Time Aggregation, Long-Run Money Demand and the Welfare Cost of Inflation

Rangan Gupta and Josine Uwilingiye

No 200825, Working Papers from University of Pretoria, Department of Economics

Abstract: Two recent studies have found markedly different measures of the welfare cost of inflation in South Africa, obtained through the estimation of long-run money demand relationships using cointegration and long-horizon approaches. Realizing that the monetary aggregate and the interest rate variables are available at higher frequencies than the measure of income and that long-run properties of data are unaffected under alternative methods of time aggregation, we test for the robustness of the two estimation procedures under temporal aggregation and systematic sampling. Our results indicate that the long-horizon method is more robust to alternative methods of time aggregation, and, given this the welfare cost of inflation in South Africa for an inflation target band of 3 percent to 6 percent lies between 0.15 percent and 0.41 percent.

Keywords: Cointegration; Long-Horizon Regression; Money Demand; Time Aggregation; Welfare Cost of Inflation. (search for similar items in EconPapers)
JEL-codes: C15 C32 C43 E31 E41 E52 (search for similar items in EconPapers)
Pages: 14 pages
Date: 2008-07
New Economics Papers: this item is included in nep-cba, nep-mac and nep-mon
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Time Aggregation, Long-Run Money Demand and the Welfare Cost of Inflation (2009)
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:pre:wpaper:200825

Access Statistics for this paper

More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rangan Gupta ().