A time varying multivariate autoregressive modeling of econometric time series is shown. Deviations from trend data are modeled, Kozin's orthogonal Legendre polynomial time varying representation, a Householder transformation method of least squares modeling and the use of Akaike's AIC for subset selection are the key ideas in this method. Frequency domain relative power contribution computations yield an interpretation of the changing with time econometric relationships in the analysis of the U.S. hog, corn and farm wage series.