Money’s predictive role in output: evidence from recent data

Taniya Ghosh and Masudul Hasan Adil

Applied Economics, 2023, vol. 55, issue 38, 4415-4440

Abstract: We measure and assess the predictive performance of money in explaining output for the US, the UK, the Euro Area and Poland. Our approach, which uses more recent data and a larger set of areas, focuses on whether money ‘Granger causes’ output while taking into account the statistical properties of the data, which has implications for Granger causality tests. In addition to simple sum monetary aggregates, we use Divisia monetary aggregates, which are theoretically shown to be the actual measure of monetary services. Our results confirm that movements in money are still relevant in explaining movements in output, particularly when Divisia monetary aggregate is used. While the models using ‘narrow’ money, both simple sum and Divisia, provide mixed evidence of support, what appears to be robust across countries, is the predictive power of ‘broad Divisia’ in explaining output. Furthermore, our research finds no evidence that the statistical significance of money decreases as more variables are added to the model, or models with level variables produce more significant results than models with growth variables. In fact, rather than the level of money, it is the growth rate of money and the deviation of the growth rate of money from its time trend, which ‘Granger causes’ output.

Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2022.2129568 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:55:y:2023:i:38:p:4415-4440

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2022.2129568

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().