Indicator and filter attributes of monetary aggregates: A nit-picking case for disaggregation

Abstract All global measures do conceal information. That is their virtue as well as their vice, and the task of science, in economics as elsewhere, is to find and devise aggregates which retain mostly essential information and discard mainly irrelevant information.

[1]  D. Lindley.  On a Measure of the Information Provided by an Experiment , 1956 .

[2]  P. Tinsley,et al.  On filtering auxiliary information in short-run monetary policy , 1977 .

[3]  Henri Theil,et al.  Economics and information theory , 1967 .

[4]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[5]  Peter A. Tinsley,et al.  Linear prediction and estimation methods for regression models with stationary stochastic coefficients , 1980 .

[6]  Walter D. Fisher.  OPTIMAL AGGREGATION IN MULTI-EQUATION PREDICTION MODELS , 1962 .

[7]  B. Friedman.  The Inefficiency of Short-Run Monetary Targets for Monetary Policy , 1977 .

[8]  J. Chipman.  Estimation and Aggregation in Econometrics: An Application of the Theory of Generalized Inverses , 1976 .

[9]  W. Barnett,et al.  The velocity behavior and information content of Divisia monetary aggregates , 1979 .

[10]  Y. Ijiri.  Fundamental Queries in Aggregation Theory , 1971 .

[11]  P. Tinsley.  On proximate exploitation of intermediate information in macroeconomic forecasting , 1975 .

[12]  John S. Chipman,et al.  On Least Squares with Insufficient Observations , 1964 .

[13]  P. Tinsley,et al.  The measurement of money demand , 1978 .

[14]  Robert B. Ash,et al.  Information Theory , 2020, The SAGE International Encyclopedia of Mass Media and Society.

[15]  D. Luenberger.  An introduction to observers , 1971 .

[16]  H. Hotelling.  Relations Between Two Sets of Variates , 1936 .