scholarly journals Divisia Monetary Aggregates for Russia: Money Demand, GDP Nowcasting, and the Price Puzzle

2021 ◽  
Author(s):  
Makram El-Shagi ◽  
Kiril Tochkov
Keyword(s):  
Money Demand ◽  
Monetary Aggregates ◽  
Divisia Monetary Aggregates ◽  
Price Puzzle

Divisia Monetary Aggregates, the Great Ratios, and Classical Money Demand Functions

2014 ◽  
Vol 46 (1) ◽  
pp. 229-241 ◽  
Author(s):  
APOSTOLOS SERLETIS ◽  
PERIKLIS GOGAS
Keyword(s):  
Money Demand ◽  
Monetary Aggregates ◽  
Demand Functions ◽  
Divisia Monetary Aggregates

scholarly journals INCORPORATING RISKY ASSETS IN DIVISIA MONETARY AGGREGATES

2003 ◽  
Vol 3 (1) ◽  
pp. 98-120
Author(s):  
Leigh Drake ◽  
Andy Mullineux ◽  
Juda Agung
Keyword(s):  
Mutual Funds ◽  
Money Demand ◽  
Demand Function ◽  
Monetary Aggregate ◽  
Risky Assets ◽  
Monetary Aggregates ◽  
Divisia Monetary Aggregates ◽  
Long Run ◽  
Causality Tests ◽  
Monetary Assets

Capital uncertain or risky assets are typically excluded from traditional broad monetary aggregates. Barnett et al (1997), however, extend the Divisia aggregation methodology to incorporate such assets. In addition, recent evidence provided by Drake et al (1998) suggests that risky assets are close substitutes for monetary assets. This paper constructs “wide” Divisia monetary aggregates which include risky assets such as unit trusts (mutual funds), equities and bonds, and contrasts their empirical properties with conventional Divisia and simple sum broad money aggregates. The key finding in the paper is that a “wide” monetary aggregate, which incorporates unit trusts, exhibits a stable long run and dynamic money demand function, has good leading indicator properties in the context of Granger causality tests, and tends to outperform all other aggregates on the basis of non-nested tests.JEL : E41, C43, E52 

Divisia monetary aggregates and money demand for Malaysia

2005 ◽  
Vol 15 (6) ◽  
pp. 1137-1153 ◽  
Author(s):  
Jauhari Dahalan ◽  
Subhash C. Sharma ◽  
Kevin Sylwester
Keyword(s):  
Money Demand ◽  
Monetary Aggregates ◽  
Divisia Monetary Aggregates

scholarly journals Money Neutrality, Monetary Aggregates and Machine Learning

Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 137 ◽  
Author(s):  
Periklis Gogas ◽  
Theophilos Papadimitriou ◽  
Emmanouil Sofianos
Keyword(s):  
Machine Learning ◽  
Economic Activity ◽  
Central Banks ◽  
Support Vector ◽  
Short Term ◽  
Monetary Aggregates ◽  
Divisia Monetary Aggregates ◽  
Vector Machines ◽  
The World ◽  
Short Run

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.

scholarly journals An Extended Series of Divisia Monetary Aggregates

1992 ◽  
Vol 74 (6) ◽  
Author(s):  
Daniel L. Thornton ◽  
Piyu Yue
Keyword(s):  
Monetary Aggregates ◽  
Divisia Monetary Aggregates
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