Money Neutrality, Monetary Aggregates and Machine Learning

Periklis Gogas, Theophilos Papadimitriou and Emmanouil Sofianos

No 4-2016, DUTH Research Papers in Economics from Democritus University of Thrace, Department of Economics

Abstract: The issue of whether or not money affects real economic activity (money neutrality) has attracted significant empirical attention over the last five decades. If money is neutral even in the short-run, then monetary policy is ineffective and its role limited. If money matters, it will be able to forecast real economic activity. In this study, we test the traditional simple sum monetary aggregates that are commonly used by central banks all over the world and also the theoretically correct Divisia monetary aggregates proposed by the Barnett Critique (Chrystal and MacDonald, 1994; Belongia and Ireland, 2014), both in three levels of aggregation: M1, M2, and M3. We use them to directionally forecast the Eurocoin index: A monthly index that measures the growth rate of the euro area GDP. The data span from January 2001 to June 2018. The forecasting methodology we employ is support vector machines (SVM) from the area of machine learning. The empirical results show that: (a) The Divisia monetary aggregates outperform the simple sum ones and (b) both monetary aggregates can directionally forecast the Eurocoin index reaching the highest accuracy of 82.05% providing evidence against money neutrality even in the short term.

Keywords: Eurocoin; simple sum; Divisia; SVM; machine learning; forecasting; money neutrality (search for similar items in EconPapers)
JEL-codes: E00 E27 E42 E51 E58 (search for similar items in EconPapers)
Pages: 11 pages
Date: 2019-07-05
New Economics Papers: this item is included in nep-big, nep-cba, nep-cmp, nep-eec, nep-for, nep-mac and nep-mon
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Persistent link: https://EconPapers.repec.org/RePEc:ris:duthrp:2016_004

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