Hostname: page-component-7b7567c8c-lpg2g Total loading time: 0 Render date: 2026-11-15T10:19:00.258Z Has data issue: false hasContentIssue false
  • English
  • Français

MEASUREMENT ERROR IN MONETARY AGGREGATES: A MARKOV SWITCHING FACTOR APPROACH

Published online by Cambridge University Press:  15 September 2009

William A. Barnett,
Marcelle Chauvet and
Heather L. R. Tierney
William A. Barnett
Affiliation:
University of Kansas
Marcelle Chauvet*
Affiliation:
University of California, Riverside
Heather L. R. Tierney
Affiliation:
College of Charleston
*
Address correspondence to: Marcelle Chauvet, Department of Economics, University of California, Riverside, CA 92521-0247, USA; e-mail: chauvet@ucr.edu.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

This paper compares the different dynamics of the simple-sum monetary aggregates and the Divisia monetary aggregate indices over time, over the business cycle, and across high and low inflation and interest-rate phases. Although traditional comparisons of the series sometimes suggest that simple-sum and Divisia monetary aggregates share similar dynamics, there are important differences around turning points that cannot be evaluated by their average behavior. We use a factor model with a regime-switching model that separates the common movements underlying the monetary aggregate indices from idiosyncratic variations in each series. We find that the major differences between the simple-sum aggregates and Divisia indices occur around the beginnings and ends of recessions and during some high-interest-rate phases. We note the inferences' policy relevance, which is particularly dramatic at the broadest (M3) level of aggregation. Indeed, as Belongia [Journal of Political Economy, 104 (5) (1996), 1065–1083] has observed in this regard, “measurement matters.”

Keywords

Measurement ErrorMonetary AggregationDivisia IndexAggregationState SpaceMarkov SwitchingMonetary PolicyIndex Number TheoryFactor Models

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 13 , Supplement S2: Measurement with Theory , September 2009, pp. 381 - 412
Copyright
Copyright © Cambridge University Press 2009

