This paper reexamines both monthly and quarterly U.S. postwar data to investigate if the observed comovements between money, real interestrates, prices and output are compatible with the money-real interest-output link suggested by existing monetary theories of output, which include both Keynesian and equilibrium models.The major empirical findings are these;1) In both monthly and quarterly data, we cannot reject the hypothesis that the ex ante real rate is exogenous, or Granger-causally prior in the context of a four-variable system which contains money, prices, nominal interest rates and industrial production.2) In quarterly data, there is significantly more information con-tained in either the levels of expected inflation or the innovationof this variable for predicting future output, given current and lagged output, than in any other variable examined (money, actualinflation, nominal interest rates, or ex ante real rates). The effect of an inflation innovation on future output is unambiguously negative. The first result casts strong doubt on the empirical importance of existing monetary theories of output, which imply that money should have a causal role on the ex ante real rates. The second result would appear incompatible with most demand driven models of output.In light of these results, we propose an alternative structural model which can account for the major dynamic interactions among the variables.This model has two central features: i) output is unaffected by money supply;and ii) the money supply process is motivated by short-run price stability.

Computes a GLS matrix weighted estimator for a panel data set. meangroup.src does a similar estimator, but uses simple weighted average rather than a matrix-weighted average. Swamy(1970), Efficient Inference in a Random Coefficient Regression Model, Econometrica, vol 38, 311-323. (This abstract was borrowed from another version of this item.)

A procedure is presented for the efficient computational solution of linear programs having a certain structural property characteristic of a large class of problems of practical interest. The property makes possible the decomposition of the problem into a sequence of small linear programs whose iterated solutions solve the given problem through a generalization of the simplex method for linear programming. 1. THE DECOMPOSED LINEAR PROGRAM MANY LINEAR programming problems of practical interest have the property that they may be described, in part, as composed of separate linear programming problems tied together by a number of constraints considerably smaller than the total number imposed on the problem. When the matrix of coefficients of such a problem, suitably ordered, is displayed in the usual way, a pattern emerges like that shown in Figure 1. In this figure the constraint matrix has been partitioned into nonzero blocks A1 and By, the right-hand side column of constants correspondingly into b, bl,..., bn; and the costs,