Money And Income, Causality Detection
AbstractIn this paper we intend to survey and suggest the theoretical framework of the important aspects of causality detection with the purpose of conveying to the reader the essential features and the different forms in which inferences may be drawn from given data. Section II presents the basic theorem characterizing the causality events and suggests two feedback detection methods which, like the one suggested by Pierce and Haugh (1977), are based on correlation analysis. In Section III we survey other well-known causality detection methods and try to relate and to compare them with the methods suggested in Section II. Section IV briefly reviews the theoretical controversy of the relationship between money and income and presents some empirical evidence based on the methods discussed in this paper. Conclusions are in Section V.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 0167.
Date of creation: Mar 1977
Date of revision:
Publication status: published as Hsiao, Cheng. "Autoregressive Modelling And Money-Income Causality Detection," Journal of Monetary Economics, 1981, v7(1), 85-106.
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