References

REFERENCES

Anderson, R., Jones, B., and Nesmith, T. (1997a) Building new monetary services indexes: Concepts data and methods. Federal Reserve Bank of St. Louis Review 79 (1), 53–82.Google Scholar
Anderson, R., Jones, B., and Nesmith, T. (1997b) Introduction to the St. Louis Monetary Services Index Project. Federal Reserve Bank of St. Louis Review 79 (1), 25–30.Google Scholar
Arrow, K.J. and Hahn, G.H. (1971) General Competitive Analysis. San Francisco: Holden–Day.Google Scholar
Barnett, William A. (1978) The user cost of money. Economics Letters 1, 145–149. [Reprinted in Barnett and Serletis (2000, Ch. 1, pp. 6–10).]CrossRefGoogle Scholar
Barnett, William A. (1980) Economic monetary aggregates: An application of aggregation and index number theory. Journal of Econometrics 14, 11–48. [Reprinted in Barnett and Serletis (2000, Ch. 1, pp. 6–10).]CrossRefGoogle Scholar
Barnett, William A. (1982) The optimal level of monetary aggregation. Journal of Money, Credit, and Banking 14, 687–710. [Reprinted in Barnett and Serletis (2000, Ch. 7, pp. 125–149).]CrossRefGoogle Scholar
Barnett, William A. (1983) Understanding the new Divisia monetary aggregate. Review of Public Data Use 11, 349–355. [Reprinted in Barnett and Serletis (2000, Ch. 4, pp. 100–108).]Google Scholar
Barnett, William A. (1987) The microeconomic theory of monetary aggregation. In Barnett, William A. and Singleton, Kenneth (eds.), New Approaches to Monetary Economics (pp. 115–168). Cambridge, UK: Cambridge University Press. [Reprinted in Barnett and Serletis (2000, Ch. 3, pp. 49–99).]CrossRefGoogle Scholar
Barnett, William A. (1997) Which road leads to stable money demand? Economic Journal 107, 1171–1185. [Reprinted in Barnett and Serletis (2000, Ch. 24, pp. 577–592).]CrossRefGoogle Scholar
Barnett, William A. (2007) Multilateral aggregation-theoretic monetary aggregation over heterogeneous countries. Journal of Econometrics 136 (2), 457–482.CrossRefGoogle Scholar
Barnett, William A. and Chauvet, Marcelle (2009) International financial aggregation and index number theory: A chronological half-century empirical overview. Open Economies Review 20 (1), 1–37.CrossRefGoogle Scholar
Barnett, William A. and Peretti, Philippe de (2009) Admissible clustering of aggregator components: A necessary and sufficient stochastic seminonparametric test for weak separability. Macroeconomic Dynamics 13 (Supplement 2), 317–334.CrossRefGoogle Scholar
Barnett, W., Fisher, D., and Serletis, A. (1992) Consumer theory and the demand for money. Journal of Economic Literature 30, 2086–2119. [Reprinted in Barnett and Serletis (2000, Ch. 18, pp. 389– 427).]Google Scholar
Barnett, W.A., Liu, Y., and Jensen, M. (2000) CAPM risk adjustment for exact aggregation over financial assets. Macroeconomic Dynamics 1, 485–512.Google Scholar
Barnett, William A., Offenbacher, Edward K., and Spindt, Paul A. (1984) The new Divisia monetary aggregates. Journal of Political Economy 92, 1049–1085. [Reprinted in Barnett and Serletis (2000, Ch. 17, pp. 360–388).]CrossRefGoogle Scholar
Barnett, W.A. and Serletis, A. (eds.) (2000) The Theory of Monetary Aggregation, Contributions to Economic Analysis Monograph Series. Amsterdam: Elsevier.CrossRefGoogle Scholar
Barnett, William A. and Wu, Shu (2005) On user costs of risky monetary assets. Annals of Finance 1, 35–50.CrossRefGoogle Scholar
Belongia, M. (1996) Measurement matters: Recent results from monetary economics reexamined. Journal of Political Economy 104 (5), 1065–1083.CrossRefGoogle Scholar
Belongia, M. and Ireland, P. (2006) The own-price of money and the channels of monetary transmission. Journal of Money, Credit, and Banking 38 (2), 429–445.CrossRefGoogle Scholar
Brock, W.A., Dechert, W.D., Schenkman, J.A., and LeBaron, B. (1996) A test for independence based on the correlation dimension. Econometric Reviews 15 (3), 197–235.CrossRefGoogle Scholar
Bry, G. and Boschan, C. (1971) Cyclical Analysis of Times Series: Selected Procedures and Computer Programs. New York: National Bureau of Economic Research.Google Scholar
Chauvet, M. (1998) An econometric characterization of business cycle dynamics with factor structure and regime switches. International Economic Review 39 (4), 969–996.CrossRefGoogle Scholar
Chauvet, M. (2001) A monthly indicator of Brazilian GDP. Brazilian Review of Econometrics 21 (1), 1–15.CrossRefGoogle Scholar
Chrystal, A. and MacDonald, R. (1994) Empirical evidence on the recent behaviour and usefulness of simple-sum and weighted measures of the money stock. Federal Reserve Bank of St. Louis Review 76, 73–109.Google Scholar
Diewert, W. (1976) Exact and superlative index numbers. Journal of Econometrics 4, 115–145.CrossRefGoogle Scholar
Divisia, F. (1925) L'Indice monétaire et la théorie de la monnaie. Revue d'Economie Politique 39, 980–1008.Google Scholar
Feenstra, R.C. (1986) Functional equivalence between liquidity costs and the utility of money. Journal of Monetary Economics 17, 271–291.CrossRefGoogle Scholar
Fischer, Stanley (1974) Money and the production function. Economic Inquiry 12, 517–533.CrossRefGoogle Scholar
Friedman, Milton and Schwartz, Anna (1970) Monetary Statistics of the United States: Estimation, Sources, Methods, and Data. New York: Columbia University Press.Google Scholar
Harrison, P.J. and Stevens, C.F. (1976) Bayesian forecasting. Journal of the Royal Statistical Society Series B 38, 205–247.Google Scholar
Haywood, E. (1973) The deviation cycle: A new index of the Australian business cycle, 1950–1973. Australian Economic Review 6 (4), 31–39.CrossRefGoogle Scholar
Hicks, J.R. (1946) Value and Capital. Oxford, UK: Clarendon Press.Google Scholar
Jones, B., Dutkowsky, D., and Elger, T. 2005. Sweep programs and optimal monetary aggregation. Journal of Banking and Finance 29, 483–508.CrossRefGoogle Scholar
Kim, Chang-Jim (1994) Dynamic linear models with Markov-switching. Journal of Econometrics 60, 1–20.CrossRefGoogle Scholar
Kim, C.J. and Nelson, C. (1998) State-Space Models with Regime-Switching: Classical and Gibbs-Sampling Approaches with Applications. Cambridge, MA: MIT Press.Google Scholar
Lucas, Robert E. (2000) Inflation and welfare. Econometrica 68 (62), 247–274.CrossRefGoogle Scholar
Phlips, Louis and Spinnewyn, Frank (1982) Rationality versus myopia in dynamic demand systems. In Basmann, R.L. and Rhodes, G.F. (eds.), Advances in Econometrics, pp. 3–33. Greenwich, CT: JAI Press.Google Scholar
Poterba, J. and Rotemberg, J. (1987) Money in the utility function: An empirical implementation. In Barnett, W.A. and Singleton, K.J. (eds.), New Approaches to Monetary Economics, pp. 219–240. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Serletis, A. (ed.) (2006) Money and the Economy. Singapore: World Scientific.CrossRefGoogle Scholar
Schunk, D. (2001) The relative forecasting performance of the Divisia and simple sum monetary aggregates. Journal of Money, Credit, and Banking 33 (2), 272–283.CrossRefGoogle Scholar