Velocity Volatility Assessment of Monetary Shocks on Cash-in-Advance Economies

Jose Cao-Alvira

Computational Economics, 2012, vol. 40, issue 3, 293-311

Abstract: A projection method employing finite elements and a parameterized expectations algorithm is proposed for the global approximation of the equilibrium of a cash-in-advance model economy. The algorithm is shown to be accurate and efficient approximating highly nonlinear regions of the policy functions, specifically along the space of state variables where the slackness multiplier of the cash-in-advance constraint alternates between zero and strictly positive values. This favorable trait allows for a rigorous analysis on the variability of velocity of money. Velocity volatility, measured by its coefficient of variation, arises in the model on a consumption smoothing purpose by the agent at instances where the variation of expected marginal utility of consumption is relatively high due to the realization of a sufficiently low serially correlated monetary shock. In a simulation of the stochastic economic environment responding to a Markovian series of monetary growth rates and no frictions present, the equilibrium approximated via the proposed numerical solution method explains 80.3% of the velocity variability recently observed in the data; a significant improvement over previous attempts found in the literature. Copyright Springer Science+Business Media, LLC. 2012

Keywords: Finite element method; Inequality constraints; Cash-in-advance; Money velocity; C63; C68; O42; E32 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s10614-011-9292-9 (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:kap:compec:v:40:y:2012:i:3:p:293-311

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-011-9292-9

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().