation 1. Definition (1) CLRM assumption: No autocorrelation exist in dishurbances ui; E(iμi)=0 Autocorrelation means: E(μiμ)≠0 (2) Autocorrelation is usually associated with time series data, but it can also occur in cross-sectional data, which is called spatial correlation