FLS (flexible least squares): A FORTRAN program for time-varying linear regression via flexible least squares. Suppose the prior theoretical beliefs concerning the generation of a time-series data set take two forms: a prior measurement specification that the data has been generated by a linear regression model; and a prior dynamic specification that the regression coefficients evolve only slowly over time, if at all. The objective is to understand the actual relationship between the observed data and the regressor variables. In particular, do the estimated regression coefficients display any systematic time-variation? Is time-constancy a reasonably satisfactory approximation? The ”flexible least squares” solution is defined to be the collection of all coefficient sequences estimates which yield vector- minimal sums of squared residual measurement and dynamic modelling errors for the given observations - i.e. which attain the “residual efficiency frontier”. A user-friendly FORTRAN program (FLS) is now available for generating the frontier estimates.

